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Intrinsic functional connectivity of the default mode network predicts the purposefulness of youths’ intended adult lives

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Intrinsic functional connectivity of the default mode network predicts the purposefulness of youths’ intended adult lives

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Content DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES

Intrinsic functional connectivity of the Default Mode Network predicts the purposefulness
of youths’ intended adult lives

By

Rodrigo A. Riveros Miranda

Department of Psychology

Master of Arts (PSYCHOLOGY)

University of Southern California

August 2017

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES ii
Table of Contents
Abstract …………………………………………………………………………………….. iii
Introduction ………………………………………………………………………………... 1
Purposeful Goals Are Highly Abstract Goals ......................................................... 1
The Default Mode Network and Imagining Our Future Intended Lives ………. 4
Methods …………………………………………………………………………………….. 6
Participants ………………………………………………………………………… 6
Interview ……………………………………………………………………………. 7
Coding of high and low-level goals ………………………………………………... 7
Resting State fMRI Acquisition and Preprocessing ……………………………... 8
Selection of the DMN Component ………………………………………………… 9
Correlation between High-Level Goals and Intrinsic DMN Connectivity ……... 10
Cognitive Measures ………………………………………………………………... 11
Results ………………………………………………………………………………………. 11
Discussion …………………………………………………………………………………... 12
Concluding remarks ……………………………………………………………….. 15
References …………………………………………………………………………………... 17
Table 1 ……………………………………………………………………………………… 24
Figure 1 ……………………………………………………………………………………... 25
Figure 2 ……………………………………………………………………………………... 25
Figure 3 ……………………………………………………………………………………... 26

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES iii
Abstract
Adolescents imagine their future adult life and set goals with varied levels of abstraction:
low-level goals pertain to acquiring skills, goods and positions; high-level goals pertain to core
values and social responsibilities. High-level goals are more purposeful. The brain’s Default
Mode Network (DMN) is involved in processing purpose: projecting the self in time, as well as
in reflecting on high-level goals and moral values.
Thirty-five adolescents (21 females, mean age=17.5 years/SD=0.84) were interviewed
about their future goals. Their reported goals were coded for level of abstraction, and high-level
goals were separately tallied. In addition, 7-minute resting state fMRI scans were collected. The
DMN was identified at the group-level using Independent Component Analysis and back-
reconstructed for each participant. Individuals’ network maps were entered into a group-level
regression analysis with the count of high-level goals entered as a regressor. Results were
examined within the DMN, corrected for multiple comparisons, and controlled for participants’
intellectual quotient scores. The frequency of adolescents’ high-level goals predicted increased
functional connectivity in the frontal pole (p=0.001, cluster size 29 voxels), and the orbital
frontal gyrus (p=0.001, cluster size 62 voxels). High-level goals predicted decreased intrinsic
functional connectivity in the anterior cingulate cortex (p=0.001, cluster size 46 voxels).
This study suggests that connectivity within the DMN contribute to imagining a
purposeful future life during adolescence. With further research, it opens the possibility that
families, therapists and educators might be able to support the positive development of purpose,
a central driving force for personal growth, moral identity and social participation, by guiding
young people in the constructive reflection of adult life.
Keywords: Default Mode Network- Functional Connectivity- Purpose
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 1
Introduction
Purpose has been defined as a stable and general intention to make efforts for something
that is meaningful to the self and consequential for the lives of others (Damon, 2008). Imagining
a purpose for long-term future is a key developmental element of the adolescent’s life, when
future goals are developed into adult plans (Crone & Dahl, 2012). Purposeful future goals are
important for contributing to the construction of our identity (D’Argembeau, Lardi, & Van der
Linden, 2012), and our morality (Damon, Menon, & Bronk, 2003). The starting point for
imagining future goals, and hence, developing a sense of purpose in life, involves setting goals
and planning goal-relevant behaviors (Patton, Renn, Guido, & Quaye, 2016; Szpunar, Spreng, &
Schacter, 2014).

