A developmental examination of amygdala response to facial expressions.

Abstract

Several lines of evidence implicate the amygdala in face-emotion processing, particularly for fearful facial expressions. Related findings suggest that face-emotion processing engages the amygdala within an interconnected circuitry that can be studied using a functional-connectivity approach. Past work also underscores important functional changes in the amygdala during development. Taken together, prior research on amygdala function and development reveals a need for more work examining developmental changes in the amygdala's response to fearful faces and in amygdala functional connectivity during face processing. The present study used event-related functional magnetic resonance imaging to compare 31 adolescents (9-17 years old) and 30 adults (21-40 years old) on activation to fearful faces in the amygdala and other regions implicated in face processing. Moreover, these data were used to compare patterns of amygdala functional connectivity in adolescents and adults. During passive viewing, adolescents demonstrated greater amygdala and fusiform activation to fearful faces than did adults. Functional connectivity analysis revealed stronger connectivity between the amygdala and the hippocampus in adults than in adolescents. Within each group, variability in age did not correlate with amygdala response, and sex-related developmental differences in amygdala response were not found. Eye movement data collected outside of the magnetic resonance imaging scanner using the same task suggested that developmental differences in amygdala activation were not attributable to differences in eye-gaze patterns. Amygdala hyperactivation in response to fearful faces may explain increased vulnerability to affective disorders in adolescence; stronger amygdala-hippocampus connectivity in adults than adolescents may reflect maturation in learning or habituation to facial expressions.

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A Developmental Examination of Amygdala Response
to Facial Expressions
Amanda E. Guyer1, Christopher S. Monk2, Erin B. McClure-Tone3,
Eric E. Nelson1, Roxann Roberson-Nay4, Abby D. Adler1,
Stephen J. Fromm1, Ellen Leibenluft1, Daniel S. Pine1,
and Monique Ernst1
Abstract
& Several lines of evidence implicate the amygdala in face–
emotion processing, particularly for fearful facial expressions.
Related findings suggest that face–emotion processing engages
the amygdala within an interconnected circuitry that can be
studied using a functional-connectivity approach. Past work
also underscores important functional changes in the amygdala
during development. Taken together, prior research on amyg-
dala function and development reveals a need for more work
examining developmental changes in the amygdala’s response
to fearful faces and in amygdala functional connectivity during
face processing. The present study used event-related func-
tional magnetic resonance imaging to compare 31 adolescents
(9–17 years old) and 30 adults (21–40 years old) on activa-
tion to fearful faces in the amygdala and other regions im-
plicated in face processing. Moreover, these data were used
to compare patterns of amygdala functional connectivity in
adolescents and adults. During passive viewing, adolescents
demonstrated greater amygdala and fusiform activation to fear-
ful faces than did adults. Functional connectivity analysis re-
vealed stronger connectivity between the amygdala and the
hippocampus in adults than in adolescents. Within each group,
variability in age did not correlate with amygdala response,
and sex-related developmental differences in amygdala re-
sponse were not found. Eye movement data collected outside
of the magnetic resonance imaging scanner using the same
task suggested that developmental differences in amygdala ac-
tivation were not attributable to differences in eye-gaze pat-
terns. Amygdala hyperactivation in response to fearful faces
may explain increased vulnerability to affective disorders in
adolescence; stronger amygdala–hippocampus connectivity in
adults than adolescents may reflect maturation in learning or
habituation to facial expressions. &
INTRODUCTION
During adolescence, changes in social perception, so-
cial cognition, and social emotion occur in tandem with
brain maturation (Ernst, Pine, & Hardin, 2006; Nelson,
Leibenluft, McClure, & Pine, 2005; Casey, Giedd, &
Thomas, 2000; Spear, 2000). To explain how these cog-
nitive and emotional processes emerge and mature over
time, research needs to focus on the development of
relevant brain regions, including those, such as the
amygdala, that mediate aspects of social–emotional
functioning. The amygdala participates in processing in-
formation about salient emotional stimuli (LeDoux,
1994), including those positive or negative in valence
(Yang et al., 2002; Breiter et al., 1996; Morris et al.,
1996), and appears to be particularly responsive to
fearful facial expressions (Whalen et al., 1998; Adolphs,
Tranel, Damasio, & Damasio, 1995). For example, adults
with amygdala lesions show significant deficits in fearful
face recognition, despite intact ability to identify other
emotions (Adolphs et al., 1995, 1999, 2005). Functional
magnetic resonance imaging (fMRI) studies also indicate
that fearful facial expressions, more than neutral or other
emotional expressions, engage the amygdala (Whalen
et al., 2001; Breiter et al., 1996; Morris et al., 1996).
Although the ability to detect facial expressions is
present quite early in life (Nelson, 1987), major ques-
tions remain about factors that lead to changes in this
ability during development. In particular, little is known
about the development of normative neural responses
to fearful faces in the amygdala and related structures
engaged during face processing. Changes during the
transition from adolescence to adulthood are of par-
ticular interest, given both that affective disorders typi-
cally begin during adolescence (Kessler et al., 2005; Pine,
Cohen, Gurley, Brook, & Ma, 1998) and that evidence
implicates the amygdala and related structures in the
onset and persistence of such conditions (Pine, 2007).
As such, charting normative neurodevelopmental path-
ways might clarify substrates of deviant neurodevelop-
ment and their relationship to psychopathology.
1National Institutes of Health (NIH), Bethesda, MD,2University
of Michigan,3Georgia State University,4Virginia Commonwealth
University
D 2008 Massachusetts Institute of TechnologyJournal of Cognitive Neuroscience 20:9, pp. 1565–1582

