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. Author manuscript; available in PMC: 2016 Jan 1.
Published in final edited form as: Psychol Med. 2014 May 15;45(1):121–131. doi: 10.1017/S0033291714001123

Dissociable cortico-striatal connectivity abnormalities in major depression in response to monetary gains and penalties

Roee Admon 1, Lisa D Nickerson 2, Daniel G Dillon 1, Avram J Holmes 3,4, Ryan Bogdan 5, Poornima Kumar 1, Darin D Dougherty 4, Dan V Iosifescu 6, David Mischoulon 4, Maurizio Fava 4, Diego A Pizzagalli 1,2
PMCID: PMC4233014  NIHMSID: NIHMS605165  PMID: 25055809

Abstract

Background

Individuals with major depressive disorder (MDD) are characterized by maladaptive responses to both positive and negative outcomes, which have been linked to localized abnormal activations in cortical and striatal brain regions. However, the exact neural circuitry implicated in such abnormalities remains largely unexplored.

Methods

In this study 26 unmedicated adults with MDD and 29 matched healthy controls completed a monetary incentive delay task during functional magnetic resonance imaging (fMRI). Psycho-physiological interaction (PPI) analyses probed group differences in connectivity separately in response to positive and negative outcomes (i.e., monetary gains and penalties).

Results

Relative to controls, MDD subjects displayed decreased connectivity between the caudate and dorsal anterior cingulate cortex (dACC) in response to monetary gains, yet increased connectivity between the caudate and a different, more rostral, dACC sub-region in response to monetary penalties. Moreover, exploratory analyses of 14 MDD patients who completed a 12-week, double-blind, placebo-controlled clinical trial after the baseline fMRI scans indicated that a more normative pattern of cortico-striatal connectivity pre-treatment was associated with more symptoms improvement 12 weeks later.

Conclusions

These results identify the caudate as a region with dissociable incentive-dependent dACC connectivity abnormalities in MDD, and provide initial evidence that cortico-striatal circuitry may play a role in MDD treatment response. Given the role of cortico-striatal circuitry in encoding action-outcome contingencies, such dysregulated connectivity may relate to the prominent disruptions in goal-directed behavior that characterize MDD.

Keywords: Caudate, Cingulate, Reward, Depression, Treatment Prediction, gPPI

Introduction

Major Depressive Disorder (MDD) is a highly prevalent psychiatric condition characterized by a range of abnormal behaviors, including dysregulated responses to both positive and negative outcomes. Functional magnetic resonance imaging (fMRI) studies have described reduced responsivity in localized brain regions including the ventral (nucleus accumbens (Nacc)) and dorsal (caudate) striatum in response to a variety of positive stimuli in individuals with MDD (Forbes et al. 2006, Forbes et al. 2009, Kumar et al. 2008, Lawrence et al. 2004, Schaefer et al. 2006, Smoski et al. 2009). Blunted reward-related striatal responsiveness in MDD has been associated with decreased positive affect (Forbes et al. 2009), in line with the well-established role of the striatum in reward processing (Haber&Knutson 2010). Depression, however, is a highly complex construct and thus likely involves circuit-level alterations, rather than isolated dysfunction in discrete brain regions (Mayberg 1997). Indeed, using functional connectivity analyses, Heller et al (2009) found that the inability to sustain positive affect in MDD was associated with blunted striatal activation as well as reduced fronto-striatal connectivity (Heller et al. 2009). In spite of these promising results, the neural circuitry underlying abnormal responses to positive outcomes in MDD remains largely unexplored. The first goal of the current study was to fill this gap by investigating whether MDD is characterized by abnormal striatal connectivity in response to monetary gains.

