Adolescence has been characterized by risk-taking behaviors that can lead to fatal outcomes. This study examined the neurobiological
driven by different time courses of development for these regions. Accumbens activity in adolescents looked like that of adults in both
frontal cortex activity in adolescents looked more like that of children than adults, with less focal patterns of activity. These findings
suggest that maturing subcortical systems become disproportionately activated relative to later maturing top–down control systems,
Onset of substance abuse often occurs during the increased risk-
taking period of adolescence (Silveri et al., 2004). Little is known
to date about neurobiological factors that may predispose ado-
regions have been implicated in reward (Knutson et al., 2001;
Knutson, 2005), and addiction (Hyman and Malenka, 2001;
Volkow et al., 2004), but less is known about the development of
that adolescence is a developmental period of increased respon-
we examined whether differences in the development of subcor-
orbital frontal cortex (OFC)] regions may characterize this pe-
riod of development to help explain the increase in risk-taking
Adolescence is characterized by continued structural and
functional development of frontostriatal circuitry implicated in
behavioral regulation. Periadolescent rats show increases in
reward-related dopamine transmission in the striatum (Laviola
et al., 1999), and nonhuman primates show increased dopami-
Lewis, 1994, 1995). Human imaging studies show frontostriatal
2005) that seem to parallel increased cognitive control (Casey et
al., 1997; Rubia et al., 2000; Luna et al., 2001; Luna and Sweeney,
2004; Steinberg, 2004). These changes appear to show activation
shifts of prefrontal regions from diffuse to more focal recruit-
2002; Durston et al., 2006). Neuroimaging studies cannot defin-
itively characterize the mechanism of such developmental
changes (e.g., synaptic pruning, myelination). However, these
volume and structural changes may reflect refinement and fine-
tuning of reciprocal projections from these brain regions during
maturation. Thus, this interpretation is only speculative.
Recently, neuroimaging studies have begun to examine
reward-related processing in adolescents and have shown NAcc
activation as shown in adults (Bjork et al., 2004; May et al., 2004;
Ernst et al., 2005). However, the results have been mixed as to
how adolescents and adults differ in activity. These studies have
focused primarily on the region of the accumbens rather than
OFC in examining changes. Furthermore, little attention has
been given to characterizing NAcc and OFC development from
childhood through adulthood. Tracking this development pro-
vides additional constraints on whether changes reported in ad-
olescence are specific to this period of development or reflect
maturational linear changes.
to examine behavioral and neural responses to reward value ma-
National Institute of Mental Health Grant P50 MH62196 (B.J.C.), and National Eye Institute Grant T32 EY07138
TheJournalofNeuroscience,June21,2006 • 26(25):6885–6892 • 6885
nipulations across development. We fo-
cused on the NAcc and OFC given previ-
ous reports in animal (Hikosaka and
Watanabe, 2000; Pecina et al., 2003), im-
aging (O’Doherty et al., 2001; Zald et al.,
Malenka, 2001) studies implicating them
in reward-related learning. Based on ro-
dent models (Laviola et al., 1999; Spear,
children and adults, adolescents would
show an exaggerated accumbens response
suggestive of refined focal activations
within the accumbens during this period,
in concert with less mature activations in
top–down PFC regions.
Participants. Sixteen children (seven females;
aged 7–11, with mean age of 9.8 years), 13 ado-
(six females; aged 23–29, with mean age of 25
years) participated in the fMRI experiment. A
separate statistical analysis on the adult data was reported previously
(Galvan et al., 2005). Three children and one adolescent were excluded
from the analysis due to excessive motion (?2 mm). Motion was ?0.5
voxels (1.56 mm) in any direction for two subjects (one child and one
adult) included in the analysis. Eliminating these subjects from the anal-
ysis did not change the results and the different age groups did not differ
significantly in in-plane motion (adults: x ? 0.48, y ? 0.76, z ? 0.49;
each gave informed consent (parental consent and child assent for ado-
lescents and children) for a protocol approved by the Institutional Re-
view Board of Weill Cornell Medical College of Cornell University. The
before the experiment, in which they were exposed to the sounds they
would hear during the actual experiment.
a delayed response two-choice task previously used in nonhuman pri-
al., 2005) in an event-related fMRI study (Fig. 1). In this task, three cues
(counterbalanced) were each associated with a distinct reward value.
