Neural mechanisms of cognitive reappraisal in remitted major
Moria J. Smoskia,n, Shian-Ling Kengb, Crystal Edler Schillerc, Jared Minkelc,
Gabriel S. Dichtera,c,d
aDepartment of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
bDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
cDepartment of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
dDuke-UNC Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, USA
a r t i c l e i n f o
Received 8 May 2013
Accepted 24 May 2013
Available online 21 June 2013
Remitted major depression
Rostral anterior cingulate cortex
a b s t r a c t
Background: Down-regulation of negative emotions by cognitive strategies relies on prefrontal cortical
modulation of limbic brain regions, and impaired frontolimbic functioning during cognitive reappraisal
has been observed in affective disorders. However, no study to date has examined cognitive reappraisal
in unmedicated euthymic individuals with a history of major depressive disorder relative to symptom-
matched controls. Given that a history of depression is a critical risk factor for future depressive episodes,
investigating the neural mechanisms of emotion regulation in remitted major depressive disorder
(rMDD) may yield novel insights into depression risk.
Method: We assessed 37 individuals (18 rMDD,19 controls) with functional magnetic resonance imaging
(fMRI) during a task requiring cognitive reappraisal of sad images.
Results: Both groups demonstrated decreased self-reported negative affect after cognitive reappraisal
and no group differences in the effects of cognitive reappraisal on mood were evident. Functional MRI
results indicated greater paracingulate gyrus (rostral anterior cingulate cortex, Brodmann area 32)
activation and decreased right midfrontal gyrus (Brodmann area 6) activation during the reappraisal of
Limitations: Trial-by-trial ratings of pre-regulation affect were not collected, limiting the interpretation
of post-regulation negative affect scores.
Conclusions: Results suggest that activation of rostral anterior cingulate cortex, a region linked to the
prediction of antidepressant treatment response, and of the right midfrontal gyrus, a region involved in
cognitive control in the context of cognitive reappraisal, may represent endophenotypic markers of
future depression risk. Future prospective studies will be needed to validate the predictive utility of these
& 2013 Elsevier B.V. All rights reserved.
Effective emotion regulation is a critical factor for psychological
health, and functional magnetic resonance imaging (fMRI) has
implicated a number of frontolimbic brain regions in emotion
regulation (Ochsner et al., 2004). In adults without psychopathology,
prefrontal cortical regions, including dorsolateral prefrontal cortex,
ventrolateral prefrontal cortex, and anterior cingulate cortex mod-
ulate emotional responses in limbic regions (Ochsner and Gross,
2008). Within this regulatory circuit, the medial prefrontal cortex
and rostral anterior cingulate cortex are positively associated with
activation in prefrontal cognitive control regions and negatively
associated with limbic activation (Urry et al., 2006; Siegle et al.,
Major depressive disorder (MDD) is characterized by dysregu-
lated biological, cognitive, and behavioral responses during affect
processing (Davidson et al., 2002; Ressler and Mayberg, 2007).
Additionally, a handful of studies have documented differential
activation of frontolimbic brain regions during emotion regulation
in MDD. Johnstone et al. (2007) reported an inverse relation
between left ventral medial prefrontal cortex activation and
amygdala activation in controls but the opposite pattern in out-
patients with MDD during cognitive reappraisal, a form of emotion
regulation in which the meaning of an emotional stimulus is
reinterpreted to change its affective tone. Consistent with this
finding, Greening et al. (2013) reported differential prefrontal
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/jad
Journal of Affective Disorders
0165-0327/$-see front matter & 2013 Elsevier B.V. All rights reserved.
nCorresponding author. Tel.: +1 919 684 6717; fax: +1 919 684 6770.
E-mail addresses: firstname.lastname@example.org, email@example.com (M.J. Smoski).
Journal of Affective Disorders 151 (2013) 171–177
cortical influence on amygdala activation in MDD during regula-
tion of both negative and positive emotions. Similarly, Beauregard
et al. (2006) reported hyperactivation in dorsal anterior cingulate
cortex, right amygdala, and right insula in MDD during down-
regulation of responses to sad film clips, and Erk et al. (2010)
reported reduced prefrontal activation, reduced prefrontolimbic
coupling, and decreased capacity to reduce amygdala activation to
negative pictures in a manner that predicted depressive symptom
severity. However, Dillon and Pizzagalli (2013) reported evidence
of successful modulation of brain activation in MDD during
reappraisal of negative stimuli in the context of specific instruc-
tions to dampen emotion responses by increasing the sense of
psychological distance, suggesting constraints on the effects of
MDD on the neural correlates of cognitive reappraisal.
Despite evidence of altered neural responses in MDD during
emotion regulation, it is unclear whether currently euthymic
individuals with remitted MDD (rMDD) show similar patterns of
frontolimbic dysregulation, a finding that would suggest a marker
of MDD vulnerability, or, conversely, whether brain-based changes
in regulation are constrained to active depressive symptom states.
Major depressive disorder is cyclical, with previous depressive
episodes serving as a powerful risk factor for future episodes
(Lewinsohn et al., 1988). Cognitive vulnerability theories of MDD
posit that individuals at heightened MDD risk are characterized by
negative cognitive biases, including negative self-evaluations
(Gemar et al., 2001) and attentional bias towards negative stimuli
(De Raedt and Koster, 2010). In euthymic individuals with a history
of MDD, these biases may be evident only in the context of an
affective stressor (Scher et al., 2005), highlighting the critical
importance of effective emotion regulation in individuals with a
history of MDD to protect against future depressive episodes.