Interestingly, neuroimaging studies in healthy populations have also demonstrated striatal involvement in response to aversive stimuli. For example, the ventral striatum (i.e., Nacc) was shown to respond to thermal pain (Baliki et al. 2013, Becerra et al. 2001), while the dorsal striatum (i.e., caudate) responded to electric shock and monetary losses (Delgado et al. 2008, Mattfeld et al. 2011, Niznikiewicz&Delgado 2011, Seymour et al. 2007, Tricomi et al. 2004). Indeed, among healthy controls, both monetary gains and penalties were found to elicit increased bilateral caudate activations (Pizzagalli et al. 2009). Moreover, relative to controls, MDD patients showed significantly lower caudate activation to both gains and penalties (Pizzagalli et al. 2009), suggesting that blunted caudate responsivity in MDD might extend to a broad range of affective stimuli. Thus, our second goal was to test whether putative striatal connectivity disruptions in MDD are valence-dependent. This was achieved by implementing psycho-physiological interaction (PPI) analysis, enabling the identification of brain regions whose direct connectivity changes in a given psychological context (Friston et al. 1997, O'Reilly et al. 2012). To this end, whole-brain PPI analyses were conducted separately for gain and penalty outcomes using the caudate as a seed. Following the fMRI scan, depressed individuals were enrolled in a 12-week, randomized, double-blind, placebo-controlled clinical trial comparing Escitalopram and SAMe – a dietary supplement with antidepressant properties (Mischoulon et al. 2013, Papakostas et al. 2010). As an exploratory third aim we investigated whether pre-treatment PPI connectivity values predict symptom change 12 weeks later.

Methods and Materials

Participants

Recruitment procedures and sample characteristics have been described in detail before (Pizzagalli et al. 2009). Briefly, depressed participants (n = 30; 15 males) had a diagnosis of MDD according to the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID) (First et al. 2002), and a score ≥16 on the 21-item Hamilton Depression Rating Scale (HDRS21) (Hamilton 1967). Exclusion criteria included: any psychotropic medication in the past 2 weeks (6 weeks for fluoxetine; 6 month for dopaminergic drugs or neuroleptics); a current or past history of MDD with psychotic features; and presence of other axis I diagnoses (including lifetime substance dependence and any substance use disorder in the past year), with the exception of anxiety disorders. Specifically, 11 depressed participants had a current anxiety disorder (37% of sample), and three had subthreshold anxiety symptoms (10% of sample size). Comparison subjects (n = 31; 18 males) were recruited from the community. They reported no medical or neurological illness, no current or past psychopathology (according to the SCID), and no use of psychotropic medications. As summarized in Supplement Table S1, MDD and comparison groups were demographically matched in age, years of education, gender and ethnicity. All participants were right-handed and provided written informed consent to a protocol approved by the Committee on the Use of Human Subjects in Research at Harvard University and the Partners Human Research Committee.

Monetary Incentive Delay Task

See Supplement Figure S1 for a graphical description of the task. In short, trials began with a visual cue (1.5 sec) indicating the potential outcome (reward: +$; loss: –$; no incentive: 0$). After a variable inter stimulus interval (3–7.5 sec), a red target square was briefly presented, to which subjects responded by pressing a button. After a second variable delay (4.4–8.9 sec), visual feedback (1.5 sec) indicated the trial outcome (gain, penalty, no change). A variable interval (3–12 sec) separated the trials. The task involved five blocks of 24 trials each. Gains and penalties were delivered in a predetermined pattern to allow a balanced design. For each block, half of the reward trials yielded a monetary gain (range = $1.96–$2.34; mean = $2.15) and half ended with no-change feedback. Similarly, half of the loss trials yielded a monetary penalty (range = $1.81–$2.19; mean = $2.00), and half resulted in no change. No-incentive trials always ended with no-change feedback. In spite of these predetermined outcomes, participants were told that responding rapidly would maximize their chances of obtaining gains and avoiding penalties. In order to maximize the perception of contingency between outcomes and participants’ responses, target presentation duration was individually titrated to be longer for trials scheduled to be successful than for those scheduled to be unsuccessful.

Data Acquisition

Data were collected on a 1.5-T Symphony/Sonata scanner (Siemens Medical Systems, Iselin, N.J.) and consisted of a T1-weighted MPRAGE acquisition (repetition time = 2730 msec; echo time = 3.39 msec; field of view = 256 mm; resolution = 1×1×1.33 mm3; 128 slices) and gradient echo T2*-weighted echoplanar images (repetition time = 2500 msec; echo time = 35 msec; field of view = 200 mm; resolution = 3.125×3.125×3 mm3; 35 interleaved slices).