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Studies in nonhuman primates suggest that amygdala
lesions produce different effects on social–emotional out-
comes as a function of ontogeny (Amaral, 2002, 2003;
Prather et al., 2001). For example, monkeys receiving
amygdala lesions in adulthood exhibit a reduction in
social fears compared to controls, whereas monkeys
receiving such lesions in childhood demonstrate in-
creased social fears (Prather et al., 2001). Thus, in studies
of nonhuman species, the developmental timing of amyg-
dala damage influences a behavioral analog of human
anxiety.
fMRI studies of face–emotion processing in adults and
adolescents with affective disorders document dysfunc-
tional neural circuitry involving amygdala regions, the
ventral prefrontal cortex, and the anterior cingulate cor-
tex (ACC) relative to psychiatrically healthy individuals
(McClure et al., 2007; Roberson-Nay et al., 2006; Straube,
Kolassa, Glauer, Mentzel, & Miltner, 2004; Stein, Goldin,
Sareen, Zorrilla, & Brown, 2002; Thomas, Drevets, Dahl,
et al., 2001). Because research on atypical and typical
development provides mutually reinforcing insights, re-
search comparing patterns of neural function in healthy
pediatric and adult samples might provide vital data for
understanding events during adolescence that lead to
persistent affective disorders.
Only a few studies have examined amygdala involve-
ment in processing fearful facial expressions among
healthy adolescents. Three fMRI studies have included
adolescent-only samples. First, in line with adult studies
(Whalen et al., 2001; Breiter et al., 1996; Morris et al.,
1996), Baird et al. (1999) reported greater amygdala ac-
tivation to fearful faces than to fixation trials or nonsense
stimuli in 12 adolescents (12–17 years old). A second
study found that amygdala response to fearful faces varied
by age and sex in 19 adolescents (9–17 years old), such
that amygdala activation correlated inversely with age,
particularly among women (n = 10) (Killgore, Oki, &
Yurgelun-Todd, 2001). Finally, in a third study of 16
adolescents (8–15 years old), no linear relationship was
found between age and amygdala activation to fearful
faces, regardless of sex (Yurgelun-Todd & Killgore, 2006).
An additional three developmental fMRI studies have
directly compared healthy adolescents and adults on
amygdala response to fearful facial expressions. One
study found sex-related developmental differences in
patterns of amygdala lateralization during passive view-
ing of fearful faces (Killgore & Yurgelun-Todd, 2004).
The other two studies yielded conflicting results (Monk
et al., 2003; Thomas, Drevets, Whalen, et al., 2001).
Thomas, Drevets, Whalen, et al. (2001) compared amyg-
dala response to fearful facial expressions between six
male adolescents (aged 9–13 years) and six male adults
(aged 18–30 years). Within each group, amygdala acti-
vation was greater when passively viewing fearful faces
versus fixations. In direct group comparisons, however,
adults showed significantly greater amygdala activation
to fearful relative to neutral faces than adolescents,
and adolescents showed greater amygdala response to
neutral versus fearful faces than adults. Monk et al.
(2003) compared amygdala response in 17 adolescents
(9–17 years old; 9 boys) and 17 adults (25–36 years old;
9 men) during presentations of emotionally engaging
faces. In a passive-viewing condition, but not in attention-
constraining conditions, adolescents showed greater amyg-
dala activation than adults to fearful versus neutral faces.
Thus, Thomas, Drevets, Whalen, et al. (2001) found that
amygdala response to fearful faces was greater in adults
than in adolescents, whereas Monk et al. found the
opposite.
In summary, the few available studies examining amyg-
dala functional development in humans generated con-
tradictory findings. Thus, the current study aimed to
collect data on a large sample of adolescents and adults
to provide sufficient statistical power to examine the ef-
fects of age and sex on amygdala function. Because past
work on the neural correlates of fearful face processing
in youth primarily focused on the amygdala (Killgore
& Yurgelun-Todd, 2004; Killgore et al., 2001; Thomas,
Drevets, Whalen, et al., 2001; Baird et al., 1999), we also
sought to expand this literature by examining develop-
mental differences in activation of additional regions that
are important for face processing: fusiform gyrus, hippo-
campus, ACC, and orbito-frontal cortex (OFC). Further-
more, although documenting activation in specific brain
regions is important for understanding neural mediators
of emotion and cognition, recent functional neuroimaging
studies have begun to integrate the understanding that
brain regions operate as part of highly interconnected
neural circuits (Yurgelun-Todd, 2007; Nelson et al., 2005).
Nevertheless, virtually no neuroimaging work considers
the manner in which amygdala-based circuits show mean-
ingful differences in functional connectivity between ado-
lescence and adulthood. Accordingly, we examined the
degree to which functional connections between the
amygdala and other brain regions exhibit meaningful
age-related variations during facial emotion processing.
We used the same event-related, face–emotion fMRI
paradigm as Monk et al. (2003) and hypothesized that,
consistent with Monk et al., adolescents would show
greater amygdala activation than adults when passively
viewing fearful relative to neutral faces. We also exam-
ined age as a continuous variable, given the large sample
size and wide age range within each developmental
group, to provide a more powerful test of continuous
relationships than was possible in previous smaller stud-
ies. Based on the findings from Yurgelun-Todd and
Killgore (2006) reviewed above, we hypothesized that
amygdala response to fearful faces would not vary line-
arly by age in adolescents or adults, even in our larger
sample. Other research suggests nonlinear relationships
between age (ranging from 4 to 22 years old) and brain
structure size (Lenroot & Giedd, 2006); thus, we ex-
plored possible nonlinear relationships between age and
amygdala activation.
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With regard to sex effects, prior research has yielded
mixed results regarding sex-related developmental differ-
ences in amygdala activation to faces (Killgore & Yurgelun-
Todd, 2004; McClure et al., 2004; Killgore et al., 2001);
however, these studies, the largest of which had 34 partic-
ipants, used samples that may have been underpowered
to detect sex-related developmental differences reliably.
Thus, a large sample would allow us to examine sex as a
moderating factor of developmental differences in amyg-
dala response during passive viewing of fearful faces.
The fusiform gyrus, the hippocampus, the ACC, and
the OFC have been implicated in face processing in gen-
eral, and in mood and anxiety disorders more specifi-
cally; each region has been reported to show changes
in activation as a function of age and face-viewing con-
text. For example, studies of adults suggest that the fusi-
form gyrus, specifically the anterior region, is involved in
the perceptual identification of faces (Haxby, Hoffman,
& Gobbini, 2000; Kanwisher, McDermott, & Chun, 1997)
and is particularly engaged in coding fearful faces (Pessoa,
McKenna, Gutierrez, & Ungerleider, 2002; Vuilleumier,
Armony, Driver, & Dolan, 2001; Breiter et al., 1996).
Developmental studies of fusiform gyrus response to
faces indicate that children have a more distributed pat-
tern of activation than adults when matching neutral
facial expressions, but not stimulus locations (Passarotti
et al., 2003), and that older versus younger children
have greater fusiform activation to neutral faces than to
houses (Aylward et al., 2005). However, such studies
have not examined age-group differences in fusiform
response to fearful versus neutral faces. Similarly, the
hippocampus has been implicated in facial encoding
(Haxby et al., 1996) but has been associated more
strongly with memory than affect (Alkire, Haier, Fallon,
& Cahill, 1998). Greater hippocampus activation has
been found in adults compared to adolescents when
viewing subsequently remembered neutral faces (Nelson
et al., 2003), however, little is known about developmen-
tal changes in hippocampus activation during face pro-
cessing generally or fearful face viewing specifically.
Turning to prefrontal regions, among adults, the
OFC and ACC circuitry modulates behavior by influenc-
ing attention to emotional stimuli, including fearful or
other negative facial expressions (Pessoa et al., 2002;
Blair, Morris, Frith, Perrett, & Dolan, 1999; Lane, Fink,
Chau, & Dolan, 1997). Across development, the OFC
and ACC show functional, anatomical, and physiolog-
ical changes in adolescence and by early adulthood
(Eshel, Nelson, Blair, Pine, & Ernst, 2007; Gogtay et al.,
2004; Adleman et al., 2002; Casey et al., 2000; Sowell,
Thompson, Holmes, Jernigan, & Toga, 1999; Casey et al.,
1997), and these regions have been implicated in the
maturation of attentional and emotional processes,
such as goal-directed attention to emotionally evocative
stimuli (Bush, Luu, & Posner, 2000). Monk et al. (2003)
found greater OFC and ACC activation in adolescents
than in adults when passively viewing fearful versus
neutral faces, as well as greater OFC activation in adults
than in adolescents when focusing on emotional versus
nonemotional aspects of fearful faces. As a whole, the
literature indicates that, like the amygdala, the fusiform
gyrus, the hippocampus, the ACC, and the OFC are
involved in facial emotion processing and the limited
developmental studies of these regions suggest possible
age-related changes in fearful-face processing.
Recent work indicates that between-group differences
in amygdala response to facial emotions are associated
with between-group differences in functional connectiv-
ity among specific brain regions in adolescent anxiety
patients as well as healthy adults (McClure et al., 2007;
Pezawas et al., 2005). However, no previous developmen-
tal study has examined amygdala functional connectivity
during facial emotion processing. A recurrent theme in
theories of brain development is that adolescence is a
time of neural refinement via synaptic pruning, myelina-
tion, and regulatory processes that may strengthen inter-
connections among brain circuits (Ernst & Spear, in press;
Nelson et al., 2005; Spear, 2000; Nelson & Bloom, 1997).
In theory, behavior is the net result of functional interac-
tions among a highly integrated network of subcortical–
subcortical and subcortical–cortical regions associated
with the human response to emotional stimuli. Because
this is the first study of developmental differences in func-
tional connectivity during face processing, we viewed
these analyses as exploratory. However, we were particu-
larly interested in amygdala connectivity with cortical and
subcortical temporal regions, such as the fusiform gyrus
and the hippocampus, given their associations with face
processing (Haxby et al., 2000).
Finally, to help interpret the potential roles of eye-
gaze patterns and the amount of time that individuals
spend looking at faces, we acquired eye movement data
outside of the MRI scanner using the same face task to
test whether developmental differences in neural func-
tion could relate to between-subject variability in eye
gaze during passive viewing. Eye movements are an im-
portant way of indexing participants’ focus of attention
while they passively view stimuli. Although we monitor
participants’ eyes during fMRI scanning to ensure that
they are looking at task stimuli, we conducted an ad-
ditional study using an eye movement tracker outside of
the scanner that permitted more precise quantification
of eye movement patterns while participants completed
the same task as used in the scanner. This allowed us to
determine with greater accuracy whether neural activa-
tion differences between adolescents and adults might
reflect differences in the location of eye gaze.
METHODS
Participants
All participants were deemed physically healthy by medical
history and physical examination. Absence of psychiatric
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illness was confirmed with a standardized, structured
psychiatric interview: the Kiddie Schedule for Affective
Disorders and Schizophrenia—Present and Lifetime ver-
sion (K-SADS-PL) (Kaufman et al., 1997) for adolescents
and the Structured Clinical Interview for DSM-IV (SCID)
(Spitzer, Williams, Gibbon, & First, 1992) for adults. Ad-
ditionally, all participants had average to above-average
IQ scores (?70) on the Wechsler Abbreviated Scale of
Intelligence (WASI) (Wechsler, 1999). Exclusion criteria
included history of psychiatric illness, neurological dis-
orders, head injury, or exposure to traumatic life events.
fMRI Sample
Thirty adults (17 men) aged 21 to 40 years (M = 31.06 ±
4.71) and 31 adolescents (16 boys) aged 9 to 17 years
(M = 14.22 ± 2.44) participated in the fMRI study. WASI
scores did not differ significantly between groups [adults:
M = 116.63 ± 11.57; adolescents: M = 116.94 ± 11.89;
t(59) = 0.10, p = .92] nor did sex distribution [x2(n =
61) = 0.13, p = .72]. Although the main contrast in this
study was the passive-viewing condition, all participants
were required to have behavioral data for at least 80%
of task trials from three attention-constrained conditions
and to exhibit less than 2.0 mm movement during fMRI
scanning. Of note, these criteria are stricter than those
used in our prior work, and we applied them here to
eliminate potential methodological factors that might
contribute to cross-study sources of variability (e.g.,
movement, inadequate behavioral data). Thus, only 15
of 17 adults and 10 of 17 adolescents originally included
in Monk et al. (2003) are included here. An additional
36 participants (15 adults, 21 adolescents) were studied.
Data from these latter participants have not been re-