Purposeful Goals Are Highly Abstract Goals
Adolescents set goals that vary in their level of abstraction, asserting goals with deep
meaning and morally loaded, focused in core values and service to others, as well as concrete
goals, oriented to acquiring goods and achieving narrowly defined tasks (Damon et al., 2003).
Imagining purpose in life requires constructing future goals psychologically distant from here
and now (Liberman & Trope, 2008). Construal Level Theory (CLT) offers a framework to
understand psychological distance of imagined future goals by describing imagination in terms
of the level of abstraction (versus concreteness) represented, and whether what is imagined
points to central and stable features of a representation or to peripheral features (Trope &
Liberman, 2010). A higher level of abstraction reflects a greater psychological distance,
projecting the far-distant self in several dimensions, such as time, space, social distance (self-
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 2
centered or others-oriented) and hypotheticality (Liberman & Trope, 2014; Liberman, Trope,
McCrea, & Sherman, 2007).
Drawing on CLT, high-level goals refer to abstract dispositions, superordinate values,
moral standards for behavior, and personality traits (Nussbaum, Trope, & Liberman, 2003). In
terms of content, future goals construed with a high level of abstraction involve obtaining central
experiences, feelings, and core values, as well as achieving personal growth and transforming the
lives of others (Damon et al., 2003). People who construe future events with a high level of
abstraction tend to perceive the importance and broader meaning of future events, enhancing the
motivation value to achieve these goals (Vasquez & Buehler, 2007). High-level goals motivate
prosocial actions and behaving in moral ways to others (Liberman & Trope, 2014).
In contrast, low-level goals refer to situation-based representations that focus on the
concrete features of how future goals can be achieved (Liberman & Trope, 2014). They refer to
future goals such as acquiring goods, gaining popularity and status, as well as narrowly defined
tasks (Liberman et al., 2007). Although they also involve psychological qualities, low-level goals
refer to obtaining personal pleasure, excitement, comfort or hedonistic and pragmatic values
(Trope, Liberman, & Wakslak, 2007). Low-level goals motivate people to work harder for self-
improvement in concrete domains, and motivate social comparisons (Pavarini, Yang, Schnall, &
Immordino-Yang, Under Review).
Under the CLT framework, purposeful goals fit the description of high-level goals.
Purposeful goals point to central values, pursue transforming the life of others, and thus, we use
high-level goals as a proxy of purposeful goals.
The level of abstraction can be related to the concept of “life domains”, the area in the
adolescent’s life in which any given goal can be placed (Oyserman, Bybee, Terry, & Hart-
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 3
Johnson, 2004). Life domains comprise achievements, personality traits, interpersonal
relationship, and material lifestyle. A goal in the material lifestyle can be coded as low-level,
whereas a goal in the interpersonal relationship domain might be classified as a high-level goal.
Nonetheless, as participants elaborate on their goals, the level of abstraction does not map
necessarily onto life domains. A participant might be set to have a high-paid career, which can be
considered a low-level goal. In the elaboration of that goal, the participant can state that this goal
is instrumental in helping his/her parents to pay the mortgage of their house. By allowing
participants to freely expressing and elaborating on their goals, we can examine the
purposefulness underlying in every goals, as well we can search for purposefulness in every
domain of their lives.
It is important to clarify that we do not to intend to take a judgmental stance towards
adolescents’ future goals, or to classify adolescents on relation to how abstract their goals are.
Rather, we aim to relate inter-individual neural differences to the frequency in which adolescents
spontaneously formulate abstract goals. Several reasons justify focusing on high-level goals.
First, high-level goals are important to develop a moral framework during adolescence. In terms
of their content, high-level goals are associated to lofty motives such as civic participation and
moral reflections (Ballard, Malin, Porter, Colby, & Damon, 2015). Second, high-level goals are
part of the identity of generative adults. Generative adults, who are adults interested in leaving a
legacy behind them and committed for the well-being of future generations, are more likely to be
involved in civic activities, religious groups and families, as well as to construe their life
according to a strong moral framework and with an optimistic view on challenges (Mc Adams &
Guo, 2015). Third, high-level goals are associated to psychological wellbeing. The desire for
more abstract resources, for example time over affluence, is associated with greater happiness
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 4
(Hershfield, Mogilner, & Barnea, 2016). Finally, high-level goals, goals focused on others for
example, also have motivational value and are action-oriented (Ko, Mejia, & Hooker, 2013).

The Default Mode Network and Imagining Our Future Intended Lives
A major brain network involved in imagining personal goals and projecting the self in
time is the Default Mode Network (DMN). The DMN is characterized by increasing activity
during internally-focused processing (Buckner, Andrews-Hanna, & Schacter, 2008), suppressing
activity during stimulus-driven processing (Fox et al., 2005), and a high degree of functional
connectivity (Greicius, Krasnow, Reiss, & Menon, 2003). The DMN is known for supporting
self-generated and internally-focused processes relevant to imagining purposeful goals, such as
mental time travel (Ostby et al., 2012), reflecting on core values (Kaplan et al., 2016), processing
social emotional feelings of others (Immordino-Yang, McColl, Damasio, & Damasio, 2009), and
in the experience of moral elevation (Pavarini, Yang, Schanll, & Immordino-Yang, Under
Review). Furthermore, prior research has shown that neural activity in the DMN activity
correlates with measures of psychological distance using the CLT framework (Gilead, Liberman,
& Maril, 2014; Tamir & Mitchell, 2011).
Anatomically, the DMN can be divided into anterior and posterior subdivisions. The
anterior part comprises medial and dorsal medial prefrontal structures, inferior frontal gyrus,
anterior temporal lobe and lateral parietal cortex (Xu, Yuan, & Lei, 2016). The posterior division
includes the hippocampal and temporal lobe, posteromedial cortices, precuneus, and inferior
lateral parietal cortex (Raichle, 2015). The involvement of the medial prefrontal cortex in self-
referential processing, subjective appraisal of mental context and motivational impact of future
thinking has lead researchers to suggest that the anterior portion of the DMN is associated with
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 5
immediate present thoughts dealing with action planning and personal goals (Stawarczyk &
D’Argembeau, 2015). The posterior part of the DMN is activated in contextual retrieval and
simulating a self-relevant future (Xu et al., 2016). Nonetheless, despite growing evidence that
DMN is associated to self-relevant future goals, prior research has not related DMN status to the
purposefulness of future goals.
Intrinsic functional connectivity at rest offers a new approach to understanding the
relationship between imagination of future intended lives and its neural substrate in adolescents.
It allows performing exploratory data-driven analysis to characterize the neural organization, as
well to identify the brain components of a superordinate complex process, such as imagination
(Ernst, Torrisi, Balderston, Grillon, & Hale, 2015). This technique is also useful for relating
neural functioning to behaviors that, by nature, cannot be easily captured, such as imagining a
purposeful life.
Examining the neural correlates of highly abstract goals will allow us to gain valuable
insight about the generative nature of purpose in youth. In this study, we aim to examine the
relationship between individual variability in the frequency of purposeful goals adolescents
express and the intrinsic functional connectivity within the Default Mode Network at rest. We
asked adolescents to imagine themselves in an open-ended interview, the Future Selves
Questionnaire (Oyserman & Markus, 1990). This interview allows adolescents to spontaneously
enunciate both high and low-level goals and elaborate on them. The frequency of high-level
goals was separately tallied. In the same day of the interview, we collected resting state scans
from participants. We expected that high-level goals would be correlated with the functional
connectivity in anterior portions of the DMN, supporting the self-relevant goal processing, as
well as reward-processing that occurs in this area (Bechara, 2000; D’Argembeau et al., 2010;
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 6
Okuda et al., 2003), rather than with the posterior division of the DMN, involved in the
simulation of future scenarios associated to setting future goals (Addis, Wong, & Schacter,
2007). As control measures, we collected general intellectual coefficient (IQ) scores and working
memory. We did not expect a significant correlation between the frequency of high-level goals
and IQ scores, supporting that the imagining future events is an independent process, separable
of intellectual abilities. We did not have a specific hypothesis for working memory scores, but it
was possible that more high-level goals, which are arguably more complex, were associated to
working memory skills, thus, we intended to explore their relationship.