fMRI Data analysis

fMRI data were analyzed using FMRIB's FSL 4.1.5. [(Smith et al. 2004); http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/]. Data pre-processing included: motion correction using MCFLIRT (Jenkinson et al. 2002), slice timing correction, removal of non-brain structures using BET (Smith 2002), spatial smoothing (6 mm), grand mean intensity normalization, and high-pass temporal filtering (σ = 60 sec). Registration of functional data to the high-resolution structural images was done using the linear registration tool in FSL, FLIRT (Jenkinson et al. 2002), and registration of structural images to the 2-mm MNI standard space template was done using the non-linear registration tool FNIRT (Smith et al. 2004). Data for four MDD and two control subjects were lost because of excessive motion (> 2 mm), leaving 26 individuals in the MDD group and 29 in the control. Notably, the present study included two fewer participants than our previous report (Pizzagalli et al. 2009) due to a stricter motion correction exclusion criterion, as motion can have particularly strong impact on connectivity analyses (Power et al. 2012). Hemodynamic responses were modeled using a gamma function and convolved with onset times of cues and outcomes to form the general linear model (GLM) at the single subject level. The six rigid-body movement parameters, target, and error trials were included in the GLM as covariates of no interest. Our previous analysis of this sample revealed that the differences in brain function between healthy controls and MDD were much more robust in response to outcomes than cues (Pizzagalli et al. 2009). Thus, current analyses focused on connectivity abnormalities in response to outcome stimuli only. In order to probe caudate responsivity and connectivity to both monetary outcomes in a balanced way, contrast maps were created by comparing responses to gains and penalties outcomes vs. responses to neutral outcome [gain = +1, penalty = +1, no-change = −2)]. These subject-level contrast maps were transformed to MNI standard space (2 mm) using the transformation matrices from the registration step during pre-processing. Group differences were evaluated using a random effects higher-level GLM (two group unpaired t-test). Left and right caudate regions of interest (ROIs) were defined by conducting a conjunction between functional and anatomical masks of the caudate. The functional caudate cluster was derived from the map of significant group differences (controls > MDD) in responses to gains and penalties outcomes vs. responses to neutral outcome (p < 0.005 or Z > 2.58, uncorrected for multiple comparisons across voxels), while the anatomical caudate template was taken from the Harvard-Oxford subcortical structural atlas (likelihood > 20%) (Desikan et al. 2006). These group-level ROIs were then warped into each individual’s native space to identify subject-specific caudate ROIs from which average BOLD signal parameter estimates were extracted separately for gain, penalty, and no-change outcomes. Next, left and right caudate ROIs were merged to create a single ROI mask of bilateral caudate from which timecourses were extracted for PPI analyses. For each subject, subject-level GLMs were constructed as described above, with the addition of the bilateral caudate seed timecourse as a regressor as well as three additional PPI regressors, that is, the product of the seed timecourse and the regressors for gain, penalty, and no-change outcomes. These regressors are orthogonal to the task and seed regressors, and thus describe the contribution of the interaction above and beyond the main effects of the task and seed timecourse. In addition, orthogonality of the task and PPI regressors ensures that the approach used to identify the caudate seed ROI for the PPI is not circular (McLaren et al. 2012). Contrasts for each PPI were assessed for group differences using a higher-level GLM (two group unpaired t-test). Inference was made using clusters determined by Z > 2.3 and a corrected cluster significance threshold of P = 0.05 (using Gaussian Random Field theory (Worsley 2001)).

Treatment and symptom evaluation

Patients in the current study were randomly chosen to undergo an fMRI scan from a larger pool of depressed individuals (n = 189) enrolled in a multi-site randomized, double-bind, placebo-controlled clinical trial comparing the dietary supplement S-adenosyl methionine (SAMe) (1600–3200 mg/day) and Escitalopram (10–20 mg/day) over a 12 week treatment period (Mischoulon et al. 2013). SAMe treatment was investigated due to previous reports supporting its antidepressant efficacy as monotherapy against placebo and tricyclic antidepressants (Papakostas 2009, Papakostas et al. 2003). Notably, this large sample clinical trial revealed that depressive symptoms significantly improved over the 12 treatment weeks; however, both primary outcome measure (% symptom change from pre- to post-treatment, defined as [(HDRS17(pre) – HDRS17(post)) / HDRS17(pre) * 100]), and secondary outcome measures (treatment response and remission rate, defined as ≥ 50% pre- to post-treatment reduction in HDRS17 scores, and a post-treatment HDRS17 score ≤ 7, respectively) revealed no significant difference among the three treatment arms (Escitalopram, SAMe, and placebo) (Mischoulon et al. 2013). As depicted in Table 1, the sample that underwent fMRI prior to their enrollment in the clinical trial was equally randomized to the three treatment arms, displayed no differences in treatment completion rate, and showed comparable efficacy among treatment arms. Thus, the fMRI sample is representative of the larger clinical trial sample. In light of these outcome data, the pre-treatment PPI connectivity values for the 14 MDD patients who completed the 12-week treatment were aggregated across treatments and tested as predictors of clinical outcome via regression analyses.