ported previously. We combined these two samples to
determine whether our past result was reproducible in a
larger, more strongly powered sample by using methods
identical to our past study; this combination yielded a
considerably larger sample than used in any previous de-
velopmental fMRI study of face processing.
Eye Movement Sample
Sixteen adults (7 men) aged 23 to 36 years (M = 29.79 ±
4.42) and 18 adolescents (9 boys) aged 10 to 17 years
(M = 14.4 ± 2.12) participated in the eye movement
study outside of the scanner. The groups did not differ
on the WASI [t(30) = 0.35, p = .73] or by sex [x2(n =
34) = 0.01, p = .91]. Ten adults and 11 adolescents were
included in both the fMRI and eye movement studies.
Participants from the fMRI sample were invited back to
perform the task with an eye tracker following a mini-
mum period of 3 months to reduce the effects of prior
exposure to the faces. The goal of measuring eye move-
ments during the face task was to consider the degree
to which different patterns of eye-gaze location (e.g.,
difference in length of time looking at eyes vs. mouth)
might possibly account for the observed age differences
in brain engagement.
Procedure
Participants were recruited through flyers and local news-
paper advertisements. All adults and parents/legal guard-
ians of adolescents gave written informed consent to
participate in the study. All adolescents provided written
informed assent. Study participation was compensated
financially according to guidelines delineated by the Na-
tional Institute of Mental Health (NIMH). The NIMH
Institutional Review Board approved all study procedures.
Task and Stimuli
Participants were instructed to passively view a series of
adult faces. This viewing condition was interleaved with
three other conditions, during which participants were
instructed to attend to specific aspects of the faces. Dur-
ing the latter three conditions, participants used a five-
key response box developed by MRI Devices (Waukesha,
WI) to rate each face from 1 (not very) to 5 (extremely)
for the subjective fear it elicited (‘‘How afraid are you?’’),
the hostility it conveyed (‘‘How hostile is the face?’’),
and the size of a nonemotional physical feature (‘‘How
wide is the nose?’’). In the passive-viewing condition,
participants’ attention was unconstrained, such that they
simply viewed the faces without making any ratings.
Only the passive-viewing condition is discussed in this
study to allow for comparison with prior developmental
fMRI studies (Killgore & Yurgelun-Todd, 2004; Monk
et al., 2003; Thomas, Drevets, Whalen, et al., 2001). Data
on healthy adolescents and adults from the three other
task conditions are presented in McClure et al. (2004)
and Monk et al. (2003).
The task used a rapid, event-related design and was
presented as a 160-trial, 14.2-min single run. As depicted
in Figure 1, each of the four task conditions began with
an instruction screen presented for 3000 msec. Follow-
ing the instruction screen, 10 randomly ordered stimu-
lus event trials (8 faces, 2 fixation crosses) were each
presented for 4000 msec. The two fixation crosses were
included to avoid potential collinearity between stimuli.
By including one randomly occurring ‘‘null event’’ for
every four randomly occurring face-viewing events, this
method introduces random jitter between the face-
viewing events of interest. Including such randomly
interposed ‘‘null-event’’ fixation trials has been shown
to mitigate collinearity in event-related analyses (Burock,
Buckner, Woldorff, Rosen, & Dale, 1998). Following
each event, an interstimulus interval displayed a blank
screen that varied from 750 to 1250 msec (averaging
1000 msec within a 10-trial block). Unlike the random
jitter introduced by the 4000-msec ‘‘null events,’’ this
jitter of considerably shorter duration was not designed
to influence interpretations of the hemodynamic re-
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sponse, but rather to reduce the degree to which sub-
jects could predict onset of each face-viewing event. A
single iteration of the four conditions was completed in
212 sec (each condition averaged 53 sec). Each of the
four task conditions was repeated four times. Presenta-
tion order of task condition and of facial expressions was
randomized across participants.
Task stimuli included faces of 56 actors selected from
three standardized sets of gray-scale photographs depict-
ing different facial expressions (Gur, 2000; Tottenham &
Nelson, 2000; Ekman & Friesen, 1976). Each participant
viewed 32 different actors, with each actor randomly as-
signed to display one of four facial expressions (happy,
angry, fearful, and neutral). For example, a given actor
might be randomly selected to portray ‘‘anger’’ across the
four task conditions for one participant; this same actor
might be randomly chosen to portray ‘‘fear’’ for another
subject and ‘‘happiness’’ for yet another participant. This
design allowed us to control for variability in nonemo-
tional features of the actors (e.g., ethnicity, hair color).
Female actors were used in half of the photographs to
control for stimulus gender. A total of 32 ‘‘null-event’’
fixation crosses were included to facilitate data analysis.
Participants viewed stimuli through the Avotec Silent
Vision visual system (Stuart, FL). As a result, task com-
pliance could be monitored continuously by visually in-
specting participants’ gaze direction.
Because the current study focused on neural response
to fear faces, the contrasts of interest compared acti-
vation during the passive-viewing condition for fearful
faces (8 trials) versus neutral faces (8 trials) or fixation
crosses (32 trials). However, the study design also in-
cluded happy and angry faces to reduce habituation to a
particular emotion and thereby to increase the proba-
bility of detecting a response to fearful faces (Fischer
et al., 2003). The same stimuli and task were used both
in and out of the scanner.
fMRI Data Acquisition
Participants were trained in an MRI simulator prior to en-
tering the scanner. Participants were also administered
a practice version of the task to ensure understanding.
The practice version contained pictures of neutral facial
expressions that were not shown in the MRI scanner.
Scanning occurred in a General Electric Signa 3-Tesla
magnet (Waukesha, WI). Head movement was con-
strained by the use of foam padding. Following sagittal
localization and a manual shim procedure, whole-brain
blood oxygenation level-dependent (BOLD) functional
T2*-weighted images were acquired. An echo-planar,
single-shot, gradient-echo pulse sequence was used with
the following parameters: matrix size of 64 ? 64 mm,
repetition time (TR) of 2000 msec, echo time (TE) of
40 msec, field of view (FOV) of 240 mm, and voxel size
of 3.75 ? 3.75 ? 5 mm. Echo-planar images (EPI) were
acquired in 23 contiguous axial slices per brain volume
positioned parallel to the anterior commissure and pos-
terior commissure (AC–PC) plane. Following EPI data
collection, a high-resolution T1-weighted anatomical im-
age was acquired using a standardized magnetization-
prepared gradient-echo sequence to facilitate spatial
normalization. Parameters for anatomical image acquisi-
tion were as follows: one hundred eighty 1-mm sagittal
slices, matrix size of 256 ? 256, TR = 11.4 msec, TE =
4.4 msec, FOV = 256, number of excitations = 1, time
to inversion = 300 msec, bandwidth = 130 Hz/pixel,
33 kHz/256 pixels.
Figure 1. Task stimuli and design. Eight facial expressions (two of happy, fearful, angry, and neutral expressions) and two fixation crosses
were presented for 4000 msec individually within a given viewing condition block. For each condition, participants rated from 1 to 5 either
nose width of the face, their subjective fear of the face, or perceived hostility in the face, or viewed the stimuli passively. Condition instructions
were displayed for 3000 msec. Condition order was random across participants. Facial expressions displayed by the actors were also varied
randomly across participants. Intertrial interval showing a blank screen varied from 750 to 1250 msec. Each of the four viewing conditions
was repeated four times, yielding a single 160-trial run.
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Eye Movement Data Acquisition
Following task training and initial calibration of eye
position, eye movements during completion of the fa-
cial emotion task were measured by high-resolution
infrared oculography using an eye tracker with remote
pan and tilt optics, autofocusing lens, and magnetic
head tracker (Applied Science Laboratories [ASL] Model
504; Bedford, MA). The eye tracker was used to illumi-
nate and detect pupil and corneal reflection (CR). Gaze
location was identified based on relative positions of
pupil and CR and displayed as a set of cross hairs super-
imposed on the image from a video monitor showing
the participant’s field of view. The range within which
valid data can be obtained is 508 (± 258) horizontally
and 358 (+ 258 to ?108) vertically, with a 0.258 visual
angle of spatial accuracy. The eye tracker uses a 60-Hz
sampling rate. The distance between the center of the
task monitor and the participant’s eye was approxi-
mately 27 inches. A magnetic head tracking device,
autofocusing lens, and chinrest were used to minimize
head movement artifacts. Recordings were obtained in
a room lit by standard overhead fluorescent lights.
Data Analysis
Behavioral Data
Group differences in behavioral ratings and reaction times
recorded during the scan were analyzed with separate
repeated measures analysis of variance (ANOVA). The
ANOVA models included a between-group factor (age
group) and two within-group factors (attention state,
face type). Multivariate three-way interaction effects
were assessed using Wilks’ Lambda F statistic; univariate
effects were interpreted given a significant three-way in-
teraction effect. Because attention and passive-viewing
conditions were interspersed, analyzing behavioral data
collected during the attention conditions provided a
check that participants were prepared to attend to the
ratings after passive viewing.
Imaging Data
Preprocessing procedures and fMRI data analyses were
performed using the Statistical Parametric Mapping soft-
ware (SPM99, Wellcome Department of Cognitive Neurol-
ogy, London, England, 1999) and supplemental routines
written in Matlab 5.3 (The Mathworks, Natick, MA, 1999).
Imaging data were included for participants who moved
less than 2.0 mm in any plane as assessed with MedX
software (Medical Numerics, Sterling, VA). Preprocessing
procedures included corrections for slice timing and mo-
tion, coregistration to the anatomical data, and spatial
normalization to a Montreal Neurologic Institute (MNI)
T1-weighted template image supplied with SPM99.
Individual subject-level, event-related response ampli-
tudes were estimated using a general linear model for
each event type. Event types were defined based on
each face type crossed by each viewing condition; we
focused only on fearful and neutral faces during the
passive-viewing condition in order to interpret our re-
sults within the available literature. Fixation trials served
as an implicit baseline. The waveform used to model
event-related responses was a rectangular pulse (4 sec
duration) convolved with the hemodynamic response
function specified in SPM99. Contrast images were cre-
ated for each subject using pairwise comparisons of the
different event-related BOLD response amplitudes across
conditions. Before performing group-level analyses,
each contrast image was divided by the subject-specific
voxel time-series mean, generating values proportional
to percentage fMRI signal change (Zarahn, Aguirre, &
D’Esposito, 1997). These normalized contrast images
were then smoothed with an isotropic Gaussian kernel
(full-width half-maximum = 11.4) to reduce nonstationar-
ity in the spatial autocorrelation structure produced by
the previous step (Friston et al., 2000).
For all group-level analyses, the contrast images pro-
duced for each participant were fit to a second-level
random effects model. Using the full sample (n = 61),
we modeled the effect of age group (adult, adolescent)
and sample group (new, old) on amygdala activation
during passive viewing of fearful faces, yielding df = 57.
If our past amygdala results were consistent in these
groups, we would then remove the sample-group factor
to increase statistical power, which would result in df =
59. Because we included a subset of participants from
our past study, it was important to ensure that results in
the combined sample were not driven by different pat-
terns within either of the smaller independent samples.
Therefore, we examined amygdala activation during pas-
sive viewing of fearful faces in the previously studied,
newly acquired, and combined samples. Based on our
a priori hypotheses, the primary statistical analyses were
region of interest (ROI)-based. A Gaussian random field
threshold was used to determine significance of statisti-
cal comparisons. Activation had to survive the small vol-
ume correction Gaussian random field threshold (a =
.05) within prespecified ROIs (Worsley et al., 1996). The
primary analyses focused on the right and left amygdala
and the secondary analyses focused on the ACC, the OFC,
the hippocampus, and the fusiform gyrus. ROIs were de-
fined using standard, previously validated, anatomical
criteria. They were hand-traced on the single MNI tem-
plate, to which fMRI data were normalized, and then ap-
plied to all normalized brains at the group level (Szeszko
et al., 1999). MNI x, y, z coordinates are reported for
significant results.
Functional connectivity was measured for each sub-
ject as the correlated activity between the mean BOLD
signal of each amygdala ROI, as the seed region, and
each voxel across the whole brain (Pezawas et al., 2005;
Greicius, Krasnow, Reiss, & Menon, 2003). The mean EPI
time series was extracted, mean-centered, and then
1570 Journal of Cognitive NeuroscienceVolume 20, Number 9