Methods
Participants
Thirty-five right-handed, native English-speaking adolescents, with no history of
neurological or psychiatric illness, were included in this study (21 females, mean age= 17.5
years, SD=0.84, range=16-19 years). These data were collected as part of a larger study on the
development of social emotions, approved by USC Institutional Review Board. Participants gave
their assent to participate and parents gave informed consent. Participants were compensated for
their participation. Twenty participants identified themselves as Asian American, and fifteen
identified themselves as Latino-American.
For the analysis of the verbal responses, the sample size used for this study is large
enough to test the null hypothesis for correlations ρ=0.5, which is considered a large effect size
for correlations (Cohen, 1988), with a power equal to 0.8 and a type I error probability of a=0.05
(sample size needed= 28).

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 7
Interview
An adapted version of the Future Selves Questionnaire (Oyserman & Markus, 1990) was
applied in a one-to-one interview. In this open-ended interview, participants were asked to
imagine what they want to become in one and ten years in the future, as well as what they want
to avoid becoming for the same years in the future. This interview allowed adolescents to freely
assert any sort of goals, giving time for follow-up questions. Each interview took approximately
20 minutes and was videotaped and transcribed. An interviewer of the same ethnicity as the
interviewee carried out every interview.

Coding of high and low-level goals
Each answer was coded for the presence (1) or absence (0) of either high or low-level
goals. High-level goals were defined as future goals that focused on obtaining experiences,
feelings, values, growth, and beliefs, as well as service to others and goals greater than the self
(Damon et al., 2003; Trope & Liberman, 2010).
Examples: “I want to make sure my daughter is doing well”, “Um, uh, I think I’d still, like
to help others, so organizations like Red Cross or just do some kind of volunteer work with my
free time”, “And [I want to] continue being a hard worker and staying humble”.
Low-level goals were defined by future goals that included acquiring goods, gaining
popularity, status, social comparisons, narrowly defined tasks, personal pleasure, excitement,
comfort, and hedonistic or pragmatic values (Damon et al., 2003; Trope & Liberman, 2010).
Examples: “I don’t want to, I don’t know… its just, maybe I don’t wanna be homeless”,
“[I want] to have a nice car”, “I want to have my motorcycle license”.
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 8
The counts of participants’ high-level goals for one and ten years were summed up into
one score. Inter-rater reliability analysis carried out in a 30% of the subjects included in this
study indicated appropriate consistency of the coding scheme (90% ICC).

Resting State fMRI Acquisition and Preprocessing
On the same day as the interview, participants underwent a 7-minute resting state MRI
scan, when they were asked to “relax and let your mind wonder”. Half of the sample was
interviewed before the MRI session, and the other half was interviewed after MRI scans were
collected. As these data are part of a larger study, resting state scans were acquired after four 8-
minute runs in which participants viewed short clips of videos eliciting social emotions (for a
detailed description of the videos, see Immordino-Yang et al. (2009)).
Neuroimaging data were collected at USC Dana and David Dornsife Neuroimaging
Center. Whole-brain images were acquired using a Siemens 3 Tesla MAGNETON TIM trio
scanner with a 20-channel matrix head coil. Functional scans were acquired using a T2*
weighted Echo Planar (EPI) sequence (TR=2 s, TE=25 ms, flip angle= 90o, acquisition matrix:
64 x 64, FOV= 192 mm) with a voxel resolution of 3 x 3 x 3 mm. PACE (Prospective
Acquisition CorrEction) was used to automatically correct for motion during data acquisition.
Forty-one continuous transverse slices were acquired to cover the whole brain and brain stem.
Anatomical images were acquired using a magnetization prepared rapid acquisition
(MPRAGE) sequence (TI=800 ms, TR= 2530 ms, TE= 3.13 ms, flip angle= 10
o
) with an
isotropic voxel of 1 mm; 180 slice were acquired to cover the whole brain, the dimension were
256 x 256 x 160.
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 9
Neuroimaging data were preprocessed using SPM12 (Wellcome Department of Cognitive
Neurology, London, UK) in Matlab 2015b (MathWorks, Inc.). Functional slices were timing
corrected, aligned to the first volume acquired and co-registered to the anatomical image. Co-
registrations were individually examined for each participant in native space to ensure quality
alignment. Anatomical images were segmented and non-linearly normalized to MNI space
(Montreal Neurological Institute) using standard probabilistic tissue maps provided in SPM12.
The same normalization transformation was applied to functional scans, which were resampled
into a resolution of 2mm x 2mm x 2mm and smoothed using an 8 mm full-width, half-maximum
Gaussian kernel.