Table 1.

Treatment outcome data. The three treatment arms were comparable across all measures, mirroring patterns observed in the larger clinical trial (Mischoulon et al., 2013).

Total SAMe Escitalopram Placebo P*
N (%) 26 (100%) 8 (31%) 11 (42%) 7 (27%) 0.82
Completion rate N (%) 14 (54%) 5 (63%) 5 (46%) 4 (57%) 0.44
% Symptom change 32% 39% 25% 32% 0.42
Response rate N (%) 7 (50%) 3 (60%) 2 (40%) 2 (50%) 0.42
Remission rate N (%) 6 (43%) 3 (60%) 2 (40%) 1 (25%) 0.39
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*

Due to the limited sample size, the three treatment arms were compared using Kruskal-Wallis non-parametric ANOVA.

Results

Caudate activation in response to gains and penalties

Whole brain analysis revealed weaker bilateral caudate activation to incentives in MDD compared to controls (Figure 1A). As depicted in Table 2, the location of those clusters highly resemble the ones described in our prior analyses (Pizzagalli et al. 2009). To further investigate caudate activations, average parameter estimates from the left and right caudate were extracted for each outcome contrast and entered as the dependent variables into a hemisphere X condition repeated-measure analysis of variance (ANOVA) with Group (controls vs. MDD) as a between-subject factor. This analysis revealed only a significant main effect of Group (F53 = 18.51, P < 0.001), with no interaction, suggesting that both left and right caudate clusters were hypo-active in MDD in response to both gains and penalties. Thus, left and right caudate ROIs were merged to create a single ROI mask of bilateral caudate. Figure 1B depicts the group average activation values as extracted from this bilateral caudate mask, indicating that relative to healthy controls, depressed individuals exhibited decreased bilateral caudate activation to both gains (P = 0.023) and penalties (P = 0.002).

Figure 1.

Figure 1

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A. Clusters in left and right caudate exhibiting hypo activation in depressed individuals (MDD) compared to healthy controls (HC) in response to monetary gains and penalties vs. responses to neutral outcome (p < 0.005 or Z > 2.58, uncorrected for multiple comparisons across voxels). B. Average activation values as extracted from bilateral caudate mask, indicating that relative to healthy controls, depressed individuals exhibited decreased bilateral caudate activation to both gains and penalties. Bars ±1 S.E.M. * p< 0.05, ** p< 0.005.

Table 2.

Caudate hypo-activations in response to gains and penalties in MDD. Left and right caudate emerged from the map of significant group differences (controls > MDD) in responses to gains and penalties outcomes vs. responses to neutral outcome (p < 0.005 or Z > 2.58, uncorrected for multiple comparisons across voxels).

Region Cluster size (#) X Y Z Z score
Gain + Penalty outcome > Neutral outcome (HC > MDD)
Left Caudate 59 −8 0 14 3.64
Right Caudate 42 14 20 8 3.43
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Caudate connectivity in response to gains and penalties

PPI analyses revealed a single cluster, located in the dorsal section of anterior cingulate cortex (dACC), which was more functionally connected to the caudate in controls compared to depressed participants during gain outcomes. On the other hand, a different dACC cluster was found to be more functionally connected to the caudate in MDD compared to controls during penalties (Figure 2A, blue and red, respectively, and Table 3). No clusters showed stronger connection with the caudate in controls compared to MDD during penalty outcomes or in MDD compared to controls during gain outcomes. Finally, no group PPI differences emerged during neutral outcomes. Figure 2B depict the mean connectivity values as extracted from each dACC ROI for each condition. Importantly, the opposite pattern of abnormal connectivity in MDD suggests that their diminished caudate activation did not bias the PPI analyses. Indeed, regression analyses with the extracted connectivity values revealed that group differences in connectivity remained significant even after accounting for caudate activation as a covariate (P = 0.018, P = 0.005 for gain and penalty, respectively).

Figure 2.

Figure 2

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A. Two distinct dACC clusters with opposite caudate connectivity abnormalities in MDD. dACC1 (blue) was more functionally connected to the caudate in controls (HC) compared to MDD during gains, whereas dACC2 (red) was more functionally connected to the caudate in MDD compared to controls during penalties. B. Mean parameter estimates (connectivity values) from each dACC section for each condition. Bars ±1 S.E.M. * p< 0.05, ** p< 0.005.