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normalized (root-mean-square) over each amygdala ROI
throughout the entire face processing task (i.e., across
passive viewing, attention-directed ratings, and all facial
expressions). The resulting time series was entered into
a subject-level general linear model as the sole regressor
of interest against activation at each brain voxel. The
model included smoothed, spatially normalized whole-
brain EPI data. Both high- and low-pass filtering were
used (applying a 128 sec cutoff and the SPM-provided
canonical hemodynamic response function, respectively).
Based on past functional connectivity studies in adults
(Pezawas et al., 2005; Greicius et al., 2003) and an ado-
lescent study using the same face-viewing task as in the
present study (McClure et al., 2007), we applied a low-
pass filter to mitigate the effect of high-frequency noise
and to place our estimates within the typical fMRI con-
text of measuring neural activity indirectly via the BOLD
response. Regression coefficients, corresponding to the
voxelwise regressor of interest, were entered into a
group-level random effects model. t tests were used to
examine group differences in functional connectivity for
each amygdala ROI. Positive connectivity reflected in-
creased activity in both the amygdala and voxels in a
given region, whereas negative connectivity reflected in-
creased activity in the amygdala and decreased activity in
a given region or vice versa.
Eye Movement Data
Eye movement data were analyzed off-line with software
(EYENAL) provided by ASL. EYENAL calculates fixations
(stationary gazes) based on an algorithm that takes into
account the distance of the eye to the screen for each
subject. A fixation was defined as occurring when at least
six consecutive data samples (corresponding to about
100 msec duration) occur within a radius of less than
0.58 visual angle. Total time (msec) looking at the eye,
nose, and mouth regions of the face stimuli (i.e., total
fixation duration), respectively, were the main depen-
dent measures. Total fixation duration was analyzed with
a Group (adults, adolescents) ? Face region (eyes, nose,
mouth) ? Facial expression (fearful, neutral) repeated
measures ANOVA. Effects of interest were between-
group effects and interactions of group by face region
and by facial expression. Multivariate effects were as-
sessed using Wilks’ Lambda F statistic; significant mul-
tivariate effects were then interpreted by examining
within- and between-group effects.
RESULTS
Between-group Differences in Behavioral Data
Mean ratings and reaction times for each face type un-
der each attention condition are presented by group
in Table 1. No significant differences were found be-
tween adolescents and adults in their task ratings [F(6,
54) = 0.69, p = .66] or reaction times [F(6, 54) = 1.85,
p = .11].
Between-group Differences in
Amygdala Activation
In our planned contrast of new adolescent participants
versus new adult participants, when attention was un-
constrained during passive viewing, displays of fearful
versus neutral expressions were associated with greater
bilateral amygdala engagement in adolescents than in
adults [left amygdala: x = ?20, y = ?8, z = ?6; right
amygdala: x = 32, y = ?8, z = ?10; t(57) = 1.71, p =
.046]. Next, we examined the contrast of past adolescent
participants versus past adult participants from Monk
et al. (2003), who met the strict criteria for task perfor-
mance and movement (see fMRI Sample section). In
this analysis, we similarly found increased amygdala ac-
tivation in adolescents versus adults [left amygdala: x =
?16, y = ?8, z = ?8, t(57) = 1.79, p = .039; right
amygdala: x = 34, y = ?6, z = ?12; t(57) = 1.67, p =
.049]. Table 2 and Figure 2A and B present results from
age-group analyses combining new and past participants
(n = 61), which produced results similar to those ob-
tained in each independent sample.
In each age group separately, post hoc analyses
examined amygdala activation for fearful versus neutral
faces, fearful faces versus fixations, and neutral faces ver-
sus fixations. Adolescents showed increased amygdala
activation in response to fearful versus neutral faces.
Adults showed no differential response to fearful versus
neutral faces in either amygdala ROI. Analyses compar-
ing each facial expression during passive viewing, rela-
tive to fixations, showed significantly greater activation
in response to fearful faces versus fixations in the left
[x = ?22, y = ?6, z = ?12; t(59) = 2.71, p = .026] and
right amygdala [x = 18, y = ?2, z = ?18; t(59) = 3.54,
p = .003] in adolescents, but not in adults (Figure 2B).
Amygdala activation to neutral faces versus fixations was
not significant in either adolescents or adults.
Because we did not detect amygdala activation to fear-
ful versus neutral faces in adults, additional contrasts
were examined post hoc to ensure that amygdala acti-
vation was measurable in adults. We found that adults
had robust bilateral amygdala activation to all faces
versus fixations [left amygdala: x = ?18, y = ?6, z =
?14, t(59) = 3.80, p = .002; right amygdala: x = 24,
y = ?4, z = ?10, t(59) = 2.92, p = .02] as well as left
amygdala activation to angry faces versus fixations [x =
?20, y = ?4, z = ?16, t(79) = 3.54, p = .004]. However,
these analyses rely on more event replicates than analy-
ses restricted to passive viewing of fearful faces. As a
result, we conducted further analyses to determine the
degree to which our task was sensitive to adult amyg-
dala engagement within a specific attention condition
for specific face–emotion types. These analyses did doc-
ument successful amygdala engagement in adults. For
Guyer et al.1571