Subjects were instructed to press either their index or middle finger to
indicate the side on which a cue appeared when prompted, and to re-
spond as quickly as possible without making mistakes.
The stimulus parameters were as follows. One of three pirate cartoon
images was presented in pseudorandom order on either the left or right
side of a centered fixation for 1000 ms (Fig. 1). After a 2000 ms delay,
their right index finger if the pirate was on the left side of the fixation or
or large amount of coins was presented in the center of the screen (1000
a 12 s intertrial interval (ITI) before the start of the next trial. Total trial
length was 20 s. Subjects were not rewarded if they failed to make a
response or if they made an error; in both cases, they received an error
message at the time they would normally receive reward feedback.
Subjects were guaranteed $50 for participation in the study and were
told they could earn up to $25 more, depending on performance (as
amounts were distinctly different from one another, the exact value of
subjects reported counting the money after each trial and we wanted to
avoid this possible distraction. Stimuli were presented with the inte-
grated functional imaging system (PST, Pittsburgh, PA) using a liquid
crystal display video display in the bore of the magnetic resonance (MR)
scanner and a fiber optic response collection device.
The experiment consisted of five runs of 18 trials (six each of small,
medium, and large reward trials), which lasted 6 min and 8 s each. Each
end of each run, subjects were updated on how much money they had
earned during that run. The amount of money earned was consistent
across all subjects and all received a continuous schedule of reinforce-
ment (rewarded on 100% of trials). Before beginning the experiment,
tion. They received detailed instructions that included familiarization
with the stimuli used. For instance, subjects were shown the three cues
and three reward amounts they would be seeing during the experiment.
They were not told how the cues related to the rewards. We explicitly
emphasized that there were three amounts of reward, one being small,
in the experiment because the number of coins in the stimuli increases
between specific stimuli and reward amounts, when asked explicitly
about this association during debriefing of the subject at the end of the
Image acquisition. Imaging was performed using a 3T General Electric
(Milwaukee, WI) MRI scanner using a quadrature head coil. Functional
scans were acquired using a spiral in and out sequence (Glover and
Thomason, 2004). The parameters included the following: repetition
time (TR), 2000 ms; echo time (TE), 30 ms; 64 ? 64 matrix; 29 5 mm
coronal slices; 3.125 ? 3.125 mm in-plane resolution; flip, 90° for 184
repetitions, including four discarded acquisitions at the beginning of
each run. Anatomical T1-weighted in-plane scans were collected (TR,
500; TE, min; 256 ? 256; field of view, 200 mm; 5 mm slice thickness) in
the same locations as the functional images in addition to a three-
dimensional data set of high-resolution spoiled gradient-recalled acqui-
sition in a steady state images (TR, 25; TE, 5; 1.5 mm slice thickness; 124
Image analysis. The Brainvoyager QX (Brain Innovations, Maastricht,
The Netherlands) software package was used to perform a random-
cessing procedures were performed on the raw images: three-
dimensional motion correction to detect and correct for small head
movements by spatial alignment of all volumes to the first volume by
6886 • J.Neurosci.,June21,2006 • 26(25):6885–6892Galvanetal.•AdolescentDevelopmentofRewardCircuitry
rigid body transformation, slice scan time correction (using sinc inter-
polation), linear trend removal, high-pass temporal filtering to remove
nonlinear drifts of three or fewer cycles per time course, and spatial data
smoothing using a Gaussian kernel with a 4 mm full width at half-
maximum. Estimated rotation and translation movements never ex-
ceeded 2 mm for subjects included in this analysis. Functional data were
coregistered to the anatomical volume by alignment of corresponding
and were then transformed into Talairach space. Functional voxels were
of 1 mm3during Talairach transformation. The NAcc and OFC were
defined by Talairach coordinates in conjunction with reference to the
Duvernoy brain atlas (Talairach and Tournoux, 1988; Duvernoy, 1999).