Table 3.

Caudate connectivity abnormalities in response to gains and penalties in MDD. The results emerged from a whole brain Family-Wise Error (FWE) corrected (P < 0.05) PPI analyses using the bilateral caudate as a seed.

Region Cluster size (#) X Y Z Z score
Gain outcome (HC > MDD)
dACC1 (BA 24) 378 8 14 36 3.61
Penalty outcome (MDD > HC)
dACC2 (BA 24) 361 −2 30 20 3.67
Superior Frontal gyrus (BA 9) 496 −28 60 −2 3.6
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Notably, although both dACC clusters were within Brodmann area (BA) 24, they were distinct and spatially segregated. For the sake of simplicity, the dACC cluster that was more connected to the caudate in controls during positive outcomes (monetary gains) will be referred to hereafter as dACC1, while the one that was more connected to the caudate in MDD during negative outcomes (monetary penalties) as dACC2 (Figure 2A, blue and red, respectively).

Prediction of symptom change

Regression analyses revealed that neither pre-treatment dACC1-caudate connectivity during gains nor pre-treatment dACC2-caudate connectivity during penalties were associated with the % symptom change 12 weeks later (r = 0.23, P = 0.42; r = 0.08, P = 0.79, respectively). Notably, both connectivity measures were also not associated with baseline depressive severity (pre-treatment HDRS17 score) (r = 0.2, P = 0.33; r = 0.03, P = 0.9; for dACC1-caudate and dACC2-caudate connectivity, respectively).

Next, we evaluated whether simultaneously accounting for connectivity abnormalities to both outcomes would increase prediction accuracy. This was done owing to the demonstrated abnormalities in response to both positive and negative outcomes in our MDD sample, as well as previous findings indicating that responses to positive and negative contexts mutually contribute to depression course (Rottenberg et al. 2002). Further, various event-related potential (ERP) studies have shown that a difference (composite) score in the feedback-related negativity (FRN) in response to monetary reward and loss correlated with depression severity (Foti&Hajcak 2009), and predicted future first onset of MDD (Bress et al. 2013). Directly relevant to the current study, the FRN is thought to originate from the ACC (Gehring&Willoughby 2002), further corroborating our approach. Thus, the individuals’ dACC2-caudate connectivity during penalty was subtracted from dACC1-caudate connectivity during gain, yielding a composite measure for which decreasing scores highlight greater deviation from the healthy controls’ pattern. Regression analyses revealed that the composite connectivity score was not associated with baseline depression severity (r = 0.35, P = 0.09), but was significantly positively correlated with the % symptom change (F12 = 6.92, r = 0.61, P = 0.022). Accordingly, the higher the score (i.e., the more normative the pre-treatment pattern of cortico-striatal connectivity), the more the symptoms improved 12 weeks later (Figure 3). To test the specificity and robustness of these findings, we conducted a hierarchical regression analysis in which treatment arm (dummy coded), gender, baseline depressive severity, and caudate (seed) activation to gain and penalty outcomes were entered in the first step, followed by the composite connectivity score in the second step; % symptom change was the dependent variable. The model in the first step was not significant (F = 1.14, P = 0.4, r = 0.4). When entering the composite score in the second step, the model became significant (Fchange = 6.61, Pchange = 0.033, rchange = 0.56, R2change = 0.36), indicating that the association between % symptom change and pre-treatment cortico-striatal connectivity remained significant even when accounting for baseline depression severity, gender and treatment arm.

Figure 3.

Figure 3

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Caudate-dACC connectivity in MDD aggregated across both incentives is positively correlated with the percentage of symptom change following 12 weeks of treatment. The closer the pattern of pre-treatment caudate-dACC connectivity was to the controls’ pattern, the larger was the improvement in symptoms. % Symptom change = [(HDRS17(pre) – HDRS17(post)) / HDRS17(pre)]. Caudate-dACC connectivity = [(dACC1-Caudate connectivity during gains) – (dACC2-Caudate connectivity during penalties)].

Discussion

Following the demonstration of blunted caudate responsiveness to positive and negative outcomes in MDD (Pizzagalli et al. 2009), the overarching goal of the present study was to evaluate whether unmedicated MDD individuals are also characterized by disrupted, valence-dependent, caudate connectivity. Using PPI whole brain analyses in a relatively large sample involving 26 unmedicated individuals with MDD and 29 healthy controls, we identified spatially distinct dACC regions characterized by opposite patterns of abnormal caudate connectivity in MDD in response to positive and negative outcomes. Specifically, one dACC sub-region showed decreased connectivity with the caudate during gain outcomes, while a distinct dACC sub-region showed increased connectivity with the caudate during penalty outcomes relative to healthy controls. In addition, an exploratory analysis revealed that a more normative pattern of pre-treatment cortico-striatal connectivity predicted greater symptoms improvement following a 12-week treatment period.

