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Social and motor skills in autism spectrum disorder & developmental coordination disorder: functional & structural neurobiology

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Social and motor skills in autism spectrum disorder & developmental coordination disorder: functional & structural neurobiology

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Content SOCIAL AND MOTOR SKILLS IN ASD & DCD 1 SOCIAL AND MOTOR SKILLS IN AUTISM SPECTRUM DISORDER & DEVELOPMENTAL COORDINATION DISORDER: FUNCTIONAL & STRUCTURAL NEUROBIOLOGY by Emily Kilroy Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (OCCUPATIONAL SCIENCE AND OCCUPATIONAL THERAPY) December, 2018 SOCIAL AND MOTOR SKILLS IN ASD & DCD 2 ACKNOWLEDGEMENTS First and foremost, I would like to thank Dr. Lisa Aziz-Zadeh and Dr. Sharon Cermak who have supported me with advice, expertise, and encouragement, without which this research and dissertation would not have happened. I would like to thank other members of my committee: Dr. Jonas Kaplan for his thoughtful feedback, insight, and technical expertise which was instrumental to the success of my research; and Dr. Antonio Damasio for providing me with the inspiration and opportunity to work and grow as a researcher in a nurturing environment and distinguished institute. I would also like to thank my friends and colleagues at the Brain and Creativity Institutive and at the Department of Occupational Science where it has been my pleasure and honor to work the last 5 years. Through their love and support, I have developed not only as a researcher but also as a person. I indebted to my family who has supported and encouraged my education throughout this journey and to all whom I can finally say, “Yes, I am done with school!” Finally, I acknowledge my partner, Jake, who has been my unwavering champion and has kept me grounded through uncertain and celebratory times. SOCIAL AND MOTOR SKILLS IN ASD & DCD 3 LIST OF TABLES Chapter 2 Table 1. Sample Size Per Chapter……………………………………………………………50 Chapter 3 Table 1. Participant Characteristics of the Final Sample…………………………………...69 Table 2. Relationship Between Imitation Activation in AON Nodes and Social and Motor Skills……………………………...……………………………………………………………...76 Table 3. An Example Set of Action Videos Presented During a Run of the Imitation Task …………………………………………………………………………………………………...87 Chapter 4 Table 1. Final Group Demographics…………………………………................................103 Table 2. Significant AON Correlation Matrix Results.......................................................107 Chapter 5 Table 1. Group Demographics……………………………………......................................136 Table 2. Group Contrast Results Classified by JHU White Matter Labels……………..140 Table 3. Social and Motor Regression Results Classified by JHU White Matter Labels………………………………………………………………………………………….144 Table 4. AON tracts and Behavior Correlations Within and Between-Group………….147 SOCIAL AND MOTOR SKILLS IN ASD & DCD 4 LIST OF FIGURES Chapter 1 Figure 1. Human Mirro Neuron System Components …………………………..……….…14 Figure 2. The social top-down response modulation (STORM) model……………………26 Chapter 2 Figure 1. Scatterplot of social and motor skills in each group………………………………50 Chapter 3 Figure 1. Stimulus and task design…………………………………………………………...65 Figure 2. Mask of the action observation network (AON)..................................................67 Figure 3. ROI analysis for task activation………….…………………………………………68 Figure 4. Scatterplot of social and motor skills across all groups………………………….71 Figure 5. Imitation versus rest by group…………………………...…………………………72 Figure 6. Action observation network group contrasts……………………………………...73 Figure 7. Scatterplots of inferior frontal gyrus (IFG) ……………………………...………...75 Figure 8. Scatter plot of catching and aiming skills and activation in a region of the inferior frontal gyrus (IFG).…………..………………………………………………………………….80 Figure 9. Boxplot and bar charts barts of activation during imitation where TD>ASDd and TD>DCD…………………………………………………………………………………………86 Figure 10. A between-group comparison of imitation versus rest………………………….87 Chapter 4 Figure 1. Default mode network (DMN) identified in use multiple imaging techniques…..95 SOCIAL AND MOTOR SKILLS IN ASD & DCD 5 Figure 2. Eight mm spheres around significant coordinates from an observation and imitation meta-analysis.....................................................................................................101 Figure 3. Scatterplot of social and motor skills across all groups………………………...105 Figure 4. Significant (p<.05) AON connectivity in typically developing (TD), Autism Spectrum Disorder and Developmental Coordination Disorder (ASDd) and DCD only individuals……………………………………………………………………………………..106 Figure 5. Bar chart of bilateral IFG connectivity in typically developing individuals (TD, blue), developmental coordination (DCD; green) and Autism Spectrum Disorder with motor deficits (ASDd)…………………………………………………………………………107 Figure 6. Scatterplot of left and right inferior frontal gyrus connectivity across all groups correlated with aiming and catching subscale of the Movement assessment battery for children (MABC-2)…………………………………………………………………………….108 Figure 7. Default Mode Network: Group main effects……………………………………..109 Figure 8. Whole brain posterior cingulate cortex (PCC) functional connectivity group contrasts on an MNI template………………………………………………………………..112 Figure 9. Scatter plots of social and motor skills and group contrast PCC connectivity…………………………………………………………………………………….113 Figure 10. Social and motor skills and PCC connectivity………………………….....…...114 Figure 11. Social and motor skills related to posterior cingulate cortex (PCC) connectivity in the typically developing (TD) group……………………………………………………….121 Chapter 5 Figure 1. Scatterplot of social and motor skills across and within all groups, TD (blue), ASDd (red) and DCD (green)………………………………………………………………...138 SOCIAL AND MOTOR SKILLS IN ASD & DCD 6 Figure 2. Between-group whole-brain tractography maps shown on an MNI template...140 Figure 3. Box Plots ROI analysis………………………………………………………….…141 Figure 4. Bar graph of the genu of corpus callosum ROI connectivity in Typically developing Group (TD; Blue), Autism Spectrum Disorder +Developmental Coordination Disorder (ASDd; red), DCD (green)………………………………………………………..142 Figure 5. Within-group whole-brain social and motor connectivity maps shown on an MNI template………………………………………………………………………………………...145 Figure 6. AON network seeds………………………………………………………………..145 Chapter 6 Figure 1. Action observation network (AON) findings across all modalities in autism spectrum disorder subgroup (ASDd; top) and developmental coordination disorder (DCD; bottom) compared to typically developing (TD) peers……………………………………..166 SOCIAL AND MOTOR SKILLS IN ASD & DCD 7 Table of Contents Acknowledgements .......................................................................................................... 2 List of Tables .................................................................................................................... 3 List of Figures .................................................................................................. 4 Table of Contents ............................................................................................................. 7 Chapter 1. A Review of Functional and Structural Neurobiology of the Action Observation Network in Autism Spectrum Disorder and Developmental Coordination Disorder ................................................................................................. 10 The Action Observation Network (AON) .............................................................. 11 Developmental Coordination Disorder (DCD) and Motor Impairments ............... 14 Task-based AON Research in ASD and DCD ..................................................... 17 Resting State Research in ASD and DCD ........................................................... 32 AON White Matter Integrity in ASD and DCD ...................................................... 37 Conclusions and Future Directions ...................................................................... 42 Chapter 2. Brief Dissertation Introduction ................................................................. 46 Participants .......................................................................................................... 47 Task-based fMRI Study ....................................................................................... 50 Resting State fMRI Study .................................................................................... 51 Diffusion Weighted Imaging Study ...................................................................... 52 Chapter 3. Action Observation Network Responses to Imitation in Autism Spectrum Disorder and Developmental Coordination Disorder .............................. 54 SOCIAL AND MOTOR SKILLS IN ASD & DCD 8 Abstract................................................................................................................ 54 Introduction .......................................................................................................... 56 Current Study ...................................................................................................... 60 Methods ............................................................................................................... 61 Results ................................................................................................................. 68 Discussion ........................................................................................................... 76 Limitations ........................................................................................................... 83 Conclusions ......................................................................................................... 84 Supplementary Material/Appendix ....................................................................... 86 Chaper 4. Resting State Networks in Children and Adolescents with Social and Motor Deficits ................................................................................................................ 88 Abstract................................................................................................................ 88 Introduction .......................................................................................................... 90 Current Study ...................................................................................................... 95 Methods ............................................................................................................... 96 Results ............................................................................................................... 102 Discussion ......................................................................................................... 114 Limitations ......................................................................................................... 118 Conclusions ....................................................................................................... 119 Supplementary Materials ................................................................................... 121 Chapter 5. Tractography Related to Social and Motor Deficits in Autism Spectrum Disorder and Developmental Coordination Disorder .............................................. 123 Abstract.............................................................................................................. 123 SOCIAL AND MOTOR SKILLS IN ASD & DCD 9 Introduction ........................................................................................................ 125 Current Study .................................................................................................... 129 Methods ............................................................................................................. 130 Results ............................................................................................................... 136 Discussion ......................................................................................................... 148 Limitations ......................................................................................................... 157 Conclusions ....................................................................................................... 158 Chapter 6. Dissertation Discussion and Conclusions ............................................ 159 Summary of Research ....................................................................................... 160 Conclusions ....................................................................................................... 164 Considerations and Future Directions ............................................................... 167 References ................................................................................................................... 173 Appendix A. MRI Screener ........................................................................................... 199 Appendix B. Instruments .............................................................................................. 200 SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 10 Chapter 1. A Review of Functional and Structural Neurobiology of the Action Observation Network in Autism Spectrum Disorder and Developmental Coordination Disorder Autism spectrum disorder (ASD) is defined clinically by the presence of social communication and social interaction impairments along with restricted and repetitive behaviors including motor movements, insistence on sameness, and/or atypical sensory processing (American Psychiatric Association [APA], 2013). Although not considered necessary for a diagnosis, imitation and motor deficits also have been associated with ASD since Kanner’s initial description of the disorder (Kanner, 1943). An ASD diagnosis may be complicated by one or more co-occurring conditions, including anxiety, attention deficit hyperactivity disorder (ADHD), epilepsy, fragile X syndrome, neuroinflammation and immune disorders, sensory disorders, obsessive-compulsive disorder, and/or developmental coordination disorder (DCD), all of which make ASD a highly heterogeneous condition that is difficult to study. Overlapping symptoms from comorbid diagnoses can mask and interact with ASD-specific symptoms. Due to the heterogeneity of ASD research participants, historically it has been challenging to identify discrete ASD behaviors and neurological patterns. Because 80% of children with ASD are thought to have motor impairment, here, we focus on variations of motor and social performance patterns in order to better understand how these dimensions may contribute to ASD’s heterogeneity. Specifically, we review neuroimaging literature on DCD, sometimes referred to as dyspraxia, and relate it to similar literature on individuals with ASD. DCD is characterized primarily by difficulty in motor learning and poor motor performance (APA, SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 11 2013) as well as challenges with motor imitation (Sinani, Sugden, & Hill, 2011). The function, structural integrity, and connectivity of social and motor brain regions and networks influence social and motor skills and performance in all humans. However, how motor perception may interact with social perception in ASD is unclear. Because individuals with DCD have primary impairments in motor skills but not social skills (Ahonen, 1990; Cantell, 1998; Cantell, Smyth, & Ahonen, 1994; Dewey, Cantell, & Crawford, 2007; Dewey, Kaplan, Crawford, & Wilson, 2002; Missiuna et al., 2008), they can act as a comparison population to help detangle potential interactions between motor performance and social processing deficits in ASD. Although several reviews on motor networks in ASD and a few on DCD have been published, to our knowledge, no reviews to date have compared these populations side-by-side. It has been argued that some motor regions of the brain, such as the action observation network (AON), may be compromised in ASD in a manner that can lead to both imitation and social deficits in this population (Alaerts et al., 2013; Dapretto et al., 2006; Oberman et al., 2005). It is further posited that AON circuits may be compromised in DCD populations as well (Zwicker, Missiuna, Harris, & Boyd, 2010). Thus, we review current AON literature across multiple levels of neurobiology as it relates both the ASD and DCD populations in order to better understand how the AON functions in these groups. After briefly describing the AON and DCD, we will look at evoked and resting state functional magnetic resonance imaging (fMRI) data followed by white matter microstructure findings in both disorders. The Action Observation Network (AON) SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 12 By observing other people’s actions, we often can obtain important social information regarding their goals and intentions. Observing others’ actions elicits activation in multiple sensorimotor brain regions that collectively comprise the AON (Caspers, Zilles, Laird, & Eickhoff, 2010; Cross, Hamilton, Kraemer, Kelley, & Grafton, 2009; Gazzola, Rizzolatti, Wicker, & Keysers, 2007). The AON’s core regions include the occipitotemporal regions, premotor cortex, and inferior parietal lobule (IPL) as well as the superior temporal gyrus (STS). Both the premotor cortex, including the inferior frontal gyrus (IFG), and regions of the IPL have been shown to be active during both the execution of, as well as the observation of, a given action (Caspers et al., 2010; Chong, Cunnington, Williams, Kanwisher, & Mattingley, 2008). These co-active regions are the human homologues to the brain areas in monkeys in which the so-called mirror neurons originally were identified (Rizzolatti & Craighero, 2004). Accordingly, the above- identified human brain regions are thought to comprise the putative human mirror neuron system (MNS; Figure 1; Rizzolatti & Craighero, 2004). Although some consider the MNS to be a distinct part of the AON because it is active both during the production and the observation of actions (Biagi et al., 2016; Quandt & Chatterjee, 2015), others do not differentiate between the two (Etzel, Valchev, Gazzola, & Keysers, 2016). In this review, the AON is defined as a broader network of regions involved in action observation, specifically: the IPL, IFG, and STS. It has been hypothesized that the AON contributes to the understanding of others’ actions by mapping those actions onto one’s own motor system (Rizzolatti & Craighero, 2004). In a sense, the AON simulates a corresponding motor representation making it possible to understand and predict outcomes of actions based on the action’s SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 13 familiarity (Gazzola, Aziz-Zadeh, & Keysers, 2006; Ortigue, Sinigaglia, Rizzolatti, & Grafton, 2010). Indeed, the AON has been related to social cognition, such as components of empathic processing (Gazzola et al., 2006; Kaplan & Iacoboni, 2006; Sobhani, Fox, Kaplan, & Aziz-Zadeh, 2012), which has led some to implicate the network’s role in social disorders such as ASD (Dapretto et al., 2006). The AON’s function and connectivity at rest and its underlying white-matter integrity have been linked to behavioral measures of social and motor skills (Fishman, Datko, Cabrera, Carper, & Müller, 2015; Williams, Kashuk, Wilson, Thorpe, & Egan, 2017). Many researchers posit that the AON is crucial to social cognition (Bastiaansen et al., 2011; Dapretto et al., 2006; Oberman & Ramachandran, 2007), while others have argued its primary role is in motor perception (Cook, Bird, Catmur, Press, & Heyes, 2014), however this theory has not been sufficiently tested. Brain imaging studies on the AON in ASD have yielded contradictory findings. Some report reduced AON activity in ASD (Dapretto et al., 2006; Ortigue et al., 2010; Schultz, 2000; Williams, Whiten, Suddendorf, & Perrett, 2001) while others have reported intact functioning (Schulte- Rüther et al., 2017). Furthermore, because social and motor deficits are often linked in ASD (Craig et al., 2018; Leary, 1996), it is difficult to understand how these deficits may interact with distributed network function. One way to try to answer this question is to compare individuals with ASD to individuals with DCD, as both disorders often share similar motor impairments, while social impairments are more singularly endemic to ASD. Through this type of comparative analysis, we may be able to tease apart ASD’s social impairments from its motor symptoms. To the best of our knowledge, only one study to date has compared ASD and DCD using neuroimaging methods SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 14 (Caeyenberghs et al., 2016). The aim of this review is to compare the findings in ASD and DCD literature in a way that informs the possible underlying mechanisms of the AON in neurodevelopmental populations. Figure 1. Human mirror neuron system components. Lateral view of brain with frontal (ventral premotor & IFG) and parietal (rostral IPL) labels of the mirror neuron system in addition to the superior temporal sulcus. IFG = inferior frontal gyrus; IPL = inferior parietal lobule; STS = superior temporal sulcus. Developmental Coordination Disorder (DCD) and Motor Impairments Developmental coordination disorder (DCD) is a neurodevelopmental disorder like ASD that is less commonly recognized despite its prevalence. DCD affects approximately 6% of the population (APA, 2013). The disorder is characterized by poor motor skills that interfere with a child's ability to perform everyday activities. Deficits in higher-order motor function can result in motor skill acquisition and execution impairments that significantly interfere with daily living. To receive a DCD diagnosis under the DSM-5, these deficits “cannot be explained by sensorimotor impairments sufficient to preclude skilled movement” nor by intellectual disability (APA, 2013). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 15 Although cognitive and psychosocial impairments are not primary symptoms in a DCD diagnosis, individuals with DCD often demonstrate challenges in social functioning, self- esteem, and psychological adjustments which are presumed to result from DCD symptomatology (Ahonen, 1990; Cantell, 1998; Cantell et al., 1994; Dewey et al., 2002). A recent behavioral study places DCD socialization skills at an “intermediate” level between typically developing children and those with ASD (Sumner, Leonard, & Hill, 2016). These secondary social symptoms can put individuals with DCD at higher risk for depression and anxiety (Dewey et al., 2007). The disorder can also co-occur with ADHD, specific language impairment (SLI), and ASD (Gomez & Sirigu, 2015; Piek & Dyck, 2004). Among DCD’s myriad motoric challenges (motor delay, poor handwriting, etc.), behavioral data also indicate the presence of imitation impairments (Zoia, Pelamatti, Cuttini, Casotto, & Scabar, 2002). Individuals with DCD make more errors and have slower response times when imitating learned or meaningful skills (Sinani et al., 2011) as well as when imitating “non-meaningful” simple and complex gestures (Reynolds, Kerrigan, Elliott, Lay, & Licari, 2017). Such deficits may be minimized, however, for very common and learned gestures, such as waving goodbye. Looking at the imitation of common representational gestures (e.g., waving goodbye, brushing teeth), one study found no differences between DCD children and typically developing (TD) peers (Dewey et al., 2007), demonstrating that individuals with DCD are capable of imitating learned motor skills. Moreover, motor imagery, or the mentalization of actions, is often used as an effective therapy for DCD (Wilson et al., 2016) providing further evidence that individuals with DCD have the ability to overcome some motor impairments. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 16 Nevertheless, the strategies used by children with DCD to achieve learned motor skills may be different than those used by their TD peers. For example, different brain regions may be activated as compensatory mechanisms to overcome imitation deficits. It is possible that individuals with DCD have greater reward activation when they successfully imitate actions, which helps them overcome their inherent motor challenges by reinforcing the social reward. This hypothesis, however, has not yet been systematically tested. Additional research is required to better understand the underlying neural correlates of motor perception and imitation in DCD. Given that individuals with DCD can effectively learn common gestures, future experimental designs should incorporate imitation of novel gestures to more accurately test and reflect imitation skills, rather than relying on representational gestures alone. When assessing imitation abilities of the DCD population, utilizing novel gestures circumvents the problem imposed by testing learned imitation skills. For these reasons, caution is advised when interpreting results from imitation studies that rely exclusively upon overlearned representational gestures in the study design. Unfortunately, the use of standardized non-representational assessments is limited in the literature, although the Postural Praxis subtest within the Sensory Integration and Praxis Tests (SIPT; Ayres,1989) does incorporate novel hand and body gestures, and the Florida Apraxia Screening Test Revised (FAST-R; Rothi, Raymer, & Heilman, 1997a) do include novel gestures along with more common representational actions. Because components of the AON have been found to be essential for imitation (Heiser, Iacoboni, Maeda, Marcus, & Mazziotta, 2003; Koski, 2002), it is possible that the imitation deficits seen in DCD are tied to AON function. Although a small but quickly SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 17 growing body of literature has begun to directly and indirectly identify atypical AON functioning within the DCD population (Debrabant, Gheysen, Caeyenberghs, Van Waelvelde, & Vingerhoets, 2013; Kashiwagi, Iwaki, Narumi, Tamai, & Suzuki, 2009; Reynolds et al., 2015; Zwicker et al., 2010), few reviews have covered AON-related hypotheses in DCD. For example, Werner et al. (2012) reviewed evidence that supports the broken AON hypothesis in DCD. In addition, a more recent systematic review by Reynolds et al. (2015) covered a range of research looking across imitation and motor imagery in neuroimaging literature to find support for MNS dysfunction, although it did not specifically review literature designed to capture AON function. Finally, a systematic review by Wilson et al., (2017) which covered cognitive and neuroimaging findings, including those in AON areas, ultimately suggested that more research is needed in order to draw conclusions regarding AON deficits. All of these reviews focused solely on individuals with DCD and did not contrast findings with the ASD population. In the sections that follow, we review the findings from fMRI studies followed by resting-state and diffusion literature in both populations. Task-based AON Research in ASD and DCD In the last few decades, a considerable body of literature has examined the neural substrates that correlate with observation, execution, and imitation skills in typical adults (for a review see Caspers et al., 2010) and in ASD populations (Williams et al., 2001; Yang & Hofmann, 2016). To date, no experimental research published on the neural mechanisms that underlie action processing in clinical populations has contrasted the ASD and DCD populations. Typically, studies examined each group SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 18 separately or in comparison to either typical controls or other developmental disorders such as ADHD (Reynolds et al., 2017; Williams et al., 2006). Below we review the fMRI literature on studies related to the AON as observed in both the ASD and DCD populations and discuss how these findings inform AON functioning in both groups. AON activity in ASD. Although behavioral imitation deficits have been reported in ASD (Williams et al., 2001; Williams, Whiten, & Singh, 2004) the types of imitation impairments and tasks are debated. Some have investigated imitation in individuals with ASD and have found it to be either typical (Hamilton, Brindley, & Frith, 2007; Press, Richardson, & Bird, 2010; Schunke et al., 2016), or even enhanced (Bird, Leighton, Press, & Heyes, 2007; Spengler, Bird, & Brass, 2010). Indeed, the ability to imitate can remain intact in the disorder, depending on context and type of imitation (Ingersoll, 2008). For a review of imitation in ASD, see Hamilton (2008) or Kana et al. (2010). Overall, there is evidence that individuals with ASD fail to mimic meaningless actions (Rogers et al., 1996) or gestures (Bryson & Smith, 1998) but perform typically on a range of other imitation tasks, such as common gestures, especially if they are goal- directed (Aldridge, Stone, Sweeney, & Bower, 2000; Meltzoff, 1999; Rogers et al., 1996). Hamilton (2008) posits that goal-directed imitation is intact in ASD whereas spontaneous mimicry of low-level kinematic features of action such as hand gestures or facial expression is impaired. These studies add to the complexity of social and motor deficits in ASD and demonstrate the need for special consideration of the type of imitation and level of motor skills when interpreting AON and MNS results. Dysfunction of the AON or the MNS in relation to ASD has been coined the “broken mirror hypothesis”. This hypothesis implies that ASD symptoms such as SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 19 imitation and social cognition are related to the dysfunction of these mirroring areas which are crucial to social cognition (Iacoboni & Dapretto, 2006; Oberman & Ramachandran, 2007; Williams et al., 2001). Imitation is thought to be foundational to social development and important for understanding others and for communication. Williams et al., (2001) was one of the first groups to hypothesize that deficits in the AON or MNS may contribute to imitation and social impairments in ASD. Indeed, there is a link between imitation and social skills such as empathy (Chartrand & Bargh, 1999; Dapretto et al., 2006; Kaplan & Iacoboni, 2006). Moreover close proximity and white matter tracts between emotional brain regions such as the insula or anterior cingulate and the AON (frontal and parietal areas) has led some to propose that these two networks (the AON and emotion related networks) work together to support empathy and social cognition through implicit imitation and/or simulation (Iacoboni, 2009; Rizzolatti, Fabbri-destro, & Cattaneo, 2009). These hypotheses are supported by fMRI studies which demonstrate reduced activation in components of the AON (e.g., IFG) in individuals with ASD while observing and imitating static images of emotional expressions compared to TD children and adolescents (Dapretto et al., 2006). Authors reported that the areas of reduced activity during observation and imitation tasks were related to ASD symptoms as measured by ASD clinical assessments (e.g., Autism Diagnostic Interview Revised; ADI-R). As the signal decreases in the IFG pars opercularis (IFGpo), the social severity scores increase in the ASD group indicating that MNS dysfunction relates to social symptoms in ASD. Other groups have replicated this effect in children and adults with ASD using emotional stimuli. Greze et al., (2009) reported reduced AON activity in adults while SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 20 viewing neutral or fearful whole-body human actions, however, the authors attribute this reduction to decreased activity in emotion-related areas of the brain (i.e., amygdala) driving attenuation of network connectivity and activity in other brain areas such as the IFG (Grèzes, Wicker, Berthoz et al, 2009). In contrast, others report typical AON responses in ASD (Schulte-Rüther et al., 2011). For example, in a study by Schulte- Rüther et al. (2011), TD and ASD participants observed and responded to happy and sad facial expressions and were asked to either “decide how this person feels” or “decide how you feel when you look at the face”. Although the study was not designed as a strict observation study, both groups activated left hemisphere IFG when instructed to think about their own emotions, which suggests that, in some instances, the IFG in ASD functions similarly to TDs. However, group differences were found in regions elicited to understand the thoughts and feelings of others known as the theory of mind network (ToM: medial prefrontal cortex [mPFC] and temporal parietal junction [TPJ]). Several fMRI studies have reported no attenuation of activity in the mirroring regions in ASD as compared to TD peers when asked to observe and imitate non- emotional actions such as finger tapping (Bird et al., 2007; Dinstein et al., 2010; Fan, Decety, Yang, Liu, & Cheng, 2010; Marsh & Hamilton, 2011; Pokorny et al., 2015; Raymaekers, Wiersema, & Roeyers, 2009; Reynolds et al., 2017). These findings go against the theory of global disruption of the AON and indicate that AON function may not be directly linked to poor imitation or social processing in ASD. However, these findings may be confounded by variability in imitation skills in the ASD samples. Motor impairment and imitation skills can vary across the ASD population. Without determining the degree of motor skills in a given sample it is impossible to determine if AON function SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 21 is intact globally or just in a subset of the population. Furthermore, the type of stimuli used may contribute to conflicting study results -- more socially relevant stimuli (facial expressions) may show greater AON differences between ASD and TD groups than less socially relevant stimuli (finger tapping). Finally, conflicting results could be due to the heterogeneity of the ASD population. It may be that the atypical IFG function is associated only with individuals who have motor impairments. Accordingly, studies that include individuals with more motor deficits may find differences while those that incorporate participants who have more typical motor skills do not find such differences. Opposing results from both behavioral and neuroimaging imitation research suggests that no one particular area or network is responsible for social deficits in all individuals with ASD. Different regions and networks related to social and imitative deficits have been identified across several studies. Since poor imitation has been linked to poor motor skills in ASD (Mostofsky et al., 2006), it is thus possible that individuals with greater motor difficulties will respond differently than those with fewer motor deficits. To date, no research has compared the AON’s response to social and motor action imitation directly in ASD. However, there is some evidence that atypical motor circuitry in ASD is related to poor motor skills. One study observed laterality differences in motor circuitry connectivity during a finger tapping test between ASD and TD children (Floris, Lai, Nath, Milham, & DiMartino, 2016). Children with ASD showed rightward lateralization which was associated with poorer performance on motor skills measured by the Physical and Neurological Exam for Subtle Signs (PANESS; Dencla & Rudel, 1974) which measures motor control among other clinical subscales. Interestingly, no association was found between motor connectivity and social and SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 22 communicative sub-scores on clinical ASD assessments (e.g., Autism diagnostic observation schedule [ADOS; Lord et al., 2000] or ADI-R; Floris et al., 2016). These findings indicate that some motor deficits in ASD may not relate to social deficits. Overall, the neural correlates that underscore social and motor skills in ASD remain unclear. Most studies have failed to examine or report both social and motor skills or how they relate to the neural underpinnings of AON function, which makes it difficult to test if variance in these skills account for the aberrant neuroimaging findings found in ASD. Theories of aberrant findings in ASD. Looking primarily at fMRI