Selection of the DMN Component
The DMN was identified at the group-level using Independent Component Analysis
(ICA) and back-reconstructed for each participant using the Infomax algorithm from the GIFT
toolbox (version 4.0a). GIFT separates each subject’s fMRI data into independent spatial
components and their respective time courses. Twenty components were estimated in this dataset
in order to assure the stability of the analysis (Li, Adalı, & Calhoun, 2007). A spatial correlation
was performed between each of the twenty components and a DMN template (Laird et al., 2011).
The component that most strongly correlated with the template was chosen as the DMN
component. The selected component for each individual was visually inspected to ensure that it
included canonical regions of the DMN. Figure 1 depicts the selected component. ICA, a data-
driven approach, was preferred over theory-driven methods since it can contribute to reveal the
multiple components of DMN sub-serving purposeful future thinking (Xu et al., 2016).

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 10
Correlation between High-Level Goals and Intrinsic DMN Connectivity
A multiple regression model was set to regress the participants’ z-scores maps on the
frequency of high-level future goals. IQ scores for each participant were entered in the model as
a covariate of no interest. Half of the participants were interviewed before being shown videos of
social emotional feelings in the MR scanner, whereas the other half was interviewed afterward.
Thus, the order of the interview was used as a covariate of no interest, as well. The whole brain
was anatomically masked to increase statistical power by reducing multiple comparisons. The
mask was created using the Anatomical Label Atlas provided by SPM12, and it included medial
prefrontal cortex, anterior cingulate cortices, hippocampi, parahippocampal gyri, middle
temporal gyri, temporal poles, and fusiform gyri, posterior cingulate cortices, precuneus, and
inferior parietal lobules. Figure 2 illustrates the anatomically defined mask.
On the group-level results, a statistical threshold of p < 0.005 and a cluster extent
threshold of 23 voxels was set. This corresponds to a p < 0.05 controlling for multiple
comparisons. The cluster extent threshold was determined by 10,000 Monte Carlo simulation
iterations conducted using the AlphaSim program in AFNI (http://afni.nimh.nih.gov/afni/). The
criteria input to AlphaSim were: uncorrected p-value of 0.005, voxel size of 2x2x2, spatial
smoothing kernel of 8 mm, and the number of voxels included in the whole brain analyses
(48420 voxels).
In order to validate the robustness of the findings, we extracted and averaged the z-scores
from the voxels in the surviving clusters for each participants using MarsBar toolbox in SPM.
The averaged z-scores and their corresponding count of high-level goals were paired. These pairs
were randomly re-sampled with replacement to generate 10,000 bootstrapped samples of 34 pairs
of values, using the R statistical software package (version 3.2.2). Pearson correlation
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 11
coefficients for each bootstrapped sample were calculated, and from the distribution of
correlations, a 95% confidence interval was estimated. Confidence intervals for each cluster are
presented in Table 1. None of the confidence intervals crossed zero, supporting the robustness of
the results presented here.

Cognitive Measures
After the interview and resting state data were collected, participants completed the
Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II) (Wechsler, 2011), in
order to obtain a measure of general intelligence. In addition, participants completed the n-back
task, a working memory measure (Sweet, 2011).

Results
During the interview, participants reported their future goals (M= 13.51, Range= 9-21,
SD= 2.57). Verbal responses included both low (M= 8.69, Range= 3-14, SD= 2.89) and high-
level (M= 4.74, Range= 1-10, SD=2.42) goals for all participants. Interestingly, the frequencies
of low and high-level future goals were negatively correlated [r(33)=-0.53, p=0.001]. There were
no effects of ethnicity, gender, or experiment condition (lowest p=0.43). For high-level goals,
participants reported goals for one (M= 2.51, Range= 0-5, SD= 1.4) and ten years (M= 2.23,
Range= 0-6, SD= 1.44) into the future.
Importantly, neither high [r(32)=0.07, p=0.68], nor low [r(32)=0.02, p=0.9] level goals
correlated with standardized measure of intellectual abilities, indicating that these results cannot
be merely explained by individual differences in general intellectual status. The level of
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 12
abstraction did not correlate with working memory performance for high [r(33)=-0.05, p=0.75]
or low-level goals [r(33)=-0.12, p=0.48], respectively.
As expected, the frequency of high-level goals was related to higher intrinsic functional
connectivity in anterior portions of the DMN, such as in the orbital frontal cortex (Brodmann
area [BA]11), and the frontal pole (BA10). In turn, high-level goals for the future predicted
decreased functional connectivity in the anterior cingulate cortex (ACC) (BA32). These findings
held after controlling for participants’ IQ scores and whether the interview was conducted before
or after the MRI session. Results are presented in Table 1 and Figure 3.