The initial omnibus general linear model (GLM) analysis included all
determine regions sensitive to reward (NAcc and OFC). To ensure that
statistical analyses were performed on the same regions for each age
group, separate GLM analyses were performed. Each group showed ac-
Localization of these regions was further confirmed for each group sep-
arately by Talairach coordinates in conjunction with reference to the
Duvernoy brain atlas (Talairach and Tournoux, 1988; Duvernoy, 1999)
as described above. Previous methodological work has shown that the
stereotactic registration and time course of the hemodynamic response
across the ages tested in the current study are not dissimilar (Burgund et
al., 2002; Kang et al., 2003). Subsequent analysis and post hoc contrasts
were performed on the regions identified with this initial omnibus GLM
for all groups together and then separately for each group. Last, a con-
monly activated across all three groups, in the NAcc and OFC (supple-
mental Fig. 1, available at www.jneurosci.org as supplemental material).
The regions of interest identified in the conjunction analysis overlapped
with those identified with the initial omnibus GLM, and post hoc tests
confirmed similar effects as those obtained with the above analyses.
In the whole-group analysis, the omnibus GLM was comprised of all
runs across the entire trial (5 runs ? 37 subjects ? 185 z-normalized
functional time courses) and was conducted with reward magnitude as
the primary predictor. The predictors were obtained by convolution of
an ideal boxcar response (assuming a value of 1 for the volume of task
presentation and a volume of 0 for the remaining time points) with a
linear model of the hemodynamic response (Boynton et al., 1996) and
used to build the design matrix of each time course in the experiment.
error trials. The total number of correct trials for each group was as
follows: 1130 for children (n ? 13), 1061 for adolescents (n ? 12), and
1067 for adults (n ? 12). The fewer number of trials for children was
corrected by including an additional child subject.
Post hoc contrast analyses were then performed based on t tests on the
? weights of predictors to identify a region of interest in the NAcc and
OFC. Contrasts were conducted with a random-effects analysis. Time
series and percent changes in MR signal, across each data point of the
duration was 20 s), were calculated using event-related averaging over
significantly active voxels obtained from the contrast analyses. The cal-
culation of number of voxels recruited in each
region by age group was based on the GLM
analyses conducted on each group described
Corrections for multiple comparisons were
based on Monte Carlo simulations, which were
run using the AlphaSim program within AFNI
ity thresholds to achieve a corrected ? level of
level of p ? 0.05 in the OFC was based on a
stringent threshold of p ? 0.01 across groups.a
The omnibus GLM analysis of the imaging data identified the
NAcc [right (x ? 6, y ? 5, z ? ?2) and left (x ? ?8, y ? 6, z ?
?2)] and right OFC (x ? 46, y ? 31, z ? 1) depicted in Figure 2,
A and C, with reward value as the primary predictor, across all
subjects and runs of the experiment for the entire trial (18 s),
trial (e.g., reward vs baseline contrast). Within these regions,
there was a main effect of reward value (F(2,72)? 8.424; p ?
0.001) (Fig. 2B) in the NAcc, but not in the OFC (F(2,72)? 1.3;
p ? 0.44) (Fig. 2D). Post hoc t tests on the main effect of reward
for the NAcc confirmed significant differences between the large
and small (t(36)? 4.35; p ? 0.001), large and medium (t(36)?
2.01; p ? 0.05), and medium and small (t(36)? 2.09; p ? 0.04)
rewards, with greater activation for greater rewards.
