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Specific Frontostriatal Circuits for Impaired Cognitive Flexibility and Goal-Directed Planning in Obsessive-Compulsive Disorder: Evidence From Resting-State Functional Connectivity

Open AccessPublished:August 11, 2016DOI:https://doi.org/10.1016/j.biopsych.2016.08.009

      Abstract

      Background

      A recent hypothesis has suggested that core deficits in goal-directed behavior in obsessive-compulsive disorder (OCD) are caused by impaired frontostriatal function. We tested this hypothesis in OCD patients and control subjects by relating measures of goal-directed planning and cognitive flexibility to underlying resting-state functional connectivity.

      Methods

      Multiecho resting-state acquisition, combined with micromovement correction by blood oxygen level–dependent sensitive independent component analysis, was used to obtain in vivo measures of functional connectivity in 44 OCD patients and 43 healthy comparison subjects. We measured cognitive flexibility (attentional set-shifting) and goal-directed performance (planning of sequential response sequences) by means of well-validated, standardized behavioral cognitive paradigms. Functional connectivity strength of striatal seed regions was related to cognitive flexibility and goal-directed performance. To gain insights into fundamental network alterations, graph theoretical models of brain networks were derived.

      Results

      Reduced functional connectivity between the caudate and the ventrolateral prefrontal cortex was selectively associated with reduced cognitive flexibility. In contrast, goal-directed performance was selectively related to reduced functional connectivity between the putamen and the dorsolateral prefrontal cortex in OCD patients, as well as to symptom severity. Whole-brain data-driven graph theoretical analysis disclosed that striatal regions constitute a cohesive module of the community structure of the functional connectome in OCD patients as nodes within the basal ganglia and cerebellum were more strongly connected to one another than in healthy control subjects.

      Conclusions

      These data extend major neuropsychological models of OCD by providing a direct link between intrinsically abnormal functional connectivity within dissociable frontostriatal circuits and those cognitive processes underlying OCD symptoms.