Given that rMDD is associated with heightened vulnerability to
future MDD episodes, identifying endophenotypes related to
rMDD status may suggest novel preventative intervention targets.
Euthymic individuals with a history of MDD show a range of
altered neurocognitive and neurobiological profiles, including
impairments in cognitive control (Vanderhasselt and De Raedt,
2009), altered resting regional homogeneity in frontal, temporal
and parietal lobes (Yuan et al., 2008), and deficits in attention and
executive functions (Paelecke-Habermann et al., 2005). Euthymic
individuals with a history of MDD also show increased orbito-
frontal and anterior cingulate cortex activity in response to sad
images, suggestive of MDD-like emotion regulation deficits (Liotti
et al., 2002). In addition, rMDD is characterized by greater left
dorsolateral prefrontal cortex activity to negative emotional dis-
tracters during working memory (Kerestes et al., 2011) and higher
calcarine cortex activity to sad film clips (Farb et al., 2011),
potentially reflecting compensatory activation to maintain ade-
quate task performance in the context of negative affective cues.
The purpose of the present study was to examine the neural
mechanisms of cognitive reappraisal of sad images in unmedicated
individuals with a history of MDD. Cognitive reappraisal is an
effective emotion regulation strategy (Gross, 2002) that predicts
depressive symptom severity (Kraaij et al., 2002; Gross and John,
2003; Joormann and Gotlib, 2010) and that may convey protection
against the impact of stressful events (Sears et al., 2003). We are
aware of one previous fMRI study of emotion regulation in rMDD:
Kanske et al. (2012) examined response to negative images and
reported increased amygdala and orbitofrontal activation during
cognitive reappraisal and increased amygdala and anterior cingu-
late cortex activation during distraction in rMDD. However, a
significant proportion of the rMDD group was taking psychiatric
medications, and depressive symptom severity differed between
the rMDD and control groups, confounding the effects of MDD
history with the effects of current MDD symptoms. The present
study builds on the findings of Kanske et al. (2012) by examining
brain activation patterns during cognitive reappraisal in an unme-
dicated rMDD sample compared to sample of controls matched on
(low) current MDD symptom severity. Given that rMDD is char-
acterized by deficits in cognitive control (Vanderhasselt and
De Raedt, 2009), particularly in affective contexts (De Raedt and
Koster, 2010), we predicted compensatory increases in prefrontal
cortical activation during cognitive reappraisal, akin to the findings
of Kanske et al. (2012), and that activation of prefrontal cortical
regions linked to emotion regulation would be associated with
levels of negative affect following reappraisal.
participants (7 male; 15 Caucasian; 27.976.3 years old; all right-
handed) were recruited from lists of potential participants main-
tained by the Duke-UNC Brain Imaging and Analysis Center (BIAC).
Nineteen adults with rMDD (4 male; 13 Caucasian; 24.575.4
years old; 17 right-handed) were recruited via a participant
database maintained at the Cognitive Behavioral Research and
Treatment Program at Duke University Medical Center. Data from
one rMDD participant were excluded due to an elevated Beck
Depression Inventory-II (BDI; Beck et al., 1996) score on the day of
the scan (BDI¼30), resulting in a final sample of 18 rMDD
participants. Exclusion criteria for both groups included age o19
or 455 years old, current Axis I psychopathology, psychiatric
medication use within the past month, verbal IQ scores (estimated
by the North American Adult Reading Test (Uttl, 2002))o80,
BDI48, or MRI contraindications. Inclusion in the rMDD group
was contingent on a prior diagnosis of MDD based on SCID I semi-
structured interview (First et al., 1996). Control participants were
lifetime-free of MDD. None of the control participants and two
rMDD participants were receiving psychotherapy at the time of
participation. Five rMDD participants had previously used psycho-
tropic medications. All participants consented to a protocol
approved by the local Human Investigations Committees at both
UNC-Chapel Hill and Duke University Medical Centers and were
paid $35 for completing the imaging portion of the study.
All participants had normal or corrected-to-normal vision and
completed a mock scan session prior to imaging. Information about
demographics and prior MDD episodes are presented in Table 1.
affectivelyhealthyright-handed adult control
2.2. fMRI task
Each trial began with a fixation cross (6 s) followed by pre-
sentation of a sad or neutral picture (Fig. 1 depicts the timing and
content of the task). After initial picture display (6 to 9 s, jittered) a
visual regulation instruction was superimposed on the bottom of
the picture, indicating the regulation strategy to use. Regulation
continued for 5 s following image offset. Finally, participants rated
their post-trial affect using a visual analogue scale. The task
included three regulation conditions. In the “attend” condition,
used with both sad and neutral pictures, participants were
instructed not to regulate their emotion response. In the “reap-
praise” condition, used with only sad images, participants were
asked to reinterpret the image to reduce its negative tone.
Both self-focused and situation-focused reappraisal strategies
were permitted (Ochsner et al., 2004). Results from a third
condition, “accept,” are not reported here. Four runs of 12 trials
each were administered (48 trials total; 4′24″ per run), and there
were 12 trials for each regulation condition.