Previous findings in healthy subjects have implicated caudate-dACC circuitry in the establishment of contingency between a given action and its outcome, regardless of its valence (Niznikiewicz&Delgado 2011, Tricomi et al. 2004). Specifically, in prior studies, striatal function was interpreted as indicating mismatch between expected and experienced outcomes (prediction error) (Delgado 2007, Rangel et al. 2008), while dACC function was associated with individuals’ evaluation of their control over a given process (Shenhav et al. 2013). In light of these findings, altered cortico-striatal connectivity in MDD may hamper learning action-outcome contingencies, which in turn might disrupt goal-directed behavior. In particular, reduced synchronization between caudate and dACC1 in response to monetary gains in MDD may reflect impaired functional integration in this circuitry during positive feedback, which might reduce the saliency of such feedback in reinforcing a repetition of this (successful) action. In support of this interpretation, compared to healthy controls, individuals with MDD show a lower probability of repeating an action that led to a positive feedback or reward (Liu et al. 2011, Pizzagalli et al. 2008, Vrieze et al. 2013), and weaker behavioral modulation of incentives (Pizzagalli et al. 2009). In addition, blunted caudate responsiveness in MDD emerged while patients learned to associate their actions with the receipt of unpredictable reward (Kumar et al. 2008, Pizzagalli et al. 2009, Smoski et al. 2009), yet no caudate abnormalities in MDD emerged when rewards were more predictable (Knutson et al. 2008). On the other hand, increased caudate-dACC2 connectivity during penalties may represent a neural mechanism for the abnormally increased representation of negative feedback upon the completion of an (unsuccessful) action in MDD. Indeed, depressed individuals amplify the significance of failures relative to controls (Wenzlaff&Grozier 1988), potentially leading to the commitment of more errors after an initial mistake (Beats et al. 1996, Elliott et al. 1996, Holmes&Pizzagalli 2008, Pizzagalli et al. 2006, Steffens et al. 2001). Intriguingly, inaccurate estimation of contingencies between behaviors and emotional outcomes has long been considered a characterizing feature of MDD (Alloy&Abramson 1979). Even further, contingency deficiencies in response to affective outcomes fit with two classical models of MDD, Seligman’s learned helplessness model and Beck’s cognitive theory (Beck 2005, Seligman 1972). The first posits that MDD patients grow to accept that negative circumstances cannot be altered through their own actions (Seligman 1972), while the second proposes that depression is associated with biased processing of feedback information in such a way that depressed individuals fail to interpret positive events as resulting from their owns’ actions yet over-attribute negative events to their actions (Beck 2005). Whether disrupted cortico-striatal connectivity is indeed linked to these cognitive diatheses is currently unknown and warrants further inquiry.

Notably, caudate-dACC connectivity before treatment was associated with symptom changes 12 weeks later, even when accounting for pre-treatment depression severity. This novel finding should be regarded as preliminary given that the current sample size prevented us from comparing individuals who reached remission vs. the ones who did not, as well as to differentiate between treatment arms. Indeed, symptom change was predicted regardless of whether it was achieved through pharmacology, a dietary supplement with antidepressant properties, or placebo. Therefore, we can only speculate that a more normative pattern of pre-treatment caudate-dACC connectivity may be associated with larger and global clinical improvement. Further highlighting the role of these neural pathways in clinical course, treatment-induced normalization of fronto-striatal functional connectivity was found to positively correlate with increases in positive affect (Heller et al. 2013). Critically, clinical improvement was achieved through either Venlafaxine or Fluoxetine, suggesting that the mechanism of action fostering improvements in positive affect and fronto-striatal connectivity did not differ between the two antidepressants (Heller et al. 2013). Similarly, a recent meta-analysis indicated that increased pre-treatment ACC and striatum activation is a robust predictor of positive response to both pharmacological and behavioral treatment in MDD (Fu et al. 2013). Moreover, the ACC cluster identified by Fu and colleagues overlaps with the dACC cluster emerging from the current connectivity analyses and predicting symptom improvement following treatment. Lastly, it warrants comment that MDD were also shown to exhibit abnormalities in the integrity of the internal capsule fibers, which connect striatal and cingulate regions (Zhang et al. 2013, Zhu et al. 2011, Zou et al. 2008), and that decreased white-matter volume in the internal capsule predicted treatment non-response to pharmacology (Phillips et al. 2012). Conversely, deep brain stimulation (DBS) to the internal capsule has been found to reduce depressive symptoms in severely depressed, treatment-resistant MDD patients (Blomstedt et al. 2011), and stimulate cingulate regions in non-human primates (Knight et al. 2013). Accordingly, the current cortico-striatal connectivity findings and prior findings highlight a key role of this circuitry in the pathophysiology of MDD and mechanisms of treatment response.