      Keywords

      Persistent intrusive thoughts and repetitive actions characterize the symptoms of obsessive-compulsive disorder (OCD). Over and above these often highly specific clinical symptoms is a general tendency toward poor performance on tasks requiring flexible behavior (
      • Abramovitch A.
      • Abramowitz J.S.
      • Mittelman A.
      The neuropsychology of adult obsessive-compulsive disorder: A meta-analysis.
      ,
      • Purcell R.
      • Maruff P.
      • Kyrios M.
      • Pantelis C.
      Cognitive deficits in obsessive-compulsive disorder on tests of frontal-striatal function.
      ,
      • Purcell R.
      • Maruff P.
      • Kyrios M.
      • Pantelis C.
      Neuropsychological deficits in obsessive-compulsive disorder: A comparison with unipolar depression, panic disorder, and normal controls.
      ). Preclinical and clinical evidence indicates the integrity of the basal ganglia and their connections with the frontal cortex to be crucial in enabling the affective, cognitive, and motor flexibility necessary for goal-directed behavior (
      • Alexander G.E.
      • DeLong M.R.
      • Strick P.L.
      Parallel organization of functionally segregated circuits linking basal ganglia and cortex.
      ,
      • Middleton F.A.
      • Strick P.L.
      Basal ganglia output and cognition: Evidence from anatomical, behavioral, and clinical studies.
      ). These data are thus broadly consistent with a leading neural model implicating frontostriatal circuits in the pathogenesis of OCD (
      • Baxter Jr, L.R.
      • Phelps M.E.
      • Mazziotta J.C.
      • Guze B.H.
      • Schwartz J.M.
      • Selin C.E.
      Local cerebral glucose metabolic rates in obsessive-compulsive disorder. A comparison with rates in unipolar depression and in normal controls.
      ,
      • Saxena S.
      • Brody A.L.
      • Schwartz J.M.
      • Baxter L.R.
      Neuroimaging and frontal-subcortical circuitry in obsessive-compulsive disorder.
      ,
      • Saxena S.
      • Rauch S.L.
      Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder.
      ). However, this model has not been clearly linked to underlying cognitive or psychological processes mediated by this circuitry. This link has recently been provided by a major hypothesis concerning OCD (
      • Gillan C.M.
      • Papmeyer M.
      • Morein-Zamir S.
      • Sahakian B.J.
      • Fineberg N.A.
      • Robbins T.W.
      • de Wit S.
      Disruption in the balance between goal-directed behavior and habit learning in obsessive-compulsive disorder.
      ,
      • Gillan C.M.
      • Apergis-Schoute A.M.
      • Morein-Zamir S.
      • Urcelay G.P.
      • Sule A.
      • Fineberg N.A.
      • et al.
      Functional neuroimaging of avoidance habits in obsessive-compulsive disorder.
      ), which postulates that OCD symptoms arise from impairments in goal-directed behavior, leading to autonomous habitual behavior as a consequence of functional imbalances in frontostriatal circuitry (
      • Graybiel A.M.
      • Rauch S.L.
      Toward a neurobiology of obsessive-compulsive disorder.
      ,
      • Gillan C.M.
      • Robbins T.W.
      Goal-directed learning and obsessive-compulsive disorder.
      ).
      Resting-state activity derived from functional magnetic resonance imaging (fMRI) enables inference of the strength of functional connectivity between different brain regions. OCD patients exhibit hyperconnectivity of ventrolimbic corticostriatal regions that correlates with symptom severity as well as hypoconnectivity of the caudate and putamen with cortical areas (
      • Harrison B.J.
      • Soriano-Mas C.
      • Pujol J.
      • Ortiz H.
      • López-Solà M.
      • Hernández-Ribas R.
      • et al.
      Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
      ). However, the behavioral significance of this pattern of functional connectivity is yet to be established.
      Here, we focused on attentional set-shifting (cognitive flexibility) as well as goal-directed planning. Deficits in these executive functions represent candidate endophenotypes for the disorder (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Menzies L.A.
      • Blackwell A.D.
      • Bullmore E.T.
      • Robbins T.W.
      • Sahakian B.J.
      Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive-compulsive disorder.
      ,
      • Delorme R.
      • Goussé V.
      • Roy I.
      • Trandafir A.
      • Mathieu F.
      • Mouren-Siméoni M.-C.
      • et al.
      Shared executive dysfunctions in unaffected relatives of patients with autism and obsessive-compulsive disorder.
      ) and have been related to OCD symptoms (
      • Chamberlain S.R.
      • Blackwell A.D.
      • Fineberg N.A.
      • Robbins T.W.
      • Sahakian B.J.
      The neuropsychology of obsessive compulsive disorder: The importance of failures in cognitive and behavioural inhibition as candidate endophenotypic markers.
      ). Planning is measured as the ability to attain a goal via a prepared series of actions controlled by a single instrumental contingency (
      • Shallice T.
      Specific impairments of planning.
      ). OCD patients are impaired in this goal-directed capacity, especially at more demanding levels (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Blackwell A.D.
      • Clark L.
      • Robbins T.W.
      • Sahakian B.J.
      A neuropsychological comparison of obsessive-compulsive disorder and trichotillomania.
      ). Compared with control subjects, OCD patients exhibit decreased functional activation of the dorsolateral prefrontal cortex (PFC), caudate, and putamen during planning (
      • van den Heuvel O.A.
      • Veltman D.J.
      • Groenewegen H.J.
      • Cath D.C.
      • van Balkom A.J.
      • van Hartskamp J.
      • et al.
      Frontal-striatal dysfunction during planning in obsessive-compulsive disorder.
      ), consistent with other behavioral data suggesting an imbalance between the control exerted by goal-directed and habit systems over behavioral output in OCD (
      • Gillan C.M.
      • Robbins T.W.
      Goal-directed learning and obsessive-compulsive disorder.
      ,
      • Gillan C.M.
      • Morein-Zamir S.
      • Urcelay G.P.
      • Sule A.
      • Voon V.
      • Apergis-Schoute A.M.
      • et al.
      Enhanced avoidance habits in obsessive-compulsive disorder.
      ).
      We hypothesized that impairment of frontostriatal circuitry entailing caudate and putamen and separate regions of PFC likely disrupts implementation of flexible goal-directed behavior in OCD patients. Notwithstanding overlap (
      • Haber S.N.
      The primate basal ganglia: Parallel and integrative networks.
      ), the existence of topographic projections of different PFC regions to striatal regions in monkeys (
      • Alexander G.E.
      • DeLong M.R.
      • Strick P.L.
      Parallel organization of functionally segregated circuits linking basal ganglia and cortex.
      ,
      • Haber S.N.
      The primate basal ganglia: Parallel and integrative networks.
      ) and humans (
      • Draganski B.
      • Kherif F.
      • Kloppel S.
      • Cook P.A.
      • Alexander D.C.
      • Parker G.J.M.
      • et al.
      Evidence for segregated and integrative connectivity patterns in the human basal ganglia.
      ) suggests that separate frontostriatal circuits are implicated in regulating cognitive control and aspects of executive functioning (
      • Alexander G.E.
      • DeLong M.R.
      • Strick P.L.
      Parallel organization of functionally segregated circuits linking basal ganglia and cortex.
      ). Thus, a lateral circuit including the ventrolateral PFC has been suggested to mediate switches in behavioral set (
      • Iversen S.D.
      • Mishkin M.
      Perseverative interference in monkeys following selective lesions of the inferior prefrontal convexity.
      ,
      • Dias R.
      • Robbins T.W.
      • Roberts A.C.
      Dissociation in prefrontal cortex of affective and attentional shifts.
      ,
      • Hampshire A.
      • Owen A.M.
      Fractionating attentional control using event-related fMRI.
      ) with a dorsolateral PFC circuit being related to goal-directed planning (
      • Baker S.C.
      • Rogers R.D.
      • Owen A.M.
      • Frith C.D.
      • Dolan R.J.
      • Frackowiak R.S.
      • Robbins T.W.
      Neural systems engaged by planning: A PET study of the Tower of London task.
      ). On the basis of its PFC inputs, the ventral striatum has alternatively been implicated in affective control and reward processing (
      • Haber S.N.
      • Knutson B.
      The reward circuit: Linking primate anatomy and human imaging.
      ).
      We used resting state to investigate functional connectivity in OCD patients and to overcome limitations of task-related studies in which case-control differences in activation might be the result of task performance, effort, or strategy rather than the reflection of underlying core abnormalities. Moreover, the topography of networks arising from synchronous spontaneous functional activity is compatible with the underlying structural connectivity and consists of regions known to share common functions (
      • Biswal B.
      • Yetkin F.Z.
      • Haughton V.M.
      • Hyde J.S.
      Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.
      ). We leveraged on a novel multiecho acquisition method with significantly increased signal-to-noise ratio and two complementary analytical approaches. First, we formulated specific a priori hypotheses and used seed-based analysis to test whether dysregulated resting-state connectivity arising from caudate and putamen accounted for impairments in cognitive flexibility and executive planning. We hypothesized that if functional abnormalities in these circuits were relevant to OCD, then we should find specific patterns of altered connectivity being associated with cognitive flexibility and goal-directed planning in patients. Consistent with previous evidence (
      • Iversen S.D.
      • Mishkin M.
      Perseverative interference in monkeys following selective lesions of the inferior prefrontal convexity.
      ,
      • Dias R.
      • Robbins T.W.
      • Roberts A.C.
      Dissociation in prefrontal cortex of affective and attentional shifts.
      ,
      • Hampshire A.
      • Owen A.M.
      Fractionating attentional control using event-related fMRI.
      ,
      • Baker S.C.
      • Rogers R.D.
      • Owen A.M.
      • Frith C.D.
      • Dolan R.J.
      • Frackowiak R.S.
      • Robbins T.W.
      Neural systems engaged by planning: A PET study of the Tower of London task.
      ), we predicted that ventrolateral and dorsolateral PFC circuits would mediate cognitive flexibility and goal-directed planning, respectively. To overcome the limitation of exclusively focusing on a priori regions, the second approach applied a whole-brain data-driven graph theoretical analysis to identify novel features of abnormal brain network organization in OCD patients (
      • Bullmore E.
      • Sporns O.
      Complex brain networks: graph theoretical analysis of structural and functional systems.
      ).