Immediately prior to the scan, participants learned and prac-
ticed the regulation strategies with an experimenter until they
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177
could correctly implement them without assistance. Task images
were drawn from two sources: (1) sad images from the Interna-
tional Affective Picture System based on normative sadness ratings
(Mikels et al., 2005), and (2) a normed set of sad and neutral
images used in previous MDD imaging studies (Wang et al., 2005,
2008; Dichter et al., 2009, 2010).
2.3. Imaging methods
Scanning was performed on a General Electric (Waukesha, WI,
USA) MR750 3.0 T scanner equipped with high-power high-duty-
cycle 50-mT/m gradients at 200 T/m/s slew rate and a 32-channel
head coil for parallel imaging. A quadrature birdcage radio frequency
head coil was used for transmit and receive. A high resolution T1-
weighted image with 166 slices was acquired using a 3D FSPGR pulse
matrix¼256? ?256; voxel size¼1 mm3) and used for coregistration
with the functional data. This structural image was aligned in a near
axial plane defined by the anterior and posterior commissures.
Whole brain functional images were acquired using a spiral pulse
sequence with SENSE reconstruction sensitive to blood oxygenation
TE¼2.984 ms; FOV¼256 mm;image
level dependent contrast (TR, 1500 ms; TE, 30 ms; FOV, 256 mm;
image matrix, 64?64; α¼601; voxel size¼4 mm3; 32 axial slices).
Functional images were aligned similarly to the T1-weighted struc-
tural image. A semi-automated high-order shimming program
ensured global field homogeneity.
2.4. Imaging data analysis
Functional data were preprocessed using FSL version 4.1.8
(Oxford Centre for Functional Magnetic Resonance Imaging of
the Brain (FMRIB), Oxford University, UK). Preprocessing was
applied in the following steps: (i) brain extraction for non-brain
removal (Smith et al., 2004), (ii) motion correction using MCFLIRT
(Smith, 2002), (iii) spatial smoothing using a Gaussian kernel of
FWHM 5 mm, (iv) mean-based intensity normalization of all
volumes by the same factor, and (v) high-pass filtering (Jenkinson
et al., 2002). Functional images of each participant were co-
registered to structural images in native space, and structural
images were normalized into a standard stereotaxic space (Mon-
treal Neurological Institute) for intersubject comparison. This trans-
formation included resampling voxel sizes to 2 mm3. The same
transformation matrices used for structural-to-standard transfor-
mations were then used for functional-to-standard space transfor-
mations of co-registered functional images. All registrations were
carried out using an intermodal registration tool (Jenkinson et al.,
2002; Smith et al., 2004). Voxel-wise temporal autocorrelation was
estimated and corrected using FMRIB's Improved Linear Model
(FILM; Jenkinson and Smith, 2001). Onset times of events were
used to model a signal response containing a regressor for each
strategy, which was convolved with a double-γ function to model
the hemodynamic response. Model fitting generated whole brain
images of parameter estimates and variances representing average
signal change from baseline. Group-wise activation images were
calculated by a mixed effects higher level analysis using Bayesian
estimation techniques, FMRIB Local Analysis of Mixed Effects (FILM,
Woolrich et al., 2001; Smith et al., 2004).
An a priori mask was created for small volume correction that
included the frontal lobes and bilateral amygdala generated in FSL
using the Harvard–Oxford cortical and subcortical structural prob-
abilistic atlases. Masks were thresholded at 25%, binarized, and
then combined into a single mask using fslmaths. For all analyses,
voxels were considered significant if they passed a statistical
threshold of po.005, uncorrected, and were part of a 35-voxel
Demographic and symptom severity information for control and rMDD partici-
pants. Two-tailed p-values for between-group t tests or chi-squared analyses are in
the final column.
n¼18 mean (SD)
n¼19 mean (SD)
No. of previous
No. of months since
NAART VIQ: North American Adult Reading Test (Uttl, 2002). BDI: Beck Depression
Inventory, 2nd ed. (Beck et al., 1996).
Sad or Neutral Image
Fig. 1. Emotion regulation task. Each trial consisted of a fixation cross, a neutral or sad image, a regulation cue, a delay, and a query for current affect.
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177
(280 mm3) cluster of contiguous significant voxels, resulting in a
cluster-corrected significance threshold of po.05. This cluster size
was determined by performing 1000 Monte Carlo simulations
using 3dClustSim (Ward, 2000).
Pre-regulation and regulation phases of the task were analyzed
separately. General linear models evaluated clusters that showed
significant interactions of Group (rMDD, control) with trial type
(sad relative to neutral images for the pre-regulation phase;
reappraise-sad relative to attend-sad for the regulation phase).
Activation localizations were based on Harvard–Oxford cortical
and subcortical structural probabilistic atlases, with Brodmann
area identification via the Talairach Daemon, as implemented in
FSLView v3.1.8. Exploratory correlation analyses between brain
activation and clinical characteristics of the rMDD group were
conducted by extracting contrast estimates from each participant
and condition within significant clusters identified by the whole-
brain general linear models described above.
3.1. Emotion regulation self-report
In-scanner self-reported emotion regulation was evaluated via a 2
(Group: rMDD, control) ?3 (Trial Type: attend-sad, attend-neutral,
reappraise-sad) repeated measures ANOVA. There was a significant
main effect of Trial Type, F(2,70)¼103.67, po.0001. Follow-up paired
t tests indicated more negative affect ratings on attend-sad trials than
reappraise-sad trials, t(36)¼5.06, po.001, and more negative affect
ratings on reappraise-sad trials than attend-neutral trials, t(36)¼
8.20, po.001. There was no main effect of Group, F(1,35)¼0.96,
p¼.34, or Group?Trial Type interaction, F(2,70)¼1.82, p¼.17. These
results indicate that both groups reported successful emotion regula-
tion, with no differences between groups.
