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Biological and behavioral correlates of emotional flexibility and associations with exposure to family aggression

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Biological and behavioral correlates of emotional flexibility and associations with exposure to family aggression

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Content Running head: EMOTIONAL FLEXIBILITY 1

Biological and Behavioral Correlates of Emotional Flexibility and Associations with Exposure to
Family Aggression

by

Larissa Borofsky Del Piero

A Dissertation 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
(PSYCHOLOGY)

August 2016

Copyright 2016 Larissa Borofsky Del Piero
EMOTIONAL FLEXIBILITY 2

Table of Contents
General Introduction........................................................................................................................6
Paper 1 - Emotional Flexibility: A Novel Neuroimaging Approach to Examine Emotion
Regulation in Adolescence............................................................................................................11
Abstract..............................................................................................................................12
Introduction........................................................................................................................13
Emotional Flexibility.............................................................................................14
Neuroimaging of Emotion Regulation...................................................................17
Present Study.........................................................................................................19
Methods..............................................................................................................................22
Participants.............................................................................................................22
Procedures..............................................................................................................23
Measures................................................................................................................28
Results................................................................................................................................31
Descriptive and Validity Data................................................................................31
Behavioral Indicators of Emotional Flexibility.....................................................32
Neuroimaging Data................................................................................................33
Associations with Self-Reported Emotion Regulation..........................................35
Discussion..........................................................................................................................36
Conclusion.............................................................................................................40
Paper 2 - Family Aggression, Emotional Flexibility, and Psychological Symptoms in
Adolescence...................................................................................................................................55
Abstract..............................................................................................................................56
EMOTIONAL FLEXIBILITY 3

Introduction........................................................................................................................57
Family Aggression and Emotion Regulation.........................................................58
Emotion Regulation as a Mechanism versus Protective Factor.............................62
Emotional Flexibility.............................................................................................63
Adolescence as a Sensitive Period.........................................................................63
Present Study.........................................................................................................64
Methods..............................................................................................................................67
Participants.............................................................................................................67
Procedures..............................................................................................................68
Measures................................................................................................................70
Results................................................................................................................................73
Parent-to-Child Aggression and Flexibility...........................................................73
Emotional Flexibility and Psychological Symptoms.............................................74
Mediation by Emotional Flexibility.......................................................................74
Moderation by Emotional Flexibility.....................................................................75
Discussion..........................................................................................................................75
Conclusion.............................................................................................................80
General Conclusion........................................................................................................................90
References......................................................................................................................................95
EMOTIONAL FLEXIBILITY 4

List of Tables
Paper 1
Table 1...............................................................................................................................41
Table 2...............................................................................................................................42
Table 3...............................................................................................................................43
Table 4...............................................................................................................................44
Supplemental Table 1........................................................................................................45
Paper 2
Table 1...............................................................................................................................81
Table 2...............................................................................................................................82
Table 3...............................................................................................................................83
Table 4...............................................................................................................................84

EMOTIONAL FLEXIBILITY 5

List of Figures
Paper 1
Figure 1..............................................................................................................................47
Figure 2..............................................................................................................................48
Figure 3..............................................................................................................................49
Figure 4..............................................................................................................................50
Figure 5..............................................................................................................................51
Figure 6..............................................................................................................................52
Figure 7..............................................................................................................................53
Figure 8..............................................................................................................................54
Paper 2
Figure 1..............................................................................................................................85
Figure 2..............................................................................................................................86
Figure 3..............................................................................................................................87
Figure 4..............................................................................................................................88
Figure 5..............................................................................................................................89

EMOTIONAL FLEXIBILITY 6

General Introduction
The two papers comprising this dissertation provide complimentary perspectives on the
importance of emotional flexibility. Emotional flexibility is defined as the ability to respond
adaptively to changing emotional demands and dynamically employ different emotion regulation
strategies to suit different situational contexts. Emotional flexibility is vital to adaptive
functioning because this type of ongoing emotional responding and modulation occurs
continuously in daily life. Responding adaptively to situations such as discovering that a conflict
with a friend was based on a misunderstanding, finding out that your partner was acting
suspiciously because they were planning a surprise for you, or alternatively, learning that a
relationship that appeared to be going well is ending, requires the ability to be emotionally
flexible.
Surprisingly, emotional flexibility has received relatively little attention in psychological
research until recently (Bonanno & Burton, 2013; Kashdan & Rottenberg, 2010). In contrast, use
of specific emotion regulation strategies (e.g., suppression, distraction, reappraisal) has been
studied across many areas of psychological research. Facets of emotion regulation have been
explored extensively in connection with different types of psychopathology (e.g., Southam-
Gerow & Kendall, 2002), quality of interpersonal relationships (e.g., Richards, Butler, & Gross,
2003), risky behaviors (e.g., Steinberg, 2004), and a multitude of other adaptive and maladaptive
outcomes. These studies support the importance of successful emotion regulation and,
conversely, the risks of emotion dysregulation. However, the quantification and measurement of
emotion regulation has varied widely.
The majority of emotion regulation studies have employed self- or parent-report
questionnaires. A smaller subset of studies has sought to test emotion regulation experimentally,
EMOTIONAL FLEXIBILITY 7

but these methods are typically far removed from how emotion regulation occurs in vivo.
Common experimental measures of emotion regulation include unregulated responding to
emotional faces or emotion-eliciting stimuli, viewing emotional faces that occur in the context of
some distracter task (e.g., dot probe task, affective go-no go task), and training participants to
employ a discrete set of regulation strategies (e.g., cognitive reappraisal, suppression). These
studies have provided important information about the nature of emotion regulation and its
associations with diverse outcomes; however, emotion regulation in daily life does not occur in
this trial-by-trial fashion, but rather is an ongoing, iterative process whereby emotional reactions
are modulated and updated in response to incoming emotional information (Gross & Thompson,
2007). This fluid process is understandably difficult to model experimentally, but developing
tasks that simulate this process is an important goal for the field.
For this reason, a primary goal of Paper 1 is the creation and validation of a novel
experimental task, the EFIC (Emotional Flexibility with Images and Captions) task, that is
designed to more closely approximate this process of emotional responding and accommodation
(i.e., emotional flexibility) than has been done in other emotion regulation paradigms. In the
EFIC task, we present participants with an emotional image and then subsequently show the
image a second time with a caption that is designed to change the emotional interpretation (e.g.,
an image of teenage girls huddling together and crying with a caption indicating that they have
just won a sports championship). Using this task, we aim to elicit this process of responding and
re-responding to emotional information in shifting emotional contexts. The behavioral measures
from this task (self-reported emotional responses during the task and reaction times) enable us to
quantify how quickly and extensively participants shift to incorporate this new emotional
information or whether they remain stuck in their initial emotional interpretations.
EMOTIONAL FLEXIBILITY 8

The EFIC task is also completed while participants undergo functional neuroimaging
(fMRI) scanning, facilitating the exploration of neural correlates of this process concurrent with
the aforementioned behavioral indices. As no prior studies have employed this type of emotional
flexibility paradigm to gather neuroimaging data, hypothesized results are based on findings
from studies examining discrete emotion regulation strategies. In particular, cognitive reappraisal
paradigms (for a review, see Buhle et al., 2014), where participants are taught cognitive
strategies to reinterpret the emotional meaning of a stimulus (e.g., by telling themselves that
things are not as they appear in a scene), contain similar elements to the present paradigm and
have been studied extensively in prior neuroimaging research. Thus, we seek to build upon prior
emotion regulation studies to explore biological and behavioral correlates of an emotional
flexibility paradigm that more closely approximates emotional processes in daily life.
One context where the importance of emotional flexibility is highly evident is within
family relationships, particularly during conflicts (Granic, O’Hara, Pepler, & Lewis, 2007;
Lichtwarck-Aschoff, Kunnen, & van Geert, 2009; Lunkenheimer, Hollenstein, Wang, & Shields,
2012). For example, if family members are not able to incorporate new emotional information
(e.g., someone saying “you misunderstood what I said” and providing clarification) and
appropriately respond to this new information (e.g., becoming less angry), they are likely to
experience escalating conflict and distress. For this reason, Paper 2 focuses on the relationship
between emotional flexibility and a facet of aversive family interactions: parent-to-child
aggression. Parent-to-child aggression and child maltreatment (e.g., abuse, neglect, witnessing of
domestic violence) have been consistently found to have a broad negative impact for youth
(Gilbert et al., 2009; Margolin & Gordis, 2000). In particular, many of the difficulties exhibited
by these youth have been linked to emotion regulation problems (Davies, Sturge-Apple,
EMOTIONAL FLEXIBILITY 9

Cicchetti, Manning, & Zale, 2009; Kim & Cicchetti, 2010). In addition, youth who have been
exposed to aggression have been found to have difficulty adapting to new emotional information
(e.g., the resolution of a simulated interpersonal conflict Pollak, Vardi, Putzer Bechner, & Curtin,
2005) and to be hyper-vigilant and hyper-reactive to negative, particularly angry, stimuli (Pollak,
2008; Pollak & Tolley-Schell, 2003). Although these findings point towards emotional flexibility
difficulties in youth exposed to family aggression, no prior research has directly tested flexibility
in this at-risk population.
Consistent with these studies, it was hypothesized that parent-to-child aggression would
reduce the ability to successfully demonstrate emotional flexibility during the EFIC task.
Additionally, emotional flexibility skills were explored as both a potential mediator of the
association between parent-to-child aggression and later psychological symptoms, and as a risk
or resilience factor that might lessen or exacerbate associations between parent-to-child
aggression exposure and later psychological symptoms.
Importantly, these relationships are all examined within the context of adolescence.
Although no adult comparison group was included in the present study, these results, within the
context of the existing literature, can provide insight into differences between deployment of
specific emotion regulation strategies versus ongoing emotional flexibility processes during
adolescence.
Finally, the youth in this study were recruited from a longitudinal study of community
violence and family aggression exposure. Measures used in the study included four waves of
data collection and parent-to-child aggression data provided by multiple reporters (youth and
both parents). Thus, these data allow for a measure of family aggression that is proximal to the
EMOTIONAL FLEXIBILITY 10

aggression, integrates information across multiple reporters, and provides rich information about
cumulative effects of aggression over time.
In sum, the two papers comprising this dissertation seek to extend the literature in several
unique and important ways. First, we hope to validate an experimental emotional flexibility task
that approximates ongoing emotional changes in daily life more accurately than has been done in
previous research. Next, we aim to provide insight into both behavioral and neural indicators of
flexibility that might be used to identify at-risk youth. Finally, we aim to extend information
about emotional flexibility to quantify a potentially unidentified deficit in youth who have been
exposed to parent-to-child aggression and to test flexibility as a potential mediator or moderator
of the association between parent-to-child aggression and later psychological symptoms. In these
ways, we build on the existing research on emotional flexibility and parent-to-child aggression to
develop a novel approach for examining this important emotional process.
EMOTIONAL FLEXIBILITY 11

Paper 1
Emotional Flexibility: A Novel Neuroimaging Approach to Examine Emotion Regulation in
Adolescence

EMOTIONAL FLEXIBILITY 12

Abstract

Emotional flexibility – the ability to update one’s emotional interpretations and reactions
as situations change – is an important target of therapeutic interventions. In fact, the ability to
flexibly deploy strategies to manage one’s emotions in response to environmental demands may
be more adaptive than any specific emotion regulation strategy. Yet few experimental paradigms
have been developed to model emotional flexibility and no studies have employed neuroimaging
methodologies. The present study introduces a novel functional neuroimaging paradigm for
eliciting emotional flexibility. We focus on an adolescent sample, as adolescence is an important
period for the development of emotion regulation strategies that can impact mental health across
the lifespan. Behavioral responses in our sample indicated that this novel task is a robust
manipulation. Functional imaging data collected during the task revealed neural activation in
regions both overlapping (dorsal and ventral mPFC) and distinct (thalamus, caudate, precuneus)
from other neuroimaging paradigms testing specific emotion regulation strategies as well as
inverse mPFC-amygala functional connectivity. Behavioral and neural measures were also
associated with a self-report measure of emotion regulation skills. Results indicate that this novel
task is effective at eliciting emotional flexibility experimentally and providing new insight into
behavioral and neural correlates of this important process.

EMOTIONAL FLEXIBILITY 13

Introduction
Emotion research has emphasized the importance of being able to respond to emotional
challenges in a flexible manner and has documented the negative impact of rigid behavior (e.g.,
Aldao, 2013). However, not until recently have researchers sought to theoretically define and
empirically test emotional flexibility – the ability to respond to changing emotional demands
(e.g., when an initially positive situation becomes negative or vice versa) and employ different
emotion regulation strategies to appropriately fit the context – as an important construct in its
own right. Emotional flexibility has been described using multiple terms (e.g., emotional
flexibility, ego-resiliency, regulatory flexibility, emotion context sensitivity). Recently,
researchers have sought to build a theoretical framework for understanding emotional flexibility
(Bonanno & Burton, 2013; Kashdan & Rottenberg, 2010) and to integrate a growing body of
empirical studies. Emerging research points to the central role of flexibility in both
psychopathology and psychological wellness (Aldao, Sheppes, & Gross, 2015; Kashdan &
Rottenberg, 2010). Despite these efforts, few experimental studies have directly tested flexibility
processes and an even smaller number have sought out biological correlates of these processes.
The present paper introduces a novel paradigm, the EFIC (Emotional Flexibility with Images and
Captions) task, that examines the behavioral and neural correlates of flexibility using functional
neuroimaging (fMRI); a methodology that has been frequently employed in prior studies of
discrete emotion regulation strategies (e.g., cognitive reappraisal, suppression), but not to
examine emotional flexibility.
As with many psychological constructs, research on emotional flexibility and mental
health has focused primarily on adult populations. Few studies (see Lougheed & Hollenstein,
2012, for an exception) have explored the role of emotional flexibility in adolescent samples.
EMOTIONAL FLEXIBILITY 14