Developmental differences in magnitude and extent of activity
Because the focus of this study was on how reward influences
neural recruitment across development, we examined develop-
mental differences in the magnitude and extent of accumbens
activity was calculated as a percent change in MR signal averaged
across the first 18 s of the trial relative to the intertrial interval of
across the entire experiment (90 trials ? 900 scans). This calcu-
lation was performed for each group. The extent of activity was
calculated as the volume of activity (number of voxels) across
runs, by group, using the same contrast.
Magnitude of activity. In the accumbens and OFC, there were
significant developmental differences in percent change in MR
signal (F(2,22)? 6.47, p ? 0.01; F(2,22)? 5.02, p ? 0.01, respec-
tively) (Fig. 3A,B). In the accumbens, adolescents showed the
ences between adolescents and children (t(11)? 4.2; p ? 0.03)
and between adolescents and adults (t(11)? 5.5; p ? 0.01) in
magnitude of accumbens activity. In the OFC, post hoc tests con-
firmed significant differences between children and adolescents
(t(11)? 4.9; p ? 0.01) and children and adults (t(11)? 3.99; p ?
0.01). Thus, adolescents showed enhanced activity in the accum-
bens and this pattern differed from that in the OFC and from
children and adults.
Galvanetal.•AdolescentDevelopmentofRewardCircuitryJ.Neurosci.,June21,2006 • 26(25):6885–6892 • 6887
the largest volume of activity in the accumbens for children
(503 ? 43 interpolated voxels) relative to adolescents (389 ? 71
interpolated voxels) (t(22)? 4.2; p ? 0.05) and adults (311 ? 84
and adults did not differ (t(22)? 0.87; p ? 0.31). For the OFC,
children (864 ? 165 interpolated voxels) (t(22)? 7.1; p ? 0.01)
and adolescents (671 ? 54) (t(22)? 5.8; p ? 0.01) showed the
largest extent of activity relative to adults (361 ? 45 voxels) (Fig.
3D), but there were no significant differences between children
and adolescents (t(22)? 1.8; p ? 0.07). This pattern of activity
Developmental differences in temporal processing of reward value
To examine differential changes in neural recruitment through-
tions with, time (early, middle, and late trials) on MR signal
in the interaction of time by group by reward in the accumbens
(F(8,136)? 3.08; p ? 0.003) and less robustly in the OFC
(F(8,136)? 2.71; p ? 0.02). This interaction was driven primarily
by changes occurring during the late trials of the experiment (for
changes as a function of early, middle, and late trials, see supple-
mental Fig. 2, available at www.jneurosci.org as supplemental
MR signal as a function of small, medium, and large reward val-
an exaggerated change in accumbens activity in adolescents rela-
occurs ?5–6 s after the response and the point in which all three
graphically in Figure 7 for clarity (for change in OFC activity at
this time point for all three age groups, see supplemental Fig. 3,
available at www.jneurosci.org as supplemental material).
The effects of time on task and reward value were tested with a 5
(runs) ? 3 (small, medium and large reward) ? 3 (group)
ANOVA for the dependent variables of mean reaction time for
correct trials and mean accuracy. There were main effects of re-
ward value (F(2,72)? 9.51; p ? 0.001) and group (F(2,220)? 4.37;
p ? 0.02) and significant interactions of reward by time
(F(8,288)? 4.176; p ? 0.001) and group by reward by time
(F(16,272)? 3.01; p ? 0.01) for mean reaction time. The main
effect of reward showed that, across all subjects, mean reaction
t(36)? 3.8; p ? 0.001) relative to medium (mean, 556.89; SD,
180.53) or small reward (mean, 552.39; SD, 180.35). The signifi-
cant interaction of reward by time was driven primarily by the
experiment (Fig. 8). Adolescents were significantly faster to the
significant differences in mean reaction time to the small, me-
dium, or large rewards. There were no significant correlations
tion differences between children and adolescents and adolescents and adults in A; greater
activation in children relative to adolescents and adults in B; greater volume of activity in
children relative to adolescents and adults in C; and greater volume of activity in children
6888 • J.Neurosci.,June21,2006 • 26(25):6885–6892Galvanetal.•AdolescentDevelopmentofRewardCircuitry
between mean reaction time or accuracy and accumbens or or-
0.40), group (F(2,220)? 0.73; p ? 0.80), or time (F(4,476)? 0.57;
accuracy across reward values (children: small, 96%; medium,
98%; large 96%; adolescents: small, 98%; medium, 99%; large,
99%; and adults: small, 98%; medium, 99%; large, 99%).