      Methods and Materials

      Participants

      The study included 87 participants, consisting of 44 OCD patients and 43 healthy control subjects matched for relevant demographic variables (Table 1, Supplement). The OCD sample included 27 medicated and 17 unmedicated patients; all but one of the medicated patients were taking selective serotonin reuptake inhibitors (Supplement). OCD patients reported higher levels of depressive symptoms and anxiety, although well below clinical threshold (Table 1). Unless otherwise reported, there were no differences between medicated and unmedicated OCD patients in the results presented.
      Table 1Demographic and Clinical Characteristics and Imaging Motion Assessment of the Studied Sample
      VariableCTL (n = 43)OCD (n = 44)Statistic
      χ2tdfp Value
      Demographic and Clinical Characteristics
       Sex, male/female22/2121/230.1031.749
       Hand, right/left38/538/60.0791.778
       Age, years37.51 ± 12.0536.14 ± 10.710.56385.575
       Education, years16.49 ± 3.8115.77 ± 3.210.94885.346
       Estimated verbal IQ
      Estimated verbal IQ was measured with the National Adult Reading Test.
      115.18 ± 6.14112.73 ± 7.201.70485.092
       OCI-R4.56 ± 4.3433.64 ± 11.79−15.19885.000
       MADRS0.77 ± 1.328.41 ± 5.29−9.18985.000
       STAI-state26.95 ± 7.8342.16 ± 10.31−7.73485.000
       STAI-trait33.23 ± 7.7454.98 ± 8.96−12.10385.000
       Y-BOCS total22.00 ± 5.31
       Y-BOCS obsessions10.95 ± 3.22
       Y-BOCS compulsions11.02 ± 2.66
       Onset, years13.39 ± 7.63
       Age at diagnosis, years24.02 ± 7.09
       Duration of disease, years12.11 ± 9.44
      Imaging Motion Assessment
       FD0.11 ± .050.13 ± 0.09−1.87385.065
       Motion, high/low
      Median split of the main cohort of 87 subjects according to a measure of total motion computed as the sum of FD (32).
      19/2424/200.9341.333
       BOLD components23.05 ± 6.4224.68 ± 8.01−1.05085.297
      Values are mean ± SD or n/n.
      BOLD, blood oxygen level–dependent; CTL, control subjects; FD, framewise displacement; MADRS, Montgomery–Åsberg Depression Rating Scale (
      • Montgomery S.A.
      • Asberg M.
      A new depression scale designed to be sensitive to change.
      ); OCD, obsessive-compulsive disorder patients; OCI-R, Obsessive-Compulsive Inventory-Revised (
      • Foa E.B.
      • Huppert J.D.
      • Leiberg S.
      • Langner R.
      • Kichic R.
      • Hajcak G.
      • Salkovskis P.M.
      The Obsessive-Compulsive Inventory: Development and validation of a short version.
      ); STAI, State-Trait Anxiety Inventory (
      • Spielberger C.D.
      Manual for the State-Trait Anxiety Inventory STAI (Form Y).
      ); Y-BOCS, Yale-Brown Obsessive Compulsive Scale (
      • Goodman W.K.
      • Price L.H.
      • Rasmussen S.A.
      • Mazure C.
      • Fleischmann R.L.
      • Hill C.L.
      • et al.
      The Yale-Brown Obsessive Compulsive Scale. I. Development, use, and reliability.
      ).
      a Estimated verbal IQ was measured with the National Adult Reading Test.
      b Median split of the main cohort of 87 subjects according to a measure of total motion computed as the sum of FD (
      • Kundu P.
      • Brenowitz N.D.
      • Voon V.
      • Worbe Y.
      • Vértes P.E.
      • Inati S.J.
      • et al.
      Integrated strategy for improving functional connectivity mapping using multiecho fMRI.
      ).

      Procedure

      Imaging Procedure

      For resting-state data acquisition, we used multiecho planar sequence with improved signal-to-noise ratio (see Supplement for imaging variables). Participants were instructed to lie quietly with their eyes open and attend to a centrally presented white fixation cross on a black projection screen for 10 minutes; we monitored their degree of alertness by asking to complete the Stanford Sleepiness Scale (
      • Hoddes E.
      • Zarcone V.
      • Smythe H.
      • Phillips R.
      • Dement W.C.
      Quantification of sleepiness: A new approach.
      ) ruling out differences in levels of arousal across participants (Supplement).

      Behavioral Testing Procedure

      To elucidate the behavioral significance of the functional abnormalities within frontostriatal circuits in OCD patients, in a separate session outside the scanner, the same participants were tested with objective and well-validated CANTAB paradigms. We used the intra-/extradimensional set shift (IED) and the One Touch Stockings of Cambridge (OTS) to measure cognitive flexibility and goal-directed planning, respectively. The IED is a nine-stage task, and the rule for correct responding is modified at the start of each stage. For the IED, crucial stages are the intradimensional shift (IDs) testing for the ability to generalize a rule to new stimuli and the extradimensional shift (EDs) testing cognitive flexibility as the ability to shift attention to a previously irrelevant dimension. On the OTS, planning abilities are tested at different difficulty levels with problem difficulty varying from 1 to 6 moves (see Supplement for description of the paradigms).