However, adolescence is an important stage for the development of emotion processing
strategies (Steinberg, 2005) that can influence mental health across the lifespan. Several studies
have examined the adaptive value and biological correlates of discrete emotion regulation
strategies (e.g., cognitive reappraisal) in adolescents (McRae et al., 2012; Pitskel, Bolling, Kaiser,
Crowley, & Pelphrey, 2011; Silvers, Shu, Hubbard, Weber, & Ochsner, 2015) and these studies
provide a basis from which we can begin to understand the nature of emotional flexibility in
adolescence.
Emotional Flexibility
Most studies of emotion regulation have focused on comparing and contrasting the value
of different specific regulatory strategies (e.g., cognitive reappraisal versus suppression).
Generally, use of active emotion regulation strategies such as cognitive reappraisal (i.e.,
reinterpreting the emotional meaning of a stimulus to change one’s emotional reaction to it) has
been linked with better emotional well-being than passive strategies such as distraction or
suppression (Aldao & Nolen-Hoeksema, 2010). However, these effects have not been universal,
and studies indicate that the context and nature of the stressor may dictate the emotion regulation
strategy that is most adaptive (Aldao & Nolen-Hoeksema, 2012a; Aldao & Nolen-Hoeksema,
2012b; Compas & Malcarne, 1988; Troy, Shallcross, & Mauss, 2013). Furthermore, the ability to
respond flexibly with different emotional responses and regulation strategies given the demands
of a situational context may actually be more adaptive than the use of any one specific strategy
(Aldao & Nolen-Hoeksema, 2012a; Cheng, Lau, & Chan, 2014). Poor emotional flexibility (i.e.,
emotional rigidity) has been postulated to have links to not only psychological distress, but also
chronic health conditions, including coronary artery disease (Rozanski & Kubzansky, 2005).
Perhaps most importantly, emotional flexibility is important to assess experimentally because it
EMOTIONAL FLEXIBILITY 15

is the emotional process that most closely parallels the way that people respond to emotional
stimuli in real world settings (i.e., with multiple emotional reactions and multiple regulatory
strategies).
Studies on emotional flexibility have typically relied on self-report questionnaires that
ask participants to describe their typical strategies for managing different emotional situations
(e.g., Lester, Smart, & Baum, 1994). In contrast, only a few studies to date have attempted to
model flexibility within a laboratory setting. These studies typically include paradigms such as
submitting participants to a laboratory stressor (e.g., an impossible puzzle) and then asking them
to indicate how many different emotion regulation strategies they used to cope with the task
(Cheng, 2001) or having participants respond emotionally to a series of two different pictures
where the valence is either sustained or altered (negative to positive or vice versa) across the two
images (Fujimura & Okanoya, 2012). In this latter task, the ability to respond to the emotional
valence of the current stimulus (e.g., a positive image) without being substantially influenced by
the valence of the previous stimulus (e.g., a negative image) is used as an indicator of good
emotional flexibility.
Performance on this second type of task has also been linked to individuals’ biological
responses. Specifically, individuals who had more carryover in emotion from the first to second
image (i.e., were unable to be flexible in their responding) on positive emotion trials also had
lower resting heart rate variability, pointing to heart rate variability (a indicator of autonomic
flexibility) as a potential physiological marker of emotional flexibility (Fujimura & Okanoya,
2012). Electromyography (EMG) has also been used to examine connections between emotional
flexibility and biological responses. One study found that individuals with high self-reported
emotional flexibility had greater divergence of corrugator and zygomatic responses to positive
EMOTIONAL FLEXIBILITY 16

versus negative images as well as greater divergence of self-reported affect (Waugh, Thompson,
& Gotlib, 2011). Consistent with studies of depression, this finding indicates that better
emotional flexibility is linked not to overall greater experience of positive emotion, but rather the
ability to experience greater intensity of both positive and negative emotions. In the present
study, we expand upon these tasks to examine both behavioral and biological measures of
flexibility.
Emotional flexibility in adolescence. Studies examining emotional flexibility have been
particularly limited in adolescent populations, with only one study to date testing correlates of
self-reported emotional flexibility. This study found that, consistent with adult research, self-
reported use of multiple emotion regulation strategies (i.e., good emotional flexibility), was
associated with fewer internalizing symptoms (Lougheed & Hollenstein, 2012). However, no
studies to our knowledge have examined how adolescents differ from adults in terms of
emotional flexibility or have used experimental paradigms to elicit flexibility in adolescence.
In contrast, a number of studies have used experimental methods to examine use of
specific emotion regulation strategies during adolescence and compared these strategies in
adolescents versus adults. For example, children and adolescents have been found to have greater
difficulty inhibiting responses in the context of emotional stimuli (Tottenham, Hare, & Casey,
2011) and demonstrate decreased success in reducing negative emotions in a cognitive
reappraisal task (Silvers, McRae, Gabrieli, Gross, & Remy, 2012) relative to adults. Individual
differences are also evident, with greater emotion regulation difficulties being linked to other
interpersonal difficulties, such as high rejection sensitivity (Silvers et al., 2012). Building upon
these studies, we explore responses to an experimental emotional flexibility task in an adolescent
population.
EMOTIONAL FLEXIBILITY 17

Neuroimaging of Emotion Regulation
Although no previous studies, to our knowledge, have examined emotional flexibility
using neuroimaging methodologies, numerous studies have tested discrete emotion regulation
strategies with neuroimaging paradigms. One methodology that has been examined extensively
in adults is cognitive reappraisal; a top-down, cognitive strategy for modifying reactive
emotional responses. Since cognitive reappraisal is generally noted to be one of the most
adaptive strategies for regulating emotions (Aldao & Nolen-Hoeksema, 2010) and has somewhat
similar demands to emotional flexibility tasks (e.g., participants must move quickly between
negative and positive emotional interpretations), these studies serve as the basis for our predicted
task results in the present study. Therefore, the nature of cognitive reappraisal tasks and related
neuroimaging findings are summarized below.
Traditional cognitive reappraisal tasks present participants with negative images and then
ask them to either “maintain” or “reappraise” their emotional response to the image. Generally,
participants are trained extensively on this procedure and are given sample reappraisal statements
to use during the task (e.g., “think to yourself that this scene is actually part of a movie” or “think
to yourself that things are not as they appear in this image”). Studies using this procedure have
found that engaging in cognitive reappraisal (relative to simply observing an emotional image) is
associated with a trade-off in brain activity between the emotionally reactive limbic system,
particularly the amygdala, and the regulatory prefrontal parts of the brain, both medial and lateral
regions, as well as the anterior cingulate cortex (for reviews, see Buhle et al., 2014; Ochsner &
Gross, 2008). Psychophysiological interaction (PPI) analyses have also indicated greater inverse
functional connectivity between the amygdala and prefrontal cortex during reappraisal (e.g.,
Banks, Eddy, Angstadt, Nathan, & Phan, 2007).
EMOTIONAL FLEXIBILITY 18

Neural responses during reappraisal tasks have also been linked to reported emotional
experience and emotion regulation strategies in daily life. Specifically, neural activation during
reappraisal has been found to correlate with participants’ subjective emotional experiences, with
greater engagement of the prefrontal cortex being linked to decreased reported emotional distress
(Ochsner, Bunge, Gross, & Gabrieli, 2002). Additionally, individuals who self-report greater use
of reappraisal strategies in daily life have been found to exhibit greater prefrontal activation and
decreased amygdala activation while processing negative emotional stimuli, indicating that these
individuals may engage in reappraisal processes spontaneously when viewing negative stimuli
(Drabant, McRae, Manuck, Hariri, & Gross, 2009). In the present study, it is hypothesized that
the emotional flexibility task will elicit spontaneous deployment of reappraisal processes, and
thus, will similarly be associated with increases in activation within the medial and lateral
prefrontal cortices, decreases in activation within the amygdala, and inverse functional
connectivity between these regions.
Neuroimaging of emotion regulation in adolescence. It has generally been assumed
that adolescents will differ from adults on functional neuroimaging measures of emotion
regulation because 1) differences between adolescents and adults have been observed
behaviorally, and 2) structural neuroimaging studies have revealed different maturational timing
of the emotionally-reactive subcortical regions and the regulatory prefrontal regions during the
adolescent period (Giedd et al., 1999; Gogtay et al., 2004). However, numerous studies have
examined functional neuroimaging correlates of emotional reactivity and emotion regulation
strategies during adolescence and results have not consistently supported age-related differences
in neural activation. However, studies have found increases in the magnitude of inverse
functional connectivity between the amygdala and prefrontal cortex across development (for a
EMOTIONAL FLEXIBILITY 19

review, see Del Piero, Saxbe, & Margolin, 2016). Furthermore, only a small subset of these
studies has focused on cognitive reappraisal. Findings from these reappraisal studies generally
parallel those seen in adults, including relative increases in prefrontal regions and down-
regulation of the amygdala (McRae et al., 2012; Pitskel et al., 2011; Silvers et al., 2015), but
knowledge about reappraisal in adolescence remains relatively limited. Building upon these
adolescent emotion regulation studies, we examine the neural correlates of emotional flexibility
as a key process during this important developmental period.
Present Study
The present study seeks to extend the literature in several ways. First, we aim to expand
current knowledge about emotional flexibility using a novel paradigm (EFIC task) that generates
several potential measures of emotional flexibility: behavioral responses (ratings and reaction
times), changes in neural activation, and indices of neural connectivity between brain regions.
Few studies have experimentally tested flexibility as an important process in its own right and no
flexibility studies have employed a neuroimaging methodology. Second, to test convergent
validity of the emotional flexibility measures used in the present study, we assess associations
between responses to the EFIC task and a well-validated self-report measure of emotion
regulation skills in daily life. Finally, most neuroimaging studies of emotion regulation strategies
have primarily examined adults, largely overlooking children and adolescents. Therefore, this
study will help further characterize neural correlates of emotional flexibility during an important
period of emotional development.
In the EFIC task, participants view emotional images that are paired with either
congruent or incongruent captions that serve to reinforce or contradict the participant’s initial
emotional response. In each trial, participants 1) view an emotionally evocative image; 2) rate
EMOTIONAL FLEXIBILITY 20

their emotional response to each image; 3) view the image again with a caption that is either
congruent with the image (e.g., a sad caption with a sad image) or incongruent (e.g., a happy
caption with a sad image); and then 4) rate their emotional response to the image a second time.
Building upon the task employed by Fujimura and colleagues (2012), flexibility in this task is
examined by looking at carryover or interference in emotion from the first to second image
presentation. However, in this task, participants are reinterpreting a single image (instead of
responding to two subsequent images) which more closely approximates real world emotional
reactions. Participants with better emotional flexibility should have greater changes in emotional
reactions between the two ratings when the captions are emotionally incongruent with the image.
Such interference effects should not be present on trials when images and captions are
emotionally congruent. Additionally, intensity of responses (very negative or very positive) to
initial images is examined as another potential marker of emotional flexibility as reduced
flexibility has been associated with more neutral responses to both negative and positive stimuli
(Waugh et al., 2011). Using these behavioral measures in conjunction with neural responses to
the task, we can examine multiple indicators of emotional flexibility.
Finally, in addition to being a conceptually distinct emotional process from discrete
regulation strategies (e.g., cognitive reappraisal) and presenting participants with more realistic
emotional demands, this task has several practical advantages. Specifically, this task requires
only brief training, reduces extraneous cognitive demands on the subjects (e.g., remembering to
employ previously-learned reappraisal strategies), and minimizes demand characteristics (i.e.,
participants never are told that captions are either emotionally congruent or incongruent or that
they should change their emotional reactions).
EMOTIONAL FLEXIBILITY 21

Hypothesis 1. We hypothesize that the EFIC task will represent a robust manipulation
and participants will respond flexibly (i.e., change their emotional reactions) to the various
emotional demands across conditions. Specifically, we predict that participants will change their
ratings of the stimuli in accordance with the intended valence of the captions (Hypothesis 1a).
Furthermore, we predict that trials that present incongruent stimuli will be associated with more
neutral (less negative or less positive) self-reported emotion following the presentation of the
caption than trials with congruent stimuli because the emotional valence of the initial image will
affect subsequent emotion (Hypothesis 1b). Third, we predict that participants will rate stimuli
more quickly when images and captions are emotionally congruent than when they are
emotionally incongruent, again due to conflicting emotional stimuli in incongruent trials
(Hypothesis 1c).
Hypothesis 2. We hypothesize that the neural regions recruited during emotionally
incongruent (relative to emotionally congruent) trials of the EFIC task will recruit brain regions
typically associated with emotion (particularly, cognitive reappraisal), including, increased
activation of the medial and lateral prefrontal cortices (Hypothesis 2a) and decreased activation
of the amygdala (Hypothesis 2b).
Hypothesis 3. Since modulation of emotional states has been associated with inverse
functional connectivity (i.e., coordination between up-regulation in one region and down-
regulation in a second region) between the prefrontal cortex and amygdala, we hypothesize that
this pattern of connectivity will increase during incongruent trials relative to congruent trials.
Hypothesis 4. We hypothesize that individuals who report more difficulty with emotion
regulation will show weaker responses to the task overall. Namely, we predict that self-reported
difficulties with emotion regulation will be negatively correlated with change in valence ratings
EMOTIONAL FLEXIBILITY 22

during the task (in incongruent trials) and associated with more neutral emotional responses to
both negative and positive initial images (Hypothesis 4a). Similarly, we predict that self-reported
emotion regulation difficulties will be negatively correlated with neural responses to the task
within the medial and lateral prefrontal cortices and positively correlated with amygdala activity
(Hypothesis 4b). Self-reported emotion regulation difficulties are also hypothesized to be
negatively correlated with functional connectivity between the amygdala and prefrontal cortex
(Hypothesis 4c).
Finally, research is currently very limited on emotional flexibility in adolescence.
Therefore, the impact of age and gender on both behavioral and neural responses to the task will
be evaluated in an exploratory manner.
Methods
Participants
23 youth (10 female), aged 15 to 18 (mean = 17.03), were recruited from the second
cohort (n = 69) of a large longitudinal study (USC Family Studies Project; for recruitment details,
see Margolin, Vickerman, Oliver, & Gordis, 2010). Participants were initially recruited through
word of mouth and print advertising. Inclusion criteria for the initial study required that youth be
in 6
th
through 8
th
grade in school, living in a two-parent household for at least 3 years at the time
of recruitment, and that all family members be able to complete study measures in English.
To be eligible for the MRI study, participants could have no metal in their body, no
medical conditions that could adversely impact MRI scanning (e.g., epilepsy), and could not be
taking psychoactive medications. Participants were also required to have participated in both
waves of the larger longitudinal study prior to completing the MRI visit. Of the 43 families who
were eligible for the MRI sub-study, 7 youth were ineligible, 5 declined to participate, and 7
EMOTIONAL FLEXIBILITY 23

could not be reached or were unable to be scheduled for a visit. Additionally, 1 participant was
excluded from analyses because they did not have useable MRI data due to excessive motion
during the scan. The sample was diverse, reflective of the urban community from which the
sample was drawn. In terms of ethnicity, 34.5% (8 youth) identified as Hispanic/Latino. For race,
52.2% (12 youth) identified as Caucasian, 13.0% (3 youth) as African-American, 8.7% (2 youth)
as Asian-American, and 26.1% (6 youth) as multi-racial. No differences were found between the
larger sample and the MRI cohort in terms of gender, race, ethnicity, or age (all ps > .2).
All of the subjects who completed the EFIC task also completed several additional tasks
focused on emotion processing and social relationships (family and peer) during adolescence
(\beyond the scope of the present study; \(Saxbe, Del Piero, Immordino-Yang, Kaplan, &
Margolin, 2015b; Saxbe, Del Piero, Immordino-Yang, Kaplan, & Margolin, 2015b). Twenty-two
of the participants were right-handed and one participant was left-handed. Analyses were run
with and without the left-handed participant. Since inclusion of the left-handed participant did
not impact the pattern of findings in any of the neuroimaging analyses, the left-handed
participant was included in the final sample.
Procedures
Participants came into the laboratory for approximately four hours. At the beginning of
the visit, they completed one hour of consent procedures, task training, and orientation to the
experimental procedures and scanner. The scanner session lasted for two hours with a 10-minute
break in the middle of the scan. Participants completed the emotional flexibility task, three other
functional neuroimaging tasks, a resting state scan, and several structural imaging scans. During
the final hour, participants were debriefed and completed post-scan questionnaires.
EMOTIONAL FLEXIBILITY 24