3.2. Imaging data: Group differences during pre-regulation
Though not a central focus of this investigation, the pre-
regulation phase was analyzed via a Group (rMDD, control)?Trial
Type (sad images, neutral images) model. This model revealed that
the rMDD group was characterized by relatively decreased activa-
tion in left frontal pole, bilateral inferior frontal gyrus, right middle
frontal gyrus, and left precentral gyrus during the pre-regulation
condition (see Table 2). Conversely, there were no clusters with
greater activation in the rMDD group. To evaluate the influence of
left-handedness on these results, the same model was evaluated
omitting the twoleft-handed
rMDDocontrol clusters remained in these regions. To evaluate
participants, and significant
the influence of current psychotherapy use on these results, the
same model was evaluated omitting the two participants who
were receiving psychotherapy. The left inferior frontal gyrus
cluster was no longer significant, but the rMDDocontrol signifi-
cant clusters in the other regions remained.
3.3. Imaging data: Group differences during emotion regulation
Of central interest were group differences during emotion
regulation. Group (rMDD, control)?Trial Type (reappraise-sad,
attend-sad) models during emotion regulation (see Table 3 and
Fig. 2) revealed that the rMDD group was characterized by
relatively decreased activation in right middle frontal gyrus
(Brodmann area 6) and by relatively greater activation in right
paracingulate gyrus (Brodmann's area 32 within rostral anterior
cingulate cortex (rACC)). Group- and condition-averaged signal
intensities extracted from these clusters revealed that, for the right
middle frontal gyrus cluster, the rMDD demonstrated significantly
decreased activation relative to the control group during the
reappraisal of sad images (po.05), and the control group demon-
strated greater activation during reappraisal of sad images relative
to attending to neural images (po.001). For the rACC cluster, the
rMDD group showed greater activation during the reappraisal of
sad images relative to attending to sad images (po.003) and a
trend towards decreased activation relative to the control group
during the attend condition (po.06). To evaluate the influence of
left-handedness and current psychotherapy use on these results,
the same model was evaluated first omitting the two left-handed
participants and next omitting the two participants who were
receiving psychotherapy, and these clusters remained significant.
3.4. Correlations between brain activation and self-reported emotion
regulation in the rMDD group
To test for relations between brain activation magnitudes and
self-reported emotion regulation in the rMDD group, correlations
between activation magnitudes within clusters reported in
Tables 2 and 3 and in-scanner reports of post-reappraisal affect
were evaluated. Even at uncorrected significance thresholds, no
relations were significant.
The purpose of this study was to extend the literature on the
neural correlates of emotion regulation in MDD to currently
euthymic individuals with a history of MDD. Studying individuals
with a prior history of depressive episodes may clarify mechanisms
by which MDD history conveys vulnerability to future depressive
episodes, and the elucidation of endophenotypes linked to MDD in
patients with a history of the disorder is a necessary, though not
Clusters showing decreased activation in the rMDD relative to the control group
while viewing sad4neutral images during the pre-regulation phase of the task
(there were no areas with relatively increased activation in the rMDD group).
Z max MNI
Middle frontal gyrus R
−16 56 36
−56 22 24
R455203.4654 20 26
32 0 54
−58 −4 44
aTwo clusters within the same region; coordinate and peak activation reported
for higher peak activation; size represents the sum of the two clusters.
Clusters showing group-based activation differences to the cognitive reappraisal of
sad images4viewing sad images contrast.
R32 2803.074 44
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177
sufficient, criteria contributing to the identification of a risk marker
for a disorder (Alloy et al., 1999).
Given the growing literature documenting differential prefron-
tal cortex and amygdala activations during emotion regulation in
MDD (Johnstone et al., 2007; Greening et al., 2013; Beauregard
et al., 2006; Erk et al., 2010), primary analyses focused on the
contrast of cognitive reappraisal of sad images versus attending to
sad images. We predicted that the rMDD group would show
relatively increased activation in prefrontal cortical regions asso-
ciated with cognitive control in the context of affective processing
(Ochsner et al., 2002, 2004). Results partially confirmed hypoth-
eses, as we found evidence of relatively greater activation in rACC,
though we also found relatively decreased activation in right
middle frontal gyrus.
The middle frontal gyrus and the rACC play critical functional
roles in MDD. The middle frontal gyrus is recruited during tasks
involving working memory, selective attention, and successful
emotion regulation (Ochsner and Gross, 2008; Ochsner et al.,
2004). Multiple studies have documented decreased middle fron-
tal gyrus activity in MDD during tasks involving emotion proces-
sing (Feeser et al., 2013; Dichter et al., 2009), cognitive control
(Kikuchi et al., 2012; Okada et al., 2009), and, most relevant in the
present context, emotion regulation (Wang et al., 2008). Addition-
ally, reduced pre-treatment middle frontal gyrus activity is a
predictor of worse antidepressant treatment response (Samson
et al., 2011; Lisiecka et al., 2011). We thus interpret the present
findings of relatively decreased middle frontal gyrus activity in
rMDD during emotion regulation of sad images to potentially
reflect decreased neural resources to exert cognitive control,
despite the fact that perhaps relatively low task demands were
not sufficient to yield group differences in self-reported emotion
The rACC, on the other hand, has emerged as a promising
predictor of antidepressant treatment response (Mayberg, 1997;
Mayberg et al., 1997; Saxena et al., 2003; Kennedy et al., 2007).