      Image Preprocessing

      Imaging data were preprocessed and analyzed using Analysis of Functional NeuroImages (AFNI) software (
      • Cox R.W.
      AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages.
      ). To denoise the data, we used a novel integrated procedure taking advantage of multiecho acquisition in combination with Multi-Echo Independent Component Analysis (ME-ICA) (AFNI tool meica.py, version 2.5 beta10) (
      • Kundu P.
      • Brenowitz N.D.
      • Voon V.
      • Worbe Y.
      • Vértes P.E.
      • Inati S.J.
      • et al.
      Integrated strategy for improving functional connectivity mapping using multiecho fMRI.
      ). The rationale behind ME-ICA is to classify sources of variance in the fMRI time-series scaling linearly with echo-time and thus confidently regarded as indicative of blood oxygen level–dependent (BOLD) contrast (Supplement). The retained independent components, representing BOLD contrast, were optimally recomposed and visually inspected (see Supplemental Figure S1 for a representative subject). According to multiple, complementary indices, patients and control subjects did not differ for movement in the scanner; there were no significant groups differences in the number of high- versus low-motion subjects in each group or in the number of BOLD components retained or motion as measured by framewise displacement (Table 1).

      Data Analysis

      Behavioral Analysis

      On the IED task, dependent measures at each stage were the number of subjects passing and the number of errors. Data were square root-transformed to stabilize variance and to reduce skewness in the distribution. On the OTS task, we measured the mean number of attempts made before obtaining the correct solution for easy (1–3 moves) and hard (4–6 moves) levels of difficulty (significance threshold, p < .025) (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Blackwell A.D.
      • Clark L.
      • Robbins T.W.
      • Sahakian B.J.
      A neuropsychological comparison of obsessive-compulsive disorder and trichotillomania.
      ). Data were statistically analyzed using χ2, analysis of variance, Student’s t test, and the Mann-Whitney U test to detect group differences between control subjects and OCD patients. Only the 44 OCD patients were included for Pearson’s correlations between clinical scales and measures of tasks yielding significant group differences.

      Image Analysis

      We tested differences in functional connectivity strength between OCD patients and control subjects from a priori anatomical regions of interest based on the known neurobiological profile of OCD and previous findings in the literature (
      • Graybiel A.M.
      • Rauch S.L.
      Toward a neurobiology of obsessive-compulsive disorder.
      ,
      • Harrison B.J.
      • Soriano-Mas C.
      • Pujol J.
      • Ortiz H.
      • López-Solà M.
      • Hernández-Ribas R.
      • et al.
      Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
      ). We examined connectivity from the dorsal caudate (DCd), putamen (PUT), and nucleus accumbens (NAc), defined in both hemispheres as 3-mm radial spheres located at Montreal Neurological Institute coordinates automatically provided by the AFNI-supplied atlas, namely, DCd: ± 12 6 14 [labeled as the body of the caudate and analogous to the dorsal striatal seed previously described in the literature (
      • Harrison B.J.
      • Soriano-Mas C.
      • Pujol J.
      • Ortiz H.
      • López-Solà M.
      • Hernández-Ribas R.
      • et al.
      Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
      )]; PUT: ± 24 0 3; NAc: ± 12 8 −8.
      Based on evidence of caudate and putamen involvement in executive functions, we tested the a priori hypothesis that dysregulated functional connectivity from the DCd and PUT selectively accounted for impairment on relevant cognitive domains in OCD patients. For the OCD patients only, we used number of errors on the EDs stage and mean number of problems attempted at the hardest level of difficulty (6 moves) of the OTS task as a covariate of interest, to identify brain regions for which significant connectivity with DCd and PUT was significantly related to cognitive flexibility and goal-directed planning. Post hoc analyses investigated NAc connectivity relation with cognitive performance and clinical scores.
      ME-ICA denoised data were entered in 3dGroupInCorr to estimate functional connectivity: time-series were extracted from each dataset averaging locally per the seed’s radius and connectivity maps computed with Pearson’s correlation; Fisher’s r-to-z transform for the appropriate degrees of freedom (i.e., number of BOLD components identified for each subject) was used to derive standard scores. Whole-brain analyses were conducted in combination with cluster-based correction. We applied voxel-level height threshold of p < .01 and used 3dClustSim to determine the corrected p values that corresponded to the resulting clusters (Supplement).

      Network Analysis

      To perform data-driven network analysis, for each subject, time-series were extracted by averaging voxel time-series within each of equal-sized cortical and subcortical defined regions (nodes) (see Supplement for parcellation template and detailed procedure). Analysis focused on data at frequency interval 0.049–0.101 Hz at 10% cost, which is compatible with prior studies (
      • Lynall M.-E.
      • Bassett D.S.
      • Kerwin R.
      • McKenna P.J.
      • Kitzbichler M.
      • Muller U.
      • Bullmore E.
      Functional connectivity and brain networks in schizophrenia.
      ). We identified modular community structure, which is a feature of many complex networks, including nervous system. The identification of modules, subsets of nodes densely intraconnected (number of connections between nodes within the module) and sparsely interconnected with nodes in other modules, may uncover functional units (
      • Newman M.E.J.
      Communities, modules and large-scale structure in networks.
      ). The Louvain algorithm (
      • Blondel V.D.
      • Guillaume J.-L.
      • Lambiotte R.
      • Lefebvre E.
      Fast unfolding of communities in large networks.
      ) as implemented in the Brain Connectivity Toolbox (
      • Rubinov M.
      • Sporns O.
      Complex network measures of brain connectivity: Uses and interpretations.
      ) was used to identify modules. Default modularity resolution (gamma = 1) was used in the Louvain algorithm for data presented in the main text and further validated at different gamma levels (Supplement).

      Results

      Functional Striatal Connectivity

      Within-group striatal connectivity patterns overlapped with previously described neuro-functional maps. Both groups showed maps of connectivity consistent with models relating the caudate and putamen to cognitive and motor control (
      • Alexander G.E.
      • DeLong M.R.
      • Strick P.L.
      Parallel organization of functionally segregated circuits linking basal ganglia and cortex.
      ) and the nucleus accumbens to motivational and emotional responses (
      • Haber S.N.
      • Knutson B.
      The reward circuit: Linking primate anatomy and human imaging.
      ) (Supplement, Supplemental Figure S2).

      Between-Group Differences in Striatal Connectivity

      Compared with control subjects, OCD patients showed decreased connectivity strength from DCd and PUT to frontal and parietal regions, whereas ventral striatal-frontal connectivity was increased, in line with previous findings (
      • Harrison B.J.
      • Soriano-Mas C.
      • Pujol J.
      • Ortiz H.
      • López-Solà M.
      • Hernández-Ribas R.
      • et al.
      Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
      ) (Supplement, Supplemental Figure S3, Supplemental Table S1).