In summary, we demonstrated that, compared to healthy controls, depressed individuals exhibit abnormal caudate connectivity with the dACC and, furthermore, that such dysregulated cortico-striatal connectivity is both incentive-dependent and predictive of treatment response. These findings may account for the commonly observed reduced action-outcome contingency learning in MDD, which may disrupt goal-directed behavior and represent a central feature of anhedonic behavior in MDD.

Supplementary Material

01

Acknowledgments

The authors are grateful to Elena L. Goetz, Jeffrey Birk, Sunny J. Dutra and Nancy Brooks Hall for their skilled assistance with this study. This study was supported by National Institute of Mental Health (NIMH) grant R01 MH068376 awarded to DAP as well as National Center for Complementary & Alternative Medicine (NCCAM) grant R21 AT002974 awarded to DAP and NCCAM R01 AT001638 awarded to MF. AJH and DGD were supported by grants K01 MH099232 and K99 MH094438, respectively.

Dr. Dougherty has received over the past three years research support and consulting/honoraria from Medtronic, travel and research support from Roche and research support from Eli Lilly and Cyberonics.

Dr. Iosifescu has received over the past three years funding through Icahn School of Medicine at Mount Sinai from AstraZeneca, Brainsway, Euthymics, Neosync, and Roche; and consulting fees from Avanir, CNS Response, Otsuka, Servier and Sunovion.

Dr. Mischoulon has received over the past three years research support from the Bowman Family Foundation, Bristol-Myers Squibb Co., Cederroth, FisherWallace, Ganeden, Lichtwer Pharma, Nordic Naturals, Laxdale (Amarin), Methylation Sciences, Inc. (MSI), and SwissMedica. Honoraria for consulting, speaking, and writing from Pamlab, Bristol-Myers Squibb Co., Nordic Naturals, Virbac, Pfizer, Reed Medical Education, and the Massachusetts General Hospital Psychiatry Academy. Royalties from Back Bay Scientific for PMS Escape, and from Lippincott Williams & Wilkins for published book “Natural Medications for Psychiatric Disorders: Considering the Alternatives.” No payment has exceeded $10,000.