A recent comprehensive meta-analysis of 23 studies that consid-
ered functional neuroimaging predictors of a range of antidepres-
therapy, rapid transcranial magnetic stimulation, sleep depriva-
tion, and psychotherapy, as well as a range of imaging modalities,
fMRI, positron emission tomography, and single photon emission
computed tomography reported that increased rACC activity is a
robust predictor of improved treatment response across various
treatments and imaging modalities (Pizzagalli, 2011). One theory
for the linkage between rACC activity and antidepressant treat-
ment response is its location as a “hub” position within the default
mode network (Shackman et al., 2011) that mediates adaptive self-
referential processing as well as task-switching with dorsal cog-
nitive control networks in depression (Pizzagalli, 2011). In this
regard, the well documented biased emotion processing that
characterizes depression (Gotlib and Joormann, 2010) may be
rooted in increased tonic rACC activation that interferes with
task-appropriate activation. In this regard, increased rACC activa-
tion may be a marker of improved emotional functioning in
individuals who recovered from a recent episode of depression.
revealed that both the rMDD and control groups were successful
at down-regulating their responses to sad images, and groups did
not differ in these ratings, consistent with prior reports (Greening
after emotion regulation
X = 10 Y = 44
X = 48 Y = 4
Fig. 2. The rMDD group demonstrated relatively less activation in right midfrontal gyrus (rMFG; Brodmann area 6) (top) and relatively greater activation in right
paracingulate gyrus (PCG; Brodmann area 32; bottom) during reappraisal of sad images contrasted with attending to sad images. Whole-brain analyses are on the left and
bar graphs from corresponding group- and condition-averaged signal intensities for the rMFG (top) and PCG (bottom) clusters are on the right. See text for results of all
between- and within-groups t-tests on extracted signal intensities.
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177
et al., 2013; Dillon and Pizzagalli, 2013). The fact that group
differences in fMRI were observed in the absence of divergence
in self-reported affect further supports the compensatory frame-
work outlined above with respect to rACC activation.
The present finding of increased prefrontal cortex activation during
cognitive reappraisal partially extends the results of Kanske et al.
(2012) who reported relatively increased right orbitofrontal cortex
activation during cognitive reappraisal and relatively increased
dorsomedial prefrontal cortex activation during distraction regulation
in rMDD. Kanske et al. (2012) used high-arousal negative images,
including mutilation images, whereas the present study used images
selected specifically for sad (i.e., low arousal) content. Sad stimuli may
be more personally relevant to individuals with a history of MDD than
stimuli eliciting physical threat or disgust (Mathews et al., 1996),
which may in turnpromote more self-relevant cognitions (Wood et al.,
1990). In this regard, the particular stimulus sets used here may have
contributed to localization of hyperactive responses in rMDD in the
present study to the rACC (Northoff et al., 2006).
Of note, whereas we did not find group differences in amygdala
activation during cognitive reappraisal, Kanske et al. (2012)
reported decreased down-regulation of amygdala responses in
rMDD during cognitive reappraisal. This may be related to the
disparity in depressive symptom severity in the rMDD groups in
both studies. In the present study, groups were matched on
current depressive symptom severity, whereas rMDD participants
had significantly more depressive symptoms than controls in
Kanske et al. (2012). Thus, aberrant prefrontal cortex activation
during emotion regulation may characterize rMDD in the context
of a range of subclinical depressive symptoms, whereas differences
in prefrontal modulatory effects on amygdala may not be evident
in rMDD participants without significant depressive symptoms.
Additionally, decreased middle frontal gyrus activity in rMDD
was not reported in Kanske et al. (2012). Reappraisal requires a
reinterpretation of the meaning of an emotional stimulus to
change its affective tone, but the form of that reinterpretation
varies across individuals. For example, self-focused strategies,
which include taking a detached, third-party perspective on a
negative stimulus, and situation-focused strategies, which involve
making a positive or optimistic reinterpretation of a negative
stimulus, have been found to activate overlapping but differenti-
able networks. The current study permitted both self-focused and
situation-focused reappraisal, and relatively decreased activation
in right middle frontal gyrus in rMDD is consistent with activation
implicated in situation-focused reappraisal (Ochsner et al., 2004).
Although group differences during the pre-regulatory phase of
the task was not a primary focus of the present study, during pre-
regulation we found relatively less activation in a number of
prefrontal cortical regions previously shown to activate during
emotion induction (Steele and Lawrie, 2004; Kober et al., 2008)
and regulation (Ochsner et al., 2004). Thus, activation of these
regions during pre-regulation may reflect automatic, nonconscious
affective regulatory processes activated to a lesser degree in the
rMDD group while viewing sad images.
One limitation in our design is the lack of measurement of trial-
by-trial pre-regulation affect, so group differences in subjective
regulation success could not be directly measured. However, the
lack of group differences in self-reported negative affect to attend-
sad trials suggests that the groups did not differ in emotional
reactivity to the sad images. Across groups, lower negative affect
scores following reappraisal versus attend-sad trials suggest that
reappraisal was associated with successful regulation. Interpretation
of the clinical relevance of the findings would be improved with
data on long-term clinical course, to test if neural activation during
cognitive reappraisal predicts continued remission versus relapse.