EFIC Task. Prior to scanning, participants were trained on the emotional flexibility task.
They were given the following instructions: The following images were taken from news sources,
snapshots, personal histories, and dramatizations of actual events. You will see each image
presented twice. First, you will just see the image. Next, you will see the same image again with
a caption that will tell you some extra information about the scene. Make sure to read the
information in each caption because it will tell you more about what is happening in the picture.
After each presentation of the image, you will be asked to rate how the scene made you feel on a
scale that looks like this. [Examiner shows a paper copy of the 4-point ratings scale (Figure 1)]
You will rate each scene using four buttons that we will give you in the scanner. There are no
right or wrong answers when you are rating the scenes. We are interested in how people respond
to pictures with and without captions, so please just rate the pictures based on your gut reaction
to each thing we show you. Do you have any questions? Participants then completed four
practice trials on neutral pictures. If participants had any difficulty completing the task or did not
appear to understand the directions, they were allowed to repeat the practice trial.
In the scanner, the participants were given an abbreviated version of the above
instructions just prior to starting the task. They were also asked to demonstrate giving “very
negative” and “very positive” ratings using the button box to test the equipment and ensure
participant understanding of the rating procedure. Importantly, participants were never given any
information about emotional flexibility or changes in emotion during the training period or in-
scanner instructions.
Task stimuli. The task involved five conditions: negative congruent (NN), positive
congruent (PP), negative incongruent (NP), positive incongruent (PN), and rest. Each condition
(except rest) included 15 images. In each condition except rest, participants were shown an
EMOTIONAL FLEXIBILITY 25

image surrounded by a black border for a four-second period. They were then asked to rate “how
the scene made them feel” on a four-point scale from “very negative” (-2) to “very positive” (+2)
using four buttons on a scanner-compatible button box. Notably, no neutral value was included
on the scale to force participants to determine whether their reaction to the image was primarily
positive or negative. Next, they were shown the same image again with a caption. In the
congruent trials (NN and PP), the caption maintained the emotional valence of the image. In the
incongruent trials (NP and PN), the caption was designed to reverse the emotional valence of the
image. Participants were then asked to rate the image a second time on the same four-point scale.
The sequence of each type of trial is shown in Figure 2. Note that images shown in Figure 2 are
not actual stimuli (due to use restrictions on the stimuli), but are sample photos with similar
emotional content to the stimuli used in the study.
Development and pilot testing of the EFIC task. Image-caption pairs for the flexibility
task were generated through a pilot study. Images used were taken from the International
Affective Picture System (IAPS), which is a set of photographs that has been extensively
validated and has standardized ratings of both valence and arousal for each image (Lang, Bradley,
& Cuthbert, 2008). Explicit permission was received for use of IAPS images with novel captions
in this way. Pictures were assigned to negative or positive conditions based on the standardized
valence ratings in the IAPS technical manual (Lang et al., 2008) and captions were generated as
described below.
First, images that did not include people were removed. Second, sexually explicit images,
images that were potentially viscerally disgusting (e.g., images with bloody wounds), and images
that depicted addictive substances were removed. These images were removed both for
appropriateness for an adolescent audience and because sexual arousal, disgust, and craving for
EMOTIONAL FLEXIBILITY 26

addictive substances can all elicit neural activation patterns that are distinct from the target
processes of interest. Finally, 80 of the remaining images that were either very positive or very
negative in terms of standardized valence ratings were selected. The first author and coauthors
generated numerous negative and positive captions for each of these 80 images. Congruent
captions were intended to match the emotional content of the image. Incongruent captions were
intended to make participants feel that the situation in the image was not as it initially appeared
(e.g., an image of a girl who is crying where the caption indicates that she is crying because her
brother has returned home safely from war). Stimuli were then winnowed down to the positive
and negative captions that were perceived to be the most believable and emotionally compelling
for each image.
Next, to validate the valence of the pictures and captions and select the final pictures and
captions for the task, we piloted the procedures with 162 undergraduate participants who were
recruited from Psychology courses at a large university. Three rater groups were created.
Participants in each group were given paper sheets to record valence ratings for each captioned
or uncaptioned image. Images and the rating scale (identical to the one used in the final task)
were presented to the group via an overhead projector. The ratings scale was also printed at the
top of each participant’s rating sheet. Participants were asked to rate either the uncaptioned,
positive caption, or negative caption version of each image. No participants saw more than one
version of any given image.
Data from the pilot study was used to determine which captions were most effective at
eliciting the intended emotional reactions. Based on these data, the 60 images (30 negative, 30
positive) that had the most discrepant valence ratings (i.e., greatest difference between ratings)
between the positive and negative captioned versions of the images were selected for use in the
EMOTIONAL FLEXIBILITY 27

study. The average discrepancy within the 60 images selected was 1.94 (range: 1.12 - 3.05).
IAPS stimulus numbers and captions for all stimuli included in the study are shown in
Supplemental Table 1.
Description of final task. For the final task, two alternate versions (Set A and Set B) of
the stimuli were created. Each set included the same 30 negative images and 30 positive images,
but images were paired with different captions across the two sets. Half of the images (15
positive images and 15 negative images) in each set had emotionally congruent captions while
the other half had emotionally incongruent captions. Thus, each set contained 15 images of each
type of image-caption pair previously described (NN, PP, NP, and PN). All images that had
congruent captions in Set A had incongruent captions in Set B and vice versa. Each participant
viewed only one stimulus set (A or B) and never saw the same image with different captions (as
this would have ruined the manipulation).
Images were matched across the four conditions (NN, PP, NP, PN) in terms of the
number, ethnicity (Caucasian vs. non-Caucasian), and gender of people in the scenes. Sets A and
B were matched in terms of valence ratings of stimuli (from the pilot study), as well as caption
word count, and caption character count within each of the four conditions. Participant
assignment to either Set A or B was randomized and randomization was done separately for male
and female participants.
In the scanner, the emotional flexibility task was presented as three runs, with each run
containing five presentations of stimuli from each condition (NN, PP, NP, PN). Runs were each
seven minutes and two seconds in length. Run order was randomized separately for female and
male participants. Order of stimulus presentation within each run was optimized using a genetic
algorithm (Wager & Nichols, 2003). This approach facilitates selection of condition orders that
EMOTIONAL FLEXIBILITY 28

ensures optimal differential overlap of the hemodynamic responses between the different task
conditions to facilitate neuroimaging analyses.
fMRI data acquisition. Images were acquired across the whole brain using a Siemens 3
Tesla MAGNETON TIM Trio scanner with a 12-channel matrix head coil. Functional MRI data
were acquired using a T2* weighted EPI sequence (TR = 2 sec, TE = 25 ms, flip angle = 90°)
with voxel resolution of 3mm × 3mm × 2.5mm. Thirty-two continuous transverse slices were
acquired covering the whole brain and brainstem. Structural MRI images were acquired using an
MPRAGE sequence (TI = 900 ms, TR = 1950 ms, TE = 2.26 ms, flip angle = 7°) with isotropic 1
mm voxel resolution.
Measures
EFIC task.
Behavioral task responses. Button box responses (valence ratings) were averaged across
all trials within a given condition for each participant. The primary measures of interest for this
study were change between the uncaptioned and captioned images for each trial type and initial
valence ratings on both positive and negative uncaptioned images. For measures of change from
initial image presentation to captioned image presentation within trials, the average initial image
ratings were subtracted from the average captioned image ratings for each participant. For
example, if a participant rated the initial images of NP trials with, on average, a score of -1.4,
and rated the captioned images of NP trials with an average score of +1.3, their total average
change score for all NP trials would be 2.7. Here, we describe initial uncaptioned image
presentations with the condition name (NN, NP, PP, or PN) and subscript “Img” (e.g., NP
Img
,
referring to the initial image within an NP trial). The second, captioned image presentations are
EMOTIONAL FLEXIBILITY 29

denoted with the condition name and subscript “Cap” (e.g., NP
Cap
). Finally, change scores are
denoted with the subscript “Change” (e.g., NP
Change
).
Reaction time (RT) data were calculated as the time (in seconds) between when the
ratings scale was displayed on the screen after each image and when participants provided a
response via the button box. Reaction times were averaged across all trials within a given
condition for each participant. The primary measure of interest was change in RT from the initial
rating to the captioned rating in each condition.
If participants did not provide a response while the ratings scale was displayed for a trial,
that trial was not included in analyses for valence ratings or RT for that participant. The average
number of missed trials (out of 60) per participant was 1.8 (range: 0 - 7).
Whole brain fMRI analyses. Imaging data preprocessing was completed using FSL
software (FMRIB, Oxford, UK). Standard preprocessing including slice timing correction,
motionTab correction, brain extraction, spatial smoothing (using a 5 mm kernel), high-pass
filtering, and pre-whitening were completed prior to contrast modeling. Registration to high-
resolution structural and standard space images was completed using FLIRT. All analyses
employed FLAME mixed effects analysis with FSL’s FEAT (fMRI Expert Analysis Tool) and a
cluster corrected threshold of z = 2.3, p < .05. This tool identifies clusters of contiguous voxels
across the whole brain that demonstrate statistically significant differences in blood oxygen
level-dependent (BOLD) signal between specified experimental conditions (e.g., NP vs. NN)
while providing a stringent correction for multiple comparisons. In these analyses, the whole 14-
second trial of each stimulus presentation was modeled as a single event, including the
presentation and rating of both the initial (uncaptioned) and captioned image.
EMOTIONAL FLEXIBILITY 30

Amygdala region of interest analyses. Due to the small volume of the bilateral amygdala
structures, anatomical region of interest (ROI) analyses were used to test activation in these
regions. ROI analyses were conducted using anatomical masks (Harvard-Oxford Structural
Atlas) of the right and left amygdalae. For whole brain analyses, contrasts were masked prior to
thresholding with a binary bilateral amygdala mask. For correlational analyses, percent signal
change was extracted using the featquery tool in FSL from the two anatomically-defined ROIs
(right amygdala and left amgydala).
Functional connectivity analyses. To test the extent to which activation in the amygdala
covaried with other regions of the brain during the negative incongruent condition relative to the
negative congruent condition (NP > NN) and during the positive incongruent condition relative
to the positive congruent condition (PN > PP), a psychophysiological interaction (PPI) analysis
(O’ ’Reilly, Woolrich, Behrens, Smith, & Johansen-Berg, 2012) was conducted. Anatomically-
defined masks of the left and right amygdala were converted from standard space to participants’
native space to co-register with functional imaging data using FSL’s FLIRT. Timeseries of the
NP > NN and PN > PP contrasts were then extracted from these seed voxel regions (left and
right amygdala) using fslmeants for each participant and each run. Lower level FEAT analyses
were conducted for each run using four regressors: timing data from the task (psychological),
timeseries data from the seed voxels (physiological), an interaction term (psychological x
physiological), and a negative interaction term. Higher-level FEAT analyses were then
conducted to combine data within participants’ runs using a fixed effects model. Subsequently,
higher-level FEAT analyses were conducted using a mixed effects model to collapse data across
participants. Similar to the whole brain BOLD analyses, these analyses were thresholded using a
cluster corrected threshold of z = 2.3, p < .05.
EMOTIONAL FLEXIBILITY 31

Self-reported emotion regulation. Self-reported emotion regulation success was
measured using the Difficulties in Emotion Regulation Scale (DERS; Gratz & Roemer, 2004).
This questionnaire probes the participant’s perception of their general success with emotion
regulation. Participants responded to 36 items using a 5-point scale from 1 (Almost Never) to 5
(Almost Always). Higher total scores on this measure indicate greater difficulty with successful
emotion regulation. The overall reliability for this measure has been found to be high
(Cronbach’s alphas = .93).
Results
Descriptive and Validity Data
Mean reaction times and valence ratings for each condition and all stimuli within a trial
are shown in Table 1. Supporting task validity, no significant differences on either valence or
reaction time were found between participants who viewed Set A versus Set B of the stimuli (ts:
-.12 to 1.86, all ps > .13).
As shown in Figure 3, and consistent with Hypothesis 1a, participants responded robustly
to the different conditions. In particular, ratings on the incongruent captioned images showed
change in the expected direction. When caption valence was congruent with the initial image
(NN or PP trials), paired-sample t-tests revealed that average ratings across trials on NN
Cap
and
PP
Cap
became more negative or positive than the ratings on NN
Img
or PP
Img
, (NN: t(22) = 8.12, p
< .001; PP: t(22) = -5.97, p < .001). In other words, if a positively-valenced caption followed a
positively-valenced image, the participant’s rating became more positive; if a negatively-
valenced caption followed a negatively-valenced image, the rating became more negative.
Table 2 shows correlations between the main task variables. Initial positive and negative
image ratings were negatively correlated, indicating that individuals who rated images as more
EMOTIONAL FLEXIBILITY 32

intensely emotional did so across both negative and positive images. Change indices on the two
incongruent trials (NP and PN) were correlated with each other and change during NN and PP
trials were correlated with each other. Few significant associations were found between RTs and
valence ratings within conditions. In particular, only change in ratings during the PP trial was
inversely associated with change in RTs during the PP trial.
Behavioral Indicators of Emotional Flexibility
Consistent with Hypothesis 1b, paired sample t-tests revealed a significant impact of the
valence rating of the initial, uncaptioned image on ratings of the second, captioned image.
Specifically, ratings were more negative or positive on captioned images when both stimuli had
the same emotional valence (NN or PP trials) than when the valence was conflicting (NP or PN
trials; Negative captions: t(22) = -5.41, p < .001; Positive captions: t(22) = -3.45, p = .002).
Consistent with Hypothesis 1c, paired sample t-tests comparing reaction times during
uncaptioned versus captioned images within each of the four conditions revealed that participants’
reaction times became significantly shorter from NN
Img
and PP
Img
ratings to NN
Cap
and PP
Cap

ratings (NN: t(22) = 4.25, p < .001; PP: t(22) = 2.26, p = .03), but became longer from NP
Img
and
PN
Img
ratings to NP
Cap
and PN
Cap
ratings (NP: t(22) = -2.50, p = .02; PN: t(22) = -2.30, p = .03),
indicating that participants had faster responses when the valence of the initial image was
supported by the caption, but slower responses when their initial emotional interpretation was
contradicted by the caption. Reaction times by condition are shown in Figure 4.
Age and gender effects. Gender and age effects were examined in an exploratory
manner. Female participants demonstrated a greater magnitude of change in their ratings on
incongruent trials than male participants (NP: t(21) = 2.10, p = .048; PN: t(21) = -2.50, p = .02).
No significant differences were observed between males and females on the magnitude of
EMOTIONAL FLEXIBILITY 33