Page 8

example, while rating nose width, adults had significant
amygdala activation to fearful faces versus fixations [x =
?20, y = ?6, z = ?14, t(59) = 2.73, p = .025]. Thus,
the amygdala activation detected within adults varied
based on the emotion and attention condition in which
it was assessed.
Several post hoc analyses were also conducted to rule
out the possibility that greater amygdala activation in
the adolescents reflects greater general activation during
face or emotion processing rather than a specific re-
sponse to fearful faces, viewed passively. First, the com-
parison of amygdala activation to all faces versus baseline
fixations between adolescents and adults was not signif-
icant. Next, comparisons of amygdala activation to happy
and to angry facial expressions each contrasted against
baseline fixations between adolescents and adults were
also not significant.
Within-group Associations with Age
Regression analyses using curve estimation for linear,
quadratic, and cubic relationships were conducted to
examine associations of age (as a continuous variable)
Table 2. Regions of Interest with Significant Activation during Passive Viewing of Fearful Contrasted with Neutral Faces in
Adolescents versus Adults
Region Number of Voxels (kE)xyz t(59)p Correcteda
Right amygdala 146 16
?4
?8
?42
?16
?6
?14
3.34.007
Left amygdala62
?20
38
2.76 .027
Right fusiform face area/Brodmann’s area 373463.53 .024
Coordinates are reported in MNI space (Collins et al., 1998).
aAll voxelwise t values are significant at a = .05 based on a small volume correction for multiple comparisons within each region.
Table 1. Mean (SD) Ratings and Reaction Times for Each Face Type under Each Attention Condition for Adolescents and Adults
Rating (1–5)a
Reaction Time (msec)b
Adolescents (n = 31) Adults (n = 30)Adolescents (n = 31) Adults (n = 30)
How Hostile Is the Face?
Happy 1.08 (0.13) 1.05 (0.11) 1605.08 (380.69) 1292.58 (302.80)
Neutral 1.73 (0.59)1.73 (0.65) 1930.06 (412.27)1781.52 (496.06)
Fearful2.03 (0.81)2.14 (0.84) 2054.56 (471.69)2042.79 (465.02)
Angry3.41 (1.00)3.61 (0.68) 2015.25 (432.29)1982.83 (388.41)
How Afraid Are You?
Happy1.10 (0.17) 1.07 (0.14)1520.04 (398.27)1278.02 (260.16)
Neutral1.51 (0.61)1.62 (0.68) 1772.99 (377.25)1650.57 (447.91)
Fearful2.08 (1.00) 2.35 (0.86) 1834.04 (419.22)1976.03 (365.84)
Angry 2.62 (1.20)2.98 (0.92) 2011.01 (470.06)1981.84 (326.02)
How Wide Is the Nose?
Happy2.64 (0.46) 2.47 (0.54)2051.81 (451.85) 1895.34 (345.53)
Neutral 2.21 (0.59)2.29 (0.50) 1929.78 (359.07)1861.94 (395.75)
Fearful2.20 (0.51) 2.23 (0.52)1963.72 (355.44) 1952.11 (350.53)
Angry2.68 (0.50)2.57 (0.49)2107.99 (462.82)1998.82 (357.83)
Results from repeated measures ANOVA (Group ? Face type ? Attention state) for ratings: F(6, 54) = 0.69, p = .66 and reaction time: F(6, 54) =
1.85, p = .11.
aEach face type was rated from 1 to 5, 1 = low level, 5 = high level of hostility, fear, or nose width.
bHigher reaction time = more time taken to rate the face.
1572Journal of Cognitive Neuroscience Volume 20, Number 9

Page 9

with percent signal change in activation in the left and
right amygdala during passive viewing of fearful relative
to neutral faces. These analyses were conducted within
the adult and adolescent groups separately. Nonsignifi-
cant linear and curvilinear relationships between age
and left or right amygdala engagement were found in
both adolescents and adults.
Between-group Associations with Sex
Examination of sex-related developmental differences
focused on the main effect of sex and the interaction
between sex and group. These effects were not signifi-
cant, indicating that males and females had a similar
amygdala response to passively viewed fearful faces and
that neither adolescent males and females nor adult
males and females differed in amygdala engagement to
fearful versus neutral faces.
Between-group Differences in Additional ROIs
Analyses examined group differences in activation of the
ACC, OFC, hippocampus, and fusiform gyrus. Signifi-
cantly greater activation in the fusiform face area was
found in adolescents versus adults while passively view-
ing fearful versus neutral faces (Table 2, Figure 3). No
significant group differences were found in the other
ROIs for fearful versus neutral faces.
Between-group Differences in
Functional Connectivity
Patterns of functional connectivity in the combined
sample showed strong positive correlations between
activity in the left amygdala and bilateral medial OFC,
hippocampus, and fusiform gyrus, and a negative cor-
relation between activation in the left amygdala and
the right dorsal ACC (Table 3). Strong positive correla-
tions between activity in the right amygdala and caudal
ACC, hippocampus, and left fusiform gyrus were found,
as well as a negative correlation with activity in the
left inferior prefrontal cortex. These findings indicate
that task performance is associated with positive func-
tional connectivity between the amygdala and a distrib-
uted network of neural regions involved in face–emotion
processing.
Figure 2. (A) Greater
amygdala activation in
adolescents was evident
relative to adults when
passively viewing fearful
contrasted with neutral faces.
A high-resolution anatomical
overlay image in MNI space
was used as provided by
SPM. The figure displays a
coronal slice of the left
and right amygdala. Cross
hairs are positioned at MNI
coordinates x = 16 mm,
y = ?4 mm, z = ?16 mm
where the adolescent–
adult between-group
difference emerges. For visual
presentation purposes, the
threshold is set at p < .05
and a bilateral amygdala mask
was applied. (B) Display of left
(MNI coordinates: x = 30 mm,
y = 53 mm, z = 23 mm)
and right (MNI coordinates:
x = 48 mm, y = 55 mm,
z = 18 mm) amygdala voxel
activation reported as a mean
contrast value ± standard
error. Each contrast value is
derived from the percent
signal change during passive
viewing of fearful faces versus
fixation and of neutral faces
versus fixation within each
age group.
Guyer et al.1573