In summary, in the absence of group differences in self-
reported emotion regulation effectiveness, we found that currently
euthymic individuals with a history of MDD showed decreased
right middle frontal gyrus activation and increased rACC activation
during cognitive reappraisal of sad images. These findings were
evident despite the fact that rMDD and controls groups were
matched to have equivalently low levels of depressive symptom
severity. These patterns of brain activity suggest a possible
endophenotypic marker of risk for future depression given that a
prior history of depressive episodes represents a powerful risk
factor for future episodes (Lewinsohn et al.,1988). Further research
is needed to determine whether these patterns of brain activation
prospectively convey greater risk for future MDD episodes or are
present before the onset of a first depressive episode.
Role of the funding source
Assistance for this study was provided by the Neuroimaging
Core of the Carolina Institute for Developmental Disabilities (P30
HD03110). This research was supported by grants from the
NARSAD Young Investigator Program. Investigator effort was
supported by NIMH K23 MH087754 to M. Smoski and NIMH K23
MH081285 to G. Dichter.
Conflict of interest statement
Our authors have no commercial or financial relationships that
could be construed as a potential conflict of interest to report.
The authors thank Josh Bizzell and Chris Petty for assistance with image
analysis, Alison Rittenberg for assistance with data collection, and MRI technolo-
gists Susan Music, Natalie Goutkin, and Luke Poole for assistance with data
Alloy, L.B., Ambramson, L.Y., Raniere, D., Dyller, I.M., 1999. Research methods in
adult psychopathology. In: Kendall, P.C., Butcher, J.N., Holmbeck, G.N. (Eds.),
Handbook of Research Methods in Clinical Psychology, second ed. Wiley, New
Beauregard, M., Paquette, V., Levesque, J., 2006. Dysfunction in the neural circuitry
of emotional self-regulation in major depressive disorder. Neuroreport 17,
Beck, A.T., Steer, R.A., Brown, G.K., 1996. Manual for Beck Depression Inventory-II.
Psychological Corporation, San Antonio, TX.
Davidson, R.J., Pizzagalli, D., Nitschke, J.B., Putnam, K., 2002. Depression: perspec-
tives from affective neuroscience. Annual Review of Psychology 53, 545–574.
De Raedt, R., Koster, E.H., 2010. Understanding vulnerability for depression from a
cognitive neuroscience perspective: a reappraisal of attentional factors and a
new conceptual framework. Cognitive, Affective, & Behavioral Neuroscience 10,
Dichter, G.S., Felder, J.N., Smoski, M.J., 2009. Affective context interferes with
cognitive control in unipolar depression: an fMRI investigation. Journal of
Affective Disorders 114, 131–142.
Dichter, G.S., Felder, J.N., Smoski, M.J., 2010. The effects of Brief Behavioral
Activation Therapy for Depression on cognitive control in affective contexts:
an fMRI investigation. Journal of Affective Disorders 126, 236–244.
Dillon, D.G., Pizzagalli, D.A., 2013. Evidence of successful modulation of brain
activation and subjective experience during reappraisal of negative emotion in
unmedicated depression. Psychiatry Research 212, 99–107.
Erk, S., Mikschl, A., Stier, S., Ciaramidaro, A., Gapp, V., Weber, B., Walter, H., 2010.
Acute and sustained effects of cognitive emotion regulation in major depres-
sion. The Journal of Neuroscience 30, 15726–15734.
Farb, N.A., Anderson, A.K., Bloch, R.T., Segal, Z.V., 2011. Mood-linked responses in
medial prefrontal cortex predict relapse in patients with recurrent unipolar
depression. Biological Psychiatry 70, 366–372.
Feeser, M., Schlagenhauf, F., Sterzer, P., Park, S., Stoy, M., Gutwinski, S., Dalanay, U.,
Kienast, T., Bauer, M., Heinz, A., Strohle, A., Bermpohl, F., 2013. Context
insensitivity during positive and negative emotional expectancy in depression
assessed with functional magnetic resonance imaging. Psychiatry Research 212,
First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B.W., 1996. Structured Clinical
Interview for DSM-IV Axis I Disorders (SCID), Clinician Version; Administration
Booklet. American Psychiatric Press, Washington, DC.
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177
Gemar, M.C., Segal, Z.V., Sagrati, S., Kennedy, S.J., 2001. Mood-induced changes on
the Implicit Association Test in recovered depressed patients. Journal of
Abnormal Psychology 110, 282–289.
Gotlib, I.H., Joormann, J., 2010. Cognition and depression: current status and future
directions. Annual Review of Clinical Psychology 6, 285–312.
Greening, S.G., Osuch, E.A., Williamson, P.C., Mitchell, D.G., 2013. The neural
correlates of regulating positive and negative emotions in medication-free
major depression. Social Cognitive and Affective Neuroscience.
Gross, J.J., 2002. Emotion regulation: affective, cognitive, and social consequences.
Psychophysiology 39, 281–291.
Gross, J.J., John, O.P., 2003. Individual differences in two emotion regulation
processes: implications for affect, relationships, and well-being. Journal of
Personality & Social Psychology 85, 348–362.