change in either congruent condition (NN and PP). Females also had more negative initial
negative image (t(21) = -3.79, p = .001) and PN
Cap
(t(22) = -2.44, p = .02) ratings as well as more
positive initial positive image (t(21) = -3.90, p = .001), and PP
Cap
(t(21) = 3.49, p = .002) ratings.
Finally, females were faster than males when rating the following stimuli: all initial negative
images (t(21) = -2.39, p = .026), NN
Cap
(t(21) = -3.02, p = .007), and PN
Cap
(t(21) = -2.40, p
= .026). No other significant gender differences in reaction time were observed. Overall, female
participants were found to have greater change in their responses, to rate their emotional
reactions to the images both more negatively and more positively, and to rate negative stimuli
more quickly than males. Neither valence ratings nor reaction times were correlated with
participant age for any of the conditions.
Neuroimaging Data
To test Hypothesis 2a, whole brain analyses examining differences in activation between
the main contrasts (NP vs. NN and PN vs. PP) were conducted. Hypothesis 2b was tested using
small volume ROI analyses of the left and right amygdalae.
Negative incongruent (NP) > negative congruent (NN). Whole brain analyses revealed
relative increases in a medial prefrontal (mPFC) cluster ([-14 24 54], z = 3.60) when comparing
negative incongruent trials to negative congruent trials. Relative decreases were found in a
cluster within the precuneus ([38 -68 6], z = 4.82). No other significant differences between these
two conditions were found in the whole brain analyses. These results are shown in Figure 5 and
cluster information is shown in Table 3. Percent signal change was extracted to further
decompose these findings. These assessments revealed increases in activation compared to rest
in the mPFC and precuneus for both the NN and NP conditions, but relatively less activation in
the mPFC cortex during the NN condition and relatively less activation in the precuneus during
EMOTIONAL FLEXIBILITY 34

the NP condition. An anatomically-defined small volume mask was used to test for activation
differences across the two conditions in the left and right amygdalae. No significant differences
were revealed.
Positive incongruent (PN) > positive congruent (PP). Whole brain analyses revealed
greater activation in the caudate and thalamus ([10 8 8], z = 4.27) during positive incongruent
trials relative to positive congruent trials. Relative decreases were found in the ventromedial
prefrontal cortex (vmPFC; [8 30 -14], z = 4.32) and the left lateral occipital cortex ([-50 -72 -2],
z = 4.00). No other significant differences between the two conditions were found in whole brain
analyses. These results are shown in Figure 6 and cluster information is shown in Table 3.
Percent signal change was extracted from these clusters to further decompose these relationships.
These assessments revealed that activation in the thalamus/caudate increased during both PP and
PN trials, but to a lesser extent during PP trials. Minimal change from baseline was observed in
the vmPFC during the PP trial and relative decreases from rest were observed during the PN trial.
In the lateral occipital cortex, relative activation was observed during both conditions but to a
lesser extent during the PN condition. No significant differences between the two conditions
were found when examining the left and right amygdalae using anatomically-defined ROIs.
Functional connectivity. Consistent with Hypothesis 3, PPI analyses revealed that
activation in the right amygdala was inversely associated with activation in both medial and
lateral prefrontal regions for the NP > NN contrast. These results are shown in Figure 7 and
cluster information is shown in Table 4. No regions were found to have significant functional
connectivity with the left amygdala for the NP > NN contrast; however, a similar pattern of
findings that did not reach statistical significance was evident. No significant associations
between the right or left amygdala and any brain regions were found for the PN > PP contrast.
EMOTIONAL FLEXIBILITY 35

Only right amygdala connectivity for the NP > NN contrast is examined in the below
correlational analyses focused on functional connectivity.
Age and gender. Exploratory analyses were conducted to assess the role of gender and
age on neural responses to the EFIC task. Between-group gender analyses revealed no brain
regions that differed significantly between male and female participants during any of the
conditions or that differed in degree of connectivity between the right amygdala and other brain
regions. Neither whole brain analyses nor connectivity analyses revealed significant correlations
with age.
Associations with Self-Reported Emotion Regulation
Behavioral results. To test Hypothesis 4a, correlations were run to examine associations
between self-reported emotion regulation and valence ratings in each condition (Table 2). Total
self-reported emotion regulation skills were significantly related to magnitude of NP
Change
and
PN
Change
, such that poorer emotion regulation (higher total DERS score) was associated with less
change in ratings during both NP (r(21) = -.50, p = .02) and PN (r(21) = .42, p = .047) trials.
Additionally, poor emotion regulation skills were associated with less negative ratings on initial
negative images (r(21) = .47, p = .03), but not more positive ratings on initial positive images.
Overall, poorer self-reported emotion regulation was associated with reduced change in both
emotionally incongruent conditions and with less negative initial emotional responses to negative
stimuli.
Neuroimaging results.
Whole brain and ROI analyses. Hypothesis 4b was tested through whole brain
regression analyses and ROI analyses within the amygdala. Whole brain analyses revealed no
associations between activation within the NP > NN contrast or PN > PP contrast and the DERS
EMOTIONAL FLEXIBILITY 36

total score. Percent signal change was extracted from the left and right amygdalae and total
DERS score was found to be associated with relative changes in activation within the right
amygdala during the PN > PP contrast (r(21) = .43, p = .04). As shown in Figure 8, youth who
self-reported worse emotion regulation skills had more amygdala activation during PN trials
relative to PP trials when compared to youth with better self-reported emotion regulation skills.
PPI analyses. Contrary to Hypothesis 4c, no associations between participants’ self-
reported emotion regulation skills and the extent of functional connectivity between the right
amygdala and other brain regions were observed.
Discussion
Using a novel emotional flexibility task, this study is the first to examine the neural
correlates of flexibility in adolescents. The EFIC task appears to provide a robust manipulation –
participants responded as intended to both emotionally congruent and incongruent stimuli. As
hypothesized, there was some carryover or emotional interference between trials such that
positive captions on negative images were not perceived as positively as positive captions on
positive images and vice versa. Similar patterns were observed in reaction time such that speed
increased across congruent trials and decreased across incongruent trials, indicating that
participants took longer to synthesize discordant emotional information. Gender differences were
also observed in task performance; female participants performed better on several indicators of
emotional flexibility. Specifically, females had greater change on incongruent trials, responded
with stronger negative responses to initial negative stimuli, and had faster responses when rating
all types of negative stimuli.
Neural responses to the task showed both overlapping and distinct findings from the
existing emotion regulation neuroimaging literature. Buhle and colleagues (2014) conducted a
EMOTIONAL FLEXIBILITY 37

meta-analysis of cognitive reappraisal studies in adults and found that reappraisal paradigms
typically elicited activation in the middle frontal gyrus, inferior frontal gyrus, medial frontal
gyrus, superior parietal lobule, and middle temporal gyrus. Relative deactivation was
consistently found in the bilateral amygdala. The three studies of cognitive reappraisal in
adolescence have found engagement of similar brain regions, but have also identified more
subtle differences from adults in complex indices such as non-linear change and functional
connectivity (McRae et al., 2012; Silvers et al., 2015; Pitskel et al., 2011). In the present study,
responses to the negative incongruent trials (which most closely parallel a cognitive reappraisal
process) were consistent with previous research and showed relative increases in the medial
prefrontal cortex. Surprisingly, downregulation of the amygdala was not observed; however,
relative decreases were found in the inferior/posterior precuneus, a region that has been
associated with mentalizing about others’ experiences as well as compassion for social pain in
prior neuroimaging studies (Araujo, Kaplan, & Damasio, 2013; Immordino-Yang, McColl,
Damasio, & Damasio, 2009). It is possible that the negative incongruent trials led to relatively
less activation in this region because the information was conflicting whereas the decidedly
negative information in the negative congruent trials was more likely to elicit feelings of
empathy or concern for the subject. Additionally, functional connectivity analyses using the left
and right amygdala as seed voxels were consistent with previous research (Banks et al., 2007)
and identified inverse connectivity between the right amygdala and several regions of the medial
and lateral prefrontal cortices during the negative incongruent trials.
In positive incongruent trials, where participants were presented with unexpected
negative information about a positive image, relative increases were found in the caudate and
thalamus and relative decreases were found in the ventromedial prefrontal cortex and left lateral
EMOTIONAL FLEXIBILITY 38

occipital cortex. These regions, with the exception of the lateral occipital cortex, have been
implicated in the ongoing, automatic processing and regulation of emotions (e.g., Goldin, McRae,
Ramel, & Gross, 2008; Phillips, Drevets, Rauch, & Lane, 2003); however, they are less
commonly found in studies of active emotion regulation processes (e.g., cognitive reappraisal,
Buhle et al., 2014). To our knowledge, no prior neuroimaging studies have explored the neural
correlates of unexpected negative information, but our findings suggest that moving from
positive to negative emotional states may engage more automatic and less conscious emotion
regulation circuitry.
Importantly, both behavioral and neural responses to the novel task were also associated
with an established self-report measure of emotion regulation, indicating that task performance is
linked to participant’s own perception of emotion regulation success in daily life. Specifically,
more change during both positive and negative incongruent trials was associated with better self-
reported emotion regulation skills. Additionally, consistent with previous research (Waugh et al.,
2011), more negative initial ratings of negative images were linked with better self-reported
emotion regulation skills. Finally, better self-reported emotion regulation skills were associated
with relative decreases in amygdala activation during the trial where participants viewed
unexpected negative information. This finding suggests that participants with better emotion
regulation skills were more successful at automatically down-regulating their negative responses
to unexpected negative information.
Future studies should extend this flexibility paradigm to both adult and pediatric samples.
This would provide important information about the developmental trajectory of this important
process. The age range examined in the present study was likely too narrow (three years) to
capture important developmental changes; however, future research employing analyses to
EMOTIONAL FLEXIBILITY 39

explore both linear and non-linear patterns of change is likely to yield valuable information about
emotional flexibility. Furthermore, providing additional validation of the task by exploring
associations with functional outcomes such as psychopathology symptoms is an important future
step. Additionally, understanding whether flexibility is differentially linked to specific
psychological symptoms (e.g., depression versus anxiety) would yield valuable insights into how
targeted interventions might be employed to address difficulties in emotional flexibility
therapeutically. “Third wave” psychotherapy treatments such as mindfulness-based stress
reduction and acceptance and commitment therapy explicitly target emotional flexibility and aim
to enhance the ability to adjust to new emotional information (Carmody, Baer, Lykins, &
Olendzki, 2009; Hayes, Luoma, Bond, & Masuda, 2006; Lutz, Slagter, Dunne, & Davidson,
2008). Therefore, it might be valuable to examine outcomes in these types of therapies in
conjunction with the EFIC task.
This study has several important limitations, including the small sample size (23
participants), which was constrained by the fact that participants were recruited from a larger
longitudinal study and needed to be eligible to complete the MRI procedure. Additionally, recent
neuroimaging research has indicated that adolescents may have distinct neural reactions to social
information about same-aged peers versus adults (e.g.,Saxbe et al., 2015b). In the current study,
stimuli depicted people across a broad age range, which may have complicated participants’ task
responses. Thus, it may be important in future studies to separate responses to stimuli depicting
adolescents versus either children or adults. Finally, this study did not include neutral conditions
for the sake of limiting task time within a long, larger neuroimaging protocol. Including neutral
images and captions as a comparison condition would facilitate additional analyses to tease apart
the impact of positive versus neutral versus negative emotional content in emotional flexibility.
EMOTIONAL FLEXIBILITY 40

Conclusion
This study provides validation for a novel experimental measure of emotional flexibility,
the EFIC task. These analyses are the first to test emotional flexibility using a neuroimaging
paradigm. Behavioral findings provide support for this experimental task as a viable way to elicit
emotional flexibility experimentally. Neural results indicate that active emotion regulation
processes were recruited during downregulation of negative responses whereas more automatic
emotion regulation processes were recruited during reactions to unexpected negative stimuli.
Additionally, consistent with previous research, inverse functional connectivity between the right
amygdala and prefrontal cortex was observed. Task performance was also associated with a self-
report measure of emotion regulation skills in daily life – better emotion regulation skills were
linked with more change in emotional responses as well as more negative responses to negative
stimuli (but surprisingly, not more positive responses to positive stimuli). Furthermore, better
self-reported emotion regulation was associated with decreased amygdala responses during
unexpected negative information. Finally, on behavioral indices, females demonstrated better
emotional flexibility relative to males on numerous indices, but no gender differences in neural
responses were observed. In sum, this study provides support for the EFIC task as a promising
approach to explore emotional flexibility within an experimental setting.
EMOTIONAL FLEXIBILITY 41

Table 1

Means and Standard Deviations of All Variables
All Participants (N = 23) Males (n = 13) Females (n = 10)
M (SD) M (SD) M (SD)
Age 17.03 (.87) 17.33 (.88) 16.65 (.73)
All Negative Image Ratings (NN
Img
+ NP
Img
)* -1.35 (.31) -1.18 (.29) -1.58 (.17)
All Positive Image Ratings (PP
Img
+ PN
Img
)* 1.38 (.36) 1.18 (.31) 1.64 (.22)
NN
Cap
Rating -1.83 (.33) -1.74 (.41) -1.94 (.11)
NP
Cap
Rating 1.37 (.47) 1.32 (.44) 1.42 (.52)
PP
Cap
Rating* 1.66 (.35) 1.48 (.37) 1.90 (.11)
PN
Cap
Rating -1.41 (.50) -1.28 (.54) -1.58 (.40)
NN
Change
Rating -.44 (.26) -.51 (.28) -.36 (.23)
NP
Change
Rating* 2.69 (.64) 2.46 (.66) 2.99 (.50)
PP
Change
Rating .33 (.27) .38 (.34) .27 (.11)
PN
Change
Rating* -2.84 (.71) -2.55 (.69) -3.22 (.57)
All Negative Image RTs (NN
Img
+ NP
Img
)* .89 (.22) .98 (.22) .77 (.18)
All Positive Image RTs (PP
Img
+ PN
Img
) .85 (.22) .92 (.22) .77 (.22)
NN
Cap
RT* .73 (.19) .82 (.20) .63 (.10)
NP
Cap
RT .99 (.25) 1.06 (.26) .90 (.22)
PP
Cap
RT .78 (.21) .85 (.26) .69 (.10)
PN
Cap
RT* .97 (.26) 1.08 (.27) .84 (.17)
NN
Change
RT -.18 (.20) -.21 (.24) -.15 (.15)
NP
Change
RT .13 (.24) .13 (.27) .12 (.22)
PP
Change
RT -.08 (.18) -.09 (.20) -.07 (.15)
PN
Change
RT .13 (.28) .19 (.31) .06 (.21)
DERS Total Score 77.59 (18.30) 79.82 (20.16) 74.70 (16.13)
*Significant gender differences (p < .05)

EMOTIONAL FLEXIBILITY 42

Table 2

Correlation Matrix of Primary Study Variables
N = 23
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. Age - .04 -.12 .11 -.15 -.15 .02 -.07 -.05 .11 -.28 -.08 -.14 -.20
2. All Negative Image Ratings - -.60
**
-.19 -.63
**
.03 .70
***
.32 .02 -.07 .19 .26 .54
**
.47
*

3. All Positive Image Ratings - -.09 .72
***
-.37 -.79
***
-.39 -.40 .01 -.20 .12 -.04 -.24
4. NN
Change
Rating - -.22 -.42
*
.18 -.19 .03 .14 .05 .24 -.46
*
-.03
5. NP
Change
Rating - -.001 -.85
***
-.24 -.23 -.13 -.19 -.12 -.02 -.50
*

6. PP
Change
Rating - -.03 .25 .17 -.13 -.20 -.46
*
.11 -.03
7. PN
Change
Rating - .24 .17 -.01 .43
*
.14 .17 .42
*

8. All Negative Image RTs - .78
***
-.48
*
-.25 -.23 .22 .06
9. All Positive Image RTs - -.26 -.03 -.48
*
-.36 -.08
10. NN
Change
RT - -.002 .28 -.28 -.23
11. NP
Change
RT - .01 -.02 .33
12. PP
Change
RT - .34 .22
13. PN
Change
RT - .24
14. DERS Total Score -
* p < .05; ** p < .01; *** p < .001
EMOTIONAL FLEXIBILITY 43