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A between-group difference was found in functional
connectivity between the left amygdala and bilateral
hippocampus, with stronger positive connectivity in
adults than in adolescents (Table 3, Figure 4A and B).
Activity in both the left (x = ?26, y = ?40, z = 0)
and right (x = 30, y = ?34, z = 2) hippocampus
showed significantly greater coupling with left amyg-
dala activation in adults as compared to adolescents.
No other between-group differences were evident with
a = .05.
Figure 3. Display of fusiform
voxel activation (MNI
coordinates: x = 59 mm,
y = 36 mm, z = 19 mm)
reported as a mean contrast
value ± standard error. Each
contrast value is derived from
the percent signal change
during passive viewing of
fearful vs. neutral faces, fearful
faces versus fixation and of
neutral faces versus fixation
within each age group.
Table 3. Voxels (MNI Coordinates) with Significant Connectivity Associations with the Amygdala
ContrastRegion Brodmann’s Area
Number of
Voxels (kE)xyz t(59) p Correcteda
Connectivity in All Participants, Independent of Group Status
Positive connectivity with
left amygdala
L medial OFC47231
?26
30
18
?6
?10
?2
?8
?14
?14
28
6.11.000
R medial OFC 47 6120 4.06.01
L hippocampus NA215
?22
16
?34
?30
?34
?36
36
8.21 .000
R hippocampus NA188 7.35 .000
L fusiform 36 138
?22
24
5.75.000
R fusiform361225.80.000
Negative connectivity with
left amygdala
R dorsal ACC3233614 4.87.001
Positive connectivity with
right amygdala
L caudal ACC32/6b
68 2
?4
?2
?8
?6
?54
34
504.92.001
R caudal ACC32/6b
474 484.33.005
L hippocampus NA194
?28
30
?16
?16
?16
9.44.000
R hippocampus NA16411.26 .000
L fusiform 37138
?34
?24
5.36.000
Negative connectivity with
right amygdala
L inferior PFC 454083.94 .01
Connectivity in Adults vs. Adolescents
Greater positive connectivity
with left amygdala
L hippocampus NA2
?26
30
?40
?34
03.49.026
R hippocampus NA192 4.09.005
L = left; R = right; OFC = orbito-frontal cortex; ACC = anterior cingulate cortex; PFC = prefrontal cortex; NA = Brodmann’s area not defined for
this subcortical region.
aAll voxelwise t values are significant at a = .05 based on a small volume correction for multiple comparisons within each region.
bRegion extends to the Supplementary Motor Area (BA 6).
1574Journal of Cognitive Neuroscience Volume 20, Number 9

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Between-group Differences in Eye Movements
There were no significant group differences or interac-
tions between group and facial expression or face region
in total fixation duration. A main effect of face region was
found [F(2, 64) = 24.50, p < .001], wherein all partic-
ipants spent more time looking at the eyes (M = 1.47,
SE = 0.10) compared to the nose (M = 0.93, SE = 0.08,
p < .01) and mouth (M = 0.57, SE = 0.07, p < .01), and
at the nose compared to the mouth ( p < .01). After re-
peating the fMRI analysis in the subgroup for which we
had eye movement data, the developmental difference
in amygdala activation for the passive viewing of fearful
versus neutral faces contrast remained significant. Thus,
the developmental differencein brain activation was found
in the subsample who exhibited no developmental differ-
ences in time spent looking at different facial regions.
DISCUSSION
The present study compared adolescents (9 to 17 years
old) and adults (21 to 40 years old) on amygdala re-
sponse to the presentation of fearful faces, focusing on
the effects of age and sex. Our current findings suggest
that maturation is associated with decreased amygdala
and fusiform engagement specifically when passively
viewing fearful faces and with increased amygdala–
hippocampus connectivity during face processing. This
is not only the largest developmentally focused fMRI
study on any aspect of face processing, but also the first
study to document developmental differences in func-
tional connectivity between the amygdala and activation
across the whole brain, as well as developmental differ-
ences in fusiform activation to fearful faces.
Our use of a previously studied task within a larger
sample adds to the growing literature on the develop-
ment of the amygdala response to fearful faces (Killgore
& Yurgelun-Todd, 2004; Monk et al., 2003; Killgore et al.,
2001; Thomas, Drevets, Whalen, et al., 2001; Baird et al.,
1999) by demonstrating the reproducible nature of de-
velopmental differences in amygdala function, an under-
taking that is particularly important in order to generate
and test new hypotheses based on established findings.
We found that passively viewing fearful faces was asso-
ciated with increased amygdala activation in adolescents
relative to adults, suggesting that amygdala involvement
in fearful-face processing varies between these two pe-
riods of development. This finding is consistent with
specific results from Monk et al. (2003), using the same
rapid event-related design, in our newly acquired sample,
in the strictly defined sample culled from Monk et al., and
in the large, combined sample including the new group
of participants and a subset of participants from Monk
et al. In particular, this developmental difference was
Figure 4. Connectivity
between the amygdala and
the hippocampus was evident.
(A and B) Adults showed
significantly greater connectivity
than adolescents between
activation in the bilateral
hippocampus (MNI coordinates
left: x = ?26 mm, y =
?40 mm, z = 0 mm; right:
x = 30 mm, y = ?34 mm, z =
2 mm) and the left amygdala
ROI across all trials of the
face-viewing task. Highlighted
areas in (A) indicate regions
where the differences in
activation between groups
were significant. Bar graphs
display mean contrast value ±
standard error.
Guyer et al.1575

Page 12

driven by greater amygdala engagement to fearful, but
not neutral, faces when compared to fixations, in ado-
lescents. Adults, on the other hand, showed no dif-
ferential amygdala response as a function of passively
viewing fearful versus neutral faces or versus fixations.
One possible explanation of the present results is that
greater amygdala activation in adolescents reflects greater
general activation during face processing rather than
a specific response to fearful faces. Post hoc fMRI analy-
ses conducted to address this possibility showed no de-
velopmental differences in amygdala activation to faces
in general or to other facial expressions. We also did not
find developmental differences in the amount of time
subjects spent looking at different facial regions while
passively viewing fearful and neutral faces, indicating
that adolescents and adults focus their eyes similarly on
distinct aspects of facial stimuli presented during pas-
sive viewing and do not focus their gaze differently as a
function of development. Thus, the developmental dif-
ference in amygdala response was specific to fearful fa-
cial expressions viewed passively. Amygdala activation to
fearful faces also did not correlate with age within either
the adult or the adolescent group, nor did it vary by sex.
Overall, the current study clarifies that, at least with an
event-related task design, the previously observed de-
velopmental difference in amygdala activation to fearful
versus neutral faces is reproducible, thus demonstrating
the reliability of our task paradigm. Within the larger
sample, we also sought to document the reliability of
our past findings in amygdala activation specifically
manifest during passive viewing of fearful versus neutral
faces, given that this comparison previously yielded the
only evidence of developmental differences in amygdala
response, albeit in different directions in two studies
(Monk et al., 2003; Thomas, Drevets, Whalen, et al.,
2001). The consistency of the developmental amygdala
finding may provide a benchmark from which new hy-
potheses and theories could be generated about the
role of the amygdala in face processing in both typical
and atypical development. Of note, however, despite
observation of a consistent developmental difference
across two independent samples, this study also re-
vealed many instances where adults and adolescents ex-
hibited similarly robust amygdala engagement. As such,
adolescent immaturity of amygdala function appears
to be relatively subtle: It occurs in an isolated set of
attention- and emotion-specific viewing conditions.
Two novel developmental findings also emerged from
the current study. First, adults had stronger amygdala–
hippocampus functional connectivity than did adoles-
cents. Second, adolescents had greater fusiform engage-
ment to fearful versus neutral faces than did adults. With
regard to functional connectivity, we found stronger cou-
pling between the amygdala and the hippocampus in
adults than in adolescents during the facial emotion view-
ing task. Functional connectivity, as assessed here, meas-
ures the temporal correlation of activity between different
brain regions. These new findings suggest that develop-
mental changes in the functional coupling between the
amygdala and the hippocampus are likely to occur in the
transition from adolescence to adulthood. Signals from
the amygdala facilitate identification and detection of
emotionally salient stimuli such as facial expressions. In
turn, memory storage and retrieval for emotionally salient
stimuli may be strengthened between these stages of
development through connections to hippocampal re-
gions (Dolcos, LaBar, & Cabeza, 2005; Richardson,
Strange, & Dolan, 2004; Kilpatrick & Cahill, 2003). In-
deed, evidence suggests that the relationship between
cognitive and affective systems continues to develop
during adolescence (Ernst et al., 2006; Nelson et al.,
2005; Casey, Tottenham, & Fossella, 2002; Casey et al.,
2000), and the degree to which emotion influences
face–memory formation may be related to pubertal
changes (Nelson et al., 2003; McGivern, Andersen, Byrd,
Mutter, & Reilly, 2002). Thus, one interpretation of the
present connectivity finding is that the greater amygdala–
hippocampus coupling in adults is due to maturational
changes in the degree to which the amygdala and hip-
pocampus interact in forming memories of emotional
faces. Among adults, emotional faces may elicit greater
amygdala–hippocampus engagement due to experience
and stronger memory formation of such stimuli. Although
both the amygdala and the hippocampus have been
found to participate in aversive memory, the mnemonic
role of the amygdala appears to be confined to simpler
functions such as stimulus emotion associations, whereas
the hippocampus is involved in more subtle and complex
processes such as context conditioning, spatial array
relations, and timing-related memory. Overall, the inter-
dependence and breadth of cognitive processes, such as
memory and attention, and affective processes, such as
emotion perception, may be stronger in the adult brain.
The present study is also the first to document a
developmentally based difference in fusiform gyrus re-
sponse to passively viewed fearful faces. Specifically,
activation in the fusiform gyrus was influenced by pas-
sively viewing fearful versus neutral faces more in ado-
lescents than in adults. These findings suggest that the
neural underpinnings of facial expression perception
instantiated in the fusiform face area may continue to
develop through adolescence. Our regionally specific
developmental findings indicated that adolescents en-
gage the amygdala and the fusiform gyrus when atten-
tion is unconstrained during passive viewing of fearful
faces more so than adults. Evidence suggests that the
amygdala has strong bidirectional connections with the
ventral visual processing stream (Amaral & Price, 1984)
and that increased fusiform activation is related to
greater input from the amygdala (Vuilleumier, Richardson,
Armony, Driver, & Dolan, 2004; Morris et al., 1998).
Additionally, structural changes in ventral posterior
brain regions have been documented across develop-
ment (Giedd et al., 1999) and the fusiform gyrus has
1576Journal of Cognitive Neuroscience Volume 20, Number 9