studies, there is no clear conclusion regarding the link between AON function and ASD symptomatology. Here we list proposed explanations for aberrant AON findings. First, the multiple route theory proposed by Hamilton (2008, 2015) hypothesizes that multiple routes (direct and indirect) underlie imitation in humans (Hamilton & Grafton, 2008). The direct route between the middle temporal gyrus (MTG) and the IFG which is elicited for spontaneous imitation of meaningless gestures or facial expressions and the indirect connection between the temporofrontal regions and the IFG via IPL is recruited for emulation of goal-directed actions (Hamilton, 2008; Wang & Hamilton, 2012). Based on behavioral imitation studies, Hamilton (2015) suggests that the direct (mimicry) route is disrupted in ASD whereas the indirect (goal processing) route is intact. This multiple route theory posits that only a part of the AON is disrupted in ASD and is congruent with research indicating that the IPL is important for goal interpretation while the IFG is important for specific action properties such as speed and body (Tunik, Rice, Hamilton, & Grafton, 2007; Urgesi, Calvo-Merino, Haggard, & Aglioti, 2007). More recently, SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 23 Hamilton and colleagues proposed that disruptions in social processing regions (such as the mPFC) known to be active during ToM might inhibit AON functioning in ASD through top-down control. The social top-down response modulation (STORM; Figure 2) model proposed by Wang and Hamilton (2012) links disruption in visual-motor mapping and the top-down modulation system with mimicry deficits in ASD. The STORM theory is built on the premise that input from social cues modulate imitation and therefore poor ToM abilities in ASD affect AON functioning and in turn result in imitation deficits. This theory suggests that individuals with ASD are capable of imitating a person when explicitly prompted to do so, however, if expected to implicitly “pick up” on the cue (i.e., through body language, such as a facial expression), they fail to imitate as a result of social deficits that impair their ability to perceive the intentions of others. In other words, Wang and Hamilton (2012) posit that imitation ability is intact in ASD, but being able to modulate imitation implicitly based on ToM processing in social situations may be impaired. Indeed, other studies indicate that individuals with ASD have impaired spontaneous mentalizing of others’ emotions despite intact deliberate empathy related motor mimicry (McIntosh, Reichmann-Decker, Winkielman, & Wilbarger, 2006; Oberman, Winkielman, & Ramachandran, 2009). This theory fits with findings of atypical activation of both ToM and AON regions (Schulte-Rüther et al., 2011). Several other studies also have reported deficits in other networks that are linked with the AON and that could result in atypical AON activity (Marsh & Hamilton, 2011; Oberman et al., 2009; Yang & Hofmann, 2016). For example, in an activation likelihood estimation (ALE) meta-analysis of observation and imitation fMRI studies in ASD, decreased activation in frontal regions such as dorsolateral prefrontal cortex (DLPFC) SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 24 were identified in ASD compared to a TD cohort (Yang & Hofmann, 2016). The DLPFC has recently been implicated in rule-based visuomotor associations during action observation (Ubaldi, Barchiesi, & Cattaneo, 2015). During a simple social interaction, such as producing a rule-based motor response to the movements of another individual, the DLPFC was found to be crucial for modulating automatic imitative responses. The DLPFC is also important for attention and executive function, therefore those with attention deficits may have different AON responses. The reward system is another network known to be disrupted in ASD (Zeeland et al., 2010) and linked with AON functioning (Ávila et al., 2012; Caggiano et al., 2012; Fuentes-Claramonte et al., 2016). In neurotypical participants, reward sensitivity has been reported to mediate the association between IFG activity and task performance on a go/no-go task. Connectivity between the IFG and the ventral striatum (a part of the reward circuit) has been shown to be related to ASD traits when viewing faces (Sims, Neufeld, Johnstone, & Chakrabarti, 2013). Authors posit that the reduced spontaneous mimicry of social stimuli seen in autism may be related to the reward system’s failure to modulate the AON rather than a circumscribed deficit in the AON itself (Sims et al., 2013). Evidence supporting the reward system-AON relationship has led some to suggest the perceived value of the action may modulate AON function (Aziz-Zadeh, Kilroy, & Corcelli, 2018). Therefore, individuals with ASD who have higher social skills may find a social reward stimulus more valuable, and therefore have higher levels of AON activation. The notion of a value based-AON link is supported by findings from an electroencephalogram (EEG) study examining mu suppression, a putative marker of ‘mirror neuron’ functioning, while children with ASD observed the actions of familiar and SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 25 unfamiliar people. Results revealed that children with ASD exhibited relatively typical AON activation while observing the actions of familiar individuals (more valued) but decreased AON activity when they observed the same actions made by unfamiliar (less valued) individuals compared to TD peers. Future studies comparing the subjective value of social and nonsocial stimuli would be useful to determine if the AON is sensitive to a broader range of action beyond those that are social. Evidence from other fMRI studies suggests a possible disruption in ASD brain function may lie in the visual-motor system pathways. Lestou et al., (2008) suggest different regions of the AON, visual areas, and the STS are involved with different aspects of action observation. Lestou and colleagues (2008) propose a bi-directional pathway between the STS and MNS such that representation of action in the STS influences motor planning in the parietal and premotor regions of the MNS as well as motor plans in the ventral premotor cortex which change to predict actions in the STS. Indeed, disruption in visuomotor pathways has been reported in ASD. Poulin-Lord et al., (2014) showed that in a visuomotor imitation task, ASD and TD participants demonstrated increased spatial variability of peak activation in the occipital cortex and MTG, as well as increased activation in the precuneus and superior and mPFC compared to peers. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 26 Figure 2. The social top-down response modulation (STORM) model. In this model, responses in the mirror neuron system (MNS) to are subject to top-down control based on an evaluation of the current context and social situation. Failure of these top-down control signals could lead to abnormal imitation and abnormal MNS brain responses in autism (Hamilton et al., 2012). ASL = associative sequence learning; IFG = inferior frontal gyrus; IPL = inferior parietal lobule; mPFC = medial prefrontal cortex; MTG = medial temporal gyrus; STS = superior temporal sulcus; TPJ = temporal parietal junction. Additionally, variations in experimental approaches, such as paradigms and effectors may produce disparate results (Caspers et al., 2010). The majority of the research methods use different methods to elicit, measure, and analyze data making it difficult to replicate findings. Lastly, the heterogeneity of ASD samples makes it nearly impossible to control for all individual differences in the ASD population. Some samples may have participants with greater social severity, others with or without motor deficits or co-morbid DCD diagnoses all of which have discrete neurological abnormalities that feed into the AON network and impact the results. Additionally, age has been found to be a factor in IFG activation (Bastiaansen et al., 2011; Oberman et al., 2013; Oberman & Ramachandran, 2007). Further research taking these factors into consideration SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 27 (motor impairment, social impairment, participant age) is needed to understand how the AON and other networks relate to ASD. AON activity in DCD. There are fewer imaging studies designed to investigate the AON system in DCD than in ASD. Two studies directly measure mirroring properties of imitation in DCD while others measure gestures and imitation in general. Research using fMRI and EEG techniques to explore AON activation while participants completed hand and fine motor tasks report decreased activation in AON regions (Zwicker et al., 2010) as well as other motor related-regions (cerebellar, parietal, and prefrontal networks) in DCD relative to same-age peers (Debrabant et al., 2013; Pangelinan, Hatfield, & Clark, 2013; Reynolds et al., 2015; Zwicker et al., 2010). Overall findings suggest there are differences in DCD brain function compared to TD children (see Wilson, 2017 for review) with some exceptions (see Reynolds et al., 2017). Limitations to synthesizing results across studies include the use of different fMRI task protocols and assessments to measure motor function. Each of the fMRI tasks administered to DCD populations implemented unique protocols making it difficult to compare findings. Moreover, the assessments used to examine motor skills also varied. There are several test batteries that assess motor ability that include a heterogeneous set of motor tests reflecting actions such as catching, throwing, hopping etc. Common measures of motor performance included in fMRI studies are the Movement Assessment Battery for Children, Second Edition (MABC-2; Henderson; 1992) and the Beery-Buktenica Developmental Test of Visual Motor Integration (Beery VMI; Lim et al., 2015; Spencer & Kruse, 2013) for visual-motor skills. Neither of the aforementioned measures assesses non-representational gestures, however. Instead, they provide measurements of motor SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 28 development and coordination (e.g., MABC-2) and identify significant difficulties in integrating or coordinating visual perceptual and motor abilities such as finger and hand movement (e.g., Beery VMI). As mentioned above, the SIPT includes one subtest of non-representational gestures, and the FAST-R and the Florida Apraxia battery (FAB; Rothi, Raymer, & Heilman, 1997) both contain non-representational gestures in their respective imitation subsections while also including tasks that more closely resemble those typically designed for action observation fMRI studies. To date, only three studies have been published directly focusing on the AON in small samples of DCD (Licari et al., 2016; Reynolds et al., 2015; 2016). In a study by Licari and colleagues (2015), 13 children with DCD and 13 age matched TD peers were scanned while performing finger sequencing and hand clenching tasks. During the finger sequence task, the DCD group activated the left superior frontal gyrus and IFG less than the TD group and activated the right postcentral gyrus more than the TD group. No group differences were found in the hand clenching condition. While the decreased activation of the IFG is consistent with the broken AON hypothesis, increased activation of the postcentral gyrus contrasts with other DCD findings. In a study not directly investigating the AON, Zwicker et al. (2010) found decreased activation in the left postcentral gyrus in children with DCD during a trail-tracing task. The authors hypothesized that the increased activation in their DCD sample may be a result of learning effects. This postulation is supported by a study which reported that children with ADHD (a common comorbid disorder in DCD) performing a very similar task were observed to have decreased activation in the same area (Mostofsky et al., 2006). Together these findings suggest that other executive function networks may SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 29 influence motor related regions in DCD. To date, reported have used non- representational gestures in imaging studies. Using a different finger sequencing task to explore observation and imitation in DCD, Reynolds, et al., (2015) reported decreased activity in the left IFG in 14 DCD children compared to 12 TD age-matched controls. Reynolds and colleagues demonstrated that motor planning (measured by the postural praxis subtest of the SIPT; Ayres, 1988) was correlated with IFG activation which indicates that motor skills are related to AON dysfunction in DCD (no social skills were collected or reported). In a follow-up study (Reynolds et al., 2017) the authors compared 10 children with DCD to nine TD controls during observation, motor imagery, action execution and action imitation and found no differences in AON activation during a finger tapping test. The results of this study do not provide support for the AON dysfunction theory as a possible causal mechanism for DCD. The authors suggest that other networks contribute to the imitation deficits seen at the behavioral level such as attentional networks and motor planning processes. Notably, there are several methodological limitations to these DCD fMRI studies. Namely, most studies have very small sample sizes and they do not correct for multiple comparisons or global brain metrics, which is considered standard practice in MRI analysis. In addition, these studies do not control for confounding effects of demographic or clinical variables (e.g. sex, age, IQ; see Wilson et al., 2016 for a detailed list). In short, these methodological limitations make reliability and consensus about the neural basis of DCD difficult to ascertain. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 30 AON activity in ASD and DCD. Conclusions regarding AON function in ASD and DCD are difficult to reach given the aberrant findings in both populations as well as the limited number of studies and low sample sizes, especially in DCD research. Overall, there is evidence both for and against AON dysfunction in both groups, especially in the IFG. The strongest evidence of AON dysfunction in ASD comes from studies that utilize more socially relevant stimuli. These findings may be the result of impaired social deficits and/or motor deficits (Wang & Hamilton, 2012). Age is another important methodological inconsistency in DCD studies (Biotteau et al., 2016). In some instances, very large age ranges are included in DCD samples (Langevin, Macmaster, & Dewey, 2015; McLeod et al., 2014). Because age has been related to AON activity in TD populations, more careful consideration should be given when assembling and investigating clinical populations. With regard to DCD, a few studies observed reduced AON activity (Reynolds et al., 2015; Reynolds et al., 2015; Werner, Cermak, & Aziz-Zadeh, 2012). Since motor skill assessments were not collected or analyzed in most ASD studies nor social skill assessments in the DCD studies, it is difficult to know for sure whether the attenuated AON function observed in both groups has a common source or is expressed differently in each group. A potential future study that could clarify the specifics of AON dysfunction in these groups would compare both populations while they observed, executed, and imitated both social and motor actions. Contrasting more socially related actions to more motoric actions would illuminate the co-occurring effects of social and motor deficits in the AON and any possible additive effects of both diagnoses. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 31 AON connectivity in ASD and DCD during tasks and at rest. Although looking at activity in specific regions of a neural network, such as the AON, can provide substantial information about potential deficits in ASD or DCD, human cognitive function is generally thought to be supported by large-scale interactions among multiple regions and networks within the brain. The strength and organization of these functional networks can be measured by functional connectivity (FC) analysis. FC is generally defined by temporal correlations of different brain regions. Differences in FC have been identified in clinical populations and linked with clinical and behavioral variables (Floris, et al., 2016; Lynch et al., 2013). In the last decade, FC during a task has been linked to FC during rest (Mennes et al., 2010). Moreover, it has been shown that inter-individual differences in task- induced blood oxygen level dependent (BOLD) activity can be predicted by resting state properties (positive connectivity strength with task-positive networks and negative connectivity strength with intrinsic resting-state networks such as the default mode network (DMN; Mennes et al., 2010). Findings from studies that predict activation during a task from activation at rest suggest that a common mechanism governs neural activity during both rest and task performance. Resting-state activity is typically collected by a five- to twenty-minute fMRI scan while a participant lies still and stares at a black screen with a central fixation cross. Participants are instructed to rest and try not to think of anything in particular. While resting, slow fluctuations in BOLD signal in the absence of a goal-directed action or external input correspond to functionally relevant networks. These networks can provide important information about network functioning during tasks. Here we review both task-based FC and resting state FC in both ASD and DCD. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 32 Resting State Research in ASD and DCD ASD AON connectivity. Altered connectivity in AON systems has been observed in functional task-based studies in ASD and DCD. Many of these studies have reported disrupted connectivity in emotional processing regions in individuals with ASD relative to TD controls. Rudie et al. (2012) showed that individuals with ASD displayed significant reductions in connectivity between right IFG and inferior and superior parietal lobules while passively viewing emotional facial expressions. During an intentional causal attribution task, Kana, Libero, Hu, Deshpande, and Colburn (2014) explored the recruitment of AON areas and found that participants with ASD showed lower activation in the TPJ, right IFG, and left premotor cortex, as well as reduced FC between the TPJ and motor areas. In a combined task-based and resting-state study by Alaerts et al. (2014), the authors found that posterior STS (pSTS) hypo-activity during an emotion discrimination task and under-connectivity with fronto-parietal AON at rest were predictive of emotion recognition deficits in adults with ASD (Alaerts et al., 2013.). In a follow-up study looking at age-related changes, the same group reported atypical development of pSTS connectivity with the fusiform and angular gyri as well as with other AON regions in ASD (Alaerts et al., 2015). No clinical measures of social severity (e.g., ADOS or ADI-R) were related to any of the resting state FC measures, however, the authors did hypothesize that deficiencies in the connections of the visual pSTS may precede alterations downstream in fronto-parietal AON regions (Alaerts et al., 2013), which supports the “multiple routes” theories of ASD. Overall, tasked-based connectivity findings indicate reduced AON connectivity with other social processing regions outside the AON in ASD populations. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 33 Findings from resting-state FC research that focus on AON regions are more mixed. Fishman et al. (2014) explored resting-state FC of the AON in children with ASD but found no significant overall group differences compared to a TD cohort. However, within a sample of their most severely symptomatic ASD participants, the authors observed greater connectivity between the right anterior inferior parietal sulcus and left superior frontal gyrus and posterior cingulate cortex in the ASD group compared to the TD group (Fishman, Keown, Lincoln, Pineda, & Müller, 2014). Shih et al., (2010) found direct group comparison differences in TD and ASD children in frontal regions (ASD > TD) but found no significant reduction in FC in a direct comparison between groups in regions associated with imitation. However, structural equation modeling revealed reduced effects of the IPL on the IFG with increased influences on the dorsal prefrontal cortex (dPFC) and on the IFG in ASD participants (Shih et al., 2010) indicating that children with ASD have atypical connectivity at rest within and between regions of the AON other networks. In a third study by Alaerts et al. (2015), the authors explored graph-theoretical properties of the AON using resting-state fMRI data of adolescents and young adults with ASD. The ASD group displayed reduced network density (fewer connections) compared to the TD group, indicating overall lower connectivity of the AON in ASD. Only one study to date has looked at the relationship between motor skills and resting state connectivity. In a recent study investigating the visual-motor network in ASD, an increase in intrinsic asynchrony was observed between visual and motor systems in children with ASD compared to TD peers (Nebel et al., 2016). The strength of visual-motor synchrony was related to imitation skills as measured by a modified FAB SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 34 test in individuals with ASD as well as social skills measured by the Social Responsiveness Scale, Second Edition (SRS-2; Nebel, Eloyan, Nettels, & Sweeney, 2016). This is the first study to relate social and motor deficits to motor dysfunction in ASD. However, because social and motor skills in ASD may be co-linear (Dewey et al., 2007) results have to be interpreted with caution. Overall, data on AON connectivity indicate that it appears to be disrupted in ASD during a task and while at rest. Both social and motor performance has been associated with FC in ASD suggesting sample variability should be more closely investigated to understand aberrant findings in network function. In general, there is decreased connectivity in the AON system in ASD, however, it should be noted that in other intrinsic resting state networks both hyper- and hypo-connectivity have been observed in ASD (e.g., salience network; Green, Hernandez, Bookheimer, & Dapretto, 2016) and these findings have been related to social processing (Cerliani et al., 2016; Hoffmann, Brück, Kreifelts, Ethofer, & Wildgruber, 2016; Jung et al., 2017). DCD resting state. Very few resting state studies have been published on DCD populations. To date, no study has looked at the intrinsic resting state network specifically, but connectivity at the region of interest (ROI) level has been investigated. The McLeod group (2014, 2016) has published two studies on primary motor cortex connectivity at rest (McLeod 2014, 2016). Both studies compared resting-state connectivity with the primary motor cortex in children with DCD, ADHD, those with dual DCD/ADHD diagnoses, and TD controls. In their first paper, McLeod et al. (2014) found decreased connectivity with structures of the basal ganglia (including the caudate, putamen and globus pallidus) in children with DCD and/or ADHD, as well as in SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 35 sensorimotor regions (inferior frontal gyri, and posterior insular cortex) compared to all other groups. The authors suggest that these connectivity disruptions may impact motor attention, planning and execution processes. The authors also speculate that co- occurrence of neurodevelopmental disorders may have a distinct impact on FC (McLeod et al., 2014). The same group published a paper on the same data looking at laterality in regions they found to have distributed connectivity with the primary motor cortex in their clinical groups. The authors observed that children with DCD had weaker within- hemisphere connectivity between the primary motor cortex and right putamen compared to the TD and ADHD groups. Interestingly, the DCD group showed stronger connectivity within- and between-hemispheres between the left and right primary motor cortex and sensory-motor cortices (McLeod, Langevin, Dewey, & Goodyear, 2016). These findings indicate that children with DCD may lack strongly lateralized functional connections between the right putamen and the motor cortex, and that this lack of lateralization may be specific to DCD. The authors hypothesized that the lack of hemispheric dominance of the right putamen’s functional connections may help explain the bimanual coordination deficits observed in children with DCD. ASD and DCD AON FC and grey matter differences. Despite the unbalanced number of studies for the two clinical populations, there is some evidence that supports overlaps in network disruption in ASD and DCD. Specifically, the primary motor cortex has been identified in both populations as a region indicated in motor deficits. McLeod et al. (2016) observed decreased connectivity with the left primary motor cortex and right IFG in the DCD group compared to controls and stronger FC between the left SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 36 primary motor cortex and the frontopolar cortex in children with co-occurring DCD and ADHD. While no primary motor cortex connectivity findings have been reported in ASD, increased cortical thickness in the primary motor cortex has been reported. In a study comparing high-resolution structural scans in ASD with similar TD and clinical populations (ADHD and those with ASD and ADHD [ASD + ADHD]), researchers found that children with ASD only showed increased grey matter volume and surface area in the bilateral primary sensory cortices and in the right primary motor cortex (Mahajan et al., 2016). They also reported that all children with ADHD regardless of ASD diagnosis had increase left inferior parietal cortex surface area. The research group related these changes to measures of functional motor skills. Impaired praxis (measured by the FAB modified for children) was associated with increased grey matter volume in the right sensory motor cortex in the ASD + ADHD group. Children with comorbid ASD + ADHD had a positive relationship between grey matter volume in the bilateral sensory motor cortices and manual dexterity, whereas children with ASD only showed a negative relationship. The authors suggest that ASD is associated with abnormal morphology of cortical circuits crucial to motor control and learning and that anomalous overgrowth of these regions, particularly the sensory motor cortex, may contribute to impaired motor skill development (Mahajan et al., 2016). Taken together, these studies suggest that motor deficits are related to hyper-connections/overgrowth of the primary motor cortex. Further research is necessary to better understand these results as well as larger intrinsic networks and overlaps between ASD, DCD, and ADHD. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 37 AON White Matter Integrity in ASD and DCD Diffusion weighted imaging (DWI) is a technique used to measure the diffusion of water in the brain based on Brownian motion of water. Disruptions in water’s diffusion are thought to reflect microscopic details about the white matter and surrounding tissue architecture. Data from DWI scans provide both qualitative and quantitative information about diffusion that can be used to map and measure the integrity of white matter in the brain. Disruptions in fractional anisotropy (FA; an index of the degree of anisotropy of a diffusion process), mean diffusivity (MD; average diffusion in all directions), and radial diffusivity (RD; index of axonal diameters) can be quantified and associated with functional brain activity (Fishman et al., 2015), as well as behavioral and clinical variables. Even though functional connections can exist between two regions with no direct anatomical connections (Greicius, Kaustubh, Menon, & Dougherty, 2009), DWI can provide information regarding organization and microstructure of white matter tracts that link cortical areas to functional circuits. Below we discuss DWI findings of the AON in both ASD and DCD populations. ASD white matter. As mentioned above, individuals with ASD may have atypical cortical activation and network function in the AON. It is possible that the white matter tracts that connect grey matter and subcortical regions also may be impaired. The arcuate fasciculus is a bundle of axons that forms part of the superior longitudinal fasciculus (SLF), which is a major white matter association tract and connects the frontal, parietal, and temporal perisylvian cortex (Catani & Thiebaut de Schotten, 2008). The SLF provides tracts between structures that correspond to the AON (Ameis & Catani, 2015). As with functional data, the few studies that focus specifically on AON SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 38 pathways in ASD report disparate results. Some find DWI differences in the network (Fishman et al., 2015) while others find none (Chien, Gau, et al., 2015) when comparing individuals with ASD to TD controls. Fishman et al., (2015) conducted a large resting state and DWI study on 50 children with ASD and 45 TD children to investigate functional and structural connectivity in brain regions related to imitation in the SLF. The group observed reduced FA and increased MD in white matter tracts connecting the bilateral IFG and dorsal lateral prefrontal cortex in the ASD group (Fishman et al., 2015). Social severity scores from clinical ASD assessments (ADOS-2 Total score) was negatively correlated with FA of the tract connecting the left IFG and left medial prefrontal cortex, such that lower FA was associated with more severe ASD symptoms. According to a meta- analysis of diffusion tensor imaging (DTI) studies --a DWI technique-- in ASD (Aoki, Abe, Nippashi, & Yamasue, 2013), the SLF is one of only a few consistent sites of reduced anisotropy in ASD (with some exceptions, see e.g., Koldewyn et al., 2014). These differences in the microstructural organization of white matter correlated with weaker resting-state FC and greater ASD symptomatology indicate that white matter tracts in AON may contribute to imitation impairment (Fishman et al., 2015). Another important tract relevant to ASD is the corpus callosum (CC). The CC is a thick tract connecting the brain’s left and right hemispheres. Regions of the CC are topographically organized and many of the sub-regions connect bilateral areas of the AON. The genu of the CC primarily connects prefrontal association areas (Hofer & Frahm, 2006) as well as anterior inferior parietal regions (De Lacoste, Kirkpatrick, & Ross,1985). The anterior part of the CC connects premotor and supplementary motor SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 39 cortices, while the mid-body of the CC connects primary motor areas followed by the posterior regions that connect the primary motor and primary sensory areas (Wahl et al., 2007). Individuals who fail to develop a CC have impairments in language and social cognition that overlap with ASD symptomatology (Paul, Corsello, Kennedy, & Adolphs, 2014). A diminished CC is another relatively consistent finding in ASD literature (Egaas, Courchesne, & Saitoh, 1995; Frazier & Hardan, 2009; Hardan et al., 2009; Keary et al., 2009; Piven, Bailey, Ranson, & Arndt, 1997; Vidal et al., 2006). In a meta-analysis of cross-sectional areas of the CC in ASD, Frazier and Hardan (2009) found that the rostral body of the CC connecting premotor and supplementary motor neurons has the greatest reduction. A more recent study, however, did not replicate this finding (Tepest et al., 2010). Once again, inconsistencies highlight how heterogeneity in ASD needs to be addressed in future research. Correlations have been found between CC measurements and neurological tests for social deficits (Keary et al., 2009), however, no studies have looked at both social and motor deficits in relationship to this tract. Nonetheless, these findings collectively indicate significant microstructural abnormalities and alterations in the organization of white matter fibers in ASD, which may translate into functional impairments in brain activation and functional connectivity. DCD white matter. Some of the earliest neuroimaging papers published on DCD are DWI studies revealing reduced white matter integrity in motor-related networks in children with DCD, particularly in sensorimotor tracts (Debrabant et al., 2016; Langevin, Macmaster, Crawford, Lebel, & Dewey, 2014; Zwicker, Missiuna, Harris, & Boyd, 2012). Zwicker et al. (2012) was the first to identify reduced axial diffusivity in the corticospinal tract and posterior thalamic radiation in children with DCD compared to TD SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 40 controls. They also found a significant positive correlation between axial diffusivity scores and motor skill level measured by the MABC-2. Another DWI study identified reduced FA in the SLF and the superior/parietal portion of the CC in children with DCD (Langevin et al., 2014). These findings were unique to DCD compared to children with ADHD, co-occurring DCD and ADHD, or TD peers. Most recently, reduced FA was identified in the internal capsule of children with DCD compared to TD children (Debrabant et al., 2016). Overall, findings indicate that children with DCD have disrupted white matter integrity in tracts that connect to motor planning and processing cortical regions. One adult study with participants with poor motor skills who were not diagnosed as children but have a probable DCD diagnosis (pDCD) found broadly similar results of decreased FA in the SLF in a group of 12 pDCD compared to 11 age-matched controls (Debranant et al., 2012). These findings suggest that neurobiological alterations along white matter tracts that are known to support motor perception and planning persisted along the lifespan of individuals with DCD or pDCD (Williams et al., 2017). Adults with pDCD also had lower FA in the corticospinal tract and lower mean diffusivity in the internal capsule and inferior longitudinal fasciculus (Williams et al., 2017). This suggests reduced white matter integrity in parietofrontal and corticospinal tracts. Structural comparison of DCD and ASD. Broadly, data from DWI studies suggest that the ASD and DCD have a common pattern of reduced FA in SLF. Motor skills have been found to be linked to FA of the SLF in DCD populations (Zwicker et al., 2012), and social severity linked to FA in the same region in ASD samples. No studies have yet explored how social skills relate to the SLF in DCD or motor skills in ASD nor SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 41 compared the two groups directly. It is possible that reduced SLF integrity has discrete patterns for each group. To date, one only neuroimaging study has compared ASD (high functioning) and DCD. Instead of looking at white matter microstructure, however, Caeyenberghs et al., (2016) used graph theory analysis to relate cortical structures to motor performance in children with DCD (n = 11), ASD (n = 15), co-occurring ASD and DCD (ASDd, n = 8), and TD (n = 19). Despite the relatively small sample size, behavioral and structural network parameters were detected. Behaviorally, individuals with any DCD diagnosis (DCD, ASDd) were found to have worse performance on motor ability (indexed by the MABC-2), and visual motor integration (indexed by the Beery VMI) compared to ASD and TD participants. At the neurological level, the ASD group was found to have the most abnormal network connectivity; notably, increased normalized path length and higher values of clustering coefficient, while children with DCD displayed a global network organization that was similar to TD children. These findings are inconsistent with Rudie et al. (2012) who reported decreased long-range FC in ASD. Caeyenberghs and colleagues (2016) concluded that increased clustering and path lengths found in ASD reflect unbalanced and inefficient network organization. At the nodal level, the ASD group displayed increased clustering coefficient in the right IFG orbitalis and decreased clustering coefficient in the right cingulate gyrus compared to the TD cohort. Unique to the DCD group was increased clustering coefficient in the lateral orbitofrontal cortex–a part of the expanded limbic system. Children with ASDd had more widespread deviations