Table 3

Peak Voxel and Maximum Z-Values for Main Effect Results

MNI Coordinates
Region Cluster Size Z-score Side x y z
NP > NN
Superior Frontal Gyrus 2707 3.60 Left -14 24 54
Frontal Pole -- 3.53 Left -10 42 42
Superior Frontal Gyrus -- 3.47 Right 14 36 46
Frontal Pole -- 3.30 Left -10 56 38
Superior Frontal Gyrus -- 3.24 Right 8 22 52
Superior Frontal Gyrus -- 3.17 Left -8 34 44
NN > NP
Lateral Occipital Cortex 8232 4.82 Right 38 -68 6
Precuneus Cortex -- 4.21 Right 16 -76 38
Intracalcarine Cortex -- 4.09 Left -10 -80 2
Cuneal Cortex -- 3.85 Left -6 -82 32
Precuneus Cortex -- 3.83 Right 20 -62 32
Precuneus Cortex -- 3.72 Right 18 -62 28
PN > PP
Caudate 2714 4.27 Right 10 8 8
Caudate -- 4.22 Right 12 2 12
Caudate -- 4.09 Left -10 4 10
Caudate -- 4.07 Left -10 6 6
Thalamus -- 3.95 Left -4 -28 2
Thalamus -- 3.74 Right 12 -12 4
PP > PN
Subcallosal Cortex 2999 4.32 Right 8 30 -12
Frontal Medial Cortex -- 4.02 Left -2 34 -16
Frontal Medial Cortex -- 3.99 Left -12 38 -12
Frontal Medial Cortex -- 3.78 Right 10 46 -12
Cerebral White Matter -- 3.72 Left -16 28 4
Cerebral White Matter -- 3.52 Left -14 54 -6
Lateral Occipital Cortex 1519 4.00 Left -50 -72 -2
Occipital Pole -- 3.79 Left -34 -94 12
Lateral Occipital Cortex -- 3.38 Left -42 -80 16
Cerebral White Matter -- 3.28 Left -30 -74 10
Lateral Occipital Cortex -- 3.23 Left -50 -82 6
Lateral Occipital Cortex -- 3.19 Left -48 -78 6
EMOTIONAL FLEXIBILITY 44

Table 4

Peak Voxel and Maximum Z-Values for Regions Showing Functional Connectivity with Right
Amygdala ROI

MNI Coordinates
Region Cluster Size Z-score Side x y z
NP > NN
Middle Frontal Gyrus 3135 4.05 Left -58 8 42
Precentral Gyrus -- 3.88 Left -56 -10 48
Precentral Gyrus -- 3.73 Left -52 6 46
Precentral Gyrus -- 3.64 Left -42 -6 60
Middle Frontal Gyrus -- 3.32 Left -36 2 64
Middle Frontal Gyrus -- 3.31 Left -48 10 52

EMOTIONAL FLEXIBILITY 45

Supplemental Table 1
Captions and Image Numbers for EFIC Stimulus Set
Study ID IAPS ID Image Valence Congruent Caption Set Incongruent Caption Set
101 2120 Negative He was furious when he caught his wife cheating A1 This was his first Oscar winning performance B1
102 2205 Negative The doctors can't save her A1 His kidney donation saved her life B1
103 2276 Negative Her house was destroyed in a fire A1 She's so happy that her father survived the war B1
104 2278 Negative They just watched their family's house burn down A1 It was the most beautiful fireworks show B1
105 2301 Negative She found out her parents are getting a divorce A1 Her brother's safe return was a huge relief B1
107 2455 Negative They lost their home in a hurricane A2 They are about to win a championship age B2
108 2456 Negative The factory is closing and they will lose their jobs B1 The family business is finally out of debt A1
109 2457 Negative His parents were arrested for domestic violence B1 He loved the circus despite the scary clowns A1
110 2490 Negative His children promised to visit, but they forgot B1 His kids are surprising him with a birthday dinner A1
112 2691 Negative Several people died in this riot B1 He protested to free his people from the dictator A1
113 2700 Negative The child's funeral was devastating B1 Their youngest sister is finally getting married A1
114 2703 Negative They watched gunmen carry their mother away B2 They were so happy to finally have clean water A2
116 2900.1 Negative His mother is still trapped in the burning car A2 They could not wait to see his mom exit the plane B2
117 3180 Negative Her husband has been abusive for many years B2 The new surgery restored her eyesight A2
118 3220 Negative The illness caused his body to waste away A2 Physical therapy helped him regain his strength B2
119 6212 Negative The soldiers shot many innocent children B2 He made it to safety due to the soldier's protection A2
120 6243 Negative He is holding people hostage B2 The undercover cop saved all the hostages A2
121 6315 Negative Her boyfriend is really scaring her B2 She is learning a lot from her self defense class A2
124 6530 Negative He is unable to control his anger B3 They are taking their first dance lesson together A3
127 6571 Negative He will kill him if he doesn't get out of the car B3 The movie made them both comedy stars A3
128 6821 Negative The gang members are about to shoot the driver A2 They heroically saved the man trapped in the car B2
129 6838 Negative It was the last day she saw her family A2 They always remembered how she saved the day B2
130 9041 Negative She is hiding from her abusive dad B3 The side hall was a great spot for hide-and-seek A3
133 9160 Negative The violent civil war would go on for fifteen years A3 He is proud to be defending his famiy's freedom B3
134 9220 Negative They just lost their oldest son A3 They were glad their grandmother lived a full life B3
135 9331 Negative He has been homeless for ten years B3 He had a real rags to riches story A3
136 9332 Negative Her eyes are getting worse B3 She just learned that her son survived the war A3
137 9415 Negative The refugees had not eaten for several days A3 The refugees were reunited with their families B3
138 9421 Negative Everyone in his troop was wounded in battle A3 He's so happy to be coming home B3
EMOTIONAL FLEXIBILITY 46

139 9429 Negative The children's school just burned down A3 These mothers just saved their children's lives B3
140 8497 Positive They wished the summer would never end A1 It was devastating when the oldest became ill B1
142 1601 Positive He loves feeding the giraffe A1 The zoo is cutting costs by firing this zookeeper B1
144 2030 Positive This picture kicked off her huge modeling career A1 Her missing person's photo was posted all over B1
145 2035 Positive She always loves being photographed A1 Getting adopted was looking less and less likely B1
146 2045 Positive He was showered with attention from his grandma A1 The baby was kidnapped by a child molester B1
151 2154 Positive He always likes arm wrestling with his dad A2 This was the last time he saw his father B2
152 2156 Positive They are proud of their strong family A2 They all died in the earthquake B2
154 2170 Positive She felt lucky to have a healthy, beautiful baby A2 She has been depressed since her baby was born B2
155 2208 Positive Their kids loved watching the wedding video A2 She found it easy to pretend that she wanted this B2
158 2299 Positive The family had fun going to dinner and a movie A2 They spent their last savings on this meal B2
159 2300 Positive Prom night exceeded her highest expectations A3 Her friend's accident ruined the special night B3
160 2304 Positive She got first place in the school spelling bee A3 Her mother's drug addiction destroyed their family B3
161 2310 Positive He credited his mother for his financial success B1 His father rarely visits them A1
162 2339 Positive They never forgot their favorite coach B1 They can never meet their father's expectations A1
163 2340 Positive They love playing with their grandfather B1 Their grandfather died from a stroke an hour later A1
164 2341 Positive They love taking care of their baby sister B1 They rarely get to visit their father in prison A1
165 2347 Positive The class had fun watching the monkey do tricks B1 Their teacher will get charged with child abuse A1
166 2360 Positive He works hard to support his wife and child B2 He drinks and yells at his wife after work A2
167 2373 Positive The popular band gets people to sing and dance B2 The band broke up after a member died suddenly A2
168 2388 Positive They go to their favorite beach every summer B2 They went to the beach to escape the fighting A2
169 2395 Positive The family reunion was a lot of fun B2 They don't know yet that their mom has cancer A2
170 2510 Positive Her first grandchild was just born B2 She hasn't seen her family in two years A2
171 2530 Positive They enjoy biking together on the weekend B3 His wife doesn't know about the other woman A3
173 2598 Positive They went to grandma's to cook a holiday feast B3 They lived with an aunt when their mom vanished A3
174 2900.2 Positive She is proud of winning the science fair B3 Her father never says he loves her A3
175 4612 Positive He is falling in love with her A3 He became a main suspect in her disappearance B3
176 4622 Positive The second honeymoon made them feel young A3 She never suspected that he was cheating B3
177 4624 Positive Their kids loved looking at their old photos B3 She is worried that he is using her for sex A3
178 4628 Positive They could not wait to start a family A3 Their families disapproved of the marriage B3
179 8461 Positive They had a great beach vacation B3 Fun memories became painful after her death A3

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Figure 1. Rating scale used in EFIC task.
EMOTIONAL FLEXIBILITY 48

Figure 2. Timeline of trials within each of the four task conditions.
EMOTIONAL FLEXIBILITY 49

Figure 3. Bar graph of valence ratings for all conditions.
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Figure 4. Bar graph of reaction time data for all conditions.
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Figure 5. Significant regions in whole brain analyses for the NP vs. NN contrast.
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Figure 6. Significant regions in whole brain analyses for the PN vs. PP contrast.

EMOTIONAL FLEXIBILITY 53

Figure 7. Regions demonstrating significant inverse connectivity with the right amygdala seed region during the NP condition relative
to the NN condition.
EMOTIONAL FLEXIBILITY 54

Figure 8. Scatterplot showing the correlation between neural activation in the right amygdala (within the PN > PP contrast) and self-
reported emotion regulation difficulties.
EMOTIONAL FLEXIBILITY 55

Paper 2

Family Aggression, Emotional Flexibility, and Psychological Symptoms in Adolescence

EMOTIONAL FLEXIBILITY 56

Abstract

Exposure to family aggression during childhood is known to compromise psychosocial
functioning later in life. This study examines the impact of parent-to-child aggression on
emotional flexibility – a facet of emotion regulation vital for psychological wellbeing. First, we
test longitudinal associations between history of parent-to-child aggression and participants’ later
emotional flexibility using a novel experimental task, the EFIC task, that yields behavioral and
neural (fMRI) measures. We also examine emotional flexibility as both a potential mediator and
moderator of the relationship between parent-to-child aggression and psychopathology. Results
indicate that parent-to-child aggression is associated with greater neural responses in posterior
brain regions linked with cognitive control of emotions and mentalizing about others’ emotional
states. Additionally, neural activation in the right inferior frontal gyrus and left angular gyrus
moderated the association between parent-to-child aggression and later externalizing symptoms.
Specifically, connections between parent-to-child aggression and later youth aggressive behavior
were exacerbated in youth with lower activation in these brain regions and attenuated in youth
with higher activation. These findings highlight the utility of the EFIC task in identifying
potential consequences of parent-to-child aggression and point to flexibility as a potential
protective factor for at-risk youth.

EMOTIONAL FLEXIBILITY 57

Introduction
Significant research indicates that exposure to family aggression during childhood and
adolescence can have a dramatic negative impact on children’s development. Lifetime
prevalence rates of child maltreatment (physical abuse, emotional abuse, sexual abuse, neglect,
and custodial interference/family abduction) for children under 18 have recently been
approximated to be around 26 percent (Finkelhor, Turner, Shattuck, & Hamby, 2013). Given that
exposure to family aggression has been consistently linked to adverse psychological (Gilbert et
al., 2009), and more recently, physical, health outcomes (Widom, Czaja, Bentley, & Johnson,
2012), family aggression is a significant public health concern.
Difficulties with emotion regulation have been commonly identified as an adverse
consequence of family aggression exposure. Youth who have been exposed to family aggression
have been shown to have poor emotional inhibition, increased emotional reactivity, and hyper-
vigilance to threatening emotional information (e.g., angry faces, Maughan & Cicchetti, 2002;
Pollak, 2008; Pollak & Tolley-Schell, 2003; Pollak, Cicchetti, Hornung, & Reed, 2000; Pollak et
al., 2005). These difficulties have also been cited as a potential explanatory mechanism for the
increased rates of psychopathology and interpersonal difficulties in adults with a history of
family aggression exposure (Davies et al., 2009; Kim & Cicchetti, 2010).
To date, the majority of studies examining the impact of family aggression on emotion
regulation have employed behavioral or psychophysiological methods. However, a small number
of studies employing neuroimaging methodologies have recently emerged and point to
differences between youth who have been exposed to aggression and those who have not in brain
regions associated with emotional reactivity, emotional salience, and top-down regulation of
emotions (McCrory, De Brito, & Viding, 2011a). Only one study, to our knowledge, has
EMOTIONAL FLEXIBILITY 58

examined neural responses as a potential mediator of the association between family aggression
and later psychopathology (Saxbe et al., 2015b). Furthermore, no studies have specifically
explored neural responses to experimentally-induced emotion regulation as the potential link
between prior aggression exposure and later symptoms.
In the present study, we extend the existing literature on family aggression to examine
associations between parent-to-child aggression and emotional flexibility – the ability to respond
to different emotional demands and flexibly employ different emotion regulation strategies as a
context demands. The flexibility task used in the present study closely parallels the changing
emotional demands that individuals experience in daily life. We use this functional neuroimaging
paradigm to examine behavioral and neural indicators of flexibility in adolescents who have
variable levels of exposure to parent-to-child aggression. We additionally explore links between
emotional flexibility and psychological symptoms (externalizing and internalizing) in late
adolescence. Finally, we examine emotional flexibility as both an explanatory mechanism
(mediator) between parent-to-child aggression and psychological symptoms and as a potential
protective factor (moderator) that might attenuate the association between parent-to-child
aggression and psychological symptoms. In this way, we seek to understand the role of
emotional flexibility in the relationship between parent-to-child aggression and psychopathology
in hopes of identifying potential targets for therapeutic interventions in these at-risk youth.
Family Aggression and Emotion Regulation
Exposure to family aggression (e.g., parent-to-child physical aggression, witnessing of
domestic violence) is known to adversely impact youth in a broad range of domains, including
problems with anger, negative affect, and peer problems (Margolin & Gordis, 2000). Difficulty
with the expression and regulation of emotions is a common underlying component of these
EMOTIONAL FLEXIBILITY 59

problems. Therefore, it is not surprising that cross-sectional (Shipman et al., 2007; Heleniak,
Jenness, Vander Stoep, McCauley, & McLaughlin, 2015), retrospective (Caldwell, Krug, Carter,
& Minzenberg, 2014; Jedd et al., 2015), and longitudinal studies (Heleniak et al., 2015; Kim &
Cicchetti, 2010) have all found associations between family aggression exposure and difficulties
with emotion regulation.
Most studies linking family aggression and emotion rely on self- or parent-report
questionnaires of emotion regulation as well as retrospective reporting of childhood family
violence exposure in adult populations, both of which increase the potential for reporter bias. Far
fewer studies have examined how exposure to family aggression impacts in vivo measures of
emotion regulation. Two exceptions include studies where children listened to simulated
interpersonal conflicts. These studies found that children with a history of maltreatment
demonstrated more emotionally dysregulated behavior during the conflict (Maughan & Cicchetti,
2002) and continued to exhibit biological markers of arousal even after the conflict had been
resolved (Pollak et al., 2005).
Several models have been proposed for the mechanism linking family aggression and
emotion regulation. Emotional security theory (Davies & Cummings, 1994) posits that youth
exposed to unstable and volatile parenting develop feelings of emotional insecurity that cause
their emotional coping resources to be easily overwhelmed in stressful situations. Alternatively,
researchers have proposed that exposure to family aggression increases the salience of negative
emotional information and leads to exaggerated attention to and delayed disengagement from
angry or threatening stimuli (da Silva Ferreira, Crippa, & de Lima Osório, 2014; Pollak, 2008;
Pollak & Tolley-Schell, 2003). Taken together, these studies highlight a robust negative impact
of family aggression on emotion regulation.
EMOTIONAL FLEXIBILITY 60