Discussion
The aim of this study was to examine whether the intrinsic functional connectivity of the
DMN was associated to setting purposeful goals for the future during adolescence. We used
goals with high level of abstraction as a proxy of purposefully imagining an adult life. Goals
with high level of abstraction are focused on core values and superordinate aspects of our
personality, and are strongly oriented toward others. In this study, adolescents exhibited a great
number of purposeful goals for their intended adult life. The frequency of purposeful goals was
not related to gender and ethnic/cultural background. Interestingly, purposeful future goals were
not correlated with standardized measures of intelligence and working memory, suggesting that
individual differences in general intellectual and executive attention abilities cannot explain the
level of abstraction, or purpose, in which adolescents frame their future goals.
The status of the intrinsic functional connectivity of brain structures within the DMN was
predicted by the frequency in which adolescents imagine purposeful goals for their intended
future lives. Setting purposeful goals for the future positively predicted the functional
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 13
connectivity in the anterior portion of the DMN, specifically, in the frontal pole and orbital
frontal cortex. The frontal pole and the orbital frontal cortex have been shown to be critical for
the experience of insight about the future self, moral competence and reward processing. Human
lesion studies have been shown future insensitivity in patients with lesions in ventromedial areas
(Bechara, 2000). A PET study in healthy participants also showed the activation of the frontal
pole when thinking prospectively about the future (Okuda et al., 2003). The activation was
greater when imagining more distant future (years versus days). The authors have suggested that
the frontopolar cortex is involved in orienting attention to future events. An alternative
explanation can be found in Andreasen et al. (1995), who showed in another PET study that
subjects activated frontal and parietal cortex in future episodic retrieval, as well as when subjects
were freely thinking about their past, suggesting that these areas might be related to self and
social-awareness, rather than future thinking. This is a sensitive explanation given that future
thinking requires generation of self and social-related reflections. Nevertheless, Nyberg, Kim,
Habib, Levine, & Tulving (2010) demonstrated that activity in frontal structures is still related to
future thinking, after controlling for mental content and movement in subjective time.
Interestingly, anti-correlations also emerged in this dataset. The frequency of purposeful
future goals predicted decreased functional connectivity of ACC. This preliminary finding is in
agreement with neuroimaging studies indicating that the medial part of the PFC is more active
when reflecting on the immediate aspects of goals relative to future thinking (Stawarczyk &
D’Argembeau, 2015), when imagining events with shorter temporal distance (Tamir & Mitchell,
2011), and in more subjective aspects of self-referential tasks, compared to more reflective tasks,
or focusing on others (Northoff et al., 2006). The involvement of the medial portion of the PFC
is related to the failure of engaging future processing, both using tasks that require imagining a
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 14
future event and in inter-temporal choice paradigms (Mitchell, Schirmer, Ames, & Gilbert,
2010).
As this study is the first attempt to describe how inter-individual differences in resting-
state neural functioning of adolescents are related to setting a purpose for their intended adult
life, this work has limitations. The nature of this study is exploratory and its design is
correlational. Therefore, a causal role of the intrinsic connectivity of DMN on the imagination of
purposeful goals cannot be inferred. Longitudinal studies might help us to address this issue. If
progressive segregation and integration of the brain, and particularly of the DMN network,
occurs during adolescence (Monique Ernst, Torrisi, Balderston, Grillon, & Hale, 2015), the
examination of brain maturational changes will help us to understand the development and
unfolding of purpose in life during adolescence. In addition, this study used future possible
selves as a proxy of purpose, instead of a scale designed to measure purpose in life. Nonetheless,
using the Future Selves Questionnaire allowed us to study the construction of purposeful goals,
as well as the readiness of these goals for attainment. The processing of purpose goes beyond the
mere enunciation of goals, they work as a high-order representation that includes episodic and
semantic images, strategies, feelings and values (Stawarczyk & D’Argembeau, 2015). For
attaining purposeful goals, setting intentions is a central component, but it is not enough; the
retrieval of representations of the self and a path to distal purposes are also required (Oyserman,
Johnson, & James, 2011; Szpunar et al., 2014). The function of memory retrieval has been
suggested to support the building of mental representation of others perspective in the immediate
environment (Buckner & Carroll, 2007), as well as reflecting on social emotions on far-distant
scenarios (Yang, Bossmann, Schiffhauer, Jordan, & Immordino-Yang, 2013). Further studies
might examine how autobiographical memories are retrieved to construct purposeful goals, as
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 15
well as how prosocial goals are organized for attainment. Also, future studies should examine
how purposeful goals are related to future expectations and concerns, in particular in groups of
adolescents at risk, such as young people from low socio-economical status, or who had
experienced violence in their community.

Concluding remarks
This work shows that non-selfish and other-oriented purposes are salient goals for
adolescents, which counters widely spread views on youth depicted as erratic and irrational
decision makers (Dahl, 2004). Indeed, young people’s valuation systems combine self-
enrichment with concerns about cooperation with others. As social emotions may serve a
function as a vehicle for morality (Immordino-Yang, 2011), possibly, the same notion applies to
purpose and future goals.
Caution is also needed for interpreting reported purpose in future goals with high level of
abstraction. Low-level goals are also an essential part of adolescent experience of imagining the
future, and they have shown to be a predictor of academic attainment (Oyserman et al., 2004).
Low-level goals are often a concrete way to approach altruistic goals (Damon, 2008), just like
the adolescent who wants to be accepted in a good college and be in a high-paid career, so he/she
can financially help his/her parents in the future. In the other hand, prosociality, a core
component of high-level goals, is not an unitary construct since it comprises altruistic prosocial
motives, but also includes norm-oriented prosociality, and strategically-oriented prosociality
(Bockler, Tusche, & Singer, 2016). Thus, low-level goals can unfold into and motivate
purposeful goals and vice versa.
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 16
Although exploratory, the findings from this work are relevant for practice and theory
building in fields related to mental health and human development. Purpose and future thinking
has been linked to health outcomes, from substance abuse and suicidal behavior in depression
(Harlow, Newcomb, & Bentler, 1986; Roepke & Seligman, 2016), to energy intake in obesity
(Daniel, Said, Stanton, & Epstein, 2015), to civic participation in the search for social change
(Ballard et al., 2015). With further research, it also opens the possibility that families, educators
and mental health professionals might be able to support the positive development of purpose by
guiding young people and children in the constructive reflection of future life (Yeager &
Bundick, 2009). Significant efforts have been done in education (Damon, 2008), and they can be
extended to mental health and counseling. However, we do not fully understand how social roles,
cultural values, and formal education affect the development of psychological and neural
systems responsible for development of purpose, self-regulation, complex social emotions, and
morality (Crone & Dahl, 2012). This study is an initial step to gain insight on how neural
changes, and the construal of future goals might contribute to cultivating purpose in youth.