      Cognitive Flexibility and Frontostriatal Connectivity

      OCD patients exhibited a profound impairment on cognitive flexibility as tested with the IED (Figure 1A). More OCD patients failed to complete all stages of the task (χ21 = 7.975, p = .005), with patients more likely than control subjects to fail selectively at the EDs stage. All subjects attempted the EDs stage (Supplemental Figure S4). There was a highly significant interaction of stage (IDs, EDs) and group (F1,84 = 7.128, p = .009) in the number of errors. Simple-effect analyses revealed significantly more errors at the EDs stage (t84 = −2.649, p = .01) in OCD patients than control subjects, but no difference at the IDs stage (t84 = 0.742, p = .460) (Figure 1B). Thus, OCD patients were able to form an attentional set and generalize to new stimuli as shown by intact performance up to the EDs stage, but they were selectively impaired when they had to shift attention to a previously irrelevant dimension. There was no significant correlation between the number of errors at the EDs stage and any of the clinical scales, including symptom subtypes and depression severity (all p > .203).
      Figure 1.
      Figure 1Cognitive flexibility and role of striatal connectivity in obsessive-compulsive disorder (OCD) patients. (A) Schematic illustration of the intra-/extradimensional set shift (IED) task testing cognitive flexibility in which stimuli comprising two dimensions (i.e., line and color-filled shape) are presented. (B) Mean number of errors by learning stage on the IED task. OCD patients showed impaired cognitive flexibility, evidenced by selectively more errors at the extradimensional shift (EDs) stage compared with matched healthy subjects (CTL). (C) Set of brain areas, including left ventrolateral prefrontal cortex (PFC; Brodmann area [BA] 10/11/47), for which significant reduced connectivity with the left dorsal caudate (DCd) was found to be significantly related to worse cognitive flexibility in OCD patients (cluster size after applying a per voxel threshold of p < .01; cluster-corrected significance at least p < .01). (D) The correlation plot shows that reduced functional connectivity between the left dorsal caudate and the left ventrolateral PFC (BA 10/11/47) predicted higher number of errors at the EDs stage in OCD patients. Regression line and 95% confidence interval are shown. (E) Bar plot showing mean functional connectivity between the left dorsal caudate and the left ventrolateral PFC (BA 10/11/47) in OCD patients (mean split according to EDs performance). Error bars represent SEM. **p ≤ .01, ***p ≤ .001. CD, superimposed compound discrimination; C_D, separated compound discrimination; CDr, superimposed compound discrimination reversal; CTL, control subjects; EDr, extradimensional shift reversal; IDs, intradimensional shift; IDr, intradimensional shift reversal; SD, simple discrimination; SDr, simple discrimination reversal.
      To test whether functional connectivity in specific frontostriatal circuits predicted patients’ cognitive flexibility, we used number of errors at the EDs stage as a covariate of interest in the connectivity maps generated from DCd and PUT. In OCD patients, a higher number of errors at the EDs stage was associated with reduced functional connectivity between the left DCd and a set of brain regions, including caudate and putamen bilaterally, right medial frontal gyrus (Brodmann area [BA] 9), and a cluster peaking at BA 10 and extending to the left lateral PFC (BA 10/11/47) (Figure 1C). Specifically, for the left BA 10/11/47, lower connectivity with the left DCd was strongly associated with impaired cognitive flexibility in the OCD sample (Figure 1D, Supplement) and when including control subjects as well (Supplement). Covariation for age and verbal IQ did not alter the results (p < .001). Mean split of OCD patients according to the number of EDs stage errors showed that patients severely impaired in cognitive flexibility (high number of EDs stage errors) had significantly reduced functional connectivity between left DCd and left BA 10/11/47 compared with OCD patients with better performance (t42 = 5.338, p < .001) (Figure 1E); the two subgroups were, however, indistinguishable in terms of severity on any of the clinical scales. Similar results were found when testing functional connectivity from the right DCd (Supplemental Table S2) but not when testing functional connectivity from left and right PUT and NAc (Supplemental Table S2, Supplemental Figure S5), revealing the specific relevance of caudate connectivity to cognitive flexibility in OCD patients.