Neuroimaging findings. In addition to the psychological impact of family aggression,
significant neurological consequences have begun to be identified. Changes have been found in
both the volume and pattern of neural activation in regions associated with the processing and
regulation of emotion. Particularly, smaller grey matter volumes have been found in adults with a
history of maltreatment in the orbitofrontal cortex, inferior frontal gyrus, insula, and amygdala
(De Bellis et al., 2002; Lim, Radua, & Rubia, 2014). Decreases in volume of the corpus callosum,
a key structure for communication of information between the cerebral hemispheres, has also
been identified in youth exposed to maltreatment (McCrory et al., 2011a).
More recently, functional imaging studies have begun to directly examine neural
responses to processing and regulating emotional information. Consistent with research
suggesting increased salience of threat cues in maltreated children, children exposed to domestic
violence were found to having increased responses in the amygdala and anterior insula while
viewing angry faces, but not sad faces (McCrory et al., 2011b) and in the amygdala during pre-
attentive presentations of both happy and angry faces using the dot-probe task (McCrory et al.,
2013). Additionally, amygdala reactivity was associated with age of abuse onset and duration of
abuse (McCrory et al., 2013). History of child maltreatment has also been associated with
decreased activation of the medial prefrontal cortex, which is linked with cognitive control of
emotions, during recognition of emotion words (van Harmelen et al., 2014). In contrast, another
study found greater activation in both the prefrontal cortex and basal ganglia during an emotion
processing task in adults with a history of maltreatment (Jedd et al., 2015). Finally, Taylor and
colleagues (2006) found that adults who grew up in risky (but not necessarily violent) family
environments showed atypical coordination of neural activity between prefrontal and limbic
brain regions while viewing and labeling emotional faces.
EMOTIONAL FLEXIBILITY 61

To date, functional neuroimaging studies have primarily employed emotion processing
tasks (e.g., emotion labeling, viewing of emotional faces). Only two studies, to our knowledge,
have sought to experimentally elicit emotion regulation during a functional neuroimaging scan in
youth exposed to maltreatment. Banihashemi and colleagues (2015) submitted adult participants
with and without a history of childhood physical abuse to in-scanner stressors tasks (stroop task
and multi-source interference task). History of abuse was correlated with responses to the
stressor tasks in the subgenual anterior cingulate, hypothalamus, amygdala, and bed nucleus of
the stria terminalis. Most recently, McLaughlin and colleagues (2015) scanned adolescents with
a history of physical and/or sexual abuse while they completed a cognitive reappraisal task. In
this task, participants were taught strategies for cognitively re-interpreting the emotional
meaning of an image (e.g., “imagine that the people in the scene are actors”). In the scanner,
participants subsequently viewed negative, neutral, and positive images and were instructed to
simply look at the image, increase their emotional response to the image, or decrease their
emotional response to the image using the previously learned strategies. Results indicated that,
consistent with prior emotion processing studies, maltreated adolescents had greater neural
responses to negative versus neutral stimuli in the amygdala and insula. Additionally, maltreated
youth demonstrated greater activation in prefrontal regions, including the superior frontal gyrus,
dorsal anterior cingulate cortex, and frontal pole when reappraising negative information. This
finding is somewhat surprising as increased activation in prefrontal regions during reappraisal
has typically been linked to positive characteristics (e.g., decreased trait rumination) in non-
maltreated individuals (Ray et al., 2005a); however, this finding may also indicate that top-down
emotional control processes are more effortful or less efficient in maltreated youth.
EMOTIONAL FLEXIBILITY 62

These studies provide insight into the negative impact of family aggression on biological
correlates of emotion regulation both during adolescence and adulthood. However, the number of
studies exploring these questions has remained small and results have been variable. Furthermore,
most studies have primarily examined processing and/or labeling of emotional faces in the
scanner and few studies have sought to directly elicit emotion regulation. Thus, expanding
knowledge of the neural correlates of experimentally-induced emotion regulation in this
population is an important goal.
Emotion Regulation as a Mechanism versus Protective Factor
Prior research has highlighted compelling associations between exposure to family
aggression and emotion regulation as well as links between family aggression and later
psychological symptoms, including both internalizing (e.g., anxiety, depression) and
externalizing (e.g., aggression, attention problems) symptoms (Gilbert et al., 2009; Margolin &
Gordis, 2000). A few studies have additionally found that emotional regulation, assessed using
self- or parent-report measures, mediates the relationship between family aggression and
psychological symptoms (Heleniak et al., 2015; Kim & Cicchetti, 2010; Shields & Cicchetti,
2001). Neuroimaging data have also recently emerged in support of this hypothesis. Specifically,
one study found that neural activation in the right amygdala, insula, thalamus, and putamen
during a task where youth viewed a video of their parents and rated their parents’ emotional state
mediated the association between prior parent-to-child aggression and later aggression of
children towards their parents (Saxbe et al., 2015b).
Another possibility is that emotion regulation abilities are not an explanatory link, but
rather a risk or protective factor for youth exposed to family aggression. Recent theoretical work
exploring these relationships has postulated that some youth exposed to maltreatment may
EMOTIONAL FLEXIBILITY 63

exhibit latent vulnerabilities that put them more at-risk for adverse psychological outcomes
(McCrory & Viding, 2015). Here we postulate that emotion regulation abilities, specifically,
success in responding flexibly to changing emotional demands, may be one potential indicator of
latent vulnerability that represents either a protective or risk factor for youth exposed to family
aggression. In the present study, we explore both of these possible roles of emotion regulation –
as a mechanistic link between family aggression and psychopathology and as a potential risk or
protective factor for adverse psychological outcomes following family aggression exposure.
Emotional Flexibility
In the present study, we extend prior research on family aggression and emotion
regulation to specifically explore emotional flexibility. In recent studies in adults, good
emotional flexibility has been found to be more adaptive and important for psychological well-
being than any one specific emotion regulation strategy (e.g., cognitive reappraisal; Aldao &
Nolen-Hoeksema, 2012a; Cheng et al., 2014). Additionally, children who have been exposed to
maltreatment have been found to continue responding defensively (i.e., with increased
physiological reactivity) to a staged interpersonal conflict, even once the conflict is resolved
(Pollak et al., 2005), indicating that remaining flexible and incorporating new emotional
information may be a particularly difficult task for these youth. Here we employ an experimental
paradigm to elicit emotional flexibility while participants undergo a functional neuroimaging
scan. In this way, we hope to extend current knowledge of behavioral and biological correlates of
this important regulatory process in youth who have been exposed to family aggression.
Adolescence as a Sensitive Period
Finally, we explore associations between history of family aggression, emotional
flexibility, and psychological symptoms during adolescence, a key period for the development of
EMOTIONAL FLEXIBILITY 64

successful peer relationships (Blakemore & Mills, 2014; Larson, Richards, Moneta, Holmbeck,
& Duckett, 1996), emotion regulation strategies (Steinberg, 2005), and a period of risk for the
onset of psychopathology (Andersen & Teicher, 2008; Kessler et al., 2005). Researchers have
conceptualized adolescence as a second “sensitive period” highlighting some of the
vulnerabilities and opportunities for growth that are evident during this time (Steinberg, 2005).
Additionally, adolescents’ structural brain development shows a mismatch in developmental
timing between the regulating prefrontal cortex and reactive limbic structures (e.g., the amygdala
Casey, Jones, & Hare, 2008; Giedd et al., 1999), which has been proposed to lead to increase
dysregulated behavior in certain contexts (Casey & Caudle, 2013). For these reasons, family
aggression may have particularly deleterious effects in adolescence. In addition, family
aggression often continues to occur during adolescence and adolescents are typically still living
with parents who can provide collateral reports of aggression, therefore minimizing the reporter
biases that can occur in retrospective studies of adults who experienced childhood family
aggression.
Present Study
The present study uses a new functional neuroimaging (fMRI) paradigm, the EFIC
(Emotional Flexibility with Images and Captions) task, to examine the impact of parent-to-child
aggression in early adolescence on subsequent emotional flexibility, as well as associations
between emotional flexibility and psychological symptoms (internalizing and externalizing) in
late adolescence. We also explore emotional flexibility as both a potential mediator and
moderator of the association between parent-to-child aggression and later psychological
symptoms.
EMOTIONAL FLEXIBILITY 65

In the EFIC task, participants are shown either negative or positive images and asked to
rate how the image makes them feel. They are subsequently shown the same image again with a
caption and told that the caption is intended to “give them more information about what is
happening in the scene.” They are then asked to again rate how the scene makes them feel after
viewing the captioned version of the image. In half of the trials, the captions are emotionally
congruent with the picture (e.g., sad picture with sad caption) and in the other trials, the captions
are incongruent with the emotional valence of the image (e.g., sad picture with happy caption).
Key outcomes include changes in valence ratings between the initial images and captioned
images, differences in reaction times between the initial images and captioned images, and
differences in neural activation between the negative congruent and negative incongruent trials.
Hypothesis 1. Exposure to parent-to-child aggression will be inversely associated with
behavioral indicators of emotional flexibility, operationalized as the ability to change a negative
emotional response when given new, conflicting (positive) information. Specifically, youth who
have greater parent-to-child aggression exposure will show: 1) smaller changes in their
emotional responses during trials in which they receive incongruent emotional information; and
2) greater increases in reaction times during trials in which they receive incongruent emotional
information (Hypotheses 1a and 1b, respectively).
Hypothesis 2. Parent-to-child aggression will be associated with reduced activation
during the emotional flexibility task in brain regions typically linked with cognitive control and
mentalizing (regions that have previously been identified in other emotion regulation
neuroimaging tasks) and increased activation in regions associated with emotional reactivity.
Specifically, parent-to-child aggression will be inversely correlated with neural activation in the
middle frontal gyrus (bilateral), angular gyrus (bilateral), superior frontal gyrus (midline),
EMOTIONAL FLEXIBILITY 66

paracingulate gyrus (midline), inferior frontal gyrus (right), and middle temporal gyrus (left)
(Hypothesis 2a). We also expect parent-to-child aggression to be positively associated with
activation in the amygdala (Hypothesis 2b).
Hypothesis 3. Poorer emotional flexibility will be associated with more psychological
symptoms (both externalizing and internalizing). Specifically, greater externalizing and
internalizing symptoms will be associated with smaller changes and greater reaction time
increases during trials where participants are required to change their emotional reactions
(Hypothesis 3a). Psychological symptoms are also hypothesized to be negatively associated with
activation in brain regions associated with cognitive control and mentalizing and positively
associated with activation in brain regions associated with emotional reactivity (Hypothesis 3b).
Hypothesis 4. Given different theories regarding the impact of emotion regulation on the
association between family aggression and psychological symptoms, emotional flexibility is
tested as both a mediator and moderator of this association. First, behavioral and biological
indices of emotional flexibility are explored as a potential mechanism through which family
aggression negatively impacts later internalizing and externalizing symptoms (Hypothesis 4a).
Second, emotional flexibility is examined as a potential resilience factor that could moderate the
association between parent-to-child aggression and later psychological symptoms. Good
emotional flexibility (as indicated by both behavioral and neural measures) is predicted to reduce
the association between parent-to-child aggression and psychological symptoms. Specifically,
high engagement of cognitive control and mentalizing regions and low engagement of brain
regions associated with emotional reactivity are predicted to reduce the association between
parent-to-child aggression and psychological symptoms (Hypothesis 4b).