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 17
References
Addis, D. R., Wong, A. T., & Schacter, D. L. (2007). Remembering the past and imagining the
future: Common and distinct neural substrates during event construction and elaboration.
Neuropsychologia, 45(7), 1363–1377.
http://doi.org/10.1016/j.neuropsychologia.2006.10.016
Andreasen, N. C., O’Leary, D. S., Cizadlo, T., Arndt, S., Rezai, K., Watkins, G. L., … Hichwa,
R. D. (1995). Remembering the past: two facets of episodic memory explored with positron
emission tomography. American Journal of Psychiatry, 152, 1576–1585.
Ballard, P. J., Malin, H., Porter, T. J., Colby, A., & Damon, W. (2015). Motivations for Civic
Participation Among Diverse Youth: More Similarities than Differences. Research in
Human Development, 12(1–2), 63–83. http://doi.org/10.1080/15427609.2015.1010348
Bechara, A. (2000). Emotion, Decision Making and the Orbitofrontal Cortex. Cerebral Cortex,
10(3), 295–307. http://doi.org/10.1093/cercor/10.3.295
Bockler, A., Tusche, A., & Singer, T. (2016). The Structure of Human Prosociality:
Differentiating Altruistically Motivated, Norm Motivated, Strategically Motivated, and
Self-Reported Prosocial Behavior. Social Psychological and Personality Science, 7(6), 530–
541. http://doi.org/10.1177/1948550616639650
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network:
Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences,
1124, 1–38. http://doi.org/10.1196/annals.1440.011
Buckner, R. L., & Carroll, D. C. (2007). Self-projection and the brain. Trends in Cognitive
Sciences, 11(2), 49–57. http://doi.org/10.1016/j.tics.2006.11.004
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York:
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 18
Academic Press.
Crone, E. A., & Dahl, R. E. (2012). Understanding adolescence as a period of social – affective
engagement and goal flexibility. Nature, 13(9), 636–650. http://doi.org/10.1038/nrn3313
D’Argembeau, A., Lardi, C., & Van der Linden, M. (2012). Self-defining future projections:
Exploring the identity function of thinking about the future. Memory, 20(2), 110–120.
http://doi.org/10.1080/09658211.2011.647697
D’Argembeau, A., Stawarczyk, D., Majerus, S., Collette, F., Van der Linden, M., Feyers, D., …
Salmon, E. (2010). The Neural Basis of Personal Goal Processing When Envisioning Future
Events. Journal of Cognitive Neuroscience, 22(8), 1701–1713.
http://doi.org/10.1162/jocn.2009.21314
Dahl, R. E. (2004). Adolescent Brain Development: A Period of Vulnerabilities and
Opportunities. Keynote Address. Annals of the New York Academy of Sciences, 1021(1), 1–
22. http://doi.org/10.1196/annals.1308.001
Damon, W. (2008). The Path to Purpose: How Young People Find their Calling in Life. New
York: The Free Press.
Damon, W., Menon, J., & Bronk, K. C. (2003). The Development of Purpose During
Adolescence. Applied Developmental Science, 7(3), 119–128.
Daniel, T. O., Said, M., Stanton, C. M., & Epstein, L. H. (2015). Episodic future thinking
reduces delay discounting and energy intake in children. Eating Behaviors, 18, 20–24.
http://doi.org/10.1016/j.eatbeh.2015.03.006
Ernst, M., Torrisi, S., Balderston, N., Grillon, C., & Hale, E. A. (2015). fMRI Functional
Connectivity Applied to Adolescent Neurodevelopment. Annual Review of Clinical
Psychology, 11, 361–377. http://doi.org/10.1146/annurev-clinpsy-032814-112753
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 19
Ernst, M., Torrisi, S., Balderston, N., Grillon, C., & Hale, E. A. (2015). fMRI Functional
Connectivity Applied to Adolescent Neurodevelopment*. Annual Review of Clinical
Psychology, 11(1), 361–377. http://doi.org/10.1146/annurev-clinpsy-032814-112753
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E.
(2005). The human brain is intrinsically organized into dynamic, anticorrelated functional
networks. Proceedings of the National Academy of Sciences of the United States of
America, 102(27), 9673–8. http://doi.org/10.1073/pnas.0504136102
Gilead, M., Liberman, N., & Maril, A. (2014). From mind to matter: neural correlates of abstract
and concrete mindsets. Social Cognitive and Affective Neuroscience, 9(5), 638–645.
http://doi.org/10.1093/scan/nst031
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003). Functional connectivity in the
resting brain: a network analysis of the default mode hypothesis. Proceedings of the
National Academy of Sciences of the United States of America, 100(1), 253–8.
http://doi.org/10.1073/pnas.0135058100
Harlow, L. L., Newcomb, M. D., & Bentler, P. M. (1986). Depression, self-derogation, substance
use, and suicide ideation: lack of purpose in life as a mediational factor. Journal of Clinical
Psychology, 42(1), 5–21. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/3950015
Hershfield, H. E., Mogilner, C., & Barnea, U. (2016). People Who Choose Time Over Money
Are Happier. Social Psychological and Personality Science, 7(7), 697–706.
http://doi.org/10.1177/1948550616649239
Immordino-Yang, M. H. (2011). Me, My “Self” and You: Neuropsychological Relations
between Social Emotion, Self-Awareness, and Morality. Emotion Review, 3(3), 313–315.
http://doi.org/10.1177/1754073911402391
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 20
Immordino-Yang, M. H., McColl, A., Damasio, H., & Damasio, A. (2009). Neural correlates of
admiration and compassion. Proceedings of the National Academy of Sciences, 106(19),
8021–8026. http://doi.org/10.1073/pnas.0810363106
Kaplan, J. T., Gimbel, S. I., Dehghani, M., Immordino-Yang, M. H., Sagae, K., Wong, J. D., …
Damasio, A. (2016). Processing Narratives Concerning Protected Values: A Cross-Cultural
Investigation of Neural Correlates. Cerebral Cortex, bhv325.
http://doi.org/10.1093/cercor/bhv325
Ko, H.-J., Mejia, S., & Hooker, K. (2013). Social possible selves, self-regulation, and social goal
progress in older adulthood. International Journal of Behavioral Development, 38(3), 219–
227. http://doi.org/10.1177/0165025413512063
Laird, A. R., Fox, P. M., Eickhoff, S. B., Turner, J. a., Ray, K. L., McKay, D. R., … Fox, P. T.