      Goal-Directed Planning and Frontostriatal Connectivity

      OCD patients showed impaired goal-directed planning abilities at the hard levels of difficulty as tested with the OTS (Figure 2A) and indexed by the increased number of attempts to obtain the correct response (t83 = −2.427, p = .017; Figure 2B) compared with control subjects. There was no group difference for the easy problems. In the medicated patients, increased self-reported severity of OCD symptoms and anxiety positively correlated with poor goal-directed performance at the hardest level of difficulty (Obsessive-Compulsive Inventory-Revised: r = .6, p < 0.001; State-Trait Anxiety Inventory-State: r = .531, p < .005, both surviving Bonferroni correction) (Figure 3).
      Figure 2.
      Figure 2Goal-directed planning and role of striatal connectivity in obsessive-compulsive disorder (OCD) patients. (A) Schematic illustration of the One-Touch Stockings of Cambridge (OTS) task testing executive planning. Examples from easy (2 moves) and difficult (5 moves) problems are shown. (B) Mean number of attempts to reach correct solution at different difficulty levels on the OTS task. OCD patients show impairment in goal-directed planning compared with matched control subjects (CTL) by requiring more attempts to reach the correct solution at the hard levels of difficulty; there was no group difference for the easy problems. (C) Set of brain areas, including right dorsolateral prefrontal cortex (PFC; Brodmann area [BA] 46), for which significant connectivity with the right putamen (PUT) was found to be significantly related to goal-directed executive planning in OCD patients (cluster size after applying a per voxel threshold of p < .01; cluster-corrected significance at least p < .01). Blue and yellow coloration for weakened and increased connectivity predicting worse or better performance, respectively. (D) The correlation plot shows that reduced functional connectivity between the right PUT and the right dorsolateral PFC (BA 46) predicted higher number of attempts at the most difficult level of goal-directed planning (6 moves) in OCD patients. Regression line and 95% confidence interval are shown. (E) Bar plot showing mean functional connectivity between the right PUT and the right dorsolateral PFC (BA 46) in OCD patients (mean split according to OTS performance at the most difficult level). Error bars represent SEM. *p ≤ .05, ***p ≤ .001.
      Figure 3.
      Figure 3Relation between obsessive-compulsive disorder (OCD) severity and goal-directed performance. Impoverished goal-directed performance at the hardest level of goal-directed planning positively correlated with (A) self-reported severity of OCD symptoms (OCI-R: r24 = .6, p = .001, surviving Bonferroni correction) and (B) anxiety (STAI-State: r24 = .531, p = .005, surviving Bonferroni correction) in OCD-medicated patients. OCI-R, Obsessive-Compulsive Inventory-Revised (
      • Montgomery S.A.
      • Asberg M.
      A new depression scale designed to be sensitive to change.
      ); STAI, State-Trait Anxiety Inventory (
      • Spielberger C.D.
      Manual for the State-Trait Anxiety Inventory STAI (Form Y).
      ).
      Functional connectivity within a specific frontostriatal circuit predicted patients’ goal-directed planning ability. A higher number of attempts at the most difficult level of the task (6 moves) was associated with reduced functional connectivity between the right PUT and the right dorsolateral PFC (BA 46). In addition, a positive relation was found for the angular gyrus bilaterally (BA 39), whereby better performance was associated with increased functional connectivity from the right PUT (Figure 2C, Supplemental Table S3). Specifically, for the right BA 46, lower connectivity with the right PUT was strongly associated with poor goal-directed planning in the OCD sample (Figure 2D, Supplement) and when including control subjects as well (Supplement). Covariation for age and verbal IQ did not alter the results (p = .007). A mean split according to mean number of attempts revealed significantly reduced functional connectivity between the right PUT and right BA 46 in severely impaired patients (t41 = 3.599, p < .001) (Figure 2E). Those patients also exhibited increased anxiety (t41 = −2.126, p = .04) compared with patients performing better on the task. These results were specific to the PUT and not to DCd or NAc (Supplemental Table S3), revealing the specific relevance of putaminal connectivity to goal-directed executive planning in OCD patients.

      Clinical Scores and Ventral Striatal Connectivity

      In OCD patients, NAc connectivity was related to clinical scores of anxiety and depression (Supplemental Table S4, Supplement).

      Network Modularity

      Data-driven network analysis disclosed that, in the OCD sample, nodes corresponding to caudate and putamen as well as the cerebellum were clustered together in a single module (Supplemental Table S5), suggestive of a cohesive functional unit. In contrast, in control subjects, the same striatal and cerebellar regions were distributed among large cortico-subcortical modules (Figure 4A, B). For all the participants, we computed number of connections for each of these nodes; in OCD patients these nodes were more strongly connected to one another (intraconnections) compared with control subjects (t85 = 2.029, p = .046), with no difference for the total number of connections (t85 = 0.338, p = .736) or for number of connections directed toward other nodes (interconnections) (t85 = 0.049, p = .9614) (Figure 4C). Although modularity algorithms are nondeterministic, clustering of these nodes in the same module in OCD and their splitting among different modules in the network of healthy volunteers was robustly observed over multiple runs and several implementations of the analysis (Supplement, Supplemental Figure S6). There were no correlations between network modularity measures and cognitive or clinical measures that survived multiple comparisons (Supplement).
      Figure 4.
      Figure 4Network modular organization in obsessive-compulsive disorder (OCD) and healthy subjects (CTL). (A) Differences in modular organization in OCD and healthy volunteers represented by an alluvial diagram. Each module is separated by white gaps. The flows indicate the nodes for which community structure changes as a function of diagnosis. Red-highlighted module in OCD patients correspond to nodes of the basal ganglia and cerebellum. These nodes are clustered in one module on their own in OCD patients; the same nodes are integrated within separate large cortico-subcortical modules in CTL. (B) Nodes for OCD and healthy subjects in anatomical space, color-coded according to module membership. The size of the nodes depends on their number of connections. Respectively, for CTL and OCD patients, lower panels highlight the nodes identified by the modularity algorithm as being part of an independent functional unit in OCD patients (and corresponding to basal ganglia and cerebellum). Nodes are colored according to module membership, highlighting that nodes corresponding to different parts of the basal ganglia (caudate, putamen) and cerebellum are clustered in one single module in OCD patients. In contrast, in healthy subjects the same brain areas are integrated within separate modules. (C) Box plot summarizing mean number of connections for nodes identified as being part of an independent functional unit in OCD patients and corresponding to the basal ganglia and the cerebellum. For those nodes, there were no group differences in total number of connections or in the number of interconnections. However, they were significantly more intraconnected in OCD patients than in healthy CTL. *p ≤ .05.