Jenkinson, M., Bannister, P., Brady, M., Smith, S., 2002. Improved optimization for
the robust and accurate linear registration and motion correction of brain
images. NeuroImage 17, 825–841.
Jenkinson, M., Smith, S., 2001. A global optimisation method for robust affine
registration of brain images. Medical Image Analysis 5, 143–156.
Johnstone, T., Van Reekum, C.M., Urry, H.L., Kalin, N.H., Davidson, R.J., 2007. Failure
to regulate: counterproductive recruitment of top-down prefrontal-subcortical
circuitry in major depression. The Journal of Neuroscience 27, 8877–8884.
Joormann, J., Gotlib, I.H., 2010. Emotion regulation in depression: relation to
cognitive inhibition. Cognition & Emotion 24, 281–298.
Kanske, P., Heissler, J., Schönfelder, S., Wessa, M., 2012. Neural correlates of emotion
regulation deficits in remitted depression: the influence of regulation strategy,
habitual regulation use, and emotional valence. NeuroImage 61, 686–693.
Kennedy, S.H., Konarski, J.Z., Segal, Z.V., Lau, M.A., Bieling, P.J., Mcintyre, R.S.,
Mayberg, H.S., 2007. Differences in brain glucose metabolism between respon-
ders to CBT and venlafaxine in a 16-week randomized controlled trial. The
American Journal of Psychiatry 164, 778–788.
Kerestes, R., Ladouceur, C.D., Meda, S., Nathan, P.J., Blumberg, H.P., Maloney, K., Ruf,
B., Saricicek, A., Pearlson, G.D., Bhagwagar, Z., Phillips, M.L., 2011. Abnormal
prefrontal activity subserving attentional control of emotion in remitted
depressed patients during a working memory task with emotional distracters.
Psychological Medicine, 1–12.
Kikuchi, T., Miller, J.M., Schneck, N., Oquendo, M.A., Mann, J.J., Parsey, R.V., Keilp, J.G.,
2012. Neural responses to incongruency in a blocked-trial Stroop fMRI task in
major depressive disorder. Journal of Affective Disorders 143, 241–247.
Kober, H., Barrett, L.F., Joseph, J., Bliss-Moreau, E., Lindquist, K., Wager, T.D., 2008.
Functional grouping and corticalâ€“subcortical interactions in emotion: a meta-
analysis of neuroimaging studies. NeuroImage 42, 998–1031.
Kraaij, V., Pruymboom, E., Garnefski, N., 2002. Cognitive coping and depressive
symptoms in the elderly: a longitudinal study. Aging & Mental Health 6,
Lewinsohn, P.M., Hoberman, H.M., Rosenbaum, M., 1988. A prospective study of risk
factors for unipolar depression. Journal of Abnormal Psychology 97, 251–264.
Liotti, M., Mayberg, H.S., Mcginnis, S., Brannan, S.L., Jerabek, P., 2002. Unmasking
disease-specific cerebral blood flow abnormalities: mood challenge in patients
with remitted unipolar depression. The American Journal of Psychiatry 159,
Lisiecka, D., Meisenzahl, E., Scheuerecker, J., Schoepf, V., Whitty, P., Chaney, A.,
Moeller, H.J., Wiesmann, M., Frodl, T., 2011. Neural correlates of treatment
outcome in major depression. The International Journal of Neuropsychophar-
macology 14, 521–534.
Mathews, A., Ridgeway, V., Williamson, D.A., 1996. Evidence for attention to
threatening stimuli in depression. Behaviour Research and Therapy 34,
Mayberg, H.S., 1997. Limbic-cortical dysregulation: a proposed model of depres-
sion. The Journal of Neuropsychiatry and Clinical Neurosciences 9, 471–481.
Mayberg, H.S., Brannan, S.K., Mahurin, R.K., Jerabek, P.A., Brickman, J.S., Tekell, J.L.,
Silva, J.A., Mcginnis, S., Glass, T.G., Martin, C.C., Fox, P.T., 1997. Cingulate function
in depression: a potential predictor of treatment response. Neuroreport 8,
Mikels, J.A., Fredrickson, B.L., Larkin, G.R., Lindberg, C.M., Maglio, S.J., Reuter-Lorenz,
P.A., 2005. Emotional category data on images from the International Affective
Picture System. Behavior Research Methods 37, 626–630.
Northoff, G., Heinzel, A., De Greck, M., Bermpohl, F., Dobrowolny, H., Panksepp, J.,
2006. Self-referential processing in our brain—a meta-analysis of imaging
studies on the self. NeuroImage 31, 440–457.
Ochsner, K.N., Bunge, S.A., Gross, J.J., Gabrieli, J.D., 2002. Rethinking feelings: an f
MRI study of the cognitive regulation of emotion. Journal of Cognitive
Neuroscience 14, 1215–1229.
Ochsner, K.N., Gross, J.J., 2008. Cognitive emotion regulation: insights from social
cognitive and affective neuroscience. Current Directions in Psychological
Science 17, 153–158.
Ochsner, K.N., Ray, R.D., Cooper, J.C., Robertson, E.R., Chopra, S., Gabrieli, J.D.E., et al.,
2004. For better or for worse: neural systems supporting the cognitive down-
and up-regulation of negative emotion. NeuroImage 23, 483–499.
Okada, G., Okamoto, Y., Yamashita, H., Ueda, K., Takami, H., Yamawaki, S., 2009.