This study examined behavioral and neural responses to reward
value manipulations across development. Our findings support
NAcc and OFC recruitment, regions previously implicated in
reward processing (Knutson et al., 2001) and addiction (Volkow
2003) and previous developmental imaging (Ernst et al., 2005)
studies of enhanced accumbens activity during adolescence.
These findings suggest that different developmental trajectories
for these regions may relate to the increased impulsive and risky
behaviors observed during this period of development.
Enhanced accumbens activity was paralleled by a refined pattern
of activity for adolescents relative to children, but similar to
adults. In contrast, adolescents showed more diffuse OFC re-
cruitment more similar to children than adults. We interpret
these data to suggest that the NAcc development may precede
that of the OFC during adolescence. Protracted development of
relative to children or adults for the small and large reward trials. Error bars indicate SEM.
Galvanetal.•AdolescentDevelopmentofRewardCircuitryJ.Neurosci.,June21,2006 • 26(25):6885–6892 • 6889
prefrontal regions, with a transition from
diffuse to focal recruitment is consistent
et al., 1999; 2003; Gogtay et al., 2004) and
fMRI studies (Casey et al., 1997, 2002;
prefrontal development (Casey et al.,
Developmental changes in volume of
of known developmental processes (e.g.,
dendritic arborization, synaptic pruning,
myelination) occurring during this pe-
riod. However, neither fMRI nor MRI
provide a level of analysis with which to
such changes. The volume measures were
used in part to constrain the interpreta-
tion of magnitude differences, but we can
only speculate that our changes in volume
OFC reflect a fine-tuning of this circuitry
with experience and development.
Differential recruitment of frontostriatal regions has been re-
ported across several developmental fMRI studies (Casey et al.,
2002; Monk et al., 2003; Thomas et al., 2004). Typically, these
findings have been interpreted in terms of immature prefrontal
tical regions. Given evidence of prefrontal regions in guiding ap-
propriate actions in different contexts (Miller and Cohen, 2001)
immature prefrontal activity might hinder appropriate estima-
thus be less influential on reward valuation than the accumbens.
This pattern is consistent with previous research showing ele-
vated subcortical, relative to cortical activity when decisions are
Furthermore, accumbens activity has been shown to positively
correlate with subsequent risk-taking behaviors (Kuhnen and
One goal of this study was to characterize reward learning across
development. Adults showed behavioral distinction to the three
cues, with fastest responses to the large reward cue. Adolescents
showed less discrete responses and children show little to no
learning. Slower learning across development parallels the imag-
ing results of protracted OFC development that may hinder as-
sociative learning between predictive events and reward out-
Watanabe, 2000; Chudasama and Robbins, 2003; Cetin et al.,
2004; Hosokawa et al., 2005) and human imaging (Elliott et al.,
2000; O’Doherty et al., 2003; McClure et al., 2004; Cox et al.,
2005; Galvan et al., 2005) studies showing the role of the OFC in
learning and representing links between predictive events (stim-
uli and responses) and reward outcomes in optimizing choice
Few imaging studies of reward to date have been able to show
et al., 2004; Delgado et al., 2005; Galvan et al., 2005). Here, our
data suggest that reward-related neural responses influence be-
havioral output. Minimal behavioral variability might have pre-
cluded previous authors from determining whether different re-
to tease apart behavioral differences might be because our para-
digm was designed to maximize behavioral responses and learn-
ing by using a continuous reinforcement schedule (Dickinson
and Mackintosh, 1978; Gottlieb, 2004, 2005). Animal studies
show faster learning with continuous relative to intermittent re-
inforcement schedules (Gottlieb, 2004) that may have explained
the faster responses to large reward trials across subjects and the
Reward preference varies based on the reward context (Tversky