      Discussion

      A double dissociation of cognitive deficits contributing to candidate endophenotypes in OCD of goal-directed behavior and cognitive flexibility was identified for separate frontostriatal circuits. A selective deficit in cognitive flexibility (attentional set-shifting) in OCD was associated with reduced functional connectivity between the ventrolateral PFC and the DCd, but not the PUT. In contrast, impaired goal-directed planning was associated with reduced functional connectivity between the dorsolateral PFC and the PUT, but not the DCd. The latter deficit predicted severity of self-reported OCD symptoms and anxiety state and is consistent with recent hypotheses proposing fundamental goal-directed learning impairments in OCD (
      • Gillan C.M.
      • Robbins T.W.
      Goal-directed learning and obsessive-compulsive disorder.
      ). Data-driven network analysis provided evidence in OCD patients of denser connectivity within a group of nodes, including the caudate and putamen, as well as the cerebellum.
      Considerable evidence has shown the ventrolateral PFC to be necessary for attentional set-shifting. Excitotoxic lesions of lateral PFC in marmosets produced selective impairments in attentional set-shifting, whereas lesions to the orbitofrontal cortex impaired another form of cognitive flexibility, reversal learning (
      • Dias R.
      • Robbins T.W.
      • Roberts A.C.
      Dissociation in prefrontal cortex of affective and attentional shifts.
      ). In a human fMRI paradigm, attentional set-shifting selectively recruited the ventrolateral PFC (
      • Hampshire A.
      • Owen A.M.
      Fractionating attentional control using event-related fMRI.
      ). Involvement of the striatum in set-shifting however has hitherto been less clear. Healthy volunteers exhibit caudate activation for reversal in rule classification, but not for extradimensional set-shifting (
      • Rogers R.
      • Andrews T.
      • Grasby P.
      • Brooks D.
      • Robbins T.
      Contrasting cortical and subcortical activations produced by attentional-set shifting and reversal learning in humans.
      ). However, set-shifting–related cortical activity was mirrored by activity in the caudate nucleus and dorsal thalamus (
      • Monchi O.
      • Petrides M.
      • Petre V.
      • Worsley K.
      • Dagher A.
      Wisconsin Card Sorting Revisited: Distinct neural circuits participating in different stages of the task identified by event-related functional magnetic resonance imaging.
      ). Recently, resting-state functional connectivity between the ventral striatum and a priori-selected dorsolateral PFC was reported to be associated with attentional set-shifting in a large sample of healthy volunteers (
      • Morris L.S.
      • Kundu P.
      • Dowell N.
      • Mechelmans D.J.
      • Favre P.
      • Irvine M.A.
      • et al.
      Fronto-striatal organization: Defining functional and microstructural substrates of behavioural flexibility.
      ). By contrast, the present study used unbiased whole-brain analysis to demonstrate that functional connectivity between the caudate and ventrolateral PFC was associated with EDs performance in OCD patients (whether or not combined with the control group for this analysis). It is however possible that additional circuitry, including the ventral striatum, may be associated with EDs performance because we did find some associations in the OCD group with this circuit, although these analyses were post hoc and constrained by multiple comparison. It is nevertheless clear that separate circuits relate to cognitive flexibility and goal-directed planning. A limitation of the present study was the insufficient variability in EDs (and also planning) performances in the control subjects to demonstrate the same relation in that group alone.
      Our results provide new evidence that, in OCD patients, the inability to switch attention from a previously relevant dimension to form a new attentional set is intimately related to weakened underlying resting-state connectivity between the DCd and a network of brain regions including the ventrolateral PFC. Consistent with previous data, OCD patients formed attentional sets, as indexed by intact performance on discrimination and intradimensional stages, but showed selective impairment in shifting attention between stimulus dimensions (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Blackwell A.D.
      • Robbins T.W.
      • Sahakian B.J.
      Motor inhibition and cognitive flexibility in obsessive-compulsive disorder and trichotillomania.
      ,
      • Watkins L.H.
      • Sahakian B.J.
      • Robertson M.M.
      • Veale D.M.
      • Rogers R.D.
      • Pickard K.M.
      • et al.
      Executive function in Tourette’s syndrome and obsessive–compulsive disorder.
      ). We augmented previous investigations by showing this effect to be independent of medication, in agreement with evidence in animals and humans that serotoninergic mechanisms are not implicated in EDs performance (
      • Clarke H.F.
      • Walker S.C.
      • Crofts H.S.
      • Dalley J.W.
      • Robbins T.W.
      • Roberts A.C.
      Prefrontal serotonin depletion affects reversal learning but not attentional set shifting.
      ,
      • Rogers R.D.
      • Blackshaw A.J.
      • Middleton H.C.
      • Matthews K.
      • Hawtin K.
      • Crowley C.
      • et al.
      Tryptophan depletion impairs stimulus-reward learning while methylphenidate disrupts attentional control in healthy young adults: Implications for the monoaminergic basis of impulsive behaviour.
      ). The set-shifting deficit was also independent of clinical severity, in agreement with evidence that it may be an endophenotype (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Menzies L.A.
      • Blackwell A.D.
      • Bullmore E.T.
      • Robbins T.W.
      • Sahakian B.J.
      Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive-compulsive disorder.
      ).
      A separate circuit was relevant for the ability to attain goals via single-contingency, instrumental response sequences. Reduced functional connectivity between the putamen and the dorsolateral PFC was associated with inferior performance in OCD patients alone, as well as in the combined sample including control subjects. In task-related imaging studies, the dorsolateral PFC has been classically implicated in executive planning together with parietal and cingulate cortices (
      • Baker S.C.
      • Rogers R.D.
      • Owen A.M.
      • Frith C.D.
      • Dolan R.J.
      • Frackowiak R.S.
      • Robbins T.W.
      Neural systems engaged by planning: A PET study of the Tower of London task.
      ). Anatomical data also support our findings; rich reciprocal connections exist between the dorsolateral PFC and the posterior parietal cortex, which project onto overlapping areas of the putamen (
      • Selemon L.D.
      • Goldman-Rakic P.S.
      Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey.
      ). In OCD patients, a direct positive association was found such that increased functional connectivity between the PUT and the parietal cortex was predictive of better performance. Goal-directed impairment at the hardest planning levels replicated previous data (
      • Chamberlain S.R.
      • Fineberg N.A.
      • Menzies L.A.