Page 13

been implicated in learning-based changes in face pro-
cessing ability (Gauthier, Tarr, Anderson, Skudlarski, &
Gore, 1999). Evidence of such structural and experience-
based changes suggests the presence of strong plasticity
in systems that process certain facial emotions (Gauthier
et al., 1999), a possibility consistent with the developmen-
tal difference we documented here in fusiform function.
Adolescence is associated with prominent changes in
social behavior and emotion regulation that are likely to
be related partly to hormonal shifts, and structural and
functional maturation in specific neural regions, such as
the amygdala, and their interconnections (Nelson et al.,
2005; Spear, 2000). As such, one explanation for the
greater amygdala and fusiform activation in adolescents
as compared to adults is that the emotional content
of stimuli engages neural systems to a greater degree
earlier in development. By adulthood, when control
over attention has increased and other higher-level cog-
nitive processes have matured, emotional as compared
to neutral stimuli may compete less for emotion pro-
cessing resources. That is, emotional stimuli may inter-
fere less with the ability of other neural regions to
engage in higher-level cognitive tasks later in develop-
ment. In adolescence, greater priority may be given
to resources that process fearful faces. Although the
current study focused on the passive-viewing condition
to isolate the influence of emotion rather than attention
manipulations on neural engagement, other work sug-
gests that changing the context of attention engages
neural systems differently across development and that
emotional stimuli can interfere with ongoing functions
(McClure et al., 2007; Perez-Edgar et al., 2007; Monk
et al., 2003; Nelson et al., 2003).
Although our primary developmental differences in-
volved amygdala and fusiform response to fearful faces,
we did not find age-related differences in amygdala–
fusiform coupling during the face processing task. How-
ever, positive connectivity between the left amygdala
and the fusiform face area [uncorrected p = .009; cor-
rected p = .56, t(59) = 2.44] was found within the whole
sample. This latter result is consistent with research
suggesting that modulatory interactions occur between
the amygdala and the fusiform gyrus (Amaral et al., 2003;
Catani, Jones, Donato, & Ffytche, 2003; Vuilleumier et al.,
2001), particularly during face–emotion processing.
We also did not find any developmental differences in
amygdala–prefrontal coupling despite strong connectiv-
ity in the entire sample between the amygdala and the
ACC or the amygdala and the OFC. Both groups dem-
onstrated similar levels of coupling between the amyg-
dala and these prefrontal regions involved in attention
allocation to emotionally salient stimuli (Adolphs, 2001;
Vuilleumier et al., 2001; Critchley, Elliott, Mathias, &
Dolan, 2000). Thus, across all attention–emotion condi-
tions of the face task, we did not find age-based differ-
ences in the functional connectivity between these
regions. Overall, our most robust developmental finding
emerges for the right amygdala, given that Monk et al.
(2003) found an age-group effect on the right amygdala
only and that we did not find similar age-group differ-
ences in ACC and OFC activation to passively viewed
fearful faces in either the new sample studied here or
in the combined, larger sample. Thus, some effects ini-
tially noted in Monk et al. occur in only a subset of the
participants studied here. As such, they represent less
consistent findings than the repeatedly documented
between-group differences in amygdala activation.
Of note, the developmental amygdala differences
reported here contrast with those of Thomas, Drevets,
Whalen, et al. (2001), who found greater amygdala
response to passively viewed neutral versus fearful faces
in children relative to adults. Clearly, several factors may
explain these opposing findings. Nevertheless, our pri-
mary hypothesis is that the use of different fMRI task
paradigms across studies remains the most influential
factor, given growing evidence documenting the strong
effects of task parameters on amygdala engagement.
Specifically, Thomas, Drevets, Whalen, et al. used a block
design, whereas Monk et al. (2003) used an event-related
design. In a block design, each experimental condition is
presented continuously for an extended time period and
the different conditions are alternated over time (e.g., a
block of fear faces, followed by a block of neutral faces).
This approach yields a measure of sustained neural acti-
vation within the block. In an event-related design, stimuli
are presented in multiple, independent-event types (e.g.,
event trials of different face emotion stimuli randomly
distributed throughout the task). The event-related de-
sign measures phasic neural activation in response to
stimuli for specific events. Past fMRI block-design studies
in adults demonstrated increased amygdala activation to
the presentation of fearful faces (Whalen et al., 2001;
Breiter et al., 1996; Morris et al., 1996), but also found
that the amygdala response can habituate to repeated
exposure to fearful faces (Whalen et al., 1998; Breiter
et al., 1996). Moreover, the stimulus duration also differs
dramatically across studies. Whereas the current study
presented faces for 4000 msec, requiring subjects to
respond to each face in the attention conditions, Thomas,
Drevets, Whalen, et al., Whalen et al. (1998), and Breiter
et al. (1996) all presented faces in rapid succession (each
for 500 msec), providing limited time for participants to
process individual faces. The repeated, rapid contiguous
presentation of fearful faces as in and Thomas, Drevets,
Whalen, et al. may have influenced amygdala habituation
differently than did the alternated, slow presentation of
fearful faces as in Monk et al., which may account for the
contradictory findings. Thus, although the findings from
these two studies are opposite, they are based on differ-
ent approaches to measuring functional neural activity,
and this difference is likely to be the most influential
factor on outcome. To better understand how amygdala
activation differs based on task design, future work is
needed that directly compares amygdala response to
Guyer et al.1577