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Methods
Participants
Participants included 20 youth (8 female), aged 15 to 18 (mean = 16.99). All participants
were recruited from the second cohort of a longitudinal study of family and community violence
exposure (USC Family Studies Project; Margolin et al., 2010). Participants were recruited for the
longitudinal study via word of mouth and print advertising. To participate in the initial study,
youth were required to be in 6
th
through 8
th
grade, living in a two-parent household for at least 3
years at the time of recruitment, and all family members needed to be able to complete the study
protocol in English.
To participate in the MRI substudy, participants could not have any medical conditions
that could prevent MRI scanning (e.g., epilepsy), could not currently be taking psychoactive
medications, and could not have any metal in their body. Participants also needed to have
completed both prior waves of the larger longitudinal study (Waves 1 and 2) before completing
the MRI visit. Forty-three participants were invited to participate in the MRI substudy and of
these participants, 5 declined to participate, 7 youth were ineligible, and 7 could not be reached
or were unable to be scheduled for a visit. Around the time of the MRI visit, participants also
completed an additional visit with a peer where they completed questionnaires about violence
exposure and psychosocial functioning, including psychological symptoms (Wave 3). Of the 24
participants who completed the MRI visit, 3 participants did not complete this additional visit.
An additional participant was excluded because he did not have usable MRI data due to
excessive motion during the scan. The sample was diverse and reflected the urban community
from which the study sample was drawn. Of the 20 participants, 35% (7 youth) identified as
Hispanic/Latino, 15% (3 youth) identified as Caucasian, 15% (3 youth) as African-American,
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5% (1 youth) as Asian-American, and 30% (6 youth) as multi-racial. Participants in this
subcohort did not differ from the larger longitudinal cohort in terms of gender, race, ethnicity, or
age (all ps > .1). All participants were right-handed. During the MRI visit, participants also
completed several additional tasks focused on interpersonal relationships (family and peer) and
basic emotion processing. The timing and age ranges for all waves of data collection are shown
in Figure 1.
Procedures
Laboratory procedures during the MRI visit lasted approximately four hours. Participants
first completed one hour of consent procedures, orientation to the experimental procedures,
orientation to the scanner, and task training. In-scanner sessions were two hours long with a 10-
minute break at approximately the middle of the scan. All subjects completed the EFIC task,
three additional functional neuroimaging tasks, several structural scans, and a resting state scan.
Last, participants completed post-scan questionnaires and were debriefed.
EFIC task.
Stimuli. The task included five conditions were as follows: negative congruent (NN),
negative incongruent (NP), positive congruent (PP), positive incongruent (PN), and rest. In each
trial, participants were shown an image surrounded by a black border. Participants then rated
“how the scene made them feel” on a four-point scale from “very negative” to “very positive”
using four buttons on a scanner-compatible button box. No neutral mid-point was included in the
scale to force participants to appraise their emotional reaction as either negative or positive. They
were then shown the same image again with a caption. In congruent trials, the caption matched
the emotional valence of the image. In the incongruent trails, the caption was discordant with the
emotional valence of the image. Last, participants were asked to rate the image a second time on
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the same four-point scale. Only the negative congruent (NN) and negative incongruent (NP)
trials are included in the analyses below. The sequence of stimuli within these two types of trials
is shown in Figure 2. It is important to note that participants are never given any information
about emotional flexibility or changes in emotion. Rather, they are simply told that they should
rate their “gut reaction” to each image or image/caption pair that they are shown. Full validation
data and task details for the EFIC task are presented in (Del Piero, Saxbe, Kaplan, & Margolin,
in preparation).
Task procedure. Prior to scanning, participants were trained on the emotional flexibility
task. They completed four practice trials on neutral pictures with neutral captions taken from the
IAPS (International Affective Picture System; Lang et al., 2008). If participants had any
difficulty completing the task or did not appear to understand the directions, they were allowed
to repeat the practice trial.
The task was presented in the scanner in three runs, each seven minutes and two seconds
in length. Each run contained five presentations of stimuli from each of the four conditions (i.e.,
20 stimuli within each run, 60 total across runs) and five rest trials (15 total across runs). Order
of the runs was counterbalanced across participants and by gender. Presentation of the stimuli
within runs was ordered using a genetic algorithm (Wager & Nichols, 2003) that optimizes the
ability to distinguish hemodynamic responses associated with the different conditions within the
task.
fMRI data collection. Whole brain images were acquired using a Siemens 3 Tesla
MAGNETON TIM Trio scanner with 12-channel matrix head coil in the USC Dornsife
Cognitive Neuroscience Imaging Center. Functional MRI data were collected using a T2*
weighted EPI sequence (TR = 2 sec, TE = 25 ms, flip angle = 90°) with voxel resolution of 3mm
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× 3mm × 2.5mm. Thirty-two continuous transverse slices were collected covering the whole
brain and brainstem. Structural MRI images were acquired using an MPRAGE sequence (TI =
900 ms, TR = 1950 ms, TE = 2.26 ms, flip angle = 7°) with isotropic 1 mm voxel resolution
Measures
EFIC task.
Rating and reaction time measures. Emotional response ratings were collected using the
in-scanner button box responses. The four possible responses included -2 (very negative), -1 (a
little negative), +1 (a little positive), and +2 (very positive). For each participant, responses
across all trials of a condition were averaged together. Here, initial uncaptioned image
presentations are described with the condition name (NN or NP) and the subscript “Img” (e.g.,
NP
Img
). The captioned images are denoted with condition name and subscript “Cap” (e.g., NP
Cap
).
The primary measure of interest is the change in ratings from uncaptioned to captioned
images for NP trials. For this change measure, denoted with the subscript “Change,” average
initial image ratings were subtracted from average captioned image ratings for each participant.
Therefore, if a participant had an average NP
Img
score of -1.4, and an average NP
Cap
score of
+1.3, their NP
Change
score would be 2.7.
Reaction time (RT) data were calculated as the time (in seconds) between the onset of the
ratings scale after each image and the time when participants provided a response via the button
box for each stimulus (“Img” and “Cap” stimuli). Average RT across all trials was calculated for
each condition and stimulus type (NN
Img
, NN
Cap
, NP
Img
, and NP
Cap
). The primary RT measure of
interest was the difference in average RTs between the “Img” stimuli and “Cap” stimuli for the
NP condition (NP
Change
RT).
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Neuroimaging preprocessing. Imaging data preprocessing was done with FSL software
(FMRIB, Oxford, UK). Standard preprocessing including slice timing correction, motionTab
correction, brain extraction, spatial smoothing (using a 5 mm kernel), high-pass filtering, and
pre-whitening were completed prior to contrast modeling. Registration to the high-resolution
structural and standard space images was completed using FLIRT. In modeling the conditions,
each 14-second trial was coded as a single event, including the presentation of both images and
both rating periods.
Whole brain analyses. Whole brain regression analyses with parent-to-child aggression,
internalizing symptoms, and externalizing symptoms were conducted using FSL’s Feat. This
analysis tests for the presence of contiguous voxels where the difference in activation between
the two conditions of interest (NN and NP) is significantly correlated with the regressor. A
standard cluster-wise threshold of Z = 2.3, p = .05 was applied to all analyses.
Region of interest analyses. Additional correlational analyses were conducted by
extracting percent signal change using FSL’s featquery from anatomically-defined regions of
interest (ROIs) for the NP > NN contrast. featquery generates an average measure across all
voxels within the defined area of the difference in activation between the NN and NP conditions
in units of percent signal change. The anatomically-defined ROIs selected were those that have
been implicated in a large meta-analysis of cognitive reappraisal (the most similar emotion
regulation paradigm that has been extensively studied with neuroimaging methods Buhle et al.,
2014). The 10 ROIs examined were: the middle frontal gyrus (bilateral), angular gyrus (bilateral),
superior frontal gyrus (midline), paracingulate gyrus (midline), inferior frontal gyrus (right),
middle temporal gyrus (left), and amygdala (bilateral).
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Parent-to-child aggression. Parent-to-child aggression was measured using youth and
parent reports of parent-to-child aggression on a modified version of the Conflict Tactics Scale
(Straus, 1979). The measure used in the present study included 17 items that included acts of
physical and emotional aggression. Mother, father, and youth reported on how frequently each
item had occurred during the past year on a scale ranging from 0 (never) to 3 (6+ times). The
maximum score reported for each item across mother, father, and youth reports was used as the
score for each item. This approach helps to correct for the tendency of individuals to underreport
the prevalence of family violence (Howard, Cross, Li, & Huang, 1999). Each family member
reported on both the mother and father’s behavior. This measure was completed at both the
Wave 1 and Wave 2 of the longitudinal study. Total family aggression scores were calculated by
averaging the 17 item maximum scores (described above) within each wave and reporter,
yielding total scores ranging from 0 to 3 and then averaging these average scores across the two
waves of data collection and across the two parents (i.e., combining 4 scores). Internal
consistency of the measure was .87 and .91 for mother and father behavior, respectively, at the
first wave and .83 and .86 at the second wave.
Psychological symptoms. Psychological symptoms were measured at Wave 3 using the
Youth Self-Report (YSR; Achenbach, 1991), which is a well-validated measure of internalizing
(e.g., depression, anxiety) and externalizing (e.g., aggression, behavior problems) symptoms
during the past 6 months. Adolescents provided ratings on symptoms using a 3-category scale
from 0 (not true) to 2 (very true or often true). T-Scores (Mean = 50, SD = 10) based on age and
gender-specific norms were used in the present analyses. The two summary scales for this
measure, internalizing and externalizing, have been found to have good internal consistency in
the validation sample (Cronbach’s alphas = .90 and .90, respectively; Achenbach & Rescorla,
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2001). Notably, few participants in the sample reported clinically-significant symptoms of either
type of psychological symptoms. Specifically, only 1 participant reported internalizing
symptoms above the “borderline clinical” threshold (T = 60) and only 3 participants reported
externalizing symptoms above this threshold.
Behavioral and moderation analyses. All behavioral and ROI analyses were completed
using SPSS software. Mediation and moderation analyses were conducted using the PROCESS
SPSS macro (Hayes, 2013). To test mediation, PROCESS employs a bias-corrected
bootstrapping method to estimate confidence intervals of direct and indirect effects between the
three variables of interest. Moderation models test for significant interactions between parent-to-
child aggression and emotional flexibility when predicting later psychological symptoms. Both
behavioral indicators of emotional flexibility on the task and percent signal change extracted
from the anatomically-defined ROIs were tested as mediators and moderators.
Results
Means and standard deviations for all behavioral variables are shown in Table 1.
Although no gender differences were hypothesized, a few gender differences emerged.
Specifically, females had greater NP
Change
scores than males, t(19) = -2.60, p = .018 and greater
externalizing symptoms (in terms of gender- and age-corrected T-scores) than males, t(19) =
2.91, p =. 009.
Parent-to-Child Aggression and Flexibility
As shown in Table 2, contrary to Hypotheses 1a and 1b, parent-to-child aggression was
not significantly associated with NP
Change
scores or changes in RT from initial images to
captioned images in NP trials.
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To test Hypotheses 2a and 2b, whole brain analyses were conducted and percent signal
change was extracted from the contrast NP > NN from the 10 previously-described ROIs. Whole
brain analyses revealed positive associations between parent-to-child aggression and activation
in the left angular gyrus, precuneus, and left lateral occipital cortex. These findings are shown in
Figure 3 and full peak coordinate information is shown in Table 3. Similarly, ROI analyses
revealed significant positive associations between parent-to-child aggression and percent signal
change in several posterior regions including the left middle temporal gyrus (r(18) = .46, p
= .043), left angular gyrus (r(18) = .52, p = .018), and right angular gyrus (r(18) = .50, p = .025).
Contrary to Hypothesis 2a, greater parent-to-child aggression was actually linked with greater
activation in these regions. These associations are shown in Figure 4. No associations between
parent-to-child aggression and activation in any of the other ROIs were identified.
Emotional Flexibility and Psychological Symptoms
Contrary to Hypothesis 3a, no measures of task performance were found to be
significantly associated with either internalizing or externalizing symptoms. Additionally,
contrary to Hypothesis 3b, no significant associations were found between either externalizing or
internalizing symptoms in either whole brain analyses or percent signal change in the
anatomically-defined ROIs. A marginally significant negative correlation was found between
internalizing symptoms and percent signal change in the right amygdala (r(18) = -.43, p = .059).
Mediation by Emotional Flexibility
Hypothesis 4a was tested using the three neural regions (left middle temporal gyrus, left
angular gyrus, right angular gyrus) that were found to have bivariate associations with parent-to-
child aggression. Percent signal change in these three regions was not found to mediate the
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association between parent-to-child aggression and either internalizing or externalizing
symptoms.
Moderation by Emotional Flexibility
No significant moderation effects were found for any of the behavioral indicators of
emotional flexibility. Interaction models testing each of the anatomically-defined ROIs as
moderators of the association between parent-to-child aggression and both externalizing and
internalizing symptoms were conducted. Consistent with Hypothesis 4b, significant moderation
effects on the association between parent-to-child aggression and externalizing symptoms were
found for the right inferior frontal gyrus and left angular gyrus. These moderation analyses are
depicted in Table 4 and moderation effects are visualized in Figure 5. Analyses indicated that at
low levels of activation in both of these regions, there was a positive association between parent-
to-child aggression and later externalizing symptoms; however, this association was reduced for
youth who had mean or high levels of neural activation in these regions. No other moderation
effects were identified for either externalizing or internalizing symptoms.
Discussion
The present study is the first to use an experimental measure of emotional flexibility to
examine behavioral and biological consequences of parent-to-child aggression. We additionally
test emotional flexibility as an important third variable (as both a mediator and moderator)
linking parent-to-child aggression and later psychological symptoms. Results indicated that
parent-to-child aggression was not associated with task performance but was associated with
neural responses to the task in several posterior brain regions typically linked with cognitive
regulation of emotion (Buhle et al., 2014), semantic and emotional associations (Kohn et al.,
2014; Seghier, Fagan, & Price, 2010), and mentalizing about others’ emotional states (bilateral
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angular gyrus, left middle temporal gyrus, precuneus; Araujo et al., 2013). Surprisingly, parent-
to-child aggression predicted greater neural activation in these regions, a pattern that is typically
associated with more adaptive engagement of emotion regulation skills; however, some studies
(McLaughlin et al., 2015) have similarly found greater activation in regions associated with
emotion regulation in maltreated versus non-maltreated youth, which was considered to be
indicator of neural inefficiency in these processes. This finding may also indicate a more
nuanced relationship between exposure to environmental stressors and neural correlates of
emotion regulation such that the type of neural response that is “adaptive” (e.g., is linked to less
psychopathology) differs between maltreated and non-maltreated youth.
Importantly, the above findings were qualified by significant moderation effects that were
found for one of these posterior brain regions (left angular gyrus) as well as a prefrontal region
(right inferior frontal gyrus) commonly implicated in inhibitory control tasks (e.g., go-no go;
Aron, Robbins, & Poldrack, 2004; Cohen et al., 2016). Both of these regions were found to
moderate the association between parent-to-child aggression in early adolescence and
psychological symptoms in late adolescence such that youth with high engagement of these
regions had reduced associations between aggression and psychopathology, but youth with lower
engagement of these regions were more at-risk for experiencing psychological symptoms after
exposure to family aggression.
These findings point to a potential biological indicator of resilience that may make some
youth less susceptive to the adverse consequences of family aggression than others. This fits well
with McCrory and Vidig’s notion (2015) of latent vulnerability, that some youth are predisposed
to develop a cascade of adverse consequences following violence exposure whereas others are
able to overcome early adversity. Potential bases of such individual differences have yet to be
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identified; however, genetic factors, such as genotype of the serotonin transporter gene (5-HTT),
brain-derived neurotrophic factor (BDNF), and monoamine oxidase-A (MAOA) have been
implicated in reactivity to stress (for a review, see McCrory et al., 2011a). The interaction of
these genetic factors with environmental influences (e.g., school engagement, supportive other
adults, community context) likely contributes to an individual’s ability to maintain resiliency
following early adversity. This finding also emphasizes something that has often been
overlooked in the study of family aggression, namely, that not all exposed children experience
adverse consequences (Heller, Larrieu, D 'Imperio, & Boris, 1999). Continuing to gather
information about these potential risk and protective factors is vital because it may help identify
youth who are most in need of early interventions as well as new ways to enhance resiliency in
all youth.
One notable difference between the present study and the majority of research examining
the impact of child maltreatment is that youth were part of a community sample and families
were not identified through the Department of Child and Family Services (i.e., families who had
previously been reported for child abuse). Thus, the present sample includes children with a
range of exposure to family aggression. The non-clinical nature of this sample may have
impacted study findings in several ways. For example, very few youth had clinically-significant
externalizing and internalizing symptoms and there were no bivariate relationships between
parent-to-child aggression and psychological symptoms, an association that has been well-
supported in prior child maltreatment research. However, a trend in the expected direction that
was not significant given the small sample size was observed. We also believe that use of a
community sample adds meaningfully to the child maltreatment literature. Specifically, the
aggression measure used in the present study included a wide spectrum of psychologically and
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physically aggressive behaviors. These types of negative, but not necessarily abusive, behaviors
are much more prevalent in families than overt physical abuse. Thus, understanding the potential
impact of more subtle and widespread aggression may yield insight into nuanced processes
occurring in a larger subset of families.
This study has several limitations that should be noted. First, the selection of participants
from a longitudinal study and inclusion of four waves of data significantly limited the number of
participants that could be included in these analyses. Additionally, the MRI visit and wave 3 visit
had variable relative timing across participants. In future studies, there ideally would be a
consistent timing gap between the emotional flexibility and psychological symptoms measures.
However, it should be noted, that there were no associations between the length of gap between
these two data collection points and any of the emotional flexibility or psychopathology
measures. Finally, the earliest time point of data collection in the present study was when youth
were in early adolescence. The majority on research on child maltreatment has examined
children who are earlier in development (particularly, infancy through preschool). Structural
brain studies indicate that the greatest vulnerability and plasticity is early in life (e.g., Knudsen,
2004; Rice & Barone Jr, 2000), thus making aggression occurring during this period potentially
the most damaging (Schore, 2001). However, adolescence is now being recognized as an
additional period of risk and vulnerability (Steinberg, 2005). Thus, examining exposure to
aggression during this second key period has the potential to identify novel risk factors. Overall,
expanding the period of data collection to cover as many points across development as possible
and examining correlates of both the duration and chronicity of aggression is ultimately needed
to fully understand the dynamic interplay between exposure to family aggression, emotional
flexibility, and psychological symptoms.
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The present study also points to several new directions for future research. Here we find
an important role of emotional flexibility in modifying the association between family aggression
and symptoms of psychopathology. Emotional flexibility is a core idea in many
psychotherapeutic approaches, particularly, “third wave” treatments (e.g.., acceptance and
commitment therapy, dialectical behavior therapy). Determining whether flexibility (as measured
by the task indices) can be enhanced through these types of therapeutic interventions and
whether increased flexibility, in turn, improves resiliency, are important questions to explore.
In the present study, we did not examine different subtypes of parent-to-child aggression,
but research indicates that subtle distinctions may impact the consequences of maltreatment.
McLaughlin and colleagues (2014) posited that there might be a differential impact of parental
behaviors that lead to deprivation (e.g., neglect, lack of resources) versus threat (e.g., direct
aggression). For example, neglect is primarily associated with changes in neural circuitry linked
with cognitive control and attention modulation whereas threat is primarily linked to changes in
neural regions involved in the processing and automatic regulation of emotional information.
This framework highlights potential differential impacts of maltreatment subtypes and
emphasizes the need for a more nuanced exploration of these behaviors.
Additionally, our findings identified associations between parent-to-child aggression and
neural activation during the EFIC task in posterior brain regions that are associated with both
cognitive control and mentalizing about others’ emotional states. Research with young children
indicates that history of maltreatment is associated with poorer emotional understanding and
theory of mind (Cicchetti, Rogosch, Maughan, Toth, & Bruce, 2003; Pears & Fisher, 2005).
Similarly, the tendency to misattribute emotional states (e.g., hyper-vigilance for angry stimuli)
that has been found in maltreated youth (Pollak et al., 2000) could disrupt the ability to correctly
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identify others’ emotions. Exploring whether difficulties with mentalizing uniquely contribute to
interpersonal difficulties in these youth, above and beyond difficulties with emotion regulation,
could generate additional targets for clinical intervention.
Finally, research should begin to quantify some of the interacting factors potentially
contributing to latent vulnerability (or resilience) in youth exposed to aggression. Contributions
from genetic factors, inflammatory responses, pubertal development, and psychosocial contexts,
as well as interactions amongst these variables, are all potential risk or resilience factors that
warrant additional consideration.
Conclusion
This study provides insight into the impact of parent-to-child aggression on the ability to
flexibly respond to different emotional demands using an experimental paradigm, the EFIC task,
with both behavioral and neural measures. Behavioral task measures were not associated with
parent-to-child aggression or later psychological symptoms. In contrast, neural responses to the
task were positively associated with parent-to-child aggression in posterior brain regions
typically associated with cognitive regulation of emotion and mentalizing processes.
Additionally, task responses in the left angular gyrus and right inferior frontal gyrus moderated
the association between parent-to-child aggression and later psychological symptoms such that
greater activation in these regions attenuated the association between parent-to-child aggression
and later psychopathology. These findings point to neural indicators of emotional flexibility as
potential risk or protective factors for youth exposed to aggression. Furthermore, as emotional
flexibility is the target of numerous psychotherapeutic interventions, it is a potential avenue for
directly intervening to promote resilience in at-risk youth.
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Table 1