      • Blackwell A.D.
      • Bullmore E.T.
      • Robbins T.W.
      • Sahakian B.J.
      Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive-compulsive disorder.
      ), with no differences between medicated and unmedicated patients. Goal-directed planning failures were associated with self-reported symptom severity and anxiety only in medicated OCD patients, probably because their underlying symptoms were more severe and mitigated by medication. Further studies of first-degree unaffected relatives will clarify whether goal-directed impairment represents a state or trait marker for OCD (
      • Vaghi M.M.
      • Hampshire A.
      • Fineberg N.A.
      • Brühl A.B.
      • Sahakian B.J.
      • Chamberlain S.R.
      • Robbins T.W.
      Hypoactivation of a fronto-striatal loop in OCD associated with goal-directed planning.
      ).
      Our whole-brain network analysis revealed that, in OCD patients but not in control subjects, nodes belonging to the basal ganglia and cerebellum were more strongly intraconnected, thus corresponding to a unit or “conglomerate.” Results were consistent with previous investigations revealing a higher degree of local connectivity for the putamen in OCD patients (
      • Beucke J.C.
      • Sepulcre J.
      • Talukdar T.
      • Linnman C.
      • Zschenderlein K.
      • Endrass T.
      • et al.
      Abnormally high degree connectivity of the orbitofrontal cortex in obsessive-compulsive disorder.
      ) and with frequent observations of elevated metabolism of those regions in PET studies during resting state (
      • Baxter Jr, L.R.
      • Phelps M.E.
      • Mazziotta J.C.
      • Guze B.H.
      • Schwartz J.M.
      • Selin C.E.
      Local cerebral glucose metabolic rates in obsessive-compulsive disorder. A comparison with rates in unipolar depression and in normal controls.
      ). In other words, the stronger intraconnectivity of basal ganglia plus cerebellar nodes drives their separation into a distinct autonomous unit as a function of diagnosis, analogous to that of high impulsive subjects in a comparable study (
      • Davis F.C.
      • Knodt A.R.
      • Sporns O.
      • Lahey B.B.
      • Zald D.H.
      • Brigidi B.D.
      • Hariri A.R.
      Impulsivity and the modular organization of resting-state neural networks.
      ). Together with the functional connectivity analysis, this evidence parsimoniously suggests that the PFC exerts less top-down control of these subcortical regions. In general, our complementary imaging analyses suggest that increased connectivity within the striatum might coexist with its decreased functional connectivity to frontoparietal cortical regions, being associated with less flexible and impoverished goal-directed forms of behavior. Although the cerebellum has not hitherto been a major focus of interest in OCD, previous (
      • Menzies L.
      • Williams G.B.
      • Chamberlain S.R.
      • Ooi C.
      • Fineberg N.A.
      • Suckling J.
      • et al.
      White matter abnormalities in patients with obsessive-compulsive disorder and their first-degree relatives.
      ,
      • Anticevic A.
      • Hu S.
      • Zhang S.
      • Savic A.
      • Billingslea E.
      • Wasylink S.
      • et al.
      Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder.
      ,
      • Menzies L.
      • Chamberlain S.R.
      • Laird A.R.
      • Thelen S.M.
      • Sahakian B.J.
      • Bullmore E.T.
      Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: The orbitofronto-striatal model revisited.
      ) and present findings suggest that it merits further study. In line with anatomical evidence of cerebellar frontostriatal circuitry overlapping (
      • Bostan A.C.
      • Dum R.P.
      • Strick P.L.
      The basal ganglia communicate with the cerebellum.
      ,
      • Hoshi E.
      • Tremblay L.
      • Féger J.
      • Carras P.L.
      • Strick P.L.
      The cerebellum communicates with the basal ganglia.
      ), we found clustering of striatum and cerebellum in our graph analysis. Much clinical and experimental evidence implicate the cerebellum in executive functions, attentional set-shifting, and motor sequencing (
      • Doyon J.
      • Gaudreau D.
      • Laforce Jr, R.
      • Castonguay M.
      • Bédard P.J.
      • Bédard F.
      • Bouchard J.P.
      Role of the striatum, cerebellum, and frontal lobes in the learning of a visuomotor sequence.
      ), consistent with our evidence that striatal-cerebellar connectivity is implicated in attentional set-shifting. We saw no involvement of the cerebellum in relation to planning, perhaps because planning relates to goal-directed rather than habitual/skilled, or what may become just perfect behavior in OCD. Imbalances in corticostriatal connectivity with increased and decreased functional connectivity within the ventral and dorsal striatal networks, respectively, are consistent with previous investigations (
      • Harrison B.J.
      • Soriano-Mas C.
      • Pujol J.
      • Ortiz H.
      • López-Solà M.
      • Hernández-Ribas R.
      • et al.
      Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
      ). Existing studies of unmedicated patients, however, only provide mixed findings (
      • Posner J.
      • Marsh R.
      • Maia T.V.
      • Peterson B.S.
      • Gruber A.
      • Simpson H.B.
      Reduced functional connectivity within the limbic cortico-striato-thalamo-cortical loop in unmedicated adults with obsessive-compulsive disorder.
      ,
      • Sakai Y.
      • Narumoto J.
      • Nishida S.
      • Nakamae T.
      • Yamada K.
      • Nishimura T.
      • Fukui K.
      Corticostriatal functional connectivity in non-medicated patients with obsessive-compulsive disorder.
      ). We directly compared medicated with unmedicated patients, showing that hyperconnectivity of the NAc and PUT to non-PFC cortical areas was more evident in medicated patients. This hyperconnectivity does not necessarily result from medication per se, because the medicated patients might have had more severe underlying symptoms; the hyperconnectivity may therefore reflect OCD symptoms.
      PFC regions found here to be functionally connected to basal ganglia and relevant for specific functions, namely ventrolateral PFC for cognitive flexibility and dorsolateral PFC for goal-directed planning, overlapped with those observed in corresponding task-related fMRI studies (
      • Hampshire A.
      • Owen A.M.
      Fractionating attentional control using event-related fMRI.
      ,
      • Baker S.C.
      • Rogers R.D.
      • Owen A.M.
      • Frith C.D.
      • Dolan R.J.
      • Frackowiak R.S.
      • Robbins T.W.
      Neural systems engaged by planning: A PET study of the Tower of London task.
      ). This adds to the burgeoning literature establishing a close relation between resting-state and task-related functional connectivity in a healthy population (
      • Cole M.W.
      • Bassett D.S.
      • Power J.D.
      • Braver T.S.
      • Petersen S.E.
      Intrinsic and task-evoked network architectures of the human brain.
      ), and with findings of resting-state functional connectivity related to response inhibition in an OCD population (
      • Kang D.-H.
      • Jang J.H.
      • Han J.Y.
      • Kim J.-H.
      • Jung W.H.
      • Choi J.-S.
      • et al.
      Neural correlates of altered response