(2011). Behavioral Interpretations of Intrinsic Connectivity Networks. Journal of Cognitive
Neuroscience, 23(12), 4022–4037. http://doi.org/10.1162/jocn_a_00077
Li, Y.-O., Adalı, T., & Calhoun, V. D. (2007). Estimating the number of independent
components for functional magnetic resonance imaging data. Human Brain Mapping,
28(11), 1251–1266. http://doi.org/10.1002/hbm.20359
Liberman, N., & Trope, Y. (2008). The Psychology of Transcending the Here and Now. Science,
322(5905), 1201–1205. http://doi.org/10.1126/science.1161958
Liberman, N., & Trope, Y. (2014). Traversing psychological distance. Trends in Cognitive
Sciences, 18(7), 364–369. http://doi.org/10.1016/j.tics.2014.03.001
Liberman, N., Trope, Y., McCrea, S. M., & Sherman, S. J. (2007). The effect of level of
construal on the temporal distance of activity enactment. Journal of Experimental Social
Psychology, 43(1), 143–149. http://doi.org/10.1016/j.jesp.2005.12.009
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 21
Mc Adams, D. P., & Guo, J. (2015). Narrating the Generative Life.
http://doi.org/10.1177/0956797614568318
Mitchell, J. P., Schirmer, J., Ames, D. L., & Gilbert, D. T. (2010). Medial prefrontal cortex
predicts intertemporal choice. Journal of Cognitive Neuroscience, 23, 1–10.
http://doi.org/10.1162/jocn.2010.21479 [doi]
Northoff, G., Heinzel, A., de Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J. (2006).
Self-referential processing in our brain—A meta-analysis of imaging studies on the self.
NeuroImage, 31(1), 440–457. http://doi.org/10.1016/j.neuroimage.2005.12.002
Nussbaum, S., Trope, Y., & Liberman, N. (2003). Creeping dispositionism: The temporal
dynamics of behavior prediction. Journal of Personality and Social Psychology, 84(3), 485–
497. http://doi.org/10.1037/0022-3514.84.3.485
Nyberg, L., Kim, A., Habib, R., Levine, B., & Tulving, E. (2010). Consciousness of subjective
time in the brain. Proceedings of the National Academy of Sciences, 107(51), 22356–22359.
http://doi.org/10.1073/pnas.1016823108
Okuda, J., Fujii, T., Ohtake, H., Tsukiura, T., Tanji, K., Suzuki, K., … Yamadori, A. (2003).
Thinking of the future and past: the roles of the frontal pole and the medial temporal lobes.
NeuroImage, 19(4), 1369–1380. http://doi.org/10.1016/S1053-8119(03)00179-4
Ostby, Y., Walhovd, K. B., Tamnes, C. K., Grydeland, H., Westlye, L. T., & Fjell, A. M. (2012).
Mental time travel and default-mode network functional connectivity in the developing
brain. Proceedings of the National Academy of Sciences, 109(42), 16800–16804.
http://doi.org/10.1073/pnas.1210627109
Oyserman, D., Bybee, D., Terry, K., & Hart-Johnson, T. (2004). Possible selves as roadmaps.
Journal of Research in Personality, 38(2), 130–149. http://doi.org/10.1016/S0092-
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 22
6566(03)00057-6
Oyserman, D., Johnson, E., & James, L. (2011). Seeing the Destination but Not the Path: Effects
of Socioeconomic Disadvantage on School-focused Possible Self Content and Linked
Behavioral Strategies. Self and Identity, 10, 474–492.
http://doi.org/10.1080/15298868.2010.487651
Oyserman, D., & Markus, H. R. (1990). Possible selves and delinquency. Journal of Personality
and Social Psychology, 59(1), 112–125. http://doi.org/10.1037/0022-3514.59.1.112
Patton, L., Renn, K., Guido, F., & Quaye, S. (2016). Student Development in College: Theory,
Research, and Practice (3rd ed.). San Francisco, CA: Jossey-Bass.
Raichle, M. E. (2015). The Brain’s Default Mode Network. Annual Review of Neuroscience,
38(1), 433–447. http://doi.org/10.1146/annurev-neuro-071013-014030
Roepke, A. M., & Seligman, M. E. P. (2016). Depression and prospection. British Journal of
Clinical Psychology, 55(1), 23–48. http://doi.org/10.1111/bjc.12087
Stawarczyk, D., & D’Argembeau, A. (2015). Neural correlates of personal goal processing
during episodic future thinking and mind-wandering: An ALE meta-analysis. Human Brain
Mapping, 36(8), 2928–2947. http://doi.org/10.1002/hbm.22818
Sweet, L. H. (2011). N-Back Paradigm. In Encyclopedia of Clinical Neuropsychology (pp. 1718–
1719). New York, NY: Springer New York. http://doi.org/10.1007/978-0-387-79948-
3_1315
Szpunar, K. K., Spreng, R. N., & Schacter, D. L. (2014). A taxonomy of prospection :
Introducing an organizational framework for future- oriented cognition, 111(52).
http://doi.org/10.1073/pnas.1417144111
Tamir, D. I., & Mitchell, J. P. (2011). The Default Network Distinguishes Construals of
DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 23
Proximal versus Distal Events. Journal of Cognitive Neuroscience, 23(10), 2945–2955.
http://doi.org/10.1162/jocn_a_00009
Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance.
Psychological Review, 117(2), 440–463. http://doi.org/10.1037/a0018963
Trope, Y., Liberman, N., & Wakslak, C. J. (2007). Construal Levels and Psychological Distance:
Effects on Representation, Prediction, Evaluation, and Behavior. Journal of Consumer
Psychology, 17(2), 83–95. http://doi.org/10.1016/S1057-7408(07)70013-X
Vasquez, N. A., & Buehler, R. (2007). Seeing future success: does imagery perspective influence
achievement motivation? Personality & Social Psychology Bulletin, 33(10), 1392–405.
http://doi.org/10.1177/0146167207304541
Wechsler, D. (2011). Wechsler Abbreviated Scale of Intelligence–Second Edition Manual.
Bloomington, MN: Pearson.
Xu, X., Yuan, H., & Lei, X. (2016). Activation and Connectivity within the Default Mode
Network Contribute Independently to Future-Oriented Thought. Nature Publishing Group,
(April 2015), 1–10. http://doi.org/10.1038/srep21001
Yang, X. F., Bossmann, J., Schiffhauer, B., Jordan, M., & Immordino-Yang, M. H. (2013).
Intrinsic default mode network connectivity predicts spontaneous verbal descriptions of
autobiographical memories during social processing. Frontiers in Psychology, 3(JAN), 1–
10. http://doi.org/10.3389/fpsyg.2012.00592
Yeager, D. S., & Bundick, M. J. (2009). The Role of Purposeful Work Goals in Promoting
Meaning in Life and in Schoolwork During Adolescence. Journal of Adolescent Research,
24(4), 423–452. http://doi.org/10.1177/0743558409336749