and Kahneman, 1981; Tremblay and Schultz, 1999). Evidence
from our study supports the notion that relative reward prefer-
ence is exaggerated during adolescence: adolescents showed an
in activity to the small reward relative to other rewards and to
other ages. Adolescents report greater intensity of positive feel-
ings and more positive BOLD signal intensity than adults during
a win condition (Ernst et al., 2005). The adolescents may have
striatal activity (Davidson et al., 2004). This finding corre-
sponded to a slowing of reaction time from early to late trials for
the smaller rewards, providing additional evidence that this con-
Together, these findings imply that reward perception might be
influenced by changes in neural systems during adolescence (Ir-
Recently, Pasupathy and Miller (2005) showed that, in monkeys,
striatal areas detected reward contingencies first, which then
seemed to bias prefrontal regions into taking action. Other work
has shown that the OFC seems to be implicated in linking re-
sponses with outcomes (Elliott et al., 2000; Galvan et al., 2005).
However, this effect may be dependent on maturity of prefrontal
systems and reciprocal connections between frontostriatal re-
6890 • J.Neurosci.,June21,2006 • 26(25):6885–6892Galvanetal.•AdolescentDevelopmentofRewardCircuitry
children and adolescents did not show learning, as indexed by
mean reaction time, to the extent that adults did. It remains an
open question whether the children could not learn to discrimi-
nate between the different reward values or whether they were
just as happy with a small reward as a large reward.
in the neural response in the younger subjects may be consistent
with previous learning studies showing that neural changes pre-
cede behavioral changes (Tremblay et al., 1998). The adolescents
were significantly faster to larger reward trials by the end of the
experiment relative to the other reward values, but the accum-
bens showed distinct patterns of activity to each reward value
similar to adults. If this explanation were true, we might expect
with additional training that the adolescents’ behavioral perfor-
mance would ultimately parallel the accumbens activity. Like-
with more extensive training.
Although the exaggerated accumbens response in adolescents
ined MR changes across the entire experiment and also during
in adolescents relative to adults.
A second difference in the current study, relative to the exist-
across subjects. In examining this main effect, we collapsed OFC
activity across age groups and across the experiment. Other re-
ward studies of the OFC have not included developmental pop-
ulations, who have diffuse and more variable patterns of activity
in this region (Casey et al., 1997). Inclusion of developmental
populations thus increased the variability in recruitment of this
region, with less consistent patterns of OFC activity. Further-
more, our data showed that, for later trials of the experiment,
OFC activity differed for larger relative to smaller rewards, but
showed a less precise mapping to reward value relative to the
NAcc, which showed discrete patterns of activity to each reward
value across age groups, consistent with our previous work (Gal-
van et al., 2005) and that of others (Elliott et al., 2003).
Our results suggest that there are protracted maturational
changes in top–down control systems relative to subcortical re-
gions implicated in appetitive behaviors. These different devel-
opmental trajectories may contribute to suboptimal choices in
systems (Spear, 2000). Understanding the development of struc-
tural and functional connectivity of reward-related mesolimbic
circuitry may further inform the field on the neurobiological
basisof increased reward-seeking
A neural framework similar to the one we propose here has
unable to appropriately modulate decisions in the context of fu-
ture consequences (Bechara, 2005). Our findings are consistent
with this speculation but occur during typical development.
Thus, disproportionate contributions of subcortical systems rel-
ative to prefrontal regulatory systems may underlie poor
decision-making that predisposes adolescents to drug use and,
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