Attenuated prefrontal activation during a verbal fluency task in remitted major
depression. Psychiatry and Clinical Neurosciences 63, 423–425.
Paelecke-Habermann, Y., Pohl, J., Leplow, B., 2005. Attention and executive functions in
remitted major depression patients. Journal of Affective Disorders 89, 125–135.
Pizzagalli, D.A., 2011. Frontocingulate dysfunction in depression: toward biomar-
kers of treatment response. Neuropsychopharmacology 36, 183–206.
Ressler, K.J., Mayberg, H.S., 2007. Targeting abnormal neural circuits in mood and
anxiety disorders: from the laboratory to the clinic. Nature Neuroscience 10,
Samson, A.C., Meisenzahl, E., Scheuerecker, J., Rose, E., Schoepf, V., Wiesmann, M.,
Frodl, T., 2011. Brain activation predicts treatment improvement in patients
with major depressive disorder. Journal of Psychiatric Researc 45, 1214–1222.
Saxena, S., Brody, A.L., Ho, M.L., Zohrabi, N., Maidment, K.M., Baxter Jr., L.R., 2003.
Differential brain metabolic predictors of response to paroxetine in obsessive-
compulsive disorder versus major depression. The American Journal of Psy-
chiatry 160, 522–532.
Scher, C.D., Ingram, R.E., Segal, Z.V., 2005. Cognitive reactivity and vulnerability:
empirical evaluation of construct activation and cognitive diatheses in unipolar
depression. Clinical Psychology Review 25, 487–510.
Sears, S.R., Stanton, A.L., Danoff-Burg, S., 2003. The yellow brick road and the
emerald city: benefit finding, positive reappraisal coping and posttraumatic
growth in women with early-stage breast cancer. Health Psychology 22,
Shackman, A.J., Salomons, T.V., Slagter, H.A., Fox, A.S., Winter, J.J., Davidson, R.J.,
2011. The integration of negative affect, pain and cognitive control in the
cingulate cortex. Nature Reviews Neuroscience 12, 154–167.
Siegle, G.J., Carter, C.S., Thase, M.E., 2006. Use of FMRI to predict recovery from
unipolar depression with cognitive behavior therapy. The American Journal of
Psychiatry 163, 735–738.
Smith, S.M., 2002. Fast robust automated brain extraction. Human Brain Mapping
Smith, S.M., Jenkinson, M., Woolrich, M.W., Beckmann, C.F., Behrens, T.E.J.,
Johansen-Berg, H., Bannister, P.R., De Luca, M., Drobnjak, I., Flitney, D.E., Niazy,
R.K., Saunders, J., Vickers, J., Zhang, Y., De Stefano, N., Brady, J.M., Matthews, P.
M., 2004. Advances in functional and structural MR image analysis and
implementation as FSL. NeuroImage 23, S208–S219.
Steele, J.D., Lawrie, S.M., 2004. Segregation of cognitive and emotional function in
the prefrontal cortex: a stereotactic meta-analysis. NeuroImage 21, 868–875.
Urry, H.L., Van Reekum, C.M., Johnstone, T., Kalin, N.H., Thurow, M.E., Schaefer, H.S.,
Jackson, C.A., Frye, C.J., Greischar, L.L., Alexander, A.L., Davidson, R.J., 2006.
Amygdala and ventromedial prefrontal cortex are inversely coupled during
regulation of negative affect and predict the diurnal pattern of Cortisol
secretion among older adults. The Journal of Neuroscience 26, 4415–4425.
Uttl, B., 2002. North American Adult Reading Test: age norms, reliability, and
validity. Journal of Clinical and Experimental Neuropsychology 24, 1123–1137.
Vanderhasselt, M.A., De Raedt, R., 2009. Impairments in cognitive control persist
during remission from depression and are related to the number of past
episodes: an event related potentials study. Biological Psychology 81, 169–176.
Wang, L., Labar, K.S., Smoski, M., Rosenthal, M.Z., Dolcos, F., Lynch, T.R., Krishnan, R.R.,
Mccarthy, G., 2008. Prefrontal mechanisms for executive control over emotional
distraction are altered in major depression. Psychiatry Research 163, 143–155.
Wang, L., Mccarthy, G., Song, A.W., Labar, K.S., 2005. Amygdala activation to sad
pictures during high-field (4 T) functional magnetic resonance imaging. Emo-
tion 5, 12–22.
Ward, B., 2000. Simultaneous inference for fMRI data. Biophysics Research Institute,
Medical College of Wisconsin, Milwaukee, WI.
Wood, J.V., Saltzberg, J.A., Goldsamt, L.A., 1990. Does affect induce self-focused
attention? Journal of Personality and Social Psychology 58, 899–908.
Woolrich, M.W., Ripley, B.D., Brady, M., Smith, S.M., 2001. Temporal autocorrelation
in univariate linear modeling of FMRI data. NeuroImage 14, 1370–1386.
Yuan, Y., Zhang, Z., Bai, F., Yu, H., Shi, Y., Qian, Y., Liu, W., You, J., Zhang, X., Liu, Z.,
2008. Abnormal neural activity in the patients with remitted geriatric depres-
sion: a resting-state functional magnetic resonance imaging study. Journal of
Affective Disorders 111, 145–152.
M.J. Smoski et al. / Journal of Affective Disorders 151 (2013) 171–177