DEFAULT MODE NETWORK PREDICTS YOUTH PURPOSES 24
Table 1. Brain regions whose intrinsic functional connectivity correlates with frequency of high-
level goals. Clusters are significant at p< 0.05, corrected for multiple comparisons; those
significant at p<0.001 are marked**. 95% confidence intervals are presented (C.I. of rho) and do
not cross zero.
Brain region Coordinates Cluster z-Score 95% C.I. of rho
x y z size
High-level goals: Positive correlation
Frontal pole -12 58 -6 3.41** 29 (0.2877, 0.7733)
Orbital frontal cortex 16 30 -14 3.36** 62 (0.2854, 0.7677)
High-level goals: Negative correlation
Anterior cingulate cortex -6 46 -4 3.07 46 (-0.8014, -0.3173)

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Figure 1. Depiction of the selected DMN component map for the sample. Note that views
presented here are taken from the same slice position as the views shown in Figure 2. MNI
coordinates are given for axial and sagittal planes. L, left; R, right.

Figure 2. Depiction of the anatomically defined DMN mask. The views depicted here are taken
from the same slice position as the views presented in Figure 1. MNI coordinates are given for
axial and sagittal planes. L, left; R, right.

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Figure 3. Neural regions from within DMN whose intrinsic functional connectivity correlated
with individual differences in frequency of spontaneous report of A) high-level goals (positive
correlation), B) high-level goals (negative correlation), enunciated during the Future Selves
Questionnaire. MNI coordinates of the sagittal and transverse planes are given. FP, frontal pole;
OFC, orbital frontal cortex; ACC, anterior cingulate cortex.

Abstract (if available)

Abstract Adolescents imagine their future adult life and set goals with varied levels of abstraction: low-level goals pertain to acquiring skills, goods and positions

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Creator Riveros Miranda, Rodrigo A. (author)

Core Title Intrinsic functional connectivity of the default mode network predicts the purposefulness of youths’ intended adult lives

School College of Letters, Arts and Sciences

Degree Master of Arts

Degree Program Psychology

Publication Date 06/28/2017

Defense Date 06/28/2017

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

Tag default mode network,functional connectivity,OAI-PMH Harvest,Purpose

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Immordino-Yang, Mary Helen (committee chair), Monterosso, John R. (committee member), Oyserman, Daphna R. (committee member)

Creator Email riverosm@usc.edu,rodrigo.riveros.miranda@gmail.com

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