Dr. Fava has received research support from Abbot Laboratories, Alkermes Inc., American Cyanamid, Aspect Medical Systems, AstraZeneca, BioResearch, BrainCells Inc., Bristol-Myers Squib, CeNeRx BioPharma, Cephalon, Clintara LLC, Covance, Covidien, Eli Lilly and Company, EnVivo Pharmaceuticals Inc., Euthymics Bioscience Inc., Forest Pharmaceuticals Inc., Ganeden Biotec, Inc., GlaxoSmithKline, Harvard Clinical Research Institute, Hoffman-LaRoche, Icon Clinical Research, i3 Innovus/Ingenix, Janssen R&D LLC, Jed Foundation, Johnson & Johnson Pharmaceutical Research & Development, Lichtwer Pharma GmbH, Lorex Pharmaceuticals, MedAvante, National Alliance for Research on Schizophrenia & Depression (NARSAD), National Center for Complementary and Alternative Medicine (NCCAM), National Institute of Drug Abuse (NIDA), National Institute of Mental Health (NIMH), Neuralstem Inc., Novartis AG, Organon Pharmaceuticals, PamLab LLC, Pfizer Inc., Pharmacia-Upjohn, Pharmaceutical Research Associates Inc., Pharmavite® LLC, PharmoRx Therapeutics, Photothera, Roche Pharmaceuticals, RCT Logic, LLC (formerly Clinical Trials Solutions, LLC), Sanofi-Aventis US LLC, Shire, Solvay Pharmaceuticals Inc., Synthelabo, Wyeth-Ayerst Laboratories. Advisory/consulting from Abbott Laboratories, Affectis Pharmaceuticals AG, Alkermes Inc., Amarin Pharma Inc., Aspect Medical Systems, AstraZeneca, Auspex Pharmaceuticals, Bayer AG, Best Practice Project Management Inc., BioMarin Pharmaceuticals Inc., Biovail Corporation, BrainCells Inc., Bristol-Myers Squibb, CeNeRx BioPharma, Cephalon Inc., Cerecor, Clinical Trials Solutions, CNS Response Inc., Compellis Pharmaceuticals, Cypress Pharmaceutical Inc., DiagnoSearch Life Sciences (P) Ltd., Dinippon Sumitomo Pharma Co. Inc., Dov Pharmaceuticals Inc., Edgemont Pharmaceuticals Inc., Eisai Inc., Eli Lilly and Company, EnVivo Pharmaceuticals Inc., ePharmaSolutions, EPIX Pharmaceuticals Inc., Euthymics Bioscience Inc., Fabre-Kramer Pharmaceuticals Inc., Forest Pharmaceuticals Inc., GenOmind LLC, GlaxoSmithKline, Grunenthal GmbH, i3 Innovus/Ingenis, Janssen Pharmaceutica, Jazz Pharmaceuticals Inc., Johnson & Johnson Pharmaceutical Research & Development LLC, Knoll Pharmaceuticals Corp., Labopharm Inc., Lorex Pharmaceuticals, Lundbeck Inc., MedAvante Inc., Merck & Co., Inc., MSI Methylation Sciences Inc., Naurex Inc., Neuralstem Inc., Neuronetics Inc., NextWave Pharmaceuticals, Novartis AG, Nutrition 21, Orexigen Therapeutics Inc., Organon Pharmaceuticals, Otsuka Pharmaceuticals, Pamlab LLC., Pfizer Inc., PharmaStar, Pharmavite® LLC., PharmoRx Therapeutics, Precision Human Biolaboratory, Prexa Pharmaceuticals Inc., Puretech Ventures, PsychoGenics, Psylin Neurosciences Inc., Rexahn Pharmaceuticals Inc., Ridge Diagnostics Inc., Roche, Sanofi-Aventis US LLC., Sepracor Inc., Servier Laboratories, Schering-Plough Corporation, Solvay Pharmaceuticals Inc., Somaxon Pharmaceuticals Inc., Somerset Pharmaceuticals Inc., Sunovion Pharmaceuticals, Supernus Pharmaceuticals Inc., Synthelabo, Takeda Pharmaceutical Company Limited, Tal Medical Inc., Tetragenex Pharmaceuticals Inc., TransForm Pharmaceuticals Inc., Transcept Pharmaceuticals Inc., Vanda Pharmaceuticals Inc. Speaking/publishing from Adamed Co, Advanced Meeting Partners, American Psychiatric Association, American Society of Clinical Psychopharmacology, AstraZeneca, Belvoir Media Group, Boehringer Ingelheim GmbH, Bristol-Myers Squibb, Cephalon Inc., CME Institute/Physicians Postgraduate Press Inc., Eli Lilly and Company, Forest Pharmaceuticals Inc., GlaxoSmithKline, Imedex LLC, MGH Psychiatry Academy/Primedia, MGH Psychiatry Academy/Reed Elsevier, Novartis AG, Organon Pharmaceuticals, Pfizer Inc., PharmaStar, United BioSource Corp., Wyeth-Ayerst Laboratories. Equity holdings in Compellis, PsyBrain Inc. Royalty/patent or other income from Patent for Sequential Parallel Comparison Design (SPCD), which are licensed by MGH to RCT Logic, LLC, and patent application for a combination of Scopolamine and Ketamine in Major Depressive Disorder (MDD). Copyright for the MGH Cognitive & Physical Functioning Questionnaire (CPFQ), Sexual Functioning Inventory (SFI), Antidepressant Treatment Response Questionnaire (ATRQ), Discontinuation-Emergent Signs & Symptoms (DESS), and SAFER, Lippincott, Williams & Wilkins, Wolkers Kluwer, World Scientific Publishing Co. Pte. Ltd.

Dr. Pizzagalli has received over the past three years honoraria/consulting fees from Advanced Neuro Technology North America, AstraZeneca, Ono Pharma USA, Pfizer, Servier, and Shire for studies unrelated to this project.

Footnotes

Financial Disclosures

All other authors have no biomedical financial interests to disclose.

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