from typical patterns of cortical thickness than those seen in children with only DCD or only ASD, such as alterations of clustering coefficients in the pars orbitalis SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 42 of the right IFG, paralimbic regions, primary motor areas, and association areas compared to the TD group. Notably, the ASDd group showed increased clustering of the AON regions (left IFGpo) compared to the ASD group as a whole. Together, these results indicate that abnormal AON function in ASD may be underscored by an additive effect of both social and motor deficits since the IFGpo had typical clustering coefficient that was not altered in the ASD only or DCD only groups. Together, diffusion and cortical thickness findings suggest that individuals with ASD have more severe structural abnormalities and that individuals with ASDd symptomatology may exhibit unique deficits compared to their peers with either ASD or DCD. Conclusions and Future Directions This review covered current literature and theories of AON across three levels of neurobiology in both ASD and DCD populations: task, resting state networks, and white matter structure. With limited published research on the DCD population, it is hard to point to any definitive findings comparing the two clinical populations. What is already apparent, however, is the complexity of the AON and motor systems networks (e.g., sensorimotor, fronto-parietal and cerebellar). Findings from dual diagnoses (e.g., ASD+ADHD, DCD+ADHD) research suggest individual symptomatological differences can have large implications for understanding neural functioning and behavior in ASD. It is clear from ASD research that social deficits are linked to AON functioning during fMRI observation and imitation tasks. What is less clear is how motor skills relate to AON function in ASD. One study looking at motor skills in ASD related motor deficits to weaker connectivity in motor areas (Nebel et al., 2016). DWI work further supports this SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 43 association between motor skills and structural connectivity in a few DCD diffusion papers (Langevin et al., 2014; Zwicker et al., 2012). Because DCD is a common comorbid condition in ASD, understanding how motor skills relate to social skills will help identify behavioral and neurological patterns discretely associated with ASD. As mentioned above, to date only one study has compared ASD and DCD populations. Future research should examine motor and social networks across these two populations as well as with a typical control group. Limitations. There are several limitations to this review. First, the volume of ASD publications related to the AON vastly outnumbers the DCD publications. This imbalance is compounded by the average difference in population sample size. The average study’s sample size for ASD is much larger than the sample sizes in DCD research. Studies with larger DCD sample sizes are needed to make fair comparisons. Secondly, this review was restricted to AON-related studies (with a few exceptions). Further examination of these two populations across other networks such as mentalizing and emotional-related networks is vital to understanding the extent to which motor impairment may affect social impairment in both disorders. Future work should also explore ASD-DCD differences in other motor regions such as the cerebellum and subcortical regions such as the basal ganglia and putamen. Previous work has posited a pathological role for the cerebellum in ASD (Fatemi et al., 2012; Mostofsky et al., 2009) as well as in DCD (Brown-Lum & Zwicker, 2015) which makes it an exceptionally relevant region to study. Potential future study designs. Future studies should examine the AON systematically across both ASD and DCD clinical populations being careful to consider SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 44 the heterogeneity of each group. The advantage of a multi-modal study that looks at both functional and structural characteristics is the ability to conduct a more comprehensive pattern analysis. Unique patterns identified from different modalities could be used to classify participants into ASD, DCD, ASDd, and TD control groups. Utilizing pattern classification of neuroimaging data, several studies have used predictive models for ASD diagnosis. For example, functional brain activation and connectivity were used for pattern classification to separate ASD from TD peers (Anderson-Hanley, Tureck, & Schneiderman, 2011; Coutanche, Thompson, & Schultz, 2012; Kaiser & Pelphrey, 2012; Kana et al., 2014; Murdaugh et al., 2012; Spencer et al., 2011). A few studies also have applied classification analyses to DWI data (Ingalhalikar, Parker, Bloy, Roberts, & Verma, 2011; Lange et al., 2010) to predict ASD group membership. Thus, accurate and reliable classification of participants with ASD is a promising step towards the diagnostic utility of such measures. To date, no study has modeled a classifier for DCD, however, if applied, one could distinguish between, ASD, DCD, ASDd, and TD given the unique functional and structural patterns identified in each group thus far. For neurodevelopmental disorders that rely on behavioral diagnoses, an applied neural classifier could be helpful in deciding difficult and borderline cases. Attempts at neural classifiers have mainly relied on measures of brain function, using experimental tasks that may be inappropriate for many individuals with ASD, particularly for those who would be considered lower- functioning or young children. Future work may find more success in classification analysis utilizing resting-state and structural MRI data. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 1 45 Ultimately, a multimodal technique could become more sensitive to symptomatology, which can lead to more accurate diagnoses of ASD and DCD (and possibly ADHD) and also aid in designing more tailored interventions for these clinical groups. ASD has been identified as a neural system disorder with complex neurobiology, and any biomarker would need to be multivariate, possibly including several aspects of biology and genetics (Ecker, Spooren, & Murphy, 2013). It has become increasingly clear that, like ASD, DCD has a partially genetic basis (Mosca et al., 2016) with heritability estimates approaching 70% (Lichtenstein, Carlström, Råstam, Gillberg, & Anckarsäter, 2010; Martin, Piek, & Hay, 2006). Distinct genetic biomarkers have also been explored between DCD and ADHD children revealing a strongly shared additive genetic component between most subtypes of ADHD and DCD and among the subtypes of each disorder compared to the other (Martin et al., 2006). Looking across ASD and DCD could help identify possible subtypes in ASD as well as additional DCD groups. The question still to be addressed is whether ASD and DCD are on continua of severity of motor and social-communication parameters with shared neural mechanisms or whether the disorders represent unique and distinct patterns of impairment. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 46 Chapter 2. Brief Dissertation Introduction This dissertation is comprised of three neuroimaging studies that investigate neural networks underlying social and motor processing in autism spectrum disorder (ASD). All three studies compared children and adolescents with ASD to a second clinical population that has motor but not social deficits, developmental coordination disorder (DCD) and to a group of typically developing children (TD) without any deficits. The overarching proposition of this dissertation is that the neural mechanisms underlying motor impairment contribute to a better understanding of the heterogeneity of neural signatures among individuals with ASD. To date, no existing research directly compares social and motor symptomatology and tests for a shared disturbance in underlying neurobiological mechanisms in ASD. Task-based functional and structural neuroimaging studies have explored either social or motor functioning in ASD discretely; however, such studies often report contradictory findings. This is in part due to the lack of consideration for the heterogeneity of this clinical population. To date, no study has used a multimodal approach to investigate the relationship between the neural mechanisms underlying multiple ASD impairments, which is essential to understanding the complexity of ASD and to developing more effective treatments. To address this scientific gap, this dissertation assesses how motor deficits relate to social and motor processing deficits through functional and structural brain imaging studies. Capitalizing on the simultaneous social and motor processes employed during imitation of human actions, imitation is used as a catalyst to evaluate how social and motor deficits interact. A set of three unified experiments was performed across ASD, DCD, and TD participants. Data from these studies elucidate interactions between social and motor neural networks and behavioral symptoms across disorder profiles. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 47 To this end, this dissertation utilizes functional task-based activation, resting state functional connectivity (FC), and diffusion-weighted imaging to examine neural activity during imitation, FC at rest, and structural connectivity (SC) in children and adolescents who vary in social and motor ability. The aims of each study and their hypothesis are described below. Participants ASD and DCD. The intent of this dissertation was to look at ASD along a continuum of those with varying degrees of motor skills. However, initial motor skill analyses revealed that 80% of our ASD sample had a dual diagnosis of DCD or qualified for DCD based on diagnostic DCD measures. Only six ASD participants did not have or qualify for DCD. Moreover, those who did not qualify for DCD had motor scores that fell well within the typical range. Thus, our ASD participants fell into two distinct subgroups, those with and without motor deficits. When removing the participants with no motor skill impairments, the correlation between social and motor skills went from non-existent (r = .013, p = .95) to a nearly significant relationship between skills (r = -.452, p = .091; Figure 1). Because the ASD without motor impairment subgroup was too small for group-level data analysis, it was decided that at this point in time, it would be more informative to compare participants who have ASD and motor impairments (ASDd) with those who have only motor impairments (DCD). The subgroup of individuals having ASD without motor impairments are thus left for future analyses and not included in this dissertation. Participant recruitment and eligibility. ASDd participants were recruited from clinics in the greater Los Angeles healthcare system, through local public and private schools, and through word-of-mouth and social media advertising. Individuals aged 8 to 15 with ASDd, SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 48 DCD, and TD controls participated in the study. ASDd participants were high functioning (IQ 80-134) and had received a diagnosis either through a clinical ASD diagnostic interview, an ASD diagnostic assessment, or both. We assessed clinical symptoms using the Autism Diagnostic Observation Schedule, Second Edition, Module 3 (ADOS-2; Lord et al., 2000) . Exclusion criteria for ASDd included: (a) IQ <80 (in cases where the full-scale IQ was less than 80, participants were included if their verbal IQ score or perceptual reasoning IQ score were greater than 80 as assessed by the Wechsler Abbreviated Scale of Intelligence fourth edition (WASI; Wechsler, 2011); (b) history of loss of consciousness greater than five minutes; (c) left handed; (d) not sufficiently fluent in English or parent who did not have English proficiency; (e) a diagnosis of other neurological or psychological disorders except for attention deficit disorders or generalized anxiety disorder (since those are highly comorbid with ASD); (f) a Movement Assessment Battery for Children, Second Edition (MABC-2; Henderson, Sudgen, & Barnett, 2007) score greater than the fifteenth percentile, indicating no clinical risk for DCD, and a score on the Developmental Coordination Disorder Questionnaire (DCDQ) indicating unlikely DCD diagnosis, (g) Gestational age < 36 weeks and screened for MRI compatibility (see supplementary materials). Participants were also evaluated for their capacity to give informed consent and then provided their written consent after being informed about the study procedures in accordance with the study protocols approved by the University of Southern California Institutional Review Board. DCD participants were recruited from therapy clinics throughout California, through Los Angeles-area public and private schools, and through national DCD/Dyspraxia support groups, as well as from community events, word of mouth, and local advertising. In addition to the exclusion criteria established for the ASDd group SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 49 (minus condition (f), which was reversed and made into an inclusionary factor, with a child needing to perform below the 15 th percentile to be included into the DCD group), DCD participants were excluded if they had (a) personal diagnosis or an immediate family member with a diagnosis of ASD or (b) a Social Responsiveness Scale-2 (SRS- 2; Constantino et al., 2003) score indicating risk of ASD (> 60) and a subsequent ADOS-2 score in the clinical range. Healthy control (TD) participants were recruited through flyers posted in the local community, social media, and website postings. Exclusion criteria for TD control participants included the first four elements of ASD exclusion criteria listed above. TD controls additionally were excluded if they had any psychological diagnosis or neurological disorder, including attention deficit disorders and generalized anxiety disorder or if they scored below the twenty-fifth percentile on the MABC-2 or were likely or suspected to have a DCD diagnosis based on the DCDQ score. Two ASDd participants and four DCD participants were on previously prescribed psychotropic medication at the time of data collection. Table 1 describes the sample size for each study. Only participants with high-quality MRI data were selected for each independent study. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 50 Table 1 Sample Size Per Chapter Chapter Controls ASDd DCD Ch. 3 Imitation n = 17 (4 female) n = 13 (1 female) n = 10 (3 female) Ch. 4 Resting State n = 18 (5 female) n = 15 (1 female) n = 10 (3 female) Ch. 5 Diffusion n = 13 (3 Female) n = 10 (1 Female) n = 9 (3 Female) Figure 1. Scatterplot of social and motor skills in each group. ASD = autism spectrum disorder; ASDd = autism spectrum disorder with motor impairments; DCD = developmental coordination disorder; TD = Typically developing. The ASD only group is not included in the remainder of this dissertation. ASD: R = .164, p = .48; DCD: R = .217, p = .95; TD: R = .164 p = .546. Task-based Functional Magnetic Resonance Imaging (fMRI) Study The first study, which is reported in Chapter 3, examines how social and motor skills mediate neural activity in the action observation network (AON) during an imitation task. Numerous neuroimaging studies have reported that imitation consistently employs brain regions that overlap with the AON and putative mirror neuron system. Because some ( SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 51 individuals with ASD have difficulty not only with social behavior but also with action imitation (Mostofsky et al., 2006), discrepancies found in ASD imitation literature may be due to the heterogeneity of motor skills in ASD. To test this hypothesis, neural activity elicited in the AON during action imitation was compared between the ASDd, DCD, and TD groups. Social and motor behavioral performance measures were then correlated with task-induced neural activity using functional magnetic resonance imaging (fMRI). We then examined brain regions that demonstrated significant differences between groups to identify shared patterns of social and motor disruption in ASDd and DCD during imitation. Group contrasts and behavioral correlations were also tested in regions of interest (ROIs) that were selected from a meta- analysis that previously examined neural activation during imitation in neurotypicals (Caspers et al., 2010). We predict that during motor imitation the ASDd and DCD participants will show altered patterns of activation, especially in the frontal areas of the AON, as compared to the TD cohort. We also predict that motor ability will significantly relate to brain activity in the AON in both clinical groups. Finally, based on previous findings (e.g., Dapretto et al., 2006), we predict that social impairments will be related to activation in the inferior frontal gyrus (IFG) in the ASD group. These results will be a first step in deciphering whether aberrant findings in neural disruptions found in previous ASD research can potentially be explained in part by the heterogeneity of motor deficits in ASD. Resting-state fMRI Study The second study, reported in Chapter 4, investigates the relationship between social and motor deficits and resting-state networks. Aberrant resting state fMRI findings are SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 52 common in ASD. Specifically, atypical FC has been observed in social and emotion-related brain regions (von dem Hagen, Stoyanova, Baron-Cohen, & Calder, 2013) and in imitation and AON-related brain regions (Shih et al., 2010). This study aims to test the hypothesis that social and motor deficits are associated with a disruption of intrinsic resting state networks, specifically, in AON and default mode network (DMN) connectivity. In order to test this, we used the same previously mentioned ROIs that were identified in an imitation meta-analysis (Caspers et al., 2010) to investigate within AON network FC. We use a different previously established ROI for the DMN network FC analysis (Fox, Zhang, Snyder, & Raichle, 2009). These connectivity measures were then compared between groups and correlated with social and motor skills. We predict that group FC differences in both networks will be related positively to social and motor skills. We also predict that the ASDd and DCD groups will have discrete and common FC patterns compared to the TD group. These results will elucidate how intrinsically organized networks at rest relate to social and/or motor impairments observed in ASD. Diffusion Weighted Imaging Study The third study, reported in Chapter 5, investigates the relationship between social and motor deficits and white matter (WM) microstructure. Abnormal WM microstructure is thought to be related to the AON in ASD (Fishman et al., 2015). In this study, we replicate and extend prior analyses of WM integrity in ASD by measuring WM microstructure in functional regions of the AON and comparing SC between groups. We hypothesize that the ASDd and DCD groups will have common and discrete disrupted patterns of SC. Moreover, we hypothesize that group WM microstructure disruption will be associated with social and motor deficits in SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 2 53 regions related to imitation. Next, generalized fractional anisotropy values will be calculated between the same functional imitation ROI’s used in study 1 and study 2 and correlated with social and motor skills. We hypothesize a positive relationship between generalized fractional anisotropy values and social and motor skills in AON connected tracts. Together, these results will elucidate the relationship between functional and structural neurobiology in social and motor networks and how impairments in social and motor skills interact in ASD. Overall, this research contributes to developing a comprehensive framework of the AON across a range of individuals with social and motor symptomatology at different neurobiological levels. A comprehensive framework with which to understand social-motor deficits in ASD will provide a valuable resource for the wider scientific community as we expand our understanding of developmental disorders. The results of this dissertation illuminate the extent to which the AON is modulated by motor deficits in ASD and how individual symptom variations interact with regions within the network. If motor deficits contribute to the modulation of social deficits in ASD, then targeted motor therapies (e.g., imitation therapy) could be developed to help improve social processing in ASD. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 54 Chapter 3. Action Observation Network Responses to Imitation in Autism Spectrum Disorder and Developmental Coordination Disorder Abstract Introduction: Previous studies have shown that motor networks like the action observation network (AON) are related to action understanding and social perception. It has been proposed that this network is disrupted in individuals with autism spectrum disorder (ASD), however, contradictory results question this hypothesis. While many clinicians and researchers report motor deficits in ASD, few have looked at how motor skills may mediate activation in these networks. To isolate the role of motor and social skills in the AON, this study aims to compare AON activation during imitation in children and adolescents with ASD who have social and also motor deficits (ASDd), to two groups: children with motor but not social deficits (developmental coordination disorder; DCD), and typically developing (TD) children. Methods: Thirteen children and adolescents with ASDd, 10 with DCD, and 18 TD children underwent functional magnetic resonance imaging while they imitated hand actions, emotional facial expressions, and non-emotional facial expressions. Between- group activation differences, as well as relationships between activation and behavioral skills, were evaluated in the AON. Results: All three groups significantly elicited the AON during imitation. However, relative to TD participants, ASDd and DCD participants displayed reduced AON activity in the bilateral inferior frontal gyrus (IFG; uncorrected). Moreover, in the ASDd group, SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 55 AON activation in the left hemisphere was generally related to motor skills whereas AON activation in the right hemisphere was related to social skills. Neither social nor motor skills were related to DCD activation in the AON. Conclusions: Overall, the findings of this study support AON disruption in ASDd during imitation. Brain-behavior relationships demonstrate that motor skills, as well as social skills, mediate AON activation in ASDd participants. Finally, these results also indicate the mediation of social and motor skills may be lateralized in the ASDd group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 56 Autism spectrum disorder (ASD) is a developmental neurological disorder characterized by social, communication, and behavioral deficits such as restricted and repetitive behaviors and sensory problems (Reynolds, Billington, et al., 2017). ASD often co-occurs with other disorders including those associated with motor impairments such as developmental coordination disorder (DCD). Over the last few decades, many researchers have proposed adding imitation (Williams, Casey, Braadbaart, Culmer, & Mon-Williams, 2014) and motor skill deficits (Fournier, Hass, Naik, Lodha, & Cauraugh, 2010) to the list of ASD’s core diagnostic features as poor imitative skills have been associated with social impairments seen in individuals with ASD (Edwards, 2014). Imitation, a fundamental aspect of human behavior, is critical to developing social, communication, and motor skills (Pfeifer, Iacoboni, Mazziotta, & Dapretto, 2008). It facilitates learning and is foundational to social development (Rogers, Hepburn, Stackhouse, & Wehner, 2003). Given the importance of imitation in typical social and cognitive development, it has been suggested that imitation deficits in ASD may lead to social processing difficulties (Hadjikhani, Joseph, Snyder, & Tager-Flusberg, 2007; Williams et al., 2006; Oberman et al., 2005; Villalobos, Mizuno, Dahl, Kemmotsu, & Müller, 2005). However, not all investigations of imitation in ASD align with this hypothesis. For example, some studies suggest that not all types of imitation skills are impaired in individuals with ASD. Specifically, Hamilton et al. (2007) found that individuals with ASD demonstrated an intact ability to imitate goal-directed hand actions. Others have suggested that intact imitation may be context dependent, such as spontaneous versus elicited imitation (Ingersoll, 2008). Thus, how and to what extent imitation may be impaired in ASD populations remains unclear. ASD manifests itself SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 57 through a variety of symptomatological presentations and comprises a full range of cognitive and language abilities, and this heterogeneity only further complicates research findings. One neural network that has received much attention in ASD and imitation literature is the mirror neuron system (MNS). The MNS is a series of brain regions elicited during both action observation and while executing the same (observed) action. Mirror neurons were initially discovered in the macaque monkey in the late 1990s (Gallese, Fadiga, Fogassi, & Rizzolatti, 1996). Since then, human neuroimaging studies have associated the MNS with several sociocognitive and motor functions (Kilner & Lemon, 2013). The core regions of the MNS include the ventral premotor cortex, the inferior frontal gyrus (IFG), and the inferior parietal lobule (IPL; Van Overwalle & Baetens, 2009). An altered neural response during imitation tasks in these regions in individuals with ASD led to the “mirror neuron dysfunction hypothesis” (Dapretto et al., 2006; Oberman & Ramachandran, 2007; Ramachandran & Oberman, 2006; Williams et al., 2001). This hypothesis states that the MNS’s self-other mapping function is impaired in ASD, which in turn leads to difficulties in imitation as well as other aspects of social cognition (Hamilton, 2013). Although several neuroimaging studies have reported abnormal MNS activation during imitation in ASD (Dapretto et al., 2006; Kana, Wadsworth, & Travers, 2011; Williams, 2008), others have failed to find atypical ASD responses in imitation tasks compared to TD peers (Dinstein et al., 2010; Fan et al., 2010; Raymaekers et al., 2009), providing evidence against a dysfunction of the MNS in ASD (Hamilton, 2013; Southgate & Hamilton, 2008). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 58 While it is possible that some of the aforementioned conflicting results may be due to age effects--for example, one study found hypoactivation of the IFG in children but not adult samples (Bastiaansen et al., 2011)--the conflicting findings also could be due, in part, to the heterogeneity of phenotypes among ASD participants among different studies. Since ASD is highly heterogeneous and frequently comorbid with conditions such as anxiety, attention deficit hyperactivity disorder (ADHD), epilepsy, fragile X syndrome, neuroinflammation and immune disorders, sensory processing disorders, obsessive-compulsive disorder, and DCD, variation in symptomatology can confound findings and make it difficult to disentangle discrete ASD-only related neural mechanisms of imitation. Specifically, because motor regions comprise the bulk of the MNS and because motor abilities are highly heterogeneous in ASD, it is possible that motor skill differences explain some of the previous divergent MNS findings. Indeed, data indicate that up to 80% of individuals with ASD have motor deficits (Fournier et al., 2010; Green et al., 2009; Hilton, Zhang, Whilte, Klohr, & Constantino, 2012). Thus, action imitation difficulties may arise from problems related to motor planning or execution, and MNS differences may be more pronounced in this ASD subgroup. Motor performance difficulties seen in individuals with ASD (Fournier et al., 2010) have been implicated in imitation deficits observed in ASD (Enticott et al., 2012; Mostofsky et al., 2006; Theoret et al., 2005). Therefore, mirroring mechanisms, mediated by motor ability as well as other networks, may respond differently in individuals with ASD and those with motor impairments such as DCD (also known as dyspraxia)--especially in the context of imitation. Moreover, there is evidence to suggest that MNS dysfunction may occur in deficits outside of ASD where motor skill SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 59 impairments are common. Specifically, MNS dysfunction has been observed in children and adults with DCD (For a review see Werner, Cermak, & Aziz-Zadeh, 2012). Individuals with DCD primarily display inherent motor and coordination deficits that are developmental in nature. If social skills impairments are present in DCD, they have been considered to be secondary effects arising from self-esteem issues related to not being picked for sports teams, etc. (Skinner & Piek, 2001). Thus, it is possible that the interaction between social and motor deficits and/or variance in motor deficits alone may resolve some of the aberrant MNS findings in ASD. Three studies have been published that directly focus on the MNS or, more expansively, on the action observation network (AON), in small samples of DCD (Licari et al., 2015; Reynolds; Reynolds, Kerrigan, et al., 2017). In a study by Licari and colleagues (2015), children with DCD activated the left superior frontal gyrus and IFG less and the right postcentral gyrus more than their TD peers during a finger sequencing task. Decreased activation of the IFG is consistent with the DCD “broken MNS” hypothesis. The authors hypothesized that the increased postcentral gyrus activation in their DCD sample was a result of learning effects. In a similar finger sequencing task, Reynolds, et al., (2015) reported decreased activity in the left IFG in 14 children with DCD compared to 12 age-matched TD controls, and found that motor skills (indexed by postural praxis) were related to activity in the IFG, thereby linking motor skills to AON dysfunction in DCD (no social skills were collected or reported). However, in a follow-up study, the authors compared 10 children with DCD to nine TD controls during observation of motor imagery, action execution, and action imitation and found no differences in MNS activation during a finger tapping SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 60 task (Reynolds et al., 2017). The results indicate that simple motor deficits in DCD do not mediate AON activation. The authors suggested that other networks contribute to the imitation deficits seen at the behavioral level such as attentional networks and motor planning processes. It is also possible that the different task protocols (finger sequences versus finger tapping) may have led to the contradictory findings. Finger tapping is arguably more common, and a simpler task may not have been salient enough to elicit group differences. Current Study The primary goal of the current fMRI study is to examine how motor skills relate to activation of the AON during motor imitation (using a faces and hand imitation task) in a subgroup of high-functioning children and adolescents with ASD who also have co- occurring or probable DCD (ASDd) compared to those with only DCD and their TD peers. Instead of restricting our functional analysis to the MNS, we decided to use the AON, which extends beyond the canonical MNS regions (such as IFG and IPL) and commonly includes also the superior temporal gyrus (STS: Caspers, Zilles, Laird, & Eickhoff, 2010) which has been tied to atypical activation in ASD during biological motion processing (Alaerts et al., 2015). We predicted that during motor imitation: (a) ASDd and DCD participants, compared to TD, will show altered patterns of activation, especially in the frontal areas of the AON; (b) motor ability will significantly predict brain activity in the AON in both clinical groups; and (c) based on previous findings (Dapretto et al., 2006), social impairments will be related to activation in the IFG the ASD group. The novelty of this study is in investigating the AON response during an imitation task SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 61 that includes both social and motor imitation using faces and hands as well as a behavioral assessment of motor ability. The findings of this study will provide further information about basic imitation in a subgroup of ASD and the functional significance of the AON in children with motor deficits. Methods Participant characteristics. Individuals ages 8 to 15 with ASDd (n = 13, 1 female), DCD (n = 10, 3 female), and TD controls (n = 17, 4 female) participated in the study. ASDd participants were recruited from clinics in the greater Los Angeles healthcare system, through local public and private schools, and through word-of-mouth and social media advertising. ASDd participants were high functioning (IQ 80-134) and had received a diagnosis either through a clinical ASD diagnostic interview, an ASD diagnostic assessment, or both. We assessed clinical symptoms using the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2; Lord et al., 2000). Exclusion criteria for ASDd included (a) IQ <80 (in cases where the full-scale IQ was less than 80, participants were included if their verbal IQ score or perceptual reasoning IQ score were greater than 80 as assessed by the Wechsler Abbreviated Scale of Intelligence 2nd edition (WASI; Wechsler, 2011); (b) history of loss of consciousness greater than five minutes; (c) left handed; (d) not sufficiently fluent in English or parent who did not have English proficiency; (e) a diagnosis of other neurological or psychological disorders except for attention deficit disorders or generalized anxiety disorder (since those are highly comorbid with ASD); (f) a Movement Assessment Battery for Children Second Edition (MABC-2; Henderson, Sudgen, & Barnett, 2011) score greater than fifteen percent, indicating minimal or no risk for DCD, and a score on SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 62 the Developmental Coordination Disorder Questionnaire (DCDQ) indicating unlikely or not suspected DCD diagnosis. All participants were born after 36 weeks of gestation and screened for MRI compatibility. Participants were also evaluated for their capacity to give informed consent and then provided their written consent after being informed about the study procedures in accordance with the study protocols approved by the University of Southern California Institutional Review Board. DCD participants were recruited from occupational therapy clinics throughout California, through Los Angeles-area public and private schools, and through national DCD/dyspraxia support groups as well as from community events, word of mouth, and local advertising. In addition to the exclusion criteria established for the ASDd group (a- f), DCD participants were excluded if they had (g) personal diagnosis or an immediate family member with a diagnosis of ASD or (h) a Social Responsiveness Scale-2 (SRS- 2; Constantino et al., 2003) score indicating risk of ASD (>60) and a subsequent ADOS- 2 score in the clinical range. Healthy control (TD) participants were recruited through flyers posted in the local community, social media, and website postings. Exclusion criteria for TD control participants included the first four elements of ASDd exclusion criteria listed above (a- d). TD controls additionally were excluded if they had any psychological diagnosis or neurological disorder, including attention deficit disorders and generalized anxiety disorder or if they scored below the twenty-fifth percentile on the MABC-2 or were likely or suspected to have probable DCD based on the DCDQ score. Two ASDd participants and four DCD participants were on previously prescribed psychotropic medication at the time of data collection. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 63 Behavioral measures. Motor skills were assessed using the MABC-2, a performance-based assessment that evaluates motor skill ability using three subtests: manual dexterity, gross-motor aiming and catching skills, and balance. Higher scores indicate better functioning. Subtest scores, as well as a total score, were calculated using the second (ages 7–10) and the third (ages 11–16) age bands. Item, subtest standard (scaled), and total scores based on the normative sample were examined in our analyses. The DCDQ is a 15-item screening questionnaire that ascertains gross and fine motor skill impairments that would contribute to a diagnosis of DCD. The questionnaire was utilized as an informative qualifier of DCD in our ASDd sample. The DCDQ yields a raw total score (score range: 15–75), higher scores indicate better motor functioning. In addition, parents of all participants completed the SRS-2. The SRS-2 is a parent survey comprised of five subscales regarding their child’s social skills: social awareness, social cognition, social communication, social motivation, and mannerisms. Scores are reported in T-scores. fMRI Task. A block design was used with separate action observation and imitation tasks in order to investigate blood oxygen dependent (BOLD) signal-related changes in the AON during imitation compared to at rest. During each task condition, subjects viewed three 3.75-second videos consisting of actors performing one of three types of actions: (a) emotional expressions (i.e., happy, sad), (b) non-emotional expressions (i.e., puffed cheeks, wiggling nose), and (c) hand actions (i.e., cutting paper, hammering a nail). See Figure 1 for stills of the video stimuli. Videos of each condition were presented three at a time with a 1.25-second black screen as a transition SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 64 between each video followed by a 15-second rest. During the rest blocks, participants were shown a black crosshair in the middle of a white screen. Five blocks of each action condition were alternated with rest in a pseudo-random sequence. Each participant’s tasks began with an additional hand condition block to habituate participants to the task which was later removed from the analysis in order to keep the number of trials between conditions equal, yielding a functional task total of eight minutes. Stimuli were presented using MATLAB with the Psychophysics Toolbox (Piven et al., 1997) with different stimuli for each block. See Appendix for a list of all stimuli used in the study. During the task condition, participants were asked to pantomime the actions they saw without moving their head or arms above their elbow and asked to lie still with their hands down during the rest condition. To help with MRI desensitization, and to ensure that all participants were pantomiming actions to a similar degree without moving their head, participants practiced the imitation task in a mock MRI. Participants were asked to practice lying still while making face and hand movements at home. If necessary, additional mock scanner practice was administered again prior to the actual fMRI scan. Furthermore, subjects were filmed while performing actions in the MRI and monitored in order to confirm they were imitating during the task. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 65 A. B. Figure 1. Stimulus and task design. (A) Stills taken from EmStim© stimuli videos. Each video played for 3.75 seconds. 1. Emotional faces (left to right: disgust, happy, angry). 2. Non-Emotional faces (left to right: puffed cheeks, closed eye, tongue to side). 3. Hand actions (left to right: drumming, hammering, grating). (B) Illustration of the task design. Stimulus blocks included three vides, each video consisted of 3.75 seconds of action followed by a 1.25-second black spacer between each video. Each resting block consisted of a 15-second white screen with a black crosshair. Image size: 800x600. The stimuli were presented via a digital goggle system. MRI data acquisition and analysis. Functional scan. fMRI data were acquired on a 3 Tesla MAGNETOM Prisma (Siemens, Erlangen, Germany) with a 20-channel head coil. The imitation scan consisted of an echo planar imaging (EPI; 150 whole brain volumes) acquired with the following parameters: TR = 2s, TE = 30 ms, flip angle = 90˚, 64x64 matrix, in-plane resolution 3x3mm, and 41 transverse slices, each 1.5mm thick, covering the whole brain with a multiband factor of three. Spin Echo EPI field mapping data was also acquired in AP and PA directions with identical geometry to the EPI data for EPI off- resonance distortion correction (TR = 1020 ms, TE1 = 10 ms, TE2 = 12.46 ms, flip angle = 90°, FOV = 224 × 224 × 191 mm 3 , voxel size = 1.5 × 1.5 × 1.5 mm). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 66 Anatomical scan. A structural T1-weighted MPRAGE was acquired for each subject (TR = 1,950ms, TE = 3.09ms, flip angle = 10˚, 256x256 matrix, 176 sagittal slices, 1mm isotropic resolution). Total scan time = 5 min. Within-subject analyses. Subject level functional imaging analyses were completed using FSL. The following preprocessing steps were taken: (a) brain extraction for non-brain removal; (b) spatial smoothing using a Gaussian kernel of FWHM 5mm; (c) B0 unwarping was performed in the y-direction; (d) standard ICA AROMA, which uses a robust set of theoretically motivated temporal and spatial features to remove motion-related spurious noise was performed on data; (e) a high pass filter with a cutoff period of 90 seconds was applied; and (f) subject-specific motion correction parameters were entered as nuisance regressors. Experimental conditions were then each modeled with a separate regressor derived from a convolution of the task design and a double gamma function to represent the hemodynamic response and temporal derivative. The first trial was discarded. Between-group analyses. For group analysis, image registration was performed using FSL’s FLIRT (Jenkinson, Bannister, Brady, & Smith, 2002; Jenkinson & Smith, 2001). Functional images were registered to the high-resolution anatomical image using a 7-degrees of freedom linear transformation. Anatomical images were registered to the MNI-152 atlas using a 12-degree of freedom affine transformation, and then this transformation was further refined using FNIRT for nonlinear registration. Each individual’s statistical images were entered into a higher level mixed-effects analysis using FSL’s FLAME algorithm. To quantify brain activity elicited by imitation, the functional data were analyzed in the following way. First, the three stimuli conditions SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 67 (emotional face, non-emotional face, and hand actions) were collapsed to find common neural correlates among conditions and compared to a resting baseline. Despite no group differences in age, age was entered as a covariate based on previous literature suggesting that imitation-related brain regions develop with age (Casey, Tottenham, Liston, & Durston, 2005; Uddin, Supekar, & Menon, 2013). Resulting group level images were thresholded using FSL’s cluster probability algorithm, with Z = 2.3 and a corrected cluster size probability of p = .05. Hypothesis-driven ROI analysis was performed on regions of the AON defined by the Harvard-Oxford atlas at 35% probability (Figure 2). Figure 2. Mask of the action observation network (AON). AON mask was anatomically defined by the Harvard-Oxford atlas thresholded at 35%. Green = superior temporal gyrus anterior division; Light blue = supramarginal gyrus anterior division; Magenta = inferior frontal gyrus pars opercularis; Orange = precentral gyrus ventral division; Red= superior temporal gyrus posterior division; Tan = angular gyrus; White = precentral gyrus dorsal division; and Yellow = supramarginal gyrus posterior division. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 68 Established ROI analysis for task activation. Activity from ten 8mm spherical ROIs around functionally significant peaks previously found to be active during observation and imitation (i.e., IFG, IPL, STS; Caspers et al., 2010) were compared across groups (Figure 3). For ROI-based analysis, social and motor skills were correlated with parameter estimates from these nodes to identify their relationship with patterns of brain activity during imitation. Figure 3. ROI analysis for task activation. Eight mm spheres around significant coordinates from an observation and imitation meta-analysis (Casper et al., 2010): Beige = Bilateral dorsal premotor cortex (dPMC, -1, 12, 52); Black = left dorsolateral premotor cortex (dlPMC, -36 -14 62); Hot pink = left inferior frontal gyrus (IFG, -60 12, 14); Royal blue = left inferior parietal lobule (IPL, -60, -51, 36); Orange = left superior temporal sulcus (STS, -54, -50, 10); Magenta = right IFG (58, 16, 10); Green = right IPL/primary somatosensory cortex (SI; 52, -36, 52); Light blue = right, IPL/secondary somatosensory cortex (SII,-60, - 26, 20); Yellow = right medial premotor cortex (mPMC,14, 6, 66;); Red = right dlPMC (42, 4, 56). Results Behavioral results. The TD, ASDd, and DCD groups were matched on age, and IQ (all p < .05). A description of the demographics and characteristics of the ASDd, DCD, and TD groups is presented in Table 1. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 69 Subject demographics. Table 1 Participant Characteristics of the Final Sample Characteristics Control n = 17 ASDd n = 13 DCD n = 10 Mean SD Range Mean SD Range Mean SD Range Sex (sum) 4 Female - - 1 Female - - 3 Female - - Age (yrs) 11.45 1.14 9.40-13.9 11.94 2.20 9.00-15.5 11.76 2.16 9.00-15.1 Full-Scale IQ 112.71 12.83 93-137 104.46 21.48 72-134 102.60 19.05 74-132 VIQ 113.88 12.82 86-136 103.62 21.36 65-151 107.80 14.34 87-136 PRIQ 108.24 13.85 84-132 104.77 23.21 63-131 98.50 26.12 74-154 MABC-2 Total 10.88 1.93 8-14 3.83 1.53 1-6 4.20 1.62 1-7 DCDQ 73.76 8.843 55-84 42.31 8.400 31-55 45.60 11.93 28-63 ADOS-2 - - - 9.64 3.23 5-16 - - - SRS-2 Total 45.59 5.00 39-57 72.92 9.13 52-88 58.10 8.77 43-72 Age, sex, and IQ did not significantly differ between groups (p > .05). SRS and MABC-2 are significantly different between groups (p < .05). VIQ = verbal IQ; PRIQ = perceptual reasoning IQ; MABC-2 = Movement Assessment Battery for Children, Second Edition; ADOS-2 = Autism Diagnostic Observation Schedule, Second Edition; SRS-2 = Social Responsiveness Scale-2. A one-way ANOVA test for the MABC-2 Total standard score indicated a significant main effect of Group [F (2, 36) = 75.11, p < .000]. The Fisher's Least Significant Difference (LSD) post hoc test indicated significant differences for all pairwise comparisons at p < .05 except for DCD and ASDd (p = .626). All pairwise comparisons at the subscale level between TD and ASDd and TD and DCD were significant at p ≤ .000, the TD group having better motor skills than the clinical groups. There were differences approaching significance in the aiming and catching subscale between the DCD and ASDd groups (ASDd M = 5.46; DCD M = 7.50; p = .134), otherwise, the remaining pairwise comparisons of the subscale measures between these two groups were non-significant (p > .653). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 70 An ANOVA test for the SRS-2 Total standard score indicated a significant main effect of Group [F (2, 37) = 48.66, p < .000]. The LSD post hoc test indicated significant differences for all pairwise comparisons at p < .000 (TD<DCD<ASDd). All pairwise comparisons at the subscale level between all groups were significant at p < .029 (TD<DCD<ASDd), except for social motivation between ASDd and DCD (ASDd M = 63.8, DCD M = 58.8, p = .217). The scatterplot for the SRS-2 Total score and MABC-2 Total for each of the three groups (TD, ASDd, and DCD) is presented below (Figure 4). Across groups, the results reveal a negative correlation between SRS-2 Total score and the MABC-2 Total score (R = -.528, p =.000) indicating a positive relationship between the social and motor skills, however, within each group the relationship is not significant. Moreover, (except for the ASDd subgroup) the direction of the relationship is reversed. These results are an example of the Simpson’s Paradox, a phenomenon in which across-group correlations are reversed within an individual group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 71 Figure 4. Scatterplot of social and motor skills across all groups. Typically developing (TD; blue), autism spectrum disorder with motor impairments (ASDd; red), and developmental coordination disorder (DCD; green). Pearson correlation across groups (trend line not shown), R = -.528, p = .000 (two-tailed). Within- group correlations were all non-significant (TD: R = .088, p = .729; ASDd: R = -.466, p = .110; DCD: R = .217, p = .546). Group activation during imitation versus rest. During imitation, the TD children and adolescents activated a neural network very similar to that previously observed in imitation literature (e.g., (Iacoboni, 2009): there was extensive bilateral activation of primary motor and premotor regions and the IFG (Brodmann's area 44; Figure 5). Head movement during scanning can lead to distortions in the data and children with ASD tend to move more than their peers. As a quality assurance check, groups were assessed for differences in head motion. Groups did not differ in relative motion (p > .05) however, the DCD group’s uncorrected absolute movement was significantly higher as compared with other groups and was negatively related to IFG activation (R = -.316, p = .047). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 72 Figure 5. Imitation versus rest by group. (A) Whole brain activation during imitation conditions compared to rest presented on the Montreal neurological institute template. Typically developing group (TD; blue); autism spectrum disorder with motor impairments subgroup (ASDd, red); developmental coordination disorder group (DCD, green); regions of overlap among all three groups (yellow). All clusters were corrected for multiple comparisons (Z = 2.3). R = right hemisphere. Group differences in the AON in imitation versus rest. No significant group contrast clusters survived cluster correction (Z = 2.3) within the AON (hypothesis-driven ROI analysis of the AON anatomically defined). Figure 6 shows how the three groups differed in patterns of brain activation within the AON that occurred during imitation compared to rest at a reduced threshold of p = .05, uncorrected. In comparison to the TD group, the ASDd and DCD groups both showed decreased activation in the bilateral IFGpo. The ASDd group also showed reduced activation of the STS, as well as smaller areas of the precentral gyrus and angular gyrus while the DCD group showed lower activation in the angular gyrus (Figure 6A). As shown in Figure 6B, the ASDd group showed a small bilateral cluster of hyperactivation in the STS compared to the TD participants. ASDd compared to DCD analysis revealed greater activation in the IFG in the ASDd group as compared to the DCD group as well as a small cluster of greater activity in the angular gyrus. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 73 The DCD group showed hyperactivation in the precentral gyrus and STS compared to the TD group. No DCD activity in the AON was significantly greater in the DCD group as compared to the ASDd group. Figure 6. Action observation network group contrasts. Between-group comparisons in the action observation network (AON). (A) Increased activity in typically developing (TD) individuals compared to individuals with autism spectrum disorder and motor impairments (ASDd; dark blue) and compared to those with developmental coordination disorder (DCD; light blue); (B) Increased activity in ASDd individuals compared to individuals TD (red); (C) DCD individuals compared to TD individuals (green); (D) Increased activity in ASDd individuals compared to individuals with DCD (orange). There were no areas in which the DCD group had greater activation than the ASDd group. All clusters were significant at p < .05, uncorrected. R= right hemisphere; L= left hemisphere; IFG= inferior frontal gyrus; STS = superior temporal sulcus; PRC = precentral gyrus; ANG = angular gyrus. Preliminary functional ROI analysis. The previous analyses generated a number of group contrast clusters. Given the small n and low threshold, we were particularly interested in areas of larger cluster sizes for post hoc analysis. We identified regions of group differences in cluster sizes greater than 50 voxels to further query in ROI analyses. Within these regions, individual difference behavioral measures were SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 74 related to mean activation in ROIs in which group level differences were observed. Parameter estimates were calculated from FSL feat query. To test whether individual social or motor skills were related to group differences between the TD and DCD groups, an ROI analysis was performed on voxels in the left and right IFG in which the TD group had greater activation than the DCD group. A nearly significant positive correlation was observed between the left and right IFG and MABC-2 manual dexterity in the TD group (left IFG: R = .426, p = .088; right IFG R = .44, p = .077). In the DCD group, left IFG activation was related to balance and standing (R = .569, p = .086). Similarly, an ROI analysis was also performed in the STS region in which the TD group had greater activation than the ASDd group. No within-group relationships were found. However, across-groups activity in this region was significantly related to the SRS-2 and all subscales (SRS-2 Total R = -.508, p = .001). Motor skills were also significantly related, however when controlling for social skills, the relationships did not survive. ROI analysis in previously established AON regions. A one-way ANOVA revealed no significant group differences in any of the predetermined AON ROIs. However, a difference approaching significance was revealed in the right precentral seed (p = .078). In post hoc analysis it was determined that TD was greater than ASDd (p = .062) and DCD (p = .055). ASD and DCD did not differ (p = .849). ASD brain-behavior relationships. Social and motor skills were related to activity in AON ROIs in the ASDd group. A general laterality pattern emerged such that left hemisphere nodes of the AON were related to motor skills, while right hemisphere SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 75 nodes were related to social skills. The left IFG ROI (-60, 12, 14) was related to increased MABC-2 subscale manual dexterity ([MD]; R = .596, p = .033; Figure 7A). The dPMC ROI (-1, 12, 53), which crosses both hemispheres, was significantly related to four SRS-2 subscores: (a) social awareness (R = -.664, p = .048), (b) social cognition (R = -.556, p = .048), (c) social communication (R = -.725, p = .005), and (d) repetitive and restrictive mannerisms (R = -616 p = .025). The left IPL ROI was related to the MABC-2 Total (R = .734, p = .007) and the MABC-2 manual dexterity subscore (R = .630, p = .021). The right IFG was related to SRS-2 subscales: social awareness (R = - .578 p = .039), social communication (R = -.703, p = .007; Figure 7B), mannerisms (R = .716, p = .000), and Total score (R = -.631, p = .021). Both right IPL ROIs (52, -36, 52; 60, -26, 20) and precentral ROIs (14, 6, 66; 42, 4, 56) were related to SRS-2 Total and subscores (see Table 2). DCD brain-behavior relationships. No AON seeds were related to social or motor skills in the DCD group, however, the analysis revealed a positive trend approaching significance between the SRS-2 social motivation subscore and IPL (R = .526, p = .054) suggesting that increased social skills were related to decreased activation. No significant relationships were found in the TD group. A. B Figure 7. Scatterplots of inferior frontal gyrus (IFG) ROI activation during imitation and behavioral measures. (A) Left IFG BOLD signal change and manual dexterity scores in the autism spectrum disorder with motor impairments subgroup (ASDd; R = -.592, p = .033 (two-tailed). (B) Scatterplot of right IFG SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 76 BOLD signal change and social communication scores in ASDd (R = -.703, p = .007; two-tailed). BOLD = blood oxygen level dependent, SRS-2 = Social Responsiveness Scale, Second Edition; MABC-2 = Movement Assessment Battery for Children, Second Edition. Table 2 Relationship Between Imitation Activation in AON Nodes and Social and Motor Skills SRS-2 MABC-2 Group Social Awareness Social cognition Social Communication Social motivation R&R Mannerisms MABC Total Manual Dexterity Aiming & Catching Balance & Standing ASDd Left dlPMC (-36, -14, 62) N.S. N.S. N.S. N.S. N.S. .572, .052 .520, .068 N.S. N.S. Left IFG (-60, 12, 14) N.S. N.S. N.S. N.S. N.S. N.S. .592*, .033 N.S. N.S. Left IPL (-60, 51, 36) N.S. N.S. N.S. N.S. N.S. .734**, .007 .630*, .021 N.S. N.S. Left STS ( -54, -50, 10) N.S. N.S. -.570*, .042 N.S. N.S. N.S. N.S. N.S. N.S. Bilateral dPMC ( -1, 12, 53) -.664*, .013 -.556*, .048 -.725**, .005 N.S. -.616*, .025 N.S. N.S. N.S. N.S. Right IFG (58, 16, 10) -.578*, .039 N.S. -.703**, .007 N.S. -.716**, .006 N.S. N.S. .539, .058 N.S. Right IPL/SI (52, -36, 52) N.S. N.S. -.619*, .024 N.S. -.720**, .006 N.S. N.S. N.S. N.S. Right IPL/SII (60, -26, 2)0 -.602*, .029 N.S. -.516, .071 N.S. -.668*, .013 N.S. N.S. N.S. N.S. Right mPMC (14, 6, 66) -.515, .072 N.S. -.753**, .003 N.S. -.612*, .026 N.S. N.S. N.S. N.S. Right dlPMC ( 42, 4, 56) N.S. N.S. -.621*, .024 N.S. -.566*, .044 N.S. N.S. N.S. N.S. Correlations between predetermined regions of interest (ROI) and social and motor skills in the autism spectrum disorder subgroup (ASDd). No significant correlations were identified in the developmental coordination disorder or typically developing groups (p > .05). *p < .05, ** p < .001, N.S. = non-significant. SRS-2 = Social Responsiveness Scale-2; MABC-2 = Movement Assessment Battery for Children-2. dlPMC = dorsal lateral premotor cortex; IFG = inferior frontal gyrus; IPL = inferior parietal lobule; STS = superior temporal sulcus; dPMC = dorsal premotor cortex; SI = first somatosensory area; SII = second somatosensory area; mPMC = medial premotor cortex. Discussion This fMRI study investigated the neural correlates of imitation in an ASDd subgroup of children, in children with DCD and in TD children using behavioral and brain activation measures. Congruent with our prediction in the first hypothesis, albeit at a less stringent threshold, we found group activation differences in the AON during imitation. Specifically, consistent with previous findings, compared to the TD group, both the ASDd and DCD groups had reduced activation in the IFG, which is the core AON SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 77 region. With a larger sample, these findings may become significant at a more stringent threshold. Previous studies have reported impaired motor performance in ASD when asked to imitate or pantomime complex motor gestures (Dowell, Mahone, & Mostofsky, 2009) as well as during writing tasks (Fuentes, Mostofsky, & Bastian, 2009). It is possible that our stimuli are not complex enough to elicit group differences in such a small sample. Another departure from ours and these behavioral studies range in the variety of imitation. Previous studies included hand-based imitation, only, as compared with the face and hand imitation tasks used in our study. Previous neuroimaging studies have shown reduced ASD activation with tasks that included face imitation (Dapretto et al., 2006) or hand imitation (Kana & Wadsworth, 2012). To date, no study has looked at AON activation in faces compared to hands; differences in imitation type may explain why our findings did not survive multiple comparison corrections. It is possible that our results are driven by activation in one condition compared to the others. For example, the ASD group may have significantly less activation for emotional faces compared to hand actions. Furthermore, the actions used in the current study are a mix of meaningful (e.g., cutting paper) and non-meaningful actions (e.g., biting top lip), and several previous studies found that ASD participants imitate meaningful gestures more accurately than non-meaningful ones (Cossu et al., 2012; Oberman et al., 2009; Rogers et al., 1996; Wild, Poliakoff, Jerrison, & Gowen, 2012). Therefore, it is possible that previous reports of significantly reduced AON activation related to imitation in ASD individuals could be specifically tied to the nature and complexity of the underlying imitative task, as well as the samples’ underlying motor abilities. We plan to conduct future analysis examining group differences between condition types when we have SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 78 collected data from a larger sample. With the exception of noticeably reduced IFG activation in the DCD group at the whole brain level, our imitation task activated the AON in all groups of participants, consistent with accounts of mirroring others’ observed actions in both human and macaque monkey populations (Rizzolatti & Craighero, 2004). The current findings also support the role of these areas in imitation as previously reported in human adults (Caspers et al., 2010) as well as human adolescent samples (Shaw, Czekóová, Chromec, Mareček, & Brázdil, 2013). Our findings of reduced AON activation in the ASDd and DCD population is consistent with previous imitation fMRI studies relating to those groups (Dapretto et al., 2006; Reynolds et al., 2015), as well as in other modalities in the ASD populations, such as abnormal mu rhythm using EEG (Oberman et al., 2005), MEG (Nishitani, Avikainen, & Hari, 2004), and transcranial magnetic stimulation-induced corticospinal excitability responses (Theoret et al., 2005). Interestingly, our DCD group had reduced IFG activation compared with the ASDd group. This is a novel finding and although we corrected for motion, it is possible that the DCD group’s reduced IFG activation may relate to extraneous motion during the imitative task. Indeed, the DCD group’s uncorrected absolute movement was significantly higher as compared with other groups and was negatively related to IFG activation. Thus, current DCD findings should be taken as preliminary. With a larger sample, we will better match our groups on head motion in the future. IFG. Both clinical groups with motor impairments (ASDd and DCD) elicited less activation in the IFG as compared to the TD group, suggesting that motor ability modulates AON activation. Moreover, the relationship between motor skills and left IFG SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 79 activation is approaching significance in the DCD group in voxels where TD>DCD (MABC-2 balance and standing, R = .596, p = .086). Although IFG hypo-activation in the ASDd cluster is relatively small (Voxels = 17), a similar positive relationship existed with motor skills and activity in the left IFG in voxels where TD>ASDd (MABC-2 aiming and catching R = .679, p = .025; Figure 8B). This finding suggests that motor skills mediate IFG activity in ASDd as well. Because social and motor skills are moderately positively correlated in our ASDd participants (R = .528, p =.110), we checked to see if this relationship was significant above and beyond socials skills. When controlling for SRS-2 Total, the left IFG remained positively related to aiming and catching skills and aiming and catching became significantly related in the right hemisphere as well (left IFG: R = .727, p = .011; right IFG: R = .688, p = .019) further indicating that motor skills may modulate AON activation in individuals with motor and social deficits, especially in the left hemisphere. Moreover, at a lower p-value, this relationship also exists when looking across all groups (R = .312, p = .050). Conversely, our results revealed that the right hemisphere IFG was primarily related to social skills in the ASDd group (SRS-2 Total and SRS-2 subscales social awareness, social communication, and mannerisms). The right IFG remained significantly related to social awareness and repetitive and restrictive mannerisms/behaviors when controlling with motor skills, while the left hemisphere activity remained unrelated to these skills (p > .543). Overall, our results suggest that the right IFG is mediated by both social and motor skills in ASD and the left is mediated primarily by motor ability in ASDd. These findings are congruent with reports of social skills being strongly related to right hemisphere IFG activation (Dapretto et al., 2006), SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 80 and also support the hypothesis that reduced activation in ASD relates to atypical motor functioning in that population (Mostofsky et al., 2009; Nebel et al., 2014). A. B. Figure 8. Scatter plot of catching and aiming skills and activation in inferior frontal gyrus (IFG) (A) the clinical groups (Autism spectrum disorder with motor impairments [ASDd] and developmental coordination disorder [DCD]) had significantly less activation during imitating than typically developing (TD) controls; (B) ASDd group only: Pearson correlation, across groups: R = .312, p = .050; ASDd: R = .679, p = .025. No significant correlations were found in the TD or DCD group when looking at them separately (p > .05). Premotor and motor cortices. Because motor skills were related to AON activation above and beyond social skills, it is surprising that other motor regions like the ventral premotor or precentral gyrus did not differ between ASDd and TD groups. Interestingly, group analysis did reveal greater precentral activation in the DCD group (DCD > TD). The precentral gyrus has been implicated in the control of fine motor movements (Liakakis, Nickel, & Seitz, 2011) and in motor response inhibition (Kana, Keller, Cherkassky, Minshew, & Just, 2009; Picazio, Ponzo, & Koch, 2016). However, given the IFG’s central role in motor inhibition (Hampshire, Chamberlain, Monti, Duncan, & Owen, 2010; Hughes, Johnston, Fulham, Budd, & Michie, 2013), increased activation of the precentral gyrus in the DCD group (which had the least IFG activation when imitating) could indicate a lack of top-down motor control during imitation. Alternatively, this group difference could be spuriously caused by greater movement in SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 81 the DCD group; this alternative hypothesis will be tested by removing subjects with large amounts of motion in the subsequent analysis when a larger sample is available. STS. During imitation, the pSTS is thought to interact with regions that support motor, perceptive (part of the ventral cortical visual processing stream), attentive (superior parietal lobule), and simulative skills (IPL, IFG; Caspers et al., 2010; Molenberghs, Cunnington, & Mattingley, 2009). The atypical patterns that we observed in the pSTS are consistent with other imitation findings (Jack & Morris, 2014). The larger cluster of ASDd hypoactivation in the right pSTS is congruent with previous work documenting structural (Boddaert et al., 2004; Hadjikhani, Joseph, Snyder, & Tager- Flusberg, 2006) and functional (Kaiser et al., 2010; Pelphrey et al., 2003; Pelphrey & Carter, 2008) differences in STS in individuals with ASD. In previous work related to the perception of biological motion, both in individuals with ASD and in typically developing individuals, effects are generally stronger in the right as compared to the left pSTS. Here we demonstrate that pSTS hypoactivation is unique to ASDd participants suggesting that decreased pSTS activation may be related to social, but not motor, skills. While within-group relationships were not significant (as reported in the Results section), when looking across groups, activity in this region was found to be significantly related to the SRS-2 Total and all SRS-2 subscales (SRS-2 Total R = -.508, p = .001). Motor skills were also significantly related, however when controlling for social skills, the relationships did not survive, further indicating that activation of the STS is more strongly modulated by social skills. Previously established AON ROIs from meta-analysis. Next, we examined activation in AON nodes chosen from an imitation meta-analysis (Caspers et al., 2010). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 82 Surprisingly, no group differences were found between any of the groups, however, this may also be due to the small sample size of the ASDd and DCD group. Similar to the ROI analysis discussed above, AON node activation revealed lateralized associations with social and motor skills. Social and motor skills were related to activity in AON ROIs such that left hemisphere nodes of the AON were related to motor skills, while right hemisphere nodes were related to social skills. The lateralized association between social and motor skills suggest group differences may confound previous discrepancies in ASD imitation findings. We did not hypothesize the laterality of AON activation and its relationship to social and motor skills, however, previous imitation literature supports both lateral and bilateral activation of the AON in neurotypicals (NT)(Barber et al., 2012; Pfeifer et al., 2008). It remains unclear if different types of imitation (social versus motor) elicit different hemispheric activation or if social or motor skills mediate activation in one hemisphere over the other. Some studies in TD children and adolescents have found a stronger right hemisphere activation during emotional face processing than in the left hemisphere (Dapretto et al., 2006). In a resting state study, Barber et al. (2012) reported greater left hemisphere motor circuit connectivity in ASD compared to TD peers, and that left hemisphere connectivity was related to better motor skills in TD individuals. However, in a later study, the same research team did not replicate its initial finding, and, in fact, found greater rightward lateralization of motor circuit connectivity associated with poorer motor performance in ASD participants (Floris, Barber, et al., 2016). Future analysis with a larger sample should investigate these lateral associations across all conditions. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 83 Limitations Some limitations of the present study must be considered. First, a relatively small sample size was analyzed. However, the group characteristics were comparable to previous studies of ASD and DCD populations (Reynolds, Thornton, et al., 2015; Travers et al., 2012). Nevertheless, our relatively small sample size, as well as a larger sample size in the TD group compared to the clinical groups, may present limitations with regards to effect size which thereby affects generalizability of our findings. In addition, our design might also entail possible ceiling effects on social and motor abilities in the TD group. Furthermore, although motor skills were evaluated before scanning, imitation skills were not considered. It is possible that individuals with poor motor skills may have intact imitation skills and vice versa. Moreover, although we carefully monitored participants’ imitative skills while they engaged in outside-the- scanner task training in order to ensure that all participants could carry out the task, we did not assess the qualitative nature of their imitative ability (e.g., correct finger or facial expression, or movement speed or accuracy) while each participant actually performed the given tasks in the scanner. Future studies would benefit from developing task imitation complexity and performance scales tasks whereby a more formal task comparison could more clearly elucidate potential effects of observed neural processing abnormalities. Furthermore, this study was comprised of high-functioning children and adolescents with ASDd who displayed normal-and-above IQ values and good verbal skills. Therefore, it remains unclear to what extent the present findings can be generalized to the larger ASD population or selected sub-groups, such as “low- functioning” individuals with ASDd or adults with ASDd. Network connectivity patterns SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 84 change throughout typical human development (Bastiaansen et al., 2011), therefore future studies should consider investigating social and motor skills across the lifespan. Also, the influence of other psychiatric comorbidities such as ADHD and medication in our ASDd and DCD sample cannot be ruled out. However, as acknowledged by Fishman and colleagues (2015) it is difficult to recruit a “pure” sample of ASD, and likely DCD as well (Visser et al., 2003). Finally, differences in motion between groups were not fully balanced. Future analysis should control for movement by more carefully matching groups on motion. Conclusions In summary, this fMRI study compared a subgroup of ASD with motor deficits to DCD and TD participants during face and hand imitation. The imitative task elicited significant activity in all participants in the AON regions with markedly reduced IFG activation preliminarily demonstrated in the DCD group. The ASDd participants showed reduced brain activity, relative to TD participants, primarily in the right pSTS and IFG during imitation. Activity in the IFG region was found to be positively correlated with social skills while motor regions, especially on the left, were positively related to motor skills. While both clinical groups performed equally well in measures of motor skills outside the MRI scanner, the reduced reliance on some key AON regions (i.e., IFG) in both groups of participants with motor deficits might suggest that individuals with motor deficits rely less on core imitation networks to accomplish the task. Interestingly, social and motor skill relationships with AON activation in the ASDd group was found to be lateralized, such that right hemisphere activation was primarily related to social deficits, and left hemisphere activation related to motor skills. These findings provide important SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 85 new insight into the neuroimaging literature on action imitation in autism. We demonstrate that motor skills correlate with activation in the AON during imitation in individuals with motor impairments, supporting the disrupted AON hypothesis for ASDd. Since not all individuals with ASD have motor impairments, these findings provide evidence that suggest heterogeneity in motor skills may account for some discrepant findings in previous ASD imitation literature which did not specifically consider motor performance. Future work using additional data in the DCD group will allow us to remove group effects related to motion and better elucidate how motor skills modulate the AON in the absence of ASD symptomatology. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 86 Supplementary Material Box plot analysis. Significant (uncorrected) comparisons between TD children and the clinical groups revealed overlapping clusters in the right and left IFG. Right hemisphere activation was approaching significance between the TD and DCD groups (p = .079). Left hemisphere activation did not differ between groups (p = .227). Box plots reveal a range of variance in the TD group, suggesting a reduced effect size (Figure 9). Figure 9. Boxplots and bar charts of activation during imitation where typically developing (TD)> autism Figure 9. Boxplots and bar charts of activation during imitation where typically developing (TD)> autism spectrum disorder subgroup (ASDd) and TD>developmental coordination disorder (DCD). Boxplots: Upper and lower ends of boxes represent 75th and 25th percentiles, respectively. “Whiskers” attached to the boxes extend out to include 100% of data (with the exception of possible outliers, represented by open circles and outliers represented by stars). Bar charts: mean IFG activation for each group. TD = blue; ASDd = red; DCD = green. Whole brain group comparisons. Direct comparisons between the typically developing children and the clinical groups revealed that that activity in the cerebellum was reliably greater in TD children compared to the ASDd group, and in the bilateral lateral occipital cortex and splenium and compared to the DCD group (Figure. 10A and 10B). The clinical groups differed in the nucleus accumbens and anterior cingulate cortex as well as in the supplementary motor cortex such that the ASDd group had greater activation in the former and the DCD in the latter (Figure. 10C and 10D). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 3 87 Figure 10. A between-group comparison of imitation versus rest. (A) Increased activity in typically developing (TD) individuals compared to individuals with autism spectrum disorder with motor impairments (ASDd; blue); (B) Increased activity in TD individuals compared to individuals ASDd (light blue); (C) ASDd individuals compared to individuals with developmental coordination disorder (DCD; red); (D) Increased activity in DCD individuals compared to individuals with ASDd (green). There were no areas in which the ASDd group had greater activation than the DCD group. All clusters were corrected for multiple comparisons (Z=2.3). R= right hemisphere; L= left hemisphere; CEV= cerebellum V; LOC = lateral occipital cortex; NAc = nucleus accumbens; ACC= anterior cingulate cortex; SMG= supplementary motor cortex; sPL = splenium. Stimuli list. An example of the video stimuli presented during one run of the imitation task (Table 3). Stimuli videos are 3.75 seconds long. Table 3 Example Set of Action Videos Presented during a Run of the Imitation Task. Emotional Faces Non-Emotional Faces Hand Actions F1_Angry F1_Excited F2_Sad F3_Happy F3_Rage F4_Angry F4_Disgust F4_Surprise M1_Sad M1_Surprise_Neg M2_Disgust M2_Rage M3_Excited M3_Fear M3_Happy F1_Bite_Bottom_Lip F1_Lips_Out F1_Wiggle_Nose F2_Clean_Teeth F2_Eye_R F3_Lips_In F4_Eyebrows_Both F4_Tongue_Out M1_Fish_Lips M1_Tonuge_To_Lip M2_Bite_Upper_Lip M2_Thinking_R M2_Tongue_Cheek_R M3_Mouth_Side_To_Side M3_Wiggle_Nose F_Accordion F_BandAid F_Can F_Counting F_Crackers F_CutStrip F_Earbuds F_Ice M_Banana M_Bubble M_Floss M_Pliers M_Train M_Unwrap M_Woodblock_tap M= Male, F= Female, numeral = actor identity. For hand actions, there were only one female and one male actor. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 88 Chapter 4. Resting State Networks in Children and Adolescents with Social and Motor Deficits Abstract Introduction: Previous neuroimaging findings have identified disrupted intrinsic resting- state networks in autism spectrum disorder (ASD). However, how these networks are altered compared to typically developing (TD) individuals is debated. Interpreting results are complicated by the heterogeneous nature of the condition, allowing for variable connectivity patterns among individuals with the disorder. Many clinicians and researchers have reported motor coordination deficits in ASD including comorbid developmental coordination disorder (DCD) symptoms. While several studies have investigated how variations in social skills relate to network connectivity, few have looked at variations in motor skills. This study investigates neural connectivity in social and motor networks during rest in a subgroup of ASD with motor deficits (ASDd) and DCD participants and its relationship with social and motor skills. Methods: Fifteen children and adolescents with ASDd, 10 with DCD, and 18 TD peers underwent functional magnetic resonance imaging while at rest. Social and motor behavioral measures also were collected. Between-group neural connectivity differences, as well as relationships between connectivity and behavioral skills, were evaluated. Results: Reduced connectivity within the action observation network (AON) was observed in both clinical groups compared to the TD group. Inferior frontal gyrus (IFG) SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 89 connectivity was reduced in the ASDd group and positively related to motor skills across groups. Atypical default mode network (DMN) connectivity was found in both clinical groups. Specifically, group analysis revealed sensorimotor hyperconnectivity in the ASDd group compared to the TD group. The DCD-only group was found to have weaker posterior parietal cortex (PrC) connectivity with frontal brain regions compared to the TD and ASDd groups and stronger PrC connectivity with occipital and parietal regions. Conclusions: Findings from this study indicate that motor skills are related to intrinsic social and motor networks in ASDd and DCD. Results also replicate previous findings regarding AON dysfunction and DMN hyper-connectivity in ASD compared to TD. Specific to ASDd individuals, hyperconnectivity was found in sensorimotor brain regions compared to TD peers. Novel DCD findings suggest that intrinsic brain connectivity is disrupted in individuals with motor deficits. These findings also suggest that motor skills, a relatively unexplored index in ASD neural functioning, are related to a network that is reliably shown to contribute to social processing. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 90 Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a highly heterogeneous presentation of social deficits such as social communication skills, repetitive and restrictive behaviors (APA, 2013) as well as motor deficits (Fournier et al., 2010). The complexity of the clinical manifestations of the disorder makes investigating its etiology and identifying specific underlying neural mechanisms difficult. In recent years, researchers have begun to hypothesize that no singular brain region is implicated in the disorder, but rather, ASD is a disorder of disrupted neural systems (Belmonte et al., 2004; Just, Keller, Malave, Kana, & Varma, 2012). This theory posits that abnormalities in functional and structural connectivity between and within networks are related to ASD symptomatology. However, the direction of network abnormalities is unclear. Both hyper- and hypoconnectivity have been demonstrated in children with ASD across multiple networks (i.e., DMN, imitation, salience; Green, Hernandez, Bookheimer, & Dapretto, 2016; Müller et al., 2011; Rane et al., 2015; Supekar et al., 2013). Because ASD is highly heterogeneous and the disorder is frequently comorbid with conditions such as anxiety, attention deficit hyperactivity disorder (ADHD), epilepsy, Fragile X syndrome, neuroinflammation and immune disorders, sensory processing disorders, obsessive-compulsive disorder, and developmental coordination disorder (DCD; Levy et al., 2010), variation in symptomatology can confound findings and make it challenging to disentangle discrete ASD-only related neural mechanisms. While it is possible that some of these conflicting results may be due to developmental effects--it has been hypothesized that ASD might be marked by early hyper-connectivity followed by hypo-connectivity later in development--conflicting results also may be due in part to the heterogeneity of ASD samples in different studies. Many SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 91 clinicians and researchers have identified motor impairments in ASD (Fournier et al., 2010; Green et al., 2009; Hilton et al., 2012) and there is evidence to suggest that social and motor impairments are positively related in ASD (Dowell et al., 2009; Dziuk et al., 2007). Therefore, it is possible that motor heterogeneity may play explain some discrepancies in motor and social circuits. Further evidence for this hypothesis comes from research on DCD, a neurodevelopmental disorder characterized by motor deficits. It has been proposed that the same sensory-motor network (the action observation network; AON) thought to be disrupted in ASD is also disrupted in DCD (for a review see Werner et. al., 2014). While individuals with DCD can exhibit social skills impairments, they are not considered to be inherent to DCD but instead a secondary effect arising from self-esteem issues related to not being picked for sports teams, etc. (Dewey et al., 2002; Skinner & Piek, 2001). To date, no studies have compared intrinsic resting state networks between ASD and DCD in order to look for the signature of ASD independent of DCD. Many recent studies in ASD have moved towards investigating functional connectivity (FC) of networks that subserve cognitive functions rather than task-based fMRI analysis (Spencer et al., 2012; Wang, 2010). It is thought that understanding intrinsic resting state networks in ASD may elucidate the connectivity patterns contributing to possible impairments in network functioning during a task. Indeed, there is a strong relationship between resting-state FC and cognitive task activation (Cole, Yang, Murray, Repovš, & Anticevic, 2016). This study aims to reduce the effects of heterogeneity in a typical sample of ASD participants by investigating neural connectivity in social and motor networks in a subgroup of ASD individuals who also SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 92 have motor deficits and DCD participants. We specifically investigate two neural circuits which have been implicated in ASD but not yet clearly understood: the AON and the DMN. AON. The AON is composed of sensorimotor brain regions that are active both when a person makes an action as well as when a person observes the same action being performed by another. Regions in this network that respond or co-activate to the observation of human actions include the superior temporal sulcus (STS), premotor cortex (PMC), inferior parietal lobule (IPL) and IFG which is considered to be the core region of the network. These latter three brain regions are thought to contain putative mirror neurons in the non-human primate brain (di Pellegrino, Fadiga, Fogassi, Gallese, & Rizzolatti, 1992; Gallese et al., 1996; Rizzolatti, Fogassi, & Gallese, 2001), and human brains (Keysers & Gazzola, 2009; Molenberghs, Cunnington, & Mattingley, 2012). Abnormalities in AON activation have been postulated to underlie social and imitation deficits in ASD (Dapretto et al., 2006; Rizzolatti et al., 2009). Specifically, this network has been associated with social deficits in several functional and structural neuroimaging studies leading some to theorize that the AON network is disrupted in ASD (Dapretto et al., 2006; Williams et al., 2001), although other studies have found no such relationship (Press et al., 2010; Schulte-Rüther et al., 2017). Most functional studies examine the co-activation of these regions during a task and although a few have looked at AON FC with other brain regions (e.g., insula, amygdala), only two have examined resting synchronization of the AON (Fishman et al., 2015; Shih et al., 2010). Shih et al. (2010), reported greater FC in frontal regions, along with reduced effective connectivity between IPL and IFG suggesting atypical AON organization in ASD. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 93 Fishman et al. (2015) found overall reduced FC within AON regions and increased FC with regions not considered part of the network in ASD children compared to TD peers. Similarly, to date, only two DCD resting-state studies from the same research group have been published. These studies compared a small sample of children and adolescents with DCD (n = 6-7) to individuals with ADHD (n = 20-21), those with both DCD and ADHD (n = 14-18), and to TD controls (n = 21-23) to investigate primary motor connectivity. The authors reported weaker within-hemisphere connections in the motor cortex (McLeod et al., 2016) and altered FC between the primary cortex and the insular cortex, somatosensory cortices, striatum, and inferior frontal gyri in children with DCD, indicating altered intrinsic network connectivity in these individuals (McLeod et al 2014). Neither study reported known intrinsic network comparisons such as the DMN or intrinsic connectivity of brain areas that participate in a neural network for imitation, nor related such connectivity measures to social measures. Default mode network. The DMN is a large-scale functional brain network comprised of the posterior cingulate cortex (PCC), precuneus (PrC), medial prefrontal cortex (mPFC), temporoparietal junction (TPJ), and hippocampus (see Figure 1). Activity in these regions is synchronized during rest and activated during socially relevant tasks (Raichle et al., 2001; Shulman et al., 1997). The PCC is thought of as the “hub” of the DMN and is elicited for self-relevant and other-relevant processing (Hagmann et al., 2008; Leech & Sharp, 2014; Tomasi & Volkow, 2011). The mPFC is associated with monitoring self and other’s mental states. The TPJ is near the angular gyrus and is thought to process social information such as understanding the mental states of others (Saxe & Kanwisher, 2013). Together, the DMN and its integral units are SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 94 thought to be a core brain system for processing a wide range of cognitive, emotional, and social functioning information. The DMN concept has been used to understand social dysfunction in ASD at an intrinsic network level and is thought to be an important system underlying social dysfunction in ASD. Since the discovery of the DMN and its apparent relation to social perception (Corbetta, Patel, & Shulman, 2008; Schilbach, Eickhoff, Rotarska-Jagiela, Fink, & Vogeley, 2008), ASD researchers have sought to contrast the DMN and other intrinsic network activity at rest with typical controls with overwhelmingly aberrant results. Many findings provide support for a disrupted DMN in ASD across the lifespan (Kennedy & Courchesne, 2008). Discrepancies in the direction and location of atypical connectivity reported in ASD have been attributed to developmental changes, methodological differences as well as the heterogeneity of the ASD sample (Hull, Mandy, & Petrides, 2017). In typical development, local functional connections diminish while long-range connections are strengthened. Some have found that individuals with ASD fail to develop necessary connections between important brain regions the way typical populations do. For example, in ASD, hyperconnected links have been reported in childhood (Chien, Lin, Lai, Gau, & Tseng, 2015) and hypoconnections in adults (Wiggins et al., 2011). This suggests that hyperconnected DMN connections in childhood ASD may become under-connected in adulthood owing to failure to strengthen long-range pathways with age in ASD (Padmanabhan, Lynch, Schaer, & Menon, 2017). However, because many studies include age as a covariate in their analysis (Washington et al., 2014), discrepancies in developmental trajectories do not explain all of the discrepancies in altered ASD connectivity. Since individuals with DCD SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 95 who have motor skill deficits have disrupted resting state networks, and motor deficits are common in ASD, it is possible that some of the FC variances are the result of motor heterogeneity in samples. To date, no resting state study has systematically examined whether their ASD participants also had DCD. Figure 1. Default mode network (DMN) identified using multiple imaging techniques (Padmanabhan et al., 2017). (A) DMN derived from positron emission tomography (B) DMN derived from independent component analysis of fMRI data (C) Tractography (D) strength of structural connections among DMN nodes can be quantified using diffusion imaging (E) Spring graph illustrates the differing functional connectivity weights between DMN nodes. Current Study The present study aims to investigate patterns in intrinsic connectivity in social and motor networks that are mediated by social and motor skills in samples of children and adolescents who: (a) are typically developing and do not have any social or motor deficits (TD), (b) have ASD as well as motor deficits (ASDd) and (c) have primarily motor deficits (DCD), but not ASD. Here, we clarify previous resting-state findings by reducing heterogeneity in our study population of ASD because we focus on a subgroup of individuals in ASD with motor deficits, our “ASDd” group, and compare them to a group of participants who have motor deficits, but not ASD (our DCD group). Based on prior literature indicating that the AON is disrupted in both clinical populations, we SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 96 predict that the ASDd and DCD groups will have abnormal within-network AON connectivity and that the degree of abnormal AON connectivity will be correlated with motor deficits. We also hypothesize that our ASDd subgroup will have hyperconnectivity compared to DCD and TD controls in the DMN based on findings suggesting that hyperconnectivity in ASD as compared to TD peers, is positively related to social deficits in ASD (Lynch et al., 2013). We also predict that there will be discrete patterns of connectivity between the ASDd group and the DCD group indicating differences between those who have both social and motor deficits and those with just motor deficits. Methods Participant Characteristics. Individuals aged 8 to 15 with ASDd (n = 15, 1 female), DCD (n = 10, 3 female), and TD controls (n = 18, 3 female) participated in the study. ASDd participants were recruited from clinics in the greater Los Angeles healthcare system, through local public and private schools, and through word of mouth and social media advertising. ASDd participants were high functioning (IQ 80-134) and had received a diagnosis either through a clinical ASD interview, an ASD diagnostic assessment, or both. We assessed clinical symptoms using the Autism Diagnostic Observation Schedule-2, Module 3 (ADOS-2; Lord et al., 2000). Exclusion criteria for ASDd included: (a) IQ <80 (in cases where the full-scale IQ was less than 80, participants were included if their verbal IQ score or perceptual reasoning IQ score were greater than 80 as assessed by the Wechsler abbreviated scale of intelligence fourth edition (WASI; Wechsler, 2011); (b) history of loss of consciousness greater than five minutes; (c) left-handed; (d) not sufficiently fluent in English or parent who did not have SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 97 English proficiency; (e) a diagnosis of other neurological or psychological disorders except for attention deficit disorders or generalized anxiety disorder; (f) a Movement Assessment Battery for Children (MABC-2; Henderson, Sudgen, & Barnett, 2011) score greater than fifteen percent indicating no clinical risk for DCD and a score on the Developmental Coordination Disorder Questionnaire (DCDQ; Wilson et al., 2009) indicating a unlikely or no suspected DCD diagnosis. All participants were born after 36 weeks of gestation and screened for MRI compatibility. Participants were also evaluated for their capacity to give informed consent and then provided their written consent after being informed about the study procedures in accordance with the study protocols approved by the University of Southern California Institutional Review Board. DCD participants were recruited from therapy clinics throughout California, through Los Angeles-area public and private schools, and through national DCD/dyspraxia support groups as well as from community events, word of mouth, and local advertising. In addition to the exclusion criteria established for the ASDd group (a- f), DCD participants were excluded if they had (g) a personal diagnosis or an immediate family member with a diagnosis of ASD or (h) a Social Responsiveness Scale-2 (SRS; Constantino et al., 2003) score indicating risk of ASD (>60) and a subsequent ADOS-2 score in the clinical range. Healthy control (TD) participants were recruited through flyers posted in the local community, social media, and website postings. Exclusion criteria for TD control participants included the first four elements of ASD exclusion criteria listed above (a-d). TD controls additionally were excluded if they had any psychological diagnosis or neurological disorder, including attention deficit disorders and generalized anxiety SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 98 disorder or if they scored below the twenty-fifth percentile on the MABC-2 score or were likely or suspected to have a DCD diagnosis based on the DCDQ score. Two ASDd participants and four DCD participants were on previously prescribed psychotropic medication at the time of data collection. Behavioral Measures. Motor skills were assessed using the MABC-2, a performance-based assessment that evaluates motor skill ability using three subtests: manual dexterity, aiming and catching skills, and balance. Higher scores indicate better functioning. Subtest scores, as well as a total score, were calculated using the second (ages 7–10) and the third (ages 11–16) age bands. Item, subtest standard (scaled), and Total scores based on the normative sample were examined in our analyses. The DCDQ is a 15-item screening questionnaire that ascertains gross and fine motor skill impairments that would contribute to a diagnosis of DCD. The questionnaire was utilized as an informative qualifier for DCD in our ASDd sample. The DCDQ yields a raw total score (score range: 15–75), higher scores indicate better motor functioning. In addition, parents of all participants completed the SRS-2. The SRS-2 is a parent survey comprised of five subscales regarding their child’s social skills: social awareness, social cognition, social communication, social motivation, and mannerisms. Scores are reported in T-scores. Task. Participants were asked to stay still with their eyes open while they looked at a white crosshair in the center of black screen. Participants were instructed not to think of anything in particular. MRI data acquisition and processing. Data collection. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 99 Functional Scan. Functional magnetic resonance imaging (fMRI) data were acquired on a 3 Tesla MAGNETOM Prisma (Siemens, Erlangen, Germany) with a 20- channel head coil. Resting state scans (150 whole brain volumes) were acquired with the following parameters: TR = 2s, TE = 30 ms, flip angle = 90˚, 64x64 matrix, in-plane resolution 3x3 mm, and 41 transverse slices, each 1.5 mm thick, covering the whole brain with a multiband factor of three. Spin Echo EPI field mapping data was also acquired in AP and PA directions with identical geometry to the EPI data for EPI off- resonance distortion correction (TR = 1020 ms, TE1 = 10 ms, TE2 = 12.46 ms, flip angle = 90°, FOV = 224 × 224 × 191 mm3, voxel size = 1.5 × 1.5 × 1.5 mm). Anatomical Scan. A structural T1-weighted MPRAGE was acquired on each subject (TR = 1,950ms, TE = 3.09ms, flip angle = 10˚, 256x256 matrix, 1 mm isotropic resolution, 150 volumes). Total scan time = 5 minutes. Functional preprocessing analysis. Analysis of functional imaging was performed using FSL (FMRIB Software Library, http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/). The following pre-statistical processes were applied to the fMRI data: non-brain removal using Brain Extraction Tool (BET); rigid-body motion correction using MCFLIRT; correction of off-resonance geometric distortions in the EPI data using PRELUDE and FUGUE, using B0 field maps derived from the dual-echo gradient echo dataset; spatial normalization to Montreal Neurological Institute (MNI152) 2 mm isotropic atlas space using boundary-based registration (BBR) and FNIRT; spatial Gaussian filtering (full width at half maximum (FWHM) = 6 mm; artifact removal based on probabilistic ICA (Independent Component Analysis) using MELODIC and AROMA; segmentation and removal of variance explained by time series extracted from masks of white matter and SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 100 cerebral spinal fluid, and high-pass temporal filtering (Gaussian-weighted least-squares fitting with frequency cutoff point of 0.01Hz). Within-subject analyses. AON correlation matrix. In order to compare within AON connectivity we compared intrinsic resting AON FC limited to connections between nodes of the AON. We performed subject level functional imaging analyses using FSL. AON: eight- millimeter spheres created from ten voxel coordinates consistently reported to be active during imitation (e.g., IFG, IPL, PMC, STS; Figure 2; Caspers et al., 2010) were used as AON seeds. Time series from these seeds were extracted to assess connectivity between functional regions of the AON network. DMN. To better compare groups along an established intrinsic resting state network, a 10 mm spherical seed located in the posterior cingulate cortex (PCC; −2, −36, 37) identified based on coordinates from Fox et al., (2009) was used as the seed for the DMN. The time series extracted from the PCC seed was modeled along with 8 continuous nuisance regressors to assess whole-brain connectivity with this region. Between-group analyses. AON correlation matrix. Time series from each AON seed were correlated across all ROIs to generate a correlation matrix of FC values between each pair of ROIs. Graphvar (GraphVar beta version 1.03) which is a graphical user interface-based toolbox run on MATLAB. GraphVar was used to compare FC values between groups. Individual FC matrices for each subject were Fisher-z transformed and then averaged across participants in each group to form an average FC matrix for each scan. A GLM SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 101 was performed with group identity as the between factor and age was added as a control variable and a threshold at p < .05. Figure 2. Eight mm spheres around significant coordinates from an observation and imitation meta- analysis (Casper et al., 2010): Beige = Bilateral dorsal premotor cortex (dPMC, -1, 12, 52); Black = left dorsolateral premotor cortex (dlPMC, -36 -14 62); Hot pink = left inferior frontal gyrus (IFG, -60 12, 14); Royal blue = left inferior parietal lobule (IPL, -60, -51, 36); Orange = left superior temporal sulcus (STS, - 54, -50, 10); Magenta = right IFG (58, 16, 10); Green = right IPL/primary somatosensory cortex (SI; 52, - 36, 52); Light blue = right, IPL/secondary somatosensory cortex (SII,-60, -26, 20); Yellow = right medial premotor cortex (mPMC,14, 6, 66;); Red = right dlPMC (42, 4, 56). DMN between and within group contrasts. For group analysis, image registration was performed using FSL’s FLIRT (Jenkinson et al., 2002; Jenkinson & Smith, 2001). Functional images were registered to the high-resolution anatomical image using a 7- degrees of freedom linear transformation. Anatomical images were registered to the MNI-152 atlas using a 12-degree of freedom affine transformation, and then this transformation was refined using FNIRT for nonlinear registration. Each individual’s statistical images were entered into a higher level mixed-effects analysis using FSL’s FLAME algorithm. Age was included in the model as a non-variable of interest. Resulting group level images were thresholded using FSL’s cluster probability algorithm, with Z = 2.3 and a corrected cluster size probability of p = .05. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 102 Social and motor skills. In addition to group contrasts, a within-group analysis was performed including social and motor skills as variables of interests. For each group, multiple regression analyses were performed to assess the relationship between individual PCC seed connectivity maps and symptom severity as assessed by the SRS- 2 total and MABC-2 Total. Three separate models were assessed with age and the following: (1) both SRS-2 Total and MABC-2 Total, (2) SRS-2 Total alone, or (3) MABC- 2 Total alone. Results A description of the demographics and characteristics of the ASDd, DCD and TD groups is presented in Table 1. Not reported in the table is medication use. Three ASDd participants and four DCD participants were on psychotropic medication at the time of data collection. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 103 Table 1 Final Group Demographics Characteristics Controls n = 18 ASDd n = 15 DCD n = 10 Mean SD Range Mean SD Range Mean SD Range Sex (female) 5 Female - - 1 female - - 3 Female - - Age (years) 11.21 1.25 9.10-13.9 11.81 2.07 9.00-15.50 11.76 2.16 9-15.1 Full-Scale IQ 112.12 11.11 93-130 104.00 20.35 72-134 102.60 19.05 74-132 VIQ 113.56 10.80 86-136 101.53 20.95 65-151 107.80 14.34 87-136 PRIQ 107.33 13.19 84-131 106.07 22.06 63-131 98.50 26.12 74-154 MABC-2 Total 10.72 1.84 8-14 4.00 1.41 1.00-6.00 6.00 1.62 1-7 DCDQ 73.27 9.32 55-84 42.31 8.4 31-55 45.60 11.93 28-63 SRS-2 Total 44.72 4.96 39-55 73.20 8.56 52-88 58.10 8.77 43-72 ADOS-2 - - - 10.08 3.64 5-17 - - Note. Age, sex, and IQ did not significantly differ between groups (p > .05). SRS-2 and MABC-2 were significantly different between groups (p < 0.05). Note, one ASDd participant did not complete the manual dexterity MABC-2 subscore and, therefore their MABC-2 total score could not be calculated. VIQ = verbal IQ; PRIQ = perceptual reasoning IQ; MABC-2 = Movement Assessment Battery for Children Second Edition; ADOS = Autism Diagnostic Observation Schedule, Second Edition; SRS-2 = Social Responsiveness Scale-2. Behavioral results. A one-way ANOVA test for the MABC-2 Total standard score indicated a significant main effect of Group [F (2, 40) = 84.59, p < .000]. The Fisher's Least Significant Difference (LSD) post hoc test indicated significant differences for all pairwise comparisons at p < .05 except for DCD and ASDd (p = .768). All pairwise comparisons at the subscale level between TD and ASDd and TD and DCD were significant at p ≤ .000, with TD having better motor skills compared to the clinical groups. There were differences approaching significance in the aiming and catching subscale between the DCD and ASDd groups (ASDd M = 5.25; DCD M = 7.50, p = .09), SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 104 otherwise, the remaining pairwise comparisons of the subscale measures between these two groups were non-significant (p > .606). An ANOVA test for the SRS-2 Total standard score indicated a significant main effect of Group [F (2, 41) = 64.689, p < .000]. The Fisher's Least Significant Difference (LSD) post hoc test indicated significant differences for all pairwise comparisons at p < .000 (TD<DCD<ASDd) All pairwise comparisons at the subscale level between all groups were significant at p < .029 except for social motivation between ASDd and DCD (ASDd M = 64.0; DCD M = 58.8, p = .166). The scatterplot for the SRS-2 Total score and MABC-2 Total for each of the three groups (TD, ASDd, and DCD) is presented below (Figure 3). Across groups, the results show a negative correlation between SRS-2 Total score and the MABC-2 Total score indicating a positive relationship between the social and motor skills (R = -.528, p = .000), however, this relationship was not found within each group. Moreover, except for the ASDd subgroup, this relationship is reversed, albeit a non-significant level. These results are an example of the Simpson’s Paradox, a phenomenon in which across- group correlations are reversed within an individual group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 105 Figure 3. Scatterplot of social and motor skills across all groups: Typically developing (TD; blue); autism spectrum disorder with motor deficits (ASDd; red); and developmental coordination disorder (DCD; green). Pearson correlation across groups, R = -.528, p = .000 (two tailed). Within-group correlations were all non-significant (TD: R = .088, p = .729; ASDd: R = -.452 p = .091; DCD: R = .217, p = .546). AON matrix. AON connectivity matrices were conducted using GraphVar in MATLAB. When using group identity as a between-subject variable, group was found to be related to FC between bilateral IFG (F(2,38) = , 6.48, p = .003), right IFG and right IPL (F(2,38) = 3.72, p = .033), and both right IPL nodes (F(2,38) = 3.24, p = .049). However, these findings did not survive multiple comparison corrections. When contrasting between group pairs, connectivity was stronger in the TD group, compared to the ASDd group between the bilateral IFG nodes (t(38) = 3.55, (p = .001) and Left IFG and IPL/SII nodes (t(38) = 2.52, (p = .016). Mean bilateral IFG connectivity in the DCD group fell between the TD and ASD groups but did not significantly differ (Figure 4 & 5). Left IPL and IPL/SII FC were significantly different at the pairwise level. However, other pairwise comparisons between groups were not significantly different (see Table SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 106 2). Overall, visual inspections suggest that the AON is more connected in the TD group compared to the clinical groups. Head movement during scanning can lead to distortions in the data and children with ASD tend to move more than their peers. As a quality assurance check, groups were assessed for differences in head motion. Groups did not differ in absolute or relative motion (p > .05). Motion was also assessed to see if it correlated with social and motor skills. Motion was not significantly related to social or motor skills within or across groups (p > .05). Figure 4. AON group connectivity matrices. (A) Significant (p < .05) AON connectivity in typically developing (TD), autism spectrum disorder with motor impairment (ASDd) and developmental coordination disorder (DCD) individuals. (B) Group differences in AON connectivity between all groups; between TD and ASDd; and between TD and DCD. 1 = bilateral dorsal premotor cortex (dPMC), 2 = left SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 107 dorsolateral premotor cortex (dlPMC), 3 = left inferior frontal gyrus (IFG), 4 = left inferior partial lobule (IPL), 5 = left superior temporal sulcus (STS), 6 = right IFG, 7 = right IPL/SI, 8 = right IPL/SII, 9 = medial premotor cortex (mPMC), 10 = right dlPMC. Table 2 Significant AON Correlation Matrix Results AON Pairs F (2,38) / t (38), p One Way ANOVA R IFG - L IFG L IFG - R IPL/SII R dPMC - R IPL/SII 6.48, .003 3.24, .049 3.72, .033 TD>ASDd R IFG - L IFG L IFG - R IPL/SII R IPL/SII - R IPL/SII 3.55, .0009 2.52, .0158 2.06, .045 TD>DCD L STS - dlPMC 2.03, .048 Table 2. Significant group AON connectivity results. IFG = left inferior frontal gyrus (-60, 12, 14); IFG = right inferior frontal gyrus (58, 16, 10); IPL/SII = inferior parietal lobule/secondary somatosensory cortex (52, -36, 52); dPMC = dorsal premotor medial cortex (-1, 12, 52); dlPMC = dorsal lateral premotor cortex (-36, -14, 62); STS = superior temporal cortex (-54, -50, 10); R = right; L = left. Figure 5. Bilateral IFG connectivity. Bar chart showing bilateral inferior frontal gyrus (IFG) connectivity in typically developing individuals (TD, blue); developmental coordination (DCD, green); and autism spectrum disorder with motor impairments (ASDd, red). Within groups bilateral IFG connectivity was not related to social or motor skills, however, across groups, bilateral IFG connectivity was positively correlated with aiming and catching on the MABC-2 (R = .419, p = .006; Figure 6). When adjusting for social SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 108 skills, this relationship remained significant (R = .380, p = .014). IFG connectivity was also related to social skills (SRS-2 Total: R = -.323, p = .037), however, when adjusted for motor skills, this relationship was non-significant. Figure 6. Left-Right inferior frontal gyrus (IFG) connectivity during motor performance. Scatter plot showing connectivity across all groups correlated with the aiming and catching subscale of the Movement Assessment Battery for Children (MABC-2; R = .512, p = .001). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 109 Within- and between-group DMN connectivity. Overall, the TD, ASDd, and DCD groups revealed DMN connectivity consistent with previous studies, with extensive PCC seed connectivity with the PrC, mPFC, and TPJ/superior lateral occipital cortex (Raichle et al., 2001; Shulman et al., 1997; Figure 7). Notably, PCC seed-based connectivity revealed bilateral TPJ/LOC nodes in the ASDd group, while the TD and DCD group only showed left hemisphere connectivity. However, bilateral TPJ/LOC nodes in these groups are present at a slightly lower significant threshold (Z = 1.96). Figure 7. Default Mode Network (DMN): Group main effects. Posterior cingulate cortex (PCC) seed whole-brain connectivity maps in each group displayed on the Montreal Neurological Institute template (A) typically developing (TD; blue) (B) autism spectrum disorder with motor impairments (ASDd; red) and (C) developmental coordination disorder (DCD; green). All results were thresholded at p = .01 and cluster TPJ/LOC SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 110 corrected at a threshold of Z = 2.3. PCC = posterior cingulate cortex; mPFC = medial prefrontal cortex; TPJ = temporal parietal junction; LOC = lateral occipital complex. L = left hemisphere. Group contrasts. TD greater than ASDd and DCD contrasts. The TD group had increased PCC connectivity with the bilateral mPFC compared to the DCD group (Figure 8B). Connectivity between the PCC and PFC was positively related to MABC total scores in the TD group (R = .613; p = .015). There were no significant areas where TD connectivity was greater than ASDd. ASDd greater than TD and DCD contrasts. The ASDd group had hyperconnectivity of the PCC and bilateral SMG/precentral gyrus compared to the TD group (Figure 8A). The PCC connectivity with this region was significantly correlated with social cognition skills in the ASDd group such that greater social skills were related to greater connectivity (R = -.561, p = .030; figure 9A). The ASDd group also had increased connectivity between the PCC and bilateral mPFC compared to the DCD group (Figure 8B). Connectivity between the PCC and mPFC was negatively correlated with manual dexterity in the DCD group (R = -.683; p = .029) such that decreased motor skills were related to increased PCC-PFC connectivity. A conjunction analysis was performed on the overlapping regions in the mPFC where both the TD and ASDd groups had significantly greater PCC connectivity than the DCD group. Manual dexterity scores in the DCD group were negatively related to PCC-mPFC FC (R = -.698, p = .025; Figure 9D). DCD greater than TD and ASDd contrasts. Stronger connectivity was detected in the DCD group compared to the TD and ASDd groups (Figure 8C). Group comparisons revealed hyperconnectivity between the PCC seed and the inferior division of the left SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 111 lateral occipital cortex (LOC) and bilateral PrC and PCC compared to the TD group (Z = 2.3). At a slightly lower threshold (Z = 1.96), similar hyperconnectivity in the superior division of the left LOC and bilateral PrC was observed compared to the ASDd group. DCD>TD connectivity in the LOC was negatively related to social motivation skills and trending towards a negative relationship with aiming and catching skills (social motivation: R = .692, p =.027; Figure 9B; catching and aiming: R = -.576, p = .082; Figure 9C). A conjunction analysis was performed on the overlapping regions in the bilateral PrC where the DCD group had significantly greater PCC connectivity than the TD and ASDd groups. DCD connectivity was not related to social or motor skills in this region. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 112 Figure 8. Whole brain posterior cingulate cortex (PCC) functional connectivity group contrasts on Montreal Neurological Institute template. (A) Regions of the default mode network (DMN) where connectivity with the posterior cingulate cortex (PCC) seed was stronger in the autism spectrum disorder with motor impairments group (ASDd) compared to the typically developing (TD) group (red). (B) Regions of the DMN where connectivity with the PCC seed was stronger in the TD (blue) and ASDd (orange) groups compared to the developmental coordination disorder (DCD) group. (C) Regions of the DMN where connectivity with the PCC seed was stronger in the DCD group compared to the ASDd (yellow) and compared to TD group. LOC = lateral occipital cortex, mPFC = medial prefrontal cortex, SMG/PRC= sensorimotor/precentral gyrus, R = right hemisphere, L = left hemisphere. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 113 A. B. C. D. Figure 9. Scatter plots of social and motor skills and group contrast posterior cingulate cortex (PCC) connectivity. Scatter plot illustrating functional connectivity (FC) with the PCC in regions that significantly differed between groups and social and motor skills. (A) Supramarginal gyrus connectivity correlated with the social cognitive subscale of the SRS-2 in the ASDd group (R = -.561, p = .030). (B) CCs-lateral occipital cortex (LOC) FC positively correlated with the social motivation subscale score of the SRS-2 in the DCD group (R = .692, p = .027) and (C) PCC-LOC FC (TD>DCD) negatively correlated with the aiming and catching subscale score of the MABC-2 in the DCD group (R = -.576, p = .082). (D) PCC- prefrontal cortex (mPFC) FC (TD and ASDd>DCD) negatively correlated with the manual dexterity subscale score of the MABC-2 in the DCD group (R = -.698, p = .025). Within-group social and motor regressions. To determine whether social skills related to DMN connectivity over and above motor skills in the ASDd and DCD groups, we controlled for motor skills when assessing PCC seed connectivity relate to social skills and vice versa for motor skills. After including age and social and motor skills in the same analysis, significantly stronger DMN connectivity was related to social skills in the superior parietal lobule (sPL) and with motor skills in the PrC in the ASDd group. Motor skills were negatively related to bilateral LOC before and after controlling for social skills. In the DCD group, social skills were positively related to DMN SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 114 connectivity in the superior LOC with and without controlling for MABC (no significant voxels overlapped with ASDd MABC-2 finding), and negatively related to motor skills in the bilateral PrC before and after controlling for social skills. Figure 10. Social and motor skills and PCC connectivity. (A) Regions in the autism spectrum disorder with motor impairments group (ASDd) where connectivity with the posterior cingulate cortex (PCC) was positively correlated with social skills measured by the Social Responsiveness Scale, Second Edition Total score (SRS-2; red) and motor skills measured by the Movement Assessment Battery for children, Second Edition (MABC-2; blue) total score. (B) Regions in the developmental coordination disorder (DCD) group where connectivity with the PCC was positively correlated with social skills measured by the SRS-2 (red). (C) Regions in the ASDd group where connectivity with the PCC was negatively correlated with motor skills measured by the MABC-2 (yellow). (D) Regions in the DCD group where connectivity with the PCC was negatively correlated with motor skills measured by the MABC-2 (yellow). LOC = lateral occipital cortex; PRC = precentral gyrus; PrC = precuneous; sPL = superior parietal lobule. R = right hemisphere. Discussion We used resting state FC MRI to examine intrinsic FC of the brain networks supporting action observation and social cognition, in samples of children and SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 115 adolescents with ASDd, DCD, and matched TD controls. Overall, reduced AON activation was observed in both clinical groups and bilateral FC of the IFG was related to motor skills across all participants. DMN analysis indicated hyper and hypoconnectivity with the PCC in the ASDd and DCD group relating to both social and motor ability. AON connectivity. The pattern of reduced correlations observed within the AON network—detected through within-network brain analyses—is consistent with previous AON resting state findings (Fishman et al., 2015) and indicative of a weaker integration of the AON network in ASD. Underconnectivity within network is in contrast to typical development, during which neural networks become simultaneously more integrated (i.e., within-network connections strengthen). Although connectivity between the AON and other intrinsic networks was not assessed here, in typical development, between- network connectivity becomes increasingly segregated (i.e., out-of-network connections weaken) with age (Fair et al., 2009). Consistent with our hypothesis, we show that individuals with motor skill deficits regardless of group status have a disruption in this network, providing evidence that motor ability may modulate brain network integration in the AON. Specifically, the reduced bilateral IFG connectivity found in ASD indicates abnormal AON connectivity at rest, supporting theories of AON disruption in ASD in general and corroborates findings of altered AON activation during action observation and imitation tasks. Moreover, IFG connectivity was positively related to motor skills above and beyond social skills when looking across groups. This finding further indicates that motor ability is related to AON connectivity. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 116 DMN connectivity. Here, we demonstrated that specific patterns of resting-state connectivity are related to both brain and behavioral markers of social and motor skills in ASDd and DCD. Specifically, we showed that in children and adolescents with social and motor developmental disorders (ASDd), the severity of social cognition deficits is associated with greater connectivity during resting state outside the DMN (e.g., sensorimotor/precentral cortex). Youth with motor deficits showed atypical PCC connectivity with regions that are part of the DMN (e.g.., prefrontal cortex and PCC) and as well as regions that are not considered part of the DMN (e.g., LOC). Findings of increased resting-state connectivity within primary sensory processing regions are consistent with previous reports that these areas over-activate when responding to sensory stimuli in youth with ASD and correlated with measures of sensory over-responsivity (SOR) in the salience network (anterior insula, anterior cingulate, temporal poles, dorsolateral prefrontal cortex, and amygdala; Green et al., 2013, 2015, 2016). Further, the fact that the DMN network is more connected with primary sensory processing regions at rest suggests that individuals with both social and motor deficits have intrinsic patterns of brain connectivity that reflect over-attribution of baseline self-referential cognition. Interestingly, when looking within the ASDd group across the whole brain, both social and motor skills were positively related to PCC-sensorimotor connectivity in a more ventral area of the same medial sensorimotor region where we found group differences and extending to superior parietal regions. These relationships were only significant when controlling for motor and social skills, respectively. Motor skills were SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 117 also negatively correlated with bilateral LOC connectivity in ASDd participants. These findings indicate that social and motor skills are related to the DMN in ASD independently. To the best of our knowledge, the DMN has not been examined in DCD. Our novel study is the first to indicate that individuals with DCD have abnormal DMN connectivity. Interestingly, our finding of increased within-network connectivity in the PCC is consistent with ASD literature (Lynch et al., 2013). It is possible that previous findings were reported on a sample of ASD with motor skill deficits while other studies that have reported reduced PCC connectivity (Weng et al., 2010) analyzed an ASD sample with fewer motor deficits. Moreover, hyperconnectivity with the right LOC was negatively related to aiming and catching skills and social motivation skills. These findings suggest that individuals with motor deficits have intrinsic patterns of brain connectivity that reflect over-attribution of resting connectivity to motor as well as social deficits. This finding was replicated in the whole brain within-group analysis revealing that motor skills were negatively related to LOC-PCC connectivity. Hyper-LOC connectivity may reflect visual motor deficits often found in children with DCD/dyspraxia (Ayres, 1988; Cairney et al., 2015). Conversely, the DCD group had decreased PCC connectivity with prefrontal regions compared to both the TD and ASDd group. Hypoconnectivity here was related to increased manual dexterity skills as measured by the MABC-2 in DCD. This finding, however, was not replicated in the whole brain motor skills analysis suggesting the hypoconnectivity may be related DCD impairments not entirely related to motor skills, at least not those measured by the MABC. Future studies may look at how other motor SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 118 measures, like the Praxis Test (Ayres, 1988), or cognitive planning measures related to the prefrontal cortex, correlate with hypoconnectivity between the PCC and prefrontal regions. Overall, by comparing the ASDd and DCD-only group, we showed that both groups have altered DMN connectivity such that a co-occurring ASD and DCD diagnosis results in hyper-sensorimotor connectivity, while motor deficits alone elicit decreased prefrontal and increased LOC connectivity. Further, consistent with our hypothesis, the clinical groups had discrete patterns of connectivity related to social and motor skills at the whole brain level. To more fully understand how social and motor skills interact in ASD, a fourth group comprised of individuals with ASD who do not have motor deficits should be compared to the ASDd and DCD groups. Comparing individuals with ASD with and without motor impairments would illuminate how motor impairments interact in individuals with social impairments. Limitations. Some limitations of the present analysis must be considered. First, the study has a relatively small sample size, and therefore future studies are needed to replicate our findings with a larger sample size. However, the group characteristics were comparable to previous studies of ASD and current DCD studies (Licari et al., 2015; Travers et al., 2012). Furthermore, this study was comprised of high-functioning children and adolescents with ASD who displayed normal IQ scores and good verbal skills. Therefore, it remains unclear to what extent the present findings can be generalized to the larger ASD population or selected sub-groups, such as “low-functioning” individuals SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 119 with ASD or adults with ASD. Network connectivity patterns change throughout typical human development (Uddin, Supekar, & Menon, 2010), therefore future studies should consider investigating social and motor skills across the lifespan. Finally, the influence of other psychiatric comorbidities such as ADHD or the use of psychotropic medications in our ASD and DCD samples cannot be ruled out. However, as acknowledged by Fishman and colleagues (2015) it is difficult to recruit a “pure” sample of ASD, and likely DCD as well (Visser et al., 2003, Williams and Lind, 2013). Conclusions. We have sought to investigate a subgroup of individuals with ASD to better understand aberrant AON and DMN connectivity previously reported in ASD neuroimaging literature. We have linked these networks connectivity with specific phenotypic features of social and motor dysfunction in ASD and have demonstrated a relationship between social and motor skills in this subgroup of ASD. We used this framing to delineate how DMN function is disrupted in children and adolescents with and without social and motor deficits. Our results suggest that atypical connectivity in the AON underlies motor deficits in individuals regardless of diagnosis or social abilities and supports the notion that AON disruption is a function of motor impairments. We also observed that atypical DMN connectivity thought to primarily underlie social cognition is also correlated with motor ability in individuals with motor impairments. Specifically, we find that both within and outside DMN network connectivity is modulated by motor skills. Since individuals with motor skill impairments and no social skill impairments have atypical connectivity patterns, these findings highlight the necessity for studying SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 120 heterogeneous patterns of FC in ASD samples who consist of both individuals with and without motor impairments. These findings provide evidence that suggest heterogeneity in motor skills may account for some discrepant findings in previous ASD resting state literature. Studies comparing subgroups of ASD will play a crucial role in moving forward. Knowledge of how functional interactions between the DMN and other brain systems differ between subgroups of ASD (e.g., with or without motor impairments) will be fundamental to the study of the neurobiological basis of ASD as well as the development of social and motor therapy. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 121 Supplementary Materials To determine whether social skills related to DMN connectivity over and above motor skills in the TD group, we controlled for motor skills when assessing PCC seed connectivity relate to social skills and vice versa for motor skills. After including age and social and motor skills in the same analysis, significantly stronger PCC connectivity was related to motor skills in within the DMN network (PCC and mPFC) and with social skills in the LOC only after controlling for motor skills. Motor skills were negatively related to the bilateral insula, angular gyrus, and precentral gyrus. However, when controlling for social skills, these findings were not significant. Social skills were negatively related to PCC connectivity in the right hemisphere insula, IFG, PRC and superior parietal lobule. After controlling for motor skills these findings were non-significant (Figure 11). Figure 11. Social and motor skills related to posterior cingulate cortex (PCC) connectivity in the typically developing (TD) group. (A) Regions in the group where connectivity with the PCC was positively correlated with motor skills measured by the Movement Assessment Battery for Children, Second Edition (MABC-2; dark blue) and motor skills when controlling for social skills measured by the Social Responsiveness Scale, Second Edition Total score (SRS-2; light blue). (B) Regions where connectivity SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 4 122 with the PCC was negatively correlated with motor skills measured by the Movement Assessment Battery for Children, Second Edition (MABC-2; red). (C) Regions where connectivity with the PCC was negatively correlated with social skills measured by the SRS-2 (yellow). (D) Regions where connectivity with the PCC was positively correlated with social skills measured by the SRS-2 (green). (E) Regions where B and D overlap (red and green). LOC = lateral occipital cortex, PRC= precentral gyrus, PrC= precuneous; sPL = superior parietal lobule, R = right hemisphere. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 123 Chapter 5. Tractography Related to Social and Motor Deficits in Autism Spectrum Disorder and Developmental Coordination Disorder Abstract Introduction: Previous research findings have linked structural white matter integrity and connectivity in the action observation network (AON) to social and imitation deficits in autism spectrum disorder (ASD; Fishman, Datko, Cabrera, Carper, & Müller, 2015; Hadjikhani, Joseph, Snyder, & Tager-Flusberg, 2007). While many clinicians and researchers have reported motor coordination deficits in ASD, few have looked at the interaction between social and motor impairments. This study investigates social and motor skills as they relate to white matter microstructure. Methods: Participants were 10 children and adolescents with ASD who also had motor impairments (ASDd), 10 with children with developmental coordination disorder (DCD), and 13 typically developing (TD) children, all aged 8 to 15. Children underwent diffusion weighted imaging (DWI). Quantitative anisotropy (QA) and generalized fractional anisotropy (GFA) were assessed on the scans to measure white matter connectivity within the AON as it relates to social and motor skills. Results: Structural connectivity in the genu of the corpus callosum (CC) was positively related to motor skills in the TD and DCD groups but not in the ASDd group. In ASDd, motor skills were positively correlated with the splenium of the CC. Interestingly, social skills were correlated with different regions in each group. Moreover, QA relationships SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 124 between tracts in the AON and social and motor skills were observed. Finally, group contrasts revealed significant differences in GFA among all groups. Conclusions: These findings demonstrate that social and motor skills have discrete and common patterns of structural connectivity. These patterns are reflected in the reduced connectivity found in the ASDd and DCD groups. Our findings indicate that altered ASDd connectivity in the genu of the CC can be modulated by motor skills. Moreover, the integrity of tracts in the AON may contribute to both social and motor skills. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 125 Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a highly heterogeneous presentation of social deficits such as social communication skills, repetitive and restrictive behaviors (APA, 2013) as well as motor deficits (Fournier et al., 2010). The disorder’s complexity makes it difficult to investigate its etiology or to identify specific neural mechanisms that may underlie the disorder. In recent years, researchers have begun to hypothesize that no one brain region is implicated in the disorder, but instead, ASD is a disorder of disrupted neural systems (Just et al., 2012; Minshew, 2008). This theory posits that abnormalities in functional and structural connectivity between and within brain networks are related to ASD symptomatology. However, the direction of network abnormalities is unclear. Both hyper- and hypoconnectivity have been demonstrated in children with ASD across multiple networks (i.e., default mode, imitation; Müller et al., 2011; Rane et al., 2015; Supekar et al., 2013). Because ASD is highly heterogeneous and the disorder is frequently comorbid with conditions such as anxiety, attention deficit hyperactivity disorder (ADHD), epilepsy, fragile X syndrome, neuroinflammation and immune disorders, sensory disorders, obsessive-compulsive disorder and developmental coordination disorder (DCD), variation in symptomatology can confound findings and make it difficult to disentangle discrete ASD-only related neural mechanisms. One network that has been linked to ASD is the action observation network (AON; Iacoboni & Dapretto, 2006). The AON is composed of sensorimotor brain regions that are active both when a person makes an action as well as when a person observes the same action. These include the superior temporal sulcus (STS), the premotor cortex (PMC), the inferior parietal lobule (IPL) and the inferior frontal gyrus (IFG). These latter SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 126 three brain regions are thought to contain putative mirror neurons in the non-human primate brain (di Pellegrino et al., 1992; Gallese et al., 1996; Rizzolatti et al., 2001), and human (Keysers & Gazzola, 2009; Molenberghs et al., 2012) brains. The AON has been postulated to underlie social and imitation deficits in ASD (Iacoboni & Dapretto, 2006; Williams et al., 2001). Specifically, this network has been associated with social deficits in several functional and structural neuroimaging studies suggesting that this network is disrupted in ASD (Fishman et al., 2015; Iacoboni & Dapretto, 2006; Williams et al., 2001), although other studies have found no such relationship (Press et al., 2010; Schulte-Rüther et al., 2017). While it is possible that some of these conflicting results may be due to age effects (Bastiaansen et al., 2011), they may also be due, in part, to the heterogeneity of ASD samples in different studies. Specifically, because AON regions are motor regions, and because motor abilities are highly heterogeneous in ASD, it may be that differences in motor ability can explain some of the previous divergent results regarding AON activation patterns. Indeed, data indicate that up to 80% of individuals with ASD have motor deficits (Fournier et al., 2010; D. Green et al., 2009; Hilton et al., 2012). There is evidence to suggest that AON dysfunction also may occur in other deficits outside of ASD where motor impairments are common. Specifically, AON dysfunction has been observed in children and adults with DCD (for a review see; Werner et al., 2012). Individuals with DCD are characterized primarily by motor and coordination deficits. If social skills impairments are present in DCD, they are considered to be secondary effects in self-esteem relating to not being picked for sports teams, etc. Thus, it is possible that the interaction between social and motor deficits SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 127 and/or variance in motor deficits alone may resolve some of the aberrant AON findings in ASD. Diffusion weighted imaging (DWI) is a non-invasive neuroimaging technique used to study structural connectivity and integrity. It has been used with ASD participants and typically developing (TD) controls (Ameis & Catani, 2015; Anagnostou & Taylor, 2011; Hadjikhani et al., 2006; Hecht, 2013; McCrimmon & Smith, 2013; Travers et al., 2012). The parieto-frontal connections, superior longitudinal fasciculus (SLF), and corpus callosum (CC) are tracts commonly identified by whole brain data-driven analyses and have been linked to social deficits in ASD (Alexander et al., 2007; Hanaie et al., 2014; Hardan et al., 2009; Lo, Chen, Hsu, Tseng, & Gau, 2017). Broadly, individuals with ASD demonstrate reduced structural integrity in these regions compared to TD control peers, albeit with some exceptions (Tepest et al., 2010; Weinstein et al., 2011; Wolff et al., 2012). Relatively few studies have directly studied the AON network in ASD, although one study found reduced AON connectivity between peak coordinates found to be active during imitation in an ALE meta-analysis (Caspers et al., 2010) in individuals with ASD compared to controls at the group level (Fishman et al., 2015). Two other studies observed no group differences but found significant relationships between social deficits and the integrity of tracts connecting regions of the AON (Chien, Gau, et al., 2015; Fründt et al., 2018). Fishman et al. (2015) found that tracts connecting the IFG and the lateral dorsal PMC (likely part of the SLF) had reduced fractional anisotropy (FA; a surrogate of white matter microstructure) in ASD. Chien et al. (2015) did not find significant group differences between structural connectivity of the AON but did report significant correlations between the integrity of the right frontal-parietal tracts (pars SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 128 opercularis and supramarginal gyrus [SMG]) and social skills in ASD. Similarly, in a study by Fründt and colleagues (2017), typical tract related microstructure was observed between individually paired regions of the AON (regions included: IFG, STS, and SMG), but correlations between social skills were related to tract connectivity. To date, and to our knowledge, no study has looked at how motor skills relate to white matter tracts across the whole brain in ASD or in individuals with co-occurring diagnosis of ASD and DCD (ASDd). However, one study did look specifically in the segmented regions of the CC among a sample of TD and ASD participants, however, they found no relationship with motor skills and the sample was relatively small (TD n = 12; ASD n = 18; Hanaie et al., 2014). It is notable, however, that groups in this study were not matched for IQ which previously has been identified as significantly related to CC integrity (Alexander et al., 2007). In DCD literature, there have been some studies that relate motor skills to structural connectivity within and between other networks. Reduced FA in the SLF and CC has been observed in individuals with DCD as compared to TD controls (Langevin et al., 2014). Overall, DWI findings in the DCD population suggest that children with DCD have disrupted white matter integrity in tracts that connect with motor planning and processing cortical regions (Debrabant et al., 2016; Zwicker et al., 2012) as well as between frontoparietal networks that connect with parts of the AON (Kashuk, 2017). Since poor motor skills and social skills both have been associated with a lack of structural integrity and connectivity in the AON, it is possible that motor skill deficits may compound some of the social deficits seen in ASD. To date, only one study has compared structural connectivity using graph theory analysis in and among ASD, DCD, and controls (Caeyenberghs et al., 2016). In this SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 129 study, researchers looked at structural connectivity between networks and found both distinct and overlapping topographical patterns. Children with DCD or ASD demonstrated alterations in network efficiency measured by clustering coefficients in paralimbic regions. Specifically, children with ASD displayed increased network efficiency in the orbital part of the right IFG and the isthmus of the cingulate gyrus, while children with DCD demonstrated increased network efficiency in the right lateral orbitofrontal cortex. Individuals with co-occurring disorders (ASDd) had a distinct widespread pattern of clustering coefficients including reduced efficiency in the IFGpo. To our knowledge, no study has examined white matter tracts related to social and motor skills in both clinical samples (ASD and DCD). Current Study The aim of our present study is to try to understand how motor and social skills impact structural and functional connectivity in children with ASD, thus aiming to explain some of the heterogeneity seen in ASD findings. To meet this aim, we include three participant groups that vary in social and motor impairments: TD (average to high social and motor skills), DCD (low motor skills; average social skills), and a subgroup of ASD who also display motor deficits similar to those seen in DCD (ASDd; low social skills; low motor skills). Based on previous findings, we hypothesize that we will find group differences in structural connectivity in the CC, SLF, and within regions of the AON which have previously reported to be atypical in ASD (Fishman et al., 2015) such that the TD group will have stronger connectivity than the DCD group followed by the ASDd SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 130 group. We further hypothesize that social and motor skills will be related to these white matter differences. Methods Participant characteristics. Individuals ages 8 to 15 with ASDd (n = 10; 1 = female), DCD (n = 9; 3 = female), and TD controls (n = 17; 3 = female) participated in the study. ASDd participants were recruited from clinics in the greater Los Angeles healthcare system, through local public and private schools, and through word of mouth and social media advertising. ASDd participants were high functioning (IQ 80-134) and had received a diagnosis either through a clinical ASD diagnostic interview, an ASD diagnostic assessment, or both. We assessed clinical symptoms using the Autism Diagnostic Observation Schedule-2, Module 3 (ADOS-2; Lord et al., 2000). Exclusion criteria for ASDd included: (a) IQ < 80 (in cases where the full-scale IQ was less than 80, participants were included if their verbal IQ score or perceptual reasoning IQ score were greater than 80 as assessed by the Wechsler a Abbreviated Scale of Intelligence, Second Edition (WASI-2; Wechsler, 2011), (b) history of loss of consciousness greater than five minutes, (c) left-handed, (d) not sufficiently fluent in English or parent who did not have English proficiency, (e) a diagnosis of other neurological or psychological disorders except for attention deficit disorders or generalized anxiety disorder, (f) a Movement Assessment Battery for Children, Second Edition (Henderson et al., 2011) score greater than fifteen percent indicating no clinical risk for DCD and a score on the Developmental Coordination Disorder Questionnaire (DCDQ; Wilson, 2007) indicating a unlikely or not suspected DCD diagnosis. All participants were born after 36 weeks of SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 131 gestation and screened for MRI compatibility. Participants were also evaluated for their capacity to give informed consent and then provided their written consent after being informed about the study procedures in accordance with the study protocols approved by the University of Southern California Institutional Review Board. DCD participants were recruited from therapy clinics throughout California, through Los Angeles-area public and private schools, and through national DCD/dyspraxia support groups. In addition to the exclusion criteria established for the ASDd group (a-f), DCD participants were excluded if they had (g) a personal diagnosis or an immediate family member with a diagnosis of ASD or (h) a Social Responsiveness Scale-2 (SRS-2) T-score indicating risk of ASD (> 60) and a subsequent ADOS-2 score in the clinical range. Healthy control (TD) participants were recruited through flyers posted in the local community, social media, and website postings. Exclusion criteria for TD control participants included the first four elements of ASDd exclusion criteria listed above (a- d). TD controls additionally were excluded if they had any psychological diagnosis or neurological disorder, including attention deficit disorders and generalized anxiety disorder or if they scored below the twenty-fifth percentile on the MABC-2 score or were likely to suspected to have a DCD diagnosis based on a DCDQ score. Three ASDd participants and four DCD participants were on psychotropic medication at the time of data collection. Social, and motor measures. Motor skills were assessed with the MABC-2, a performance-based assessment that evaluates motor skill ability. The second (ages 7– 10) and the third (ages 11–16) age bands were administered. The MABC-2 consists of SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 132 three subtest scores: manual dexterity, gross-motor aiming and catching skills, and balance as well as a total score. Higher scores indicate better functioning. Item and subtest standard (scaled) total scores based on the normative sample were examined in our analyses. The DCDQ is a 15-item screening questionnaire that ascertains gross and fine motor skill impairments that would contribute to a diagnosis of DCD. The questionnaire was utilized as an informative qualifier for DCD in our ASDd sample. The DCDQ yields a raw total score (score range 15–75), with higher scores indicating better motor function. In addition, parents of all participants completed the SRS-2. The SRS-2 is a parent-completed survey comprised of five subscales regarding their child’s social skills: social awareness, social cognition, social communication, social motivation, and mannerisms. Scores are reported in T-scores. MRI data acquisition and processing. Data collection. DW was acquired on a three Tesla MAGNETOM Prisma (Siemens, Erlangen, Germany) using a 20-channel head coil and the following parameters: A multi-shell diffusion scheme was used, with b-values of approximately 1500 and 3000 s/mm2. The number of diffusion sampling directions were 90 collected in the AP and PA direction separately. The slice thickness was 1.5 mm. A structural scan also was acquired for each participant (T1-weighted MPRAGE; TR = 1,950 ms, TE = 3.09 ms, flip angle = 10˚, 256 x 256 matrix, 208 coronal slices, 1 mm isotropic resolution). Total acquisition time was 14 minutes. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 133 Diffusion spectrum imaging preprocessing. For each subject, AP and PA diffusion scans were aligned to the T1 structural image and reconstructed in a common stereotaxic space (Montreal Neurological Institute [MNI-152] template) using q-space diffeomorphic reconstruction (QSDR; Yeh, Tang, & Tseng, 2013). The mapping function φ was obtained by registering the FA maps of the subject to the FMRIB 1 mm FA template (FSL, Oxford, UK) using a nonlinear registration (Ashburner & Friston, 1999) implemented in DSI Studio (http://dsi-studio.labsolver.org). The spin distribution functions (SDFs) were reconstructed in the MNI-152 space using QSDR. Head motion was assessed by FSL’s MCFLIRT. Participants who had moved more than three mm in any direction (X, Y, Z) in either their AP or PA scan were removed from the final analysis. Four participants were removed from the TD group, three were removed from the ASDd group, zero were removed from the DCD group. Group connectometry and tractography. Analyses between groups were conducted on three separate connectometry databases (TD and ASDd, TD and DCD, ASDd and DCD) which included scans from each group. Diffusion connectometry measures white matter tract density by calculating SDF in every voxel in the brain and length of the affected track. For each database, the diffusion data were reconstructed in the MNI space using QSDR to obtain the SDF. A diffusion sampling length ratio of 1.25 was used, and the output resolution was 2 mm. Generalized fractional anisotropy (GFA) values were used in the connectometry analysis. Similar to FA, GFA has been used to infer microstructural integrity to the white matter fiber tracts (Fritzsche, Laun, Meinzer, & Stieltjes, 2010; Gorczewski, Mang, & Klose, 2009). GFA can be thought of as a higher- order generalization of FA (Descoteaux, Angelino, Fitzgibbons, & Deriche, 2007) and is SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 134 strongly correlated with FA. Since age is linked to white matter brain development (Barnea-Goraly et al., 2005), multiple regression was used to consider age and group. A T-score threshold of 2.0 was assigned to select local connectomes, and the local connectomes were tracked using a deterministic fiber tracking algorithm (Yeh et al., 2013). Track trimming was conducted with 1 iteration. All tracks generated from bootstrap resampling were included. A length threshold of 40 mm was used to select tracks. The seeding density was 20 seeds per mm 3 . To estimate the false discovery rate (FDR), a total of 2000 randomized permutations were applied to the group label to obtain the null distribution of the track length. Social and motor connectometry and tractography. Diffusion MRI connectometry (Yeh, Badre, & Verstynen, 2016) was also used to study the effect of social and motor skills. Using QSDR (Yeh et al., 2013) with a diffusion sampling length ratio of 1.25, the diffusion data were reconstructed. The output resolution was 2 mm. A multiple regression model was used to consider age and MABC-2 Total, or SRS-2 Total as a regressor separately for each group. A T-score threshold of 2 was assigned to select local connectomes, and the local connectomes were tracked using a deterministic fiber tracking algorithm (Yeh et al., 2013). Track trimming was conducted with 1 iterations. All tracks generated from bootstrap resampling were included. A length threshold of 40 mm was used to select tracks. The seeding density was 20 seed(s) per mm3. To estimate the false discovery rate, a total of 2000 randomized permutations were applied to the group label to obtain the null distribution of the track length. AON analysis. Tractography seeds were placed in seven regions of interest (ROIs) in the AON found to be consistently activated by imitation tasks in an ALE meta- SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 135 analysis (Caspers et al., 2010). These ROIs also have been reported to have significant FA differences between TD and ASD groups in a recent paper by Fishman and colleagues (2015). The seeds included regions in the bilateral IFG, dorsolateral premotor cortex (dlPMC), medial premotor cortex (mPMC), IPL, and left superior temporal sulcus (STS; see Figure 6 for seed placements and MNI coordinates). Seeds were created using 10 mm-radius spheres around peak coordinates and were nudged towards the local grey-white matter boundary as performed by Fishman et al. (2015) to increase projection from the functionally defined gray matter ROIs into the adjacent white matter. The SLF also was tracked from the created left and right hemisphere IFG seed to the Harvard-Oxford mid-temporal sulcus ROI. Pairs of ROIs to track were chosen based on significant group (TD and ASD) findings in previous literature (Fishman et al., 2015). For each ROI pair, 1,000,000 streamlines were initiated across the whole brain, propagating with 0.5 mm step length, a quantitative anisotropy (QA) threshold of 0.15, a minimum track of 40 mm, and an angular threshold of 65 degrees. QA is defined for each peak of the spin distribution function, making this technique less sensitive to partial volume effects and therefore provides a useful index for filtering fiber populations and for defining track termination in deterministic tractography (Yeh et al., 2013). While QA is related to FA they are not interchangeable indices. For example, while FA and GFA measure how fast water diffuses, QA measures how much water diffuses (Fang-Cheng, Van Jay, & Tseng, 2010) and quantifies the measure of fiber integrity within each resolved fiber population. QA values were calculated for each tract that passed through each AON pair and averaged for each participant. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 136 Results A description of the demographics and characteristics of the TD, ASDd, and DCD groups is presented in Table 1. Table 1 Group Demographics. Controls n = 13 ASDd n = 10 DCD n = 9 Characteristic Mean SD Range Mean SD Range Mean SD Range Sex (sum) 3 female - - 1 female - - 3 female - - Age 11.16 1.38 9.1-13.9 11.51 1.95 9.4-15.5 12.07 2.05 9.4-15.1 Full-Scale IQ 117.00 9.87 102-137 104.90 21.92 74-134 104.44 19.23 74-132 VIQ 118.15 9.71 108-136 103.40 25.38 65-151 108.78 14.87 87-136 PRIQ 110.46 13.11 92-132 105.70 20.25 72-130 100.78 26.63 74-154 DCDQ 72.85 9.15 55-85 44.0 9.15 31-55 44.0 11.45 28-63 MABC-2 Total 10.92 1.50 9-14 3.89 1.36 2-6 4.11 1.69 1-7 SRS-2 (t-score) 45.54 6.35 39-57 73.90 6.03 64-82 58.44 9.24 43-72 ADOS-2 - - - 11.22 3.53 7-17 - - - Note. Table of sample demographics. Age, sex, and IQ did not significantly differ between groups (p > .05). SRS and MABC-2 were significantly different between groups (p < 0.05). Note, one ASDd participant did not complete the manual dexterity MABC-2 subscore and therefore their MABC-2 Total score could not be calculated. VIQ = verbal IQ; PRIQ = perceptual reasoning IQ; MABC-2 = Movement Assessment Battery for Children, Second Edition; ADOS = Autism Diagnostic Observation Schedule, Second Edition; SRS-2 = Social Responsiveness Scale-2 Behavioral results. A one-way analysis of variance (ANOVA) test for the MABC- 2 Total standard score indicated a significant main effect of Group [F (2, 27) = 73.74, p < .000]. The LSD post hoc test indicated significant differences for all pairwise comparisons at p < 0.05 except for DCD and ASDd (p = 0.756). All pairwise comparisons at the subscale level between, TD and ASDd and TD and DCD were significant at p ≤ 0.001. There were marginally significant differences in the aiming and catching subscale between the DCD and ASDd groups (p = 0.058), otherwise, the remaining pairwise comparisons of the subscales non-significant (p > 0.617). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 137 An ANOVA test for the SRS-2 Total standard score indicated a significant main effect of Group [F (2, 28) = 46.76, p < 0.000]. The LSD post hoc test indicated significant differences for all pairwise comparisons at p < .0001. All pairwise comparisons at the subscale level between were significant at p < .025 except for social awareness between TD and DCD (p = .138) and social motivation between DCD and ASDd (p = .293). Finally, one ASDd participant’s diffusion data (QA, GFA) was constantly found to be greater two standard deviations outside the mean and was considered an outlier and removed from the analysis. The scatterplot for the SRS-2 Total score and MABC-2 total for each of the three groups (TD, ASDd, and DCD) is presented in Figure 1. Across groups the results show a negative correlation between SRS Total score and the MABC-2 Total score indicating a positive relationship between the social and motor skills, albeit one that is non- significant, and this relationship is reversed in each group except in the dual diagnosis group which had a slightly negative slope (ASDd, R = -0.135). Results are later discussed in relation to the Simpson’s Paradox, a phenomenon in which across-group correlations are reversed within an individual group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 138 Figure 1. Scatterplot of social and motor skills across and within all groups, typically developing (TD; blue), autism spectrum disorder with motor impairments (ASDd; red), and developmental coordination disorder (DCD; green). Pearson correlation across groups indicated a significant negative correlation between SRS-2 scores and MABC-2 scores suggesting a positive relationship between social and motor skills (R = -0.422, p = 0.009 two-tailed). All within-group correlations were non-significant (TD: R = .285, p = .345; ASDd: R = -0.135, p = .730; DCD: R = .245, p = .526). MABC-2 = Movement Assessment Battery for Children, Second Edition 4.2 Tractography results. Head movement during scanning can lead to distortions in the data and children with ASD tend to move more than their peers. As a quality assurance check, groups were assessed for differences in head motion. Groups did not differ in absolute or relative motion (p > .05). Motion was also assessed to see if it correlated with social and motor skills. Motion was not significantly related to social or motor skills within or across groups (p > .05). Group contrast tractography. TD greater than ASDd, and DCD. The connectometry analysis identified tracts with increased connectivity in the TD group compared to the ASDd group approaching a significant false discovery rate (FDR) detection threshold of .05 in the genu and body of the CC and bilateral cingulum (p < 0.05; FDR = 0.058). The connectometry analysis SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 139 identified statistically significant tracts in the genu of the CC (Figure 2A) with increased connectivity in the TD group compared to the DCD group (p < .05; FDR = .033). Figure 4 illustrates the mean connectivity in each group in CC tracts that are hypoconnected in the ASDd and DCD groups as compared to TDs. ASDd greater than TD and DCD. Although none our analyses passed FDR corrections, here we report some results that approached significance with FDR correction. Tracts with increased connectivity in the ASDd group were found at a moderately lower FDR threshold in the genu and splenium compared to the DCD group of the CC compared to the DCD group (p < 0.05; FDR = 0.084; Figure 2B). Social awareness SRS-2 subscores were negatively related to GFA in the splenium of the CC with tracts suggesting that as social awareness skills improved, connectivity in the splenium increases (R = -0.790, p = 0.011). DCD greater than TD, ASDd. The connectometry analysis identified no statistically significant tracts with increased connectivity in the DCD group compared to the TD group. However, the connectometry analysis did identify tracts that approached significance with increased connectivity in the DCD group compared to the ASDd group in the left cingulum (p < .05; FDR = .138; Figure 2C). See Figure 3 for box plots that show the differences in connectivity (GFA) in tracts that were significant between each group contrast analysis. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 140 Figure 2. Between-group whole-brain tractography maps shown on a Montreal Neurological Institute template. (A) Typically developing (TD) greater than autism spectrum disorder with motor impairments (ASDd; dark blue; FDR = .058) and TD greater than developmental coordination disorder (DCD; light blue; FDR = .033). (B) DCD greater than ASDd (green; FDR = .138). (C) ASDd greater than TD (purple; FDR = .268) and ASDd greater than DCD (pink; FDR = .084). FDR= false discovery rate. Table 2 Group Contrast Results Classified by JHU White Matter Labels Group contrast Tracts FDR, TRK count TD greater connectivity compared to: ASDd Genu CC Bilateral cingulum .058*, 923 DCD: Genu CC .033*, 437 ASDd greater connectivity compared to: TD: Splenium CC .268, 98 DCD: Genu CC Splenium .084*, 121 DCD greater connectivity compared to: TD: NA NA ASDd Left Cingulum 0.137, 28 Note. There were significant tractography findings between groups thresholded at t = 2. * FDR < .01 TD = typically developing; ASDd = autism spectrum disorder with motor impairments; DCD = developmental coordination disorder; CC = corpus callosum; NA = non-significant findings. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 141 Figure 3. Box Plots ROI analysis. Box plots which show differences in connectivity in tracts that were significant in group contrast analysis. TD = typically developing; ASDd = autism spectrum disorder with motor deficits; DCD = developmental coordination disorder; CC = corpus callosum; GFA = generalized fractional anisotropy. Connectivity analysis in the genu of CC across groups. The genu of the CC had significantly stronger connectivity (GFA) in the TD group compared to the ASDd and DCD groups. Moreover, a pattern of stronger connectivity in the posterior genu was also observed in the ASDd group compared to the DCD group. A conjunction analysis then was performed to compare connectivity between all three groups in tracts of the genu that differed across all three groups such that TD>ASDd> DCD (Figure 4). A one-way ANOVA test for these tracts indicated a main effect of group approaching significance [F (2, 28) = 2.274, p < .112]. The LSD post hoc test indicated nearly significant differences SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 142 for pairwise comparisons between TD and DCD (p = .058) and TD and ASDd (p = .133). The DCD and ASDd group did not differ (p = .700). See Figure 4 for a bar chart of mean connectivity. Connectivity in these tracts was also tested for relationships between social and motor skills. Connectivity in these tracts were found to be positively related to balance and standing skills in the DCD group (R = 0.753, p = .019). This pattern also approached significance in the TD group (R = 0.489, p = .09). Social skills were not related to connectivity in these tracts in any group. Figure 4. Bar graph of the genu of corpus callosum ROI connectivity in the typically developing (TD) group (blue), autism spectrum disorder with motor impairments group (ASDd; red), and developmental coordination disorder (DCD; green). GFA = generalized fractional anisotropy. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 143 Group level behavioral tractography results. Motor skills adjusted for age. TD group. The connectometry analysis identified no tracts were significant with FDR correction (FDR < 0.05) with increased or decreased connectivity related to MABC-2 Total (FDR = 0.857; p = .380). ASDd group. Statistically significant tracts were identified to be negatively related to the anterior body of the CC (p < .05; FDR = .043) such that decreased motor skills (lower MABC Total score) were related to increased connectivity in these regions. Furthermore, a nearly significant effect was found in both the posterior genu of the CC and cerebellum which was positively related to the MABC-2 Total score (p < .05; FDR = .221) such that increased motor skills were related to increased connectivity in these regions. DCD group. The connectometry analysis identified no tracts with increased connectivity related to the MABC-2 Total score that survived FDR correction (p < .05; FDR = 1.0). Patterns of decreased connectivity in tracts related to the MABC-2 Total score were identified in the splenium of the CC and bilateral cerebellum at a moderately lower threshold (p < .05; FDR = 0.170). Social skills adjusted for age. TD group. The connectometry analysis identified no tracts with increased or decreased connectivity related to the SRS-2 Total score that survived FDR correction (p < .05; FDR >.826). ASDd group. The connectometry analysis identified tracts with connectivity related to the SRS-2 Total score at a slightly reduced FDR threshold in the posterior SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 144 portion of the genu of the CC and bilateral middle cerebellar peduncle (p < .05; FDR = .074). This result indicates that social skills are negatively related to connectivity in these regions. DCD group. The connectometry analysis identified tracts with significantly increased connectivity related to the SRS-2 Total score (FDR = .063) in the genu of the CC, the left cingulum, and the corticospinal tract (CST) and decreased connectivity related to the SRS-2 Total score (FDR = 0.012) were identified in the splenium of the CC and the middle cerebellar peduncle of the cerebellum. Table 3 Social and Motor Regression Results Classified by JHU White Matter Labels Motor Skills (MABC-2) Social Skills (SRS-2) Tracts FDR Tract # FDR Tract # TD Positive: Negative: Genu of the CC Splenium of the CC Posterior body of the CC Left cingulum .857, 98 .381, 207 Genu of the CC Posterior body of the CC Bilateral cingulum Left cingulum .826, 89 FDR = 1.0, 8 ASDd Positive: Negative: Posterior genu of the corpus Callosum Bilateral middle cerebellar peduncle genu of the CC Anterior body of the CC Left cingulum .237, 105 .043, 496 Genu of the CC Splenium of the CC Right Inferior fronto occipital Genu of CC Splenium of CC .074, 300 .292, 51 DCD Positive: Negative: Left cingulum Splenium of CC Bilateral thalamic tract Right middle cerebellar peduncle Splenium of CC .187, 23 .187, 127 Left cingulum Bilateral middle cerebellar peduncle Splenium of CC Right cingulum .199, 22 .012, 467 CC = corpus callosum; TD = typically developing; ASDd = autism spectrum disorder with motor impairments; DCD = developmental coordination disorder; FDR = false discovery rate. MABC-2 = Movement Assessment Battery for Children, Second Edition; SRS-2 = Social Responsiveness Scale-2. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 145 Figure 5. Within-group whole-brain social and motor connectivity maps shown on a Montreal Neurological Institute template. (A) Structural connectivity negatively related to motor skills measured by the MABC-2 in ASDd (FDR = .043) and DCD (FDR = .026) groups. (B) Structural connectivity positively related to social skills measured by the SRS-2 Total in the DCD group (FDR = .024). (C) Structural connectivity negatively related to social skills measured by the SRS-2 Total in the DCD group (FDR = .074). FDR = false discovery rate; CC = corpus callosum; CST = corticospinal tract; SCP = superior cerebellar peduncle; SLF = superior longitudinal fasciculus; ASDd = autism spectrum disorder with motor impairments; DCD = developmental coordination disorder; FDR = false discovery rate; MABC-2 = Movement Assessment Battery for Children, Second Edition; SRS-2 = Social Responsiveness Scale-2 SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 146 Figure 6. Top: AON network seeds. IFG = inferior frontal gyrus (−60, 12, 14 and 58, 16, 10, left and right, respectively); SI/IPL = primary somatosensory cortex/inferior parietal lobule (52, −36, 52); L = left; lat- dPMC = lateral dorsal premotor cortex (−36, −14, 62 and 42, 4, 56); mPMC = medial premotor cortex (−1, 12, 52 and 14, 6, 66); SI/IPS = primary somatosensory cortex/intraparietal sulcus (−38, −40, 50); R = right; SII/IPL = secondary somatosensory cortex/inferior parietal lobule (60, −26, 20). Bottom left: Three- dimensional (3D) representation shows the tract connecting left hemisphere IFG and dlPMC, IFG and dPMC and SLF (IFG to temporal mid sulcus). Bottom right: 3D representation shows the tract connecting right hemisphere: IFG and IPL, IFG and dlPMC, IFG and dPMC and SLF (IFG to temporal mid sulcus). (A) and (B) shown over a standard Montreal Neurological Institute template. AON seed results. Group differences. An ANOVA was performed to compare QA in tract pairs of the AON between groups (TD, ASDd, DCD). The ANOVA revealed no group differences (data not shown). Behavioral correlations. Social skills were related to track QA. Within the ASDd group the SRS Total scores were negatively related to mean QA in the right hemisphere IFG-dmPMC tract (R = -0.681, p = .03) and the IFG-IPL tract (R = -0.670, p = .034). SRS social awareness and communication subscores were negatively related to mean QA in the right hemisphere SLF tract (R = -0.670, p = .034; R = -0.695, p = .026). In the DCD group, the SRS social awareness subscores were negatively related to mean QA in the left hemisphere IFG-dmPMC tract (R = .683, p = .043). Neither the SRS total nor any subscores were related to any tracts in the TD group. Motor skills were related to track QA. In the TD group, MABC-2 aiming and catching subscores were positively correlated with the left hemisphere IFG-dmPMC (R = .677, p = .020). QA in the same track was positively related to manual dexterity in the DCD group (R = .872, p = .002). In the ASDd group the left SLF was negatively related to the MABC Total score (R = -0.896, p = .003). SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 147 Table 4 AON Tracts and Behavior Correlations Within and Between-Groups Group Measure Left SLF IFG-dmPMC Right IFG-dmPMC IFG-dlPMC IFG-IPL SLF TD SRS-2 MABC-2 Total Manual Dexterity Aiming & catching Balance and standing N.S N.S N.S N.S N.S N.S N.S. N.S. N.S. N.S. N.S N.S .677, .020* N.S N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. ASDd SRS-2 Total Social awareness Cognition Communication Motivation Mannerisms MABC-2 Total Manual Dexterity Aiming & catching Balance and standing N.S. N.S. N.S. N.S N.S. N.S N.S. N.S. N.S. N.S N.S. N.S -.681, .03* N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S N.S. N.S -.641, .046* N.S. N.S. N.S. N.S. N.S. N.S. -.670, .034* -.695, .026* -.898, .003** N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. DCD SRS-2 Total Social awareness Cognition Communication Motivation Mannerisms MABC-2 Total Manual Dexterity Aiming & catching Balance and standing N.S. N.S. N.S. N.S N.S. N.S N.S. -.683, .043* N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S N.S. N.S N.S. N.S. N.S. N.S N.S. N.S N.S. N.S. N.S. N.S N.S. N.S N.S. N.S. N.S. N.S N.S. N.S N.S. N.S. N.S. N.S. .872, .002** N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. N.S. *p < 0.05, **p < 0.01 N.S. p > 0.05 Pearson correlations between AON tracts and social (Social Responsiveness Scale, Second Edition [SRS-2]) and motor (Movement Assessment Battery for Children-2 [MABC-2]) skills. N.S. = non- significant; ASDd= autism spectrum disorder subgroup; TD = typically developing; DCD = developmental coordination disorder; SLF = superior longitudinal fasciculus; IFG = inferior frontal gyrus; dmPMC = dorsal medial premotor cortex; dlPMC = dorsal lateral premotor cortex; IPL = inferior parietal lobule. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 148 Discussion In this study, we compared the structural white matter properties related to social and motor processing in three groups who vary in social and motor skills (TD, ASDd, and DCD) in order to expand upon previous research and further explore how social and motor skills relate to structural connectivity in the brain and specifically in the AON. We found reduced structural connectivity in the cingulum in individuals who demonstrate both social and motor deficits (ASDd) and in the genu of the CC in individuals with motor skill deficits regardless of social skill ability (ASDd, DCD). Furthermore, individuals with ASDd showed increased structural connectivity in the splenium of the CC. Finally, ROI analyses indicate that white matter integrity between AON regions is associated with both social and motor skills. Quantitative anisotropy in the SLF was positively related to social skills and inversely related to motor skills in the ASDd group. QA in tracts between the IFG and mPFC were related to motor skills in the TD and DCD group, but not the ASD group. We discuss these data further below. Group differences. Our results are the first to demonstrate white matter differences between all three groups in the genu of the CC. The TD group showed more connectivity than both the ASDd and DCD group, while the ASDd group showed more connectivity than the DCD group. Thus, the DCD group had the least connectivity in the genu of the CC than the other groups. Connectivity in genu of the CC that shared this relationship (TD>ASDd>DCD) were found to be related to motor skills in the DCD group. This relationship is the first to be observed with structural connectivity in these populations but is consistent with research in gait and balance in elderly cohorts (Bhadelia et al., 2009; Van Impe, Coxon, Goble, Doumas, & Swinnen, 2012) as well as SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 149 with postural responses to surface displacements in individuals with multiple sclerosis (Peterson et a., 2016) that show reduced genu connectivity (FA) with motor impairments. Since the genu fibers are presumed to connect prefrontal cortical areas (Witelson, 1989) and thus are likely to be involved in frontal–parietal structural connectivity, it is possible that balance is related to visuospatial attention (Mihara, Miyai, Hatakenaka, Kubota, & Sakoda, 2008). The ASDd group revealed a pattern of hyperconnectivity in the splenium of the CC compared to both the TD and DCD groups. Increased connectivity in these tracts were related to symptom severity. That is to say, the ASDd group, which displayed both social and motor deficits had greater connectivity in this region, followed by the DCD group who primarily display motor deficits, followed by the TD group which displayed no deficits. This finding does not replicate other studies that have observed reduced connectivity and/or reduced volume of the splenium in ASD (Casanova et al., 2011; Prigge et al., 2013; Vidal et al., 2006). However, in those previous studies, the proportion of the included ASD participants known to have specific motor deficits was not reported. The hyperconnectivity in our data may be unique to our ASDd subgroup. The splenium fibers connect occipital and parietal cortices, as well as inferior and medial temporal regions including the posterior cingulate. Increased connectivity here may reflect a disruption in the transmission of visual and sensorimotor information between the hemispheres which may reflect an additive effect of both social and motor deficits in the ASDd. Finally, significant hypoconnectivity of cingulum was found in the ASDd group compared to the TD group. This pattern of hypoconnectivity in the cingulum for the SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 150 ASDd group was nearly significant compared to the DCD group. Taken together, these results corroborate previous findings suggesting that cingulum connectivity is related to social deficits (Ameis et al., 2013). The cingulum bundle runs longitudinally along the dorsal surface of the CC and connects frontal, parietal, and temporal regions, similar to the SLF. While the SLF primarily links ventral (fronto-temporal) limbic system structures, the cingulum bundle enables intra-hemispheric long-range brain connectivity and mediates dorsal emotion-related brain region integration. Specifically, the cingulum bundle provides a link between grey matter structures that are important for mentalization, abstraction, and emotional reflection. Together, these results indicate that the common hypoconnectivity of the genu of the CC in both clinical groups is related to motor deficits while hypoconnectivity of the cingulum is related to social deficits. The hyper-connectivity of the splenium appears to be unique to the ASDd group. Interestingly, a post-hoc analysis of the hyperconnectivity in the splenium was positively related to social awareness skills in ASDd as measured by the SRS-2 social awareness subscore. Considering that the splenium is thought to be involved in the transfer of visual information (Bersani et al., 2010), future studies should investigate how connectivity in the splenium relate to visual sensory responsivity. Group social and motor relationships. Next, we correlated whole brain structural connectivity measures with measures of social and motor ability within- groups. Across-group analysis was not conducted because the measures used for the whole brain analysis were used to stratify groups and the relationship between social and motor skills across groups represents a shift in social and motor severity related to group and not the relationship between social and motor skills within each group (i.e., SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 151 the Simpson's Paradox). No relationship between social or motor skills and structural connectivity was observed in the TD group. This is likely due to the limited range of social and motor skills in this group. Interestingly, motor skills were found to be negatively related to structural connectivity in both clinical groups which is in contrast to the positive relationships reported in other DCD studies (Langevin et al., 2015). Social skills, however, were positively related to structural connectivity in the DCD group, and negatively related in the ASDd group. Below we discuss the results based on tracts. Genu of the CC. While the genu of the CC differed across groups and these differences in connectivity were positively related to motor skills in the DCD group, an inverse relationship between genu connectivity and motor skills was observed in the ASDd group. Despite the fact that the ASDd group had overall reduced connectivity compared to the TD group, structural connectivity in this region was negatively related to motor skills as well as social skills. Thus, as motor and social skills improved the more hypoconnected this region became relative to TD peers. While there is substantial overlap between the tracts related to social skills and those related to motor skills, those related to motor skills are more anterior and those related to social skills are more posterior. Interestingly, no relationship between motor skills and the genu were found in the DCD group at the whole brain level. Splenium. The hyperconnectivity of the splenium of the CC in the ASDd group as well as its negative relationship to social skills suggests that increased connectivity in the splenium may be a compensatory mechanism in the ASDd group related to social ability. Interestingly, at a very low threshold, this pattern also was observed in the DCD group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 152 Overall, our results are consistent with previously observed abnormalities found in the of CC in individuals with ASD (Chung, Dalton, Alexander, & Davidson, 2004; Egaas et al., 2004.; Filipek, 1996; Freitag et al., 2009; Hardan et al., 2009; Keary et al., 2009; Vidal et al., 2006). Several studies have shown that the volume of the CC is reduced (Alexander et al., 2002; Freitage et al., 2009, 2012; Harden et al., 2009; Keary et al., 2009; Vidale et al., 2006). In a meta-analysis of a cross-sectional area of the CC in ASD, Frazier & Hardan (2009) reported that the rostral body of the CC connecting premotor and supplementary motor neurons had the greatest white matter reduction. In regard to connectivity, attenuated FA of the CC was observed in a study by Alexander et al., (2007), especially so in a subgroup of ASD children with lower IQ. More recently, Kumar et al., (2010) replicated this pattern of lower FA in the CC. Further, when examining a group of high functioning males with ASD, (Barnea-Goraly et al., 2005) reported lower FA in the genu and rostral body of the CC as well. However, other studies have not replicated these findings (Tepest et al., 2010). Once again, inconsistencies highlight how heterogeneity in ASD must be addressed in future research. Several studies have found relationships between CC measurements and behavioral metrics such as social deficits (Keary et al., 2009), however, only one has looked at both social and motor deficits in relation to the CC (Hanaie et al., 2014). Hanaie et al., (2014) found no relationship between motor skills and the CC. They did, however, find an inverse relationship between the splenium of the CC and ASD symptom severity scores as measured by the ADOS-Generic. This finding is congruent with the current study’s finding of increased connectivity in the splenium among individuals with ASDd as compared to the DCD and TD groups. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 153 Cingulum. Our study observed a similar pattern of results in the cingulum as in the CC. The ASDd group showed hypoconnectivity of the cingulum bilaterally compared to the other groups. Our finding of decreased connectivity in the cingulum of the ASDd group is in agreement with Ameis et al. (2013) who observed reduced FA in the cingulum bundle among individuals with ASD compared to TD controls. Given the cingulum’s role in connecting emotion-related brain regions, this may explain some of the social impairments seen in ASD. Cerebellum. No group differences were found in the cerebellum, however, connectivity of the superior cerebellar peduncles was inversely related to motor skills and positively related to social skills in the DCD group. Thus, there seems to be an interaction between social and motor skills and connectivity in individuals with primarily motor deficits. The cerebellum, which sits behind the pons and connects to the brainstem via three pairs of peduncles, has long been implicated in motor skill learning. More recently, evidence points to a role for the cerebellum in cognition and emotion (Van Overwalle, D’aes, & Mariën, 2015). Previous DCD diffusion studies have reported mixed findings regarding the cerebellum, one study reported typical cerebellum diffusivity compared to peers (Zwicker et al., 2012) while another observed decreased global efficiency (Debrabant et al., 2016). To the best of our knowledge, no diffusion studies have investigated social skills in DCD. In ASD, however, the increased diffusivity of the cerebellar peduncles is a consistent finding (Sivaswamy et al., 2010). Moreover, correlations between the degree of social impairment and the integrity of the superior cerebellar peduncle have been also reported (Catani et al., 2008). For example, cerebellar white matter abnormalities have also been associated with SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 154 restrictive and repetitive behaviors (Cheung et al., 2009). It is surprising, therefore, that no social or motor relationship was found in our ASDd group. In a post-hoc analysis to investigate social and motor skills across all individuals with ASD-all (those with and without motor impairment; n = 15), the right superior cerebellar peduncle was related to motor skills after controlling for social skills (p < .05, FDR = .059). This finding is consistent with Hannie et al., (2013) who reported a positive relationship between the MABC-2 Total score and FA in the superior cerebellar peduncle in ASD. Thus, it is possible that some of the cerebellar findings in ASD were related to motor and not social skills as previously reported. These findings further support the need to better understand motor heterogeneity in ASD. CST. The most robust behavioral correlation observed in our analysis was between CST integrity and social skills in the DCD group. Increased connectivity in the CST was related to increased social skills. The primary purpose of the CST is thought to be for voluntary motor control of the body and limbs. However, connections to the somatosensory cortex suggest that the pyramidal tracts also are responsible for modulating sensory information from the body (Kolb & Whishaw, 2009). The reduced structural integrity of this region in the DCD group may therefore affect long-range communication in a large number of cortical regions including frontal, parietal, temporal areas associated with social cognition. In regards to motor skills, we did not replicate Zwicker et al.’s (2012) findings who found that CST axial diffusivity was positively related to motor skills (as measured by the MABC-2). There are a few methodological reasons why we did not replicate Zwicker et al. First, Zwiker et al., analyzed a smaller DCD sample size with a larger variance in motor skills as compared to our sample. With SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 155 a larger sample size, these findings may not survive. Second, we collected more robust diffusion data (99 directions compared to their 16) enabling more accurate fiber tracking of complex tracts like the CST. However, until a large sample has been analyzed, these results should be considered with caution. AON tracts. Our study did not replicate previous literature reporting reduced ASD FA in white matter tracts directly connecting key imitation regions in a larger sample of ASD and TD participants (Fishman et a., 2016). Our current sample may be too small to reveal group differences in AON tracts. However, we did replicate findings of ASD and DCD symptomatology related to AON tract integrity. We observed that AON and SLF tracts were related to both social skills and motor skills. In regions outside of the AON, ASD diffusion literature has reported mixed findings, especially in the SLF -- some reporting greater connectivity (Cheung et al., 2009; Weinstein et al., 2011) while others reporting less (Noriuchi et al., 2010; Shukla, Keehn, & Müller, 2011). No studies to date have looked at a subgroup of ASD with motor deficits. The SLF is a major bidirectional association tract that extends from the frontal to parietal lobes. There is evidence to suggest that these connections may be crucial for planning of reach-to- grasp actions (Koch et al., 2010). Despite finding no group differences in SLF connectivity, our data suggests that the left SLF is related to motor skills and not social skills in ASDd. Group differences may emerge with a larger sample in future analyses. Finally, we found that motor skills were positively related to QA in the left IFG- dmPMC tract in the TD group and negatively related in the DCD group. The negative correlation in the DCD group may be related to attention deficits typically present in DCD individuals (Piek, Pitcher, & Hay, 2007). Although non-significant, the DCD group SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 156 did have hyperconnectivity with the prefrontal cortex compared to the TD group. Future analysis should control for attention deficits to better understand this relationship. While few studies have looked at AON white matter connectivity in ASD, there are some studies looking at these motor-related tracts in DCD. Previous DWI studies in individuals with DCD have revealed reduced white matter integrity in motor-related networks in children with DCD, particularly in sensorimotor tracts (Debrabant et al., 2016; Langevin et al., 2014; Zwicker et al., 2012). Zwicker et al. (2012) found a significant positive correlation between axial diffusivity in the CST and posterior thalamic radiation and motor skill level across DCD and TD groups as measured by the MABC-2. Other studies have identified reduced FA in the SLF (Debranant et al., 2012; Langevin et al., 2014; William et al., 2017) and in the CC (Langevin et al., 2014), which are consistent with the current study’s findings. However, other research has identified different tracts associated with DCD such as the internal capsule (IC) which was observed to have reduced FA in children with DCD compared to TD children (Debranant et al., 2016). Since the IC was not a part of our original hypothesis, we did not conduct an ROI analysis for this region, which may explain the differences between our study and the previous one. Future studies should examine this connection more closely. Identification of the shared and/or separate etiologies for concurrent neurodevelopmental disorders in ASD represents a critical step in the identification of neural mechanisms that underlie specific ASD symptomatology. By comparing ASDd to DCD we were able to better understand how abnormalities in ASD may relate to motor impairments. Here, we have shown that children with ASDd or DCD display regionally- distinct yet related alterations in the CC. We have additionally shown that concurrent SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 157 ASD and DCD individuals display aspects of both ASD and DCD specific callosal abnormalities, as well as alterations in other white matter tracts. To fully investigate how motor and social skills interact, future studies should include a fourth group, ASD- without motor impairment, to compare these findings with other individuals without motor impairments. Limitations Some limitations of the present analysis must be considered. First, a relatively small sample size was analyzed. However, the group characteristics were comparable to previous studies of ASD and current DCD studies (Licari et al., 2015; Travers et al., 2012). Furthermore, this study was comprised of high-functioning children and adolescents with ASD who displayed normal IQ values and good verbal skills. Therefore, it remains unclear to what extent the present findings can be generalized to the larger ASD population or selected sub-groups, such as “low-functioning” individuals with ASD or adults with ASD. White matter tract integrity measured by FA increases during typical human development (Bashat et al., 2005), therefore future studies should consider investigating social and motor skills throughout the lifespan. Finally, the influence of other psychiatric comorbidities such as ADHD or the use of psychotropic medications in our ASD and DCD sample cannot be ruled out. However, as acknowledged by Fishman and colleagues (2015) it is difficult to recruit a “pure” sample of ASD, and likely DCD as well. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 5 158 Conclusions In sum, our study provides tract-related microstructural data related to social and motor skills across three clinical populations. Our study also suggests that social and motor skills correlate with the integrity of the CC, specifically in the genu and body of the CC. Interestingly the splenium of the CC may be hyperconnected in ASDd. Furthermore, in ASDd the cingulum appears to by hypoconnected compared to both DCD and TD groups, while the left cingulum is hyperconnected in the DCD group compared to the TD group. Finally, looking at structural integrity in the AON, we find no specific differences within AON connecting tracts. However, these tracts are correlated with social and motor ability. Specifically, our data indicate that as motor skills improve, there is increased connectivity between the left IFG and dmPMC in TDs but decreased connectivity in DCD. However, increased motor skills correlate with increased connectivity in the SLF in the ASDd group. Our data support the need to look at structural connectivity across a spectrum of individuals with social and motor deficits in addition to examining discrete groups based on clinical diagnosis. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 159 Ch 6. Dissertation Discussion and Conclusions This dissertation combines multiple levels of neurobiological investigation— behavioral, functional imaging, and structural imaging—to investigate a subgroup of individuals with autism spectrum disorder (ASD) who also exhibit developmental coordination disorder (DCD) symptomatology. We refer to this subgroup as our ASDd sample. Specifically, this research focuses on the action observation network (AON), a neural network involved in action observation and imitation processing. There is some evidence that the AON is hypoactive in ASD and its activity has been linked to social deficits in ASD (Dapretto et al., 2006; Kana, Libero, & Moore, 2011; Williams, 2008). However, not all studies support this hypothesis (Dinstein et al., 2010; Fan et al., 2010; Raymaekers et al., 2009), nor is the underlying cause of the hypoactivity clear, especially in terms of underlying structural or functional connectivity (FC), where the literature remains divided (Hull, Mandy, & Petrides, 2017). Furthermore, little focus has been given to how this motor network might be modulated by motor deficits in ASD. Currently, research on AON function in individuals with ASD and comorbid DCD has not been conducted. This dissertation aimed to fill these research gaps. This dissertation is the first research to use multiple neuroimaging techniques to examine the AON in ASDd individuals and contrast it with individuals with DCD as well as typically developing (TD) peers. The central aims of this dissertation were: (a) to determine the relationship between social and motor skills and AON functioning across different neural properties, namely, functional activation, connectivity, and white matter structure; and (b) to assess how these relationships differ between groups in which SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 160 social and motor skills vary. Neuroimaging studies were carried out utilizing different neuroimaging modalities to address these aims. Results from this dissertation support the theory that AON dysfunction underlies both social and motor impairments found in ASDd and DCD populations. Results across the neuroimaging studies further bolster the AON dysfunction theory by providing evidence for atypical functional activation and atypical functional and structural connectivity in the AON in both the ASDd and DCD groups. Our results also demonstrate that these neural abnormalities may be related to observed behavioral differences in these two clinical groups. Summary of Research Chapter 3: Imitation task. We first investigated how motor and social skills relate to activation in the AON during an imitation task. Participants who had (a) ASD with social and motor deficits (ASDd), (b) only motor deficits (DCD), and (c) no deficits (TD) underwent a functional magnetic resonance imaging (fMRI) scan while imitating face and hand actions. Across all conditions, the imitation task elicited significant activity in the AON regions in each group with markedly reduced inferior frontal gyrus (IFG) activation in the DCD group. Although group differences did not survive multiple comparisons, perhaps due to the low number of participants, at a lower threshold (uncorrected) our hypotheses were supported. While imitating, the ASDd participants showed reduced brain activity relative to TD participants in the bilateral IFG and right superior temporal sulcus (STS). Also, consistent with our hypothesis, atypical AON activation in the ASDd group was positively correlated with both social and motor skills. To our knowledge, this was the first study to show that IFG activation (TD > ASDd) was SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 161 positively correlated with motor skills above and beyond controlling for social skills. We also demonstrated that this same relationship (IFG activation positively related to motor skills) exists when looking across all groups. Together these data indicate that heterogeneity in motor skills is related to IFG activation regardless of diagnosis and controlling for individual variation in social skills. Because both clinical groups performed comparably in measures of motor skills outside of the MRI scanner, the reduced involvement of key AON regions, namely the IFG, in both groups of participants with motor deficits might suggest that individuals with motor deficits rely less on this core imitation network to accomplish an imitation task. Surprisingly, the DCD group had significantly less IFG activation than did the ASDd group. However, this may be the result of increased motion during the fMRI capture protocol in the DCD participants compared to those in the ASDd subgroup. An increased sample size with better motion control will better allow us to comment on this further. Interestingly, social and motor skill relationships with AON activation in the ASDd group was found to be lateralized, such that right hemisphere activation was related to social deficits and left hemisphere activation was related to motor skills. This may reflect the left hemisphere (right hand) motor dominance in our participants. It may be interesting to see if these results are reversed in individuals with right hemisphere (left hand) motor dominance. Overall findings from this chapter provide important new insights into existing neuroimaging literature relating to motor heterogeneity and action imitation in ASD. Because not all individuals with ASD have motor impairments, these SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 162 data indicate that heterogeneity in motor skills may account for some discrepant findings in previous ASD imitation literature. Chapter 4: Resting state. Next, we investigated connectivity within the AON network at rest as well as FC within another intrinsic resting state network thought to underlie social deficits with ASD: the default mode network (DMN). We linked FC of these networks with specific phenotypic features of social and motor dysfunction in ASD and demonstrated a relationship between social and motor skills in individuals with ASDd. We used this framing to delineate how intrinsic resting state networks are disrupted in children and adolescents with and without social and motor deficits. Our results suggest that functional hypoconnectivity between the bilateral IFG, a core region of the AON, is the most pronounced in the ASDd group. We demonstrate that the strength of bilateral IFG connectivity is related to motor skills regardless of diagnosis or social abilities across participant groups, further supporting theories that the AON is disrupted in ASD (Dapretto et al., 2006; Fishman et al., 2014; Kana et al., 2011) and DCD (McLeod et al., 2014; Werner et al., 2012) at the resting state level. We also observed that in both the ASDd and DCD groups, motor ability is related to DMN connectivity, which is thought to primarily underlie social cognition (Mars et al., 2012). Motor skills were positively related to FC between the posterior cingulate cortex (PCC) and the superior parietal lobule and negatively related to PCC and lateral occipital cortex (LOC) connectivity in ASDd. In the DCD group, motor skills were found to be negatively related to DMN connectivity in the precuneus. Thus, although the ASDd and DCD groups may share comparable levels of motor impairments, these results suggest that ASDd and DCD groups may have discrete underlying disruptions in the SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 163 DMN. Future studies should investigate whether these brain-behavior relationships are consistent across other intrinsic networks implicated in ASD, including the salience network. In sum, by relating motor and social skills to group differences in resting state functional connectivity, our findings support our hypothesis that discrepancies in the field of resting connectivity in ASD may be partially resolved by considering motor as well as social heterogeneity in ASD symptomatology. This result suggests the importance of incorporating various individual difference measures (social and motor skills) in future FC analyses. Chapter 5: Structural connectivity. Finally, we examined differences in white matter microstructure between the ASDd, DCD, and TD groups and their relationship to social and motor skills in the AON. Consistent with our hypothesis, we observed tract- related microstructural data related to social and motor skills in all three populations. Our study demonstrated that social and motor skills are related to the integrity of the corpus callosum (CC), specifically in the genu and body of the CC. Our findings also indicated that the splenium of the CC may be hyper-connected in individuals with ASDd. Furthermore, the cingulum was uniquely atypical in both clinical groups. Compared to the TD group, the bilateral cingulum was hypo-connected in the ASDd group and the left cingulum was hypo-connected in the DCD group. Finally, looking at structural integrity in the AON, we found no specific differences within AON connecting tracts between groups. However, tract integrity was correlated with social and motor ability. Our data specifically indicated that motor skills are positively related to connectivity between the left IFG and dorsolateral premotor cortex in TD individuals but negatively related in individuals with DCD. We also observed that increased motor skills correlated with SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 164 increased connectivity in the superior longitudinal fasciculus in the ASDd group. This data supports the need to look at structural connectivity across a spectrum of individuals with social and motor deficits in addition to examining discrete groups based on clinical diagnoses in order to better understand how differences in brain structure may give rise to differing clinical presentations. Ultimately, a better understanding of ASD’s different presentations will enable more tailored therapy and care for individuals. Conclusions Generally, findings from this research provided evidence for disruption of the AON in ASD. Moreover, we demonstrated that both social and motor skills are related to the AON at multiple neurological levels and, in some cases, motor impairments were more strongly related to the AON above and beyond social impairments. These findings suggest that motor impairments may be indicative of ASD pathology and may even underlie some of its core cognitive and behavioral features. In particular, a core region of the AON (the IFG) was found to be related to motor ability at all neurological levels suggesting that this region, more than other regions of the AON, may be modulated by motor ability in ASD as well as across populations (cf. Chapter 2 and Chapter 3). When looking across all imaging modalities, this research also provides preliminary evidence for discrete neural signatures in ASDd and DCD. Despite both clinical groups having reduced IFG activation when imitating compared to the TD group, only the ASDd had significantly reduced bilateral IFG resting-state FC. This reduced bilateral IFG connectivity is supported by our structural data reported in Chapter 5. There we showed that the ASDd group displayed hypoconnectivity in the anterior SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 165 body/posterior genu of the CC, which may indicate poor homotopic white matter connections between the left and right IFG (Hofer & Frahm, 2006; see Figure 1 for a cross-modal summary of results). Further, atypical occipital and parietal cortex functioning found in our task and resting-state data also suggest that dorsal stream disruptions may underlie motor impairments in DCD. We found that the DCD group had significantly reduced LOC and inferior parietal lobule (IPL) activation during imitation compared to the TD group (see Chapter 3 supplementary material). This hypo-activation was not observed in the ASDd group, indicating that specific impairment in the DCD group may be related to hypoactivation of the dorsal stream. Moreover, this is supported by DMN hypoconnectivity of the LOC during rest (see Chapter 4 supplementary material). Overall these findings provide preliminary evidence to suggest that ASDd and DCD are different disorders with unique neurological signatures. Thus, although our participants with ASD all have motor impairments, the neurological underpinnings for those motor impairments may not be the same as the DCD group. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 166 Figure 1. Action observation network (AON) findings across all modalities in autism spectrum disorder subgroup (ASDd; top) and developmental coordination disorder (DCD; bottom) compared to typically developing (TD) peers. Boxes represent areas of the AON where group differences were found. Pink boxes represent hyperactivation and blue boxes represent hypoactivation. Yellow arches with solid lines represent group differences in tractography. Arches with dotted lines represent tractography that was related to social or motor skills. Blue lines represent group differences in AON FC during rest. Orange circles represent whole brain group differences during the imitation task. FC = functional connectivity, DWI = diffusion weighted imaging; +Social = positive correlation with social skills; +Motor = positive correlation with motor skills; -Motor = negative correlation with motor skills. CC = corpus callosum; IFG = inferior frontal gyrus; STS = superior temporal sulcus; mPFC = medial premotor cortex; IPL/SI = inferior parietal lobule/ primary somatosensory cortex I; IPL/SII = inferior parietal lobule/ secondary somatosensory cortex II; dLPFC = dorsal lateral prefrontal cortex; LOC = lateral occipital cortex; PRC= precentral gyrus. This dissertation gives further support to the importance of understanding motor heterogeneity in ASD. Motor impairment is one of the earliest signs of some forms of ASD (Ozonoff et al., 2008). Accordingly, assessing motor disorders might enable the early and quantitative diagnosis of ASD pathology and the identification of other potentially dysfunctional brain regions and circuits. Because motor skills are relatively SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 167 easy to evaluate and do not require testing for an invasive biomarker, diagnostic motor skill research in ASD may lead to novel therapeutic interventions. By focusing some portion of therapy on addressing motor impairments, one also might alleviate some of the social deficits that are characteristic of ASD. This may be especially true for individuals with ASD who have comorbid DCD (80% of our sample population). Future research is needed to better understand motor network deficits in individuals with ASD who do not have DCD. Furthermore, future research can investigate how motor therapies (e.g., imitation therapy) in individuals with ASD who have comorbid DCD may modulate activity in the IFG and functional and structural connectivity in the AON. Considerations and Future Directions Sample characteristics. Although significant findings were obtained in this research, more data collection and further analysis are needed to fully understand the relationship between motor skills and AON functioning in ASD. One limitation of this research is the relatively small sample size. The smaller sample size of the ASDd subgroup and disproportionately larger TD sample may reduce the generalizability of these findings. Furthermore, it is difficult to make generalizations regarding the relationship between AON functioning across each of the three imaging modalities used because the sample of participants with usable images varied over each of the different modalities. Future work should include a larger, equally distributed, sample and compare findings across levels of neurobiology in the same cohort in order to better inform how structural and FC relates to task activation and behavioral outcomes in the same sample. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 168 Moreover, this dissertation included participants ranging from 8-15 years old. To account for this, age was added as a control variable, however, it is possible that age does not correlate with puberty in our sample. While puberty scales were not analyzed, it is possible that pubertal stages may have influenced our findings. Network activation and connectivity patterns change throughout typical human development (Bastiaansen et al., 2011). Future studies should match for puberty as well as age to better control for pubertal effects on brain development. Further, future studies should consider investigating social and motor skills across the lifespan, not just in children and adolescents. Although ASD is generally considered a lifelong condition, previous research has identified a subgroup of ASD who improve to the extent they no longer meet ASD criteria (Anderson, Liang, & Lord, 2014; Fein et al., 2013). Moreover, compensatory and normalized brain activity has been observed in these individuals (Eigsti et al., 2016). Future longitudinal research should follow motor development in children with ASD across the lifespan as it relates to AON activation to more fully understand motor heterogeneity in ASD. Limitations in group characteristics. The ASDd group was comprised of high- functioning children and adolescents who displayed average IQ values and good verbal skills. Therefore, it remains unclear to what extent the present findings can be generalized to the larger ASD population or any additionally selected sub-groups, such as “low-functioning” individuals with ASDd or adults with ASDd. Furthermore, the degree of prior or current social or motor therapy involvement was not controlled for in this dissertation. It is possible that the ASD and DCD groups had different opportunities to seek treatment for their impairments. In the DCD group, not all participants had met SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 169 with a clinician and received a formal DCD diagnosis. Because of this, it is possible that some of the DCD participants had received specific therapies and treatments, while others did not. Conversely, all participants in the ASD group had a formal diagnosis and therefore had met with a clinician and had the opportunity to discuss and explore various therapeutic options. Because therapy has been found to influence brain as well as behavioral outcomes (Eigsti et al., 2016), not controlling for heterogeneity in social and motor therapy is another possible limitation to this research. Finally, the influence of other psychiatric comorbidities such as ADHD and the use of psychotropic medications in our ASDd and DCD sample cannot be ruled out. Neurobiology of both clinical groups may have been influenced by other diagnoses and/or medication. Future directions. This research highlights the relevance of motor deficits in ASD, however, no analysis was conducted on individuals with ASD who did not have motor impairments. Here we compared two different populations with motor deficits, but it may be possible that other unique characteristics of ASD or DCD may interact with motor ability. Future analysis should include a subgroup of ASD without motor impairments (ASDnd). Comparing ASDnd and ASDd groups would specifically demonstrate how social and motor skills interact in ASD directly. Building on previous literature relating motor impairments to imitation deficits (Dewey et al., 2007), the next steps in this research also includes imitation skill analysis. It is possible that the AON may also be modulated by imitation ability in addition to motor impairment. Comparing how imitation skills vary in individuals with ASDd and ASDnd may reveal different neural signatures of ASD. SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 170 Imitation may also differ between groups based on imitation type. Future analysis will also compare AON activation between conditions (emotional faces, non-emotional faces and hand actions). Some studies have found group differences between groups (TD, ASD) while imitating faces (Dapretto et al., 2006) while a few studies utilizing hand- based imitation paradigms have reported no group difference in AON activation (Dinstein, Gardner, Jazayeri, & Heeger, 2008; Dinstein et al., 2010; Marsh & Hamilton, 2011; Pokorny et al., 2015; Poulin-Lord et al., 2014). Therefore, some of the differences we report in our imitation analysis may be driven by one particular imitation condition. For example, reduced IFG activation may be driven by the emotional face condition in the ASDd participants, and by the hand condition in DCD participants. Research has shown that the AON has connections to other neural circuits (Petrides & Pandya, 2002; Rushworth, Behrens, & Johansen-Berg, 2005), including direct reciprocal connections with higher visual processing regions (e.g., STS) and emotion-related brain regions (e.g., insula). In line with this, other networks elicited by emotional faces may influence the AON. More specifically, a network has been described, comprised of emotion- related regions such as the anterior insula (also known to be disturbed in ASD), that interfaces with the frontal AON pars opercularis of the IFG and adjacent ventral premotor cortex and other emotion-related brain regions (e.g., insula, amygdala; Iacoboni et al., 2005). Therefore, other networks recruited when imitating different types of action may influence the AON. Thus, future studies should also assess how motor skills relate to connectivity between the AON and other networks during imitation. Another future direction for a multimodal study like the dissertation research presented above would be to identify neurobiological patterns across findings from SOCIAL AND MOTOR SKILLS IN ASD & DCD – CHAPTER 6 171 different modalities and to apply that knowledge to classify participants into ASDnd, ASDd, DCD, and TD control groups. Utilizing pattern classification of neuroimaging data, several studies have used predictive models for ASD diagnosis. For example, functional brain activation and connectivity were used for pattern classification to separate ASD from TD peers (Anderson-Hanley et al., 2011; Coutanche et al., 2012; Deshpande, Libero, Sreenivasan, Deshpande, & Kana, 2013; Kaiser & Pelphrey, 2012; Murdaugh et al., 2012; Spencer et al., 2011). A few studies also have applied classification analyses to diffusion weighted imaging data (Ingalhalikar et al., 2011; Lange et al., 2010) to predict ASD group membership. Thus, accurate and reliable classification of participants with ASD is a promising step towards the diagnostic utility of such measures. To date, no study has modeled a classifier for DCD specifically, however, if applied, one could distinguish between, ASDnd, ASDd, DCD, and TD given the unique functional and structural patterns identified in each group thus far. For neurodevelopmental disorders that rely on behavioral diagnoses, an applied neural classifier could be helpful in deciding difficult or borderline cases. Currently, attempts at neural classifiers have mainly relied on measures of brain function, based on experimental tasks, which may be inappropriate for many individuals with ASD, particularly those who are young or would be considered low-functioning or experiencing other comorbid diagnoses that could interfere with obtaining imaging data. Ultimately, a multimodal technique could become more sensitive to symptomatology, which could improve diagnostic accuracy for ASD and DCD (and possibly ADHD, a common co-morbid diagnosis in both populations) and also aid in designing more tailored interventions for these groups. 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Pediatric Neurology, 46(3), 162–167. https://doi.org/10.1016/j.pediatrneurol.2011.12.007 Appendices 199 Appendix A: MRI Screener All participants filled out an MRI Screener provided by the Brain and Creativity Institute prior to their scan to rule out any MRI safe incompatibility such as the presence of metal in their body. Appendices 200 Appendix B: Instruments Developmental Coordination Disorder Questionnaire, 2007 Edition (DCDQ) The DCDQ has demonstrated acceptable validity and reliability in children ages 5-15 years old (Brenda N. Wilson et al., 2009). This questionnaire was used screening tool together with the MABC-2. Appendices 201 Movement Assessment for Children-Second Edition (MABC-2) The MABC-2, a performance-based assessment that evaluates motor skill ability using three subtests: manual dexterity, gross-motor ball skills, and balance. Higher scores indicate better functioning. Subtest scores, as well as a total score, were calculated using the second (ages 7–10) and the third (ages 11–16) age bands. Item, subtest standard (scaled), and total scores based on the normative sample were examined in our analyses. Appendices 202 Social Responsivity Scale Second Edition (SRS-2) The SRS-2 is a parent survey comprised of five subscales: social awareness, social cognition, social communication, social motivation, and mannerisms. Scores are reported in T- scores. Appendices 203

Abstract (if available)

Abstract Introduction: Previous studies have shown that motor networks like the action observation network (AON) are related to action understanding and social perception. It has been proposed that this network is disrupted in individuals with autism spectrum disorder (ASD), however, contradictory results question this hypothesis. While many clinicians and researchers report motor deficits in ASD, few have looked at how motor skills may mediate activation in these networks. To isolate the role of motor and social skills in the AON, this dissertation aims to compare AON activation, connectivity, and structure in children and adolescents with ASD who have social and also motor deficits (ASDd), to two groups: children with motor but not social deficits (developmental coordination disorder

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Creator Kilroy, Emily (author)

Core Title Social and motor skills in autism spectrum disorder & developmental coordination disorder: functional & structural neurobiology

School School of Dentistry

Degree Doctor of Philosophy

Degree Program Occupational Science

Publication Date 12/11/2020

Defense Date 07/25/2018

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag autism spectrum disorder,developmental coordination disorder,functional neurobiology,imitation,OAI-PMH Harvest,structural neurobiology

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Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Aziz-Zadeh, Lisa (committee chair), Cermak, Sharon (committee member), Damasio, Antonio (committee member), Kaplan, Jonas (committee member)

Creator Email emilykilroy@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-112228

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