Means and Standard Deviations of All Behavioral Variables
All Participants (N = 20)

Males (n = 12)

Females (n = 8)
M (SD)

M (SD)

M (SD)
Wave 1 Age (years) 12.92 (.71)

13.05 (.67)

12.72 (.75)
Wave 2 Age (years) 15.39 (.87)

15.56 (.96)

15.13 (.70)
Wave 3 Age (years) 17.04 (1.02)

17.09 (1.02)

16.97 (1.09)
MRI Visit Age (years) 16.99 (.80)

17.22 (.81)

16.66 (.70)
MRI Visit to Wave 3 Visit Lag (years) .05 (.55)

-.13 (.47)

.32 (.58)
Parent-to-Child Aggression .55 (.41)

.60 (.50)

.49 (.21)
NN
Change
-.48 (.26)

-.52 (.29)

-.41 (.22)
NP
Change
* 2.68 (.66)

2.38 (.61)

3.14 (.44)
NN
Change
RT (seconds) -.19 (.21)

-.22 (.25)
-
-.15 (.16)
NP
Change
RT (seconds) .12 (.26)

.13 (.28)

.11 (.24)
YSR Externalizing (T-Score)* 49.80 (8.25)

46.08 (5.70)

55.38 (8.65)
YSR Internalizing (T-Score) 51.05 (9.61)

48.08 (11.40)

55.50 (2.98)
*Significant gender differences (p < .05)

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Table 2

Correlation Matrix of all Behavioral Variables
* p < .05; ** p < .001
1 2 3 4 5 6 7 8 9 10 11 12
1. Wave 1 Age

- .88
**
.88
**
.83
**
.43 -.16 .19 -.29 .07 -.24 -.13 -.02
2. Wave 2 Age

- .84
**
.93
**
.18 -.12 .27 -.33 .11 -.22 -.05 -.17
3. Wave 3 Age

- .85
**
.63
**
-.29 .42 -.16 .15 -.22 -.10 -.04
4. MRI Visit Age

- .13 -.05 .20 -.35 .15 -.26 -.17 -.13
5. MRI visit to Wave 3 Lag

- -.47
*
.50
*
.22 .08 -.02 .06 .12
6. Parent-to-Child Aggression

- -.33 .15 -.10 -.18 .28 -.01
7. NN
Change
Rating

- -.21 .11 .03 -.05 .38
8. NP
Change
Rating

- -.16 .17 .23 .10
9. NN
Change
RT

- -.02 -.01 -.06
10. NP
Change
RT

- .08 -.39
11. YSR Externalizing

- .44
12. YSR Internalizing

-
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Table 3

Peak Voxel and Maximum Z-Scores for Whole Brain Correlations with Parent-to-Child
Aggression

MNI Coordinates
Region Cluster Size Z-score Side x y z
NP > NN
Lateral Occipital Cortex 1651 2.99 Left -50 -66 24
Lateral Occipital Cortex -- 2.99 Left -32 -66 22
Precuneus -- 2.97 Left -10 -72 34
Angular Gyrus -- 2.96 Left -36 -52 28
Lateral Occipital Cortex -- 2.96 Left -54 -64 32
Precuneus -- 2.91 Left -10 -66 26
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Table 4

Results of ROI Moderation Analyses

* p < .05; ** p < .01
Wave 3 Externalizing Symptoms

R
2
/ΔR
2
F ß
Model 1 .34 4.30
*
-
Parent-to-Child Aggression 7.11

Right Inferior Frontal Gyrus (% signal change) -3.92
Model 2 .27 4.50
*
-
Aggression x RIFG -85.65
*

Model 1 .35 4.79
*
-
Parent-to-Child Aggression 15.36
*

Left Angular Gyrus (% signal change) -10.81
Model 2 .21 13.59
**
-
Aggression x L Ang. Gyr. -87.76
**

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Figure 1. Timeline of data collection and age ranges for all waves of the longitudinal study.

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Figure 2. Timeline of trials within the negative congruent and negative incongruent task
conditions.
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Figure 3. Regions showing significant positive correlations between the NP > NN contrast and history of parent-to-child aggression.
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Figure 4. Scatterplots of percent signal change in the three ROIs with significant associations with parent-to-child aggression.
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Figure 5. Moderation effects of neural activation in the right inferior frontal gyrus and left angular gyrus on the association between
parent-to-child aggression and later externalizing symptoms.
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General Conclusion
Taken together, the results presented in these two papers make several novel
contributions to the literature on emotional flexibility and family aggression. In contrast to the
study of discrete emotion regulation strategies, the study of emotional flexibility remains in its
infancy. This study is one of the first to experimentally model emotional flexibility in a
laboratory setting and the first to link emotional flexibility measures to family aggression
exposure and later psychological symptoms. Additionally, we captured emotional flexibility
during adolescence, a time when youth are undergoing substantial emotional changes (Arnett,
1999) and are in a period of risk for the onset of numerous emotion-related disorders (Kessler et
al., 2005).
In Paper 1, building upon the small body of prior emotional flexibility research, we found
several behavioral indices of flexibility including greater changes in rating scores and smaller
increases in reactions times. These findings supported the notion that participants experienced
interference from emotional information in the initial image on trials with emotionally
incongruent information. Additionally, consistent with research indicating that individuals with
better self-reported emotional flexibility have greater divergence of emotional reactions (i.e., less
neutral ratings; Waugh et al., 2011), more negative ratings of initial negative stimuli were
associated with better self-reported emotion regulation skills.
As no previous studies have employed a neuroimaging emotional flexibility paradigm,
we based our neural hypotheses on a well-studied specific emotion regulation strategy –
cognitive reappraisal. Results indicated that neural activation patterns during negative
incongruent trials were generally similar to reappraisal (Buhle et al., 2014; Ochsner & Gross,
2008) whereas activation patterns during positive incongruent trials were more similar to
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automatic, unconscious emotion regulation processes (Goldin et al., 2008; Phillips et al., 2003).
Additionally, consistent with prior research (Banks et al., 2007), there was increased inverse
connectivity between the amygdala and several prefrontal regions during the negative
incongruent trials relative to negative congruent trials. Finally, activation in the right amygdala
during positive incongruent versus congruent trials was positively associated with self-reported
emotion regulation difficulties. These findings point to the ability of this task to elicit emotional
flexibility across all participants as well as interindividual differences that were associated with
self-reported emotion regulation skills in daily life.
Building upon these individual differences, we examined how parent-to-child aggression
exposure might impact experimental measures of emotional flexibility in Paper 2. Given that no
prior studies of parent-to-child aggression had examined this type of paradigm, we focused
analyses on the negative congruent and incongruent conditions of the task, as these conditions
were most similar to other well-studied emotion regulation paradigms (e.g., cognitive
reappraisal). Surprisingly, our results found that greater parent-to-child aggression was not
associated with any of the behavioral indices of emotional flexibility.
We did find significant associations between parent-to-child aggression and neural
responses to the task. Specifically, greater parent-to-child aggression exposure was associated
with greater neural activation in posterior brain regions associated with cognitive control of
emotions and mentalizing about others’ emotional states (Araujo et al., 2013; Goldin et al., 2008).
These findings were somewhat surprising because greater activation in cognitive control regions
during cognitive reappraisal has been linked to better psychological outcomes (Ray et al., 2005).
However, our findings were consistent with McLaughlin and colleagues’ results (2015)
indicating that adolescents with a history of maltreatment had greater neural activation in several
EMOTIONAL FLEXIBILITY 92

prefrontal regions during reappraisal trials than youth without a maltreatment history. They
interpreted this finding as evidence that these processes are more effortful and less efficient when
youth have suffered maltreatment. The differences may also be linked to developmental changes
as findings linking reduced activation and negative outcomes have been in adults whereas both
the present study and the McLaughlin study employed adolescent populations.
Finally, we explored associations between parent-to-child aggression, emotional
flexibility, and psychopathology symptoms in late adolescence. Numerous prior studies have
supported association between family aggression and later psychological symptoms. We did not
find such an association in the present study; however, a non-significant trend in the expected
direction was evident. We additionally propose that this difference may be due, in part, to the
fact that the participants were recruited from non-clinical community sample. Thus, we may
have had an insufficient range of psychological symptoms within our cohort to identify this
relationship. Our findings also supported a moderating effect of emotional flexibility on the
association between parent-to-child aggression and psychological symptoms. Specifically, for
youth who had relatively greater activation in the right inferior frontal gyrus and left angular
gyrus during negative incongruent trials, the association between aggression exposure and
psychological symptoms was attenuated. In contrast, this association was exacerbated in the
context of reduced activation in these regions. This finding highlights a unique potential role of
emotional flexibility – as a potential risk or protective factor for youth exposed to family
aggression, similar to the type of latent vulnerability factors that have recently proposed
(McCrory & Viding, 2015). Further research is needed to understand why some youth might be
more predisposed to have better or worse emotional flexibility following aggression exposure,
such as genetic factors, environmental factors, and interactions between these factors.
EMOTIONAL FLEXIBILITY 93

Other important extensions of this work include examination of associations between
emotional flexibility and adaptive outcomes beyond psychopathology symptoms, such as
romantic and peer relationship satisfaction or academic and vocational success. Additionally,
there are numerous evidence-based interventions that seek to directly enhance emotional
flexibility processes (e.g., acceptance and commitment therapy, mindfulness-based stress
reduction; Hayes et al., 2006; Lutz et al., 2008). Therefore, if good emotional flexibility is indeed
a key protective factor for youth who have been exposed to aggression, testing whether it is
effective to therapeutically target flexibility in these youth could greatly mitigate future adverse
consequences. Alternatively, the EFIC task could be used to track the efficacy of these
interventions. Finally, testing emotional flexibility across different age ranges and linking
flexibility to the age of onset and chronicity of family aggression exposure, would help to
identify the optimal timing for intervening to increase flexibility in youth exposed to aggression.
Importantly, it is also possible that there are contexts in which increasing flexibility is not
adaptive for youth. For example, hyper-vigilance to anger and threat in maltreated youth appears
to develop as a protective reaction to an environment that is actually threatening. Similarly, it
may not be adaptive, or even safe, for youth who remain in aggressive homes to become more
flexible and less attuned to negative information.
In sum, our findings point to emotional flexibility as an important and understudied
construct in research on both emotion regulation and family aggression. We found support for
use of this novel paradigm as a way to more accurately capture the process of emotional
responding, updating, and re-responding that happens continuously in daily life, particularly in
family interactions. We also found evidence of emotional flexibility as a previously unidentified
risk or protective factor for youth who have been exposed to family aggression.
EMOTIONAL FLEXIBILITY 94

Taken together, these results highlight the importance of examining emotional flexibility
as a unique process, one that appears to play a particularly important role within interpersonal
(parent-to-child, marital, peer) relationships. For this reason, developing a better understanding
of how this process unfolds in real world settings, how it impacts important functional outcomes
(e.g., job success), and whether it is amenable to direct intervention remain important goals for
future research.

EMOTIONAL FLEXIBILITY 95

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Asset Metadata

Creator Del Piero, Larissa Borofsky (author)

Core Title Biological and behavioral correlates of emotional flexibility and associations with exposure to family aggression

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Psychology

Publication Date 07/27/2016

Defense Date 06/01/2016

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

Tag emotion regulation,emotional flexibility,family aggression,fMRI,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Margolin, Gayla (committee chair), Saxbe, Darby (committee chair), Immordino-Yang, Mary Helen (committee member), Levitt, Pat (committee member), Manis, Frank (committee member)

Creator Email larissa.b.delpiero@gmail.com,ldelpier@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-281729

Unique identifier UC11279549

Identifier etd-DelPieroLa-4642.pdf (filename),usctheses-c40-281729 (legacy record id)

Legacy Identifier etd-DelPieroLa-4642.pdf

Dmrecord 281729

Document Type Dissertation

Format application/pdf (imt)

Rights Del Piero, Larissa Borofsky

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

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