Page 14

fearful faces using a block design and an event-related
design.
The present study has some methodological limita-
tions. We selected the passive-viewing context to be con-
sistent with past studies of amygdala response to fearful
faces. However, the passive-viewing condition does not
allow for experimental control over subjects’ attention,
possibly leading to individually generated cognitive activ-
ity during face processing. Indeed, past fMRI work sug-
gests that cognitive processes can attenuate amygdala
response (Hariri, Mattay, Tessitore, Fera, & Weinberger,
2003; Hariri, Bookheimer, & Mazziotta, 2000). The eye
movement data we collected out of the scanner do not
support this possibility because they indicate no differ-
ences between adolescents and adults in the amounts
of time spent looking at different facial regions (i.e.,
eyes, nose, mouth) or facial expressions (i.e., fearful vs.
neutral). Despite inherent limitations of passive viewing,
using conditions implemented previously in multiple
studies in adults is advantageous given the relative scar-
city of data on adolescents. Further, because passive-
viewing tasks have consistently been effective at evoking
amygdala responses to fearful faces, they offer an estab-
lished method for examining the questions of interest
in the present study.
A second limitation concerns the relatively indirect im-
plications that our between-group ROI-focused findings
carry for our findings from the functional connectivity
analysis. Although the former analysis focused on a sub-
set of data, generated in two face–emotions passively
viewed, the latter analysis focuses on activity across the
entire task. As noted above, we focused on specific
events for our ROI analysis, based on prior findings in
Monk et al. (2003). For our functional connectivity analy-
sis, we relied on methods that have been most consis-
tently implemented in previous work (McClure et al.,
2007; Pezawas et al., 2005). However, recent advances
in functional connectivity analysis approaches also de-
lineate methods for examining changes in connectivity
during one or another event class.
Future studies, using alternative task designs and
statistical approaches, may allow for tighter integration
between ROI-based and functional connectivity-based
analytic approaches, with each approach focusing on
the same specific event classes. Certainly, the current
task has proved useful in generating insights into the
manner in which face–emotions and attention states in-
teract. Nevertheless, as discussed below, when consider-
ing novel functional connectivity approaches, efforts to
extend current insights on amygdala development might
best be devoted to future studies using novel tasks that
address limitations in the current task. For example, be-
cause the current study demonstrates the importance
of passive viewing, future functional connectivity studies
might implement designs that only collect data in this
one attention state while focusing on changes in con-
nectivity during specific face–emotion events. Exclusive
focus on this one attention state would allow a novel
task of similar length to the task used here to yield far
more data in the most relevant classes of events than
was possible in the current study.
A third limitation of the present study relates to the
age range of our sample. There was a gap in study par-
ticipants between the ages of 17 and 21 years, making
it difficult to interpret potential changes in amygdala
function that may occur across the very early ages of
adulthood. In particular, the present findings do not al-
low for a clear demarcation of a specific age at which
changes in amygdala activation to fearful faces may ini-
tiate. It is possible that, with increased age, and thus,
experience, the hippocampus and associated memory
functions may play a modulatory role over the amygdala;
some support for this may stem from our finding of
greater amygdala–hippocampus connectivity later in de-
velopment. Another age-related limitation involves clas-
sifying the adolescent group solely based on age in
years. It may be fruitful in future research to also define
human adolescence based on pubertal status. The wide
range of pubertal stages requires a study to examine a
large number of adolescents who fall within each stage;
unfortunately, the current study did not have enough
data available regarding pubertal status to make mean-
ingful comparisons across puberty stages. We also found
that within-group variability in age did not relate to
amygdala activation to fearful faces linearly or curvili-
nearly. Although our result is consistent with work ex-
amining age effects on amygdala function in adolescence
(Yurgelun-Todd & Killgore, 2006), other research has
documented nonlinear relationships between age and
the size of certain brain structures, such as the prefrontal
cortex, that undergo protracted development from ages
4 through 22 years (Lenroot & Giedd, 2006). Samples
with a sufficiently large number of individuals to be di-
vided into bins of narrowly defined age groups, across
specified periods of development, are needed to under-
stand more fully how age is associated with changes in
amygdala function across development.
Finally, the present study failed to detect amygdala ac-
tivation in adults while they passively viewed fearful versus
neutral faces. This result runs counter to the observation
from adult fMRI block-design studies that consistently
demonstrated amygdala activation to fearful faces (Breiter
et al., 1996; Morris et al., 1996), although not all previous
block-design studies of facial fear perception in adults
have found amygdala activation (Sprengelmeyer, Rausch,
Eysel, & Przuntek, 1998). Of note, amygdala engagement
in passive-viewing, event-related fearful-face presentation
paradigms, such as the one used in the current study,
occurs less consistently than in block-design paradigms,
as exemplified by a recent event-related fMRI study in
adults that failed to detect amygdala activation to fearful
faces (Deeley et al., 2007). It is possible that a failure to
detect amygdala activation to fearful versus neutral faces
in adults may reflect the small number of event-replicates
1578Journal of Cognitive Neuroscience Volume 20, Number 9

Page 15

in each attention condition, each of which included only
eight trials of fearful faces. As noted above in the dis-
cussion of functional connectivity approaches, future stud-
ies should consider the advantages and disadvantages
of implementing studies with novel task parameters. Spe-
cifically, the inclusion of a greater number of fearful face
trials might engage the adult amygdala response on this
condition; likewise, more trials could alter the adolescent
response. Although alternative designs or contrasts may
be more sensitive to adult amygdala response to fearful
faces, one must also consider the possibility that these
different approaches could potentially yield reduced sen-
sitivity to developmental differences in amygdala activa-
tion through distinct, task-related effects on temporal
processes such as fatigue, learning, or habituation.
The number of task trials cannot entirely account for
the lack of adult amygdala engagement to fear-faces
viewed passively. Indeed, in analyses of the nose-rating
attention state, we did detect amygdala activation in
adults in a similarly constructed contrast using eight
fearful faces. Regardless, as noted above, future studies
would benefit from a paradigm with more event repli-
cates across fewer attention states. We used a relatively
low number of task trials in the current study in order
to employ the identical task paradigm from our prior
study. This paradigm was designed originally with rela-
tively few within-condition stimulus replications, in part,
so that it would be tolerable to younger participants and
would generate data across four attention conditions.
This approach has been effective in prior research for
eliciting amygdala activation in adolescents recruited
from different sources and who are either healthy or
at risk for or currently affected with a mental disorder
(Monk et al., 2003, 2008; McClure et al., 2007; Perez-
Edgar et al., 2007; Roberson-Nay et al., 2006; Nelson
et al., 2003) and in two past developmental studies
(Monk et al., 2003; Nelson et al., 2003). Although we
have achieved within-lab reliability with this face-viewing
task design, it remains important for other research
groups to use the same task design to increase the com-
parability and generalizability of findings across studies
and laboratories.
Despite these limitations, the present findings inform
our understanding of fundamental changes in neuro-
physiological function across development. Overall, the
main results suggest that there are different balances of
neural input at different periods across human develop-
ment. In adolescence, there may be a greater tendency
toward using neural resources for facial identification
and perception, whereas in adulthood, there may be
a greater bias toward using resources for memory of
emotional information. For example, the greater amyg-
dala and fusiform activation in adolescents than in adults
suggests that these regions utilize neurophysiological
input to a greater degree during the perception of fear-
ful faces earlier in development. The amygdala and the
fusiform gyrus are important for quick detection and
recognition of emotionally salient stimuli (LeDoux, 2000;
Whalen et al., 1998), and the amygdala additionally is
implicated in learning and generating responses to such
stimuli (LeDoux, 2000; Bechara, Damasio, Damasio, &
Lee, 1999) and in modulating their consolidation into
memory (Hamann, Ely, Grafton, & Kilts, 1999; Cahill &
McGaugh, 1998). Activations of these regions may reflect
a perception of fearful faces as more novel in adoles-
cence than in adulthood, possibly leading to greater in-
put via these neural regions when processing fearful
faces than during adulthood. Perhaps through enhanced
cognitive control and memory function that comes with
age, adults by comparison use less input from the amyg-
dala and the fusiform gyrus to perceive fearful faces.
The connectivity findings indicate that the neural cir-
cuitry underlying memory of facial emotion changes
between adolescence and adulthood, suggesting that
maturation of adult-level memory of emotional faces
involves the functional integration of both the amygdala
and the hippocampus, and perhaps a greater tightening
of the communication between these two regions by
adulthood. As this is the first developmental study to
measure the functional connectivity of neural responses
to emotional faces, these findings provide a foundation
from which other studies of connectivity may build and
underscore the need for more research on patterns of
functional connectivity during face processing across de-
velopment to increase our understanding of the brain–
behavior intersection.
There are several possible extensions of the present
study. First, the influence of task design remains an im-
portant methodological question, and more work is
needed to tease apart how event-related and block task
designs may influence amygdala response to fearful
faces in different ways. Although it is beyond the scope
of the present study, future studies could compare the
time course of amygdala response between event-related
and block task designs to understand possible task-
related differences in the amygdala habituation process
found to occur while viewing fearful faces. Second,
further developmental investigations will be needed to
monitor location of gaze during performance of this task
in the scanner. Simultaneously tracking eye movements
and measuring functional brain changes during face
viewing may clarify neural mechanisms underlying de-
velopmental differences in processing facial emotion.
A recent study indicates that a deficit in fear recognition
in a patient with bilateral amygdala damage stems from
an inability to use information from the eye region in
faces (Adolphs et al., 2005) and other work has found
amygdala response to direct eye contact to be an im-
portant social signal (Kawashima et al., 1999). Third,
one direction for the functional connectivity work pre-
sented here would be to use other analytical approaches
to infer directionality of influence between functionally
connected regions during facial expression processing
(Ramnani, Behrens, Penny, & Matthews, 2004). Finally, it
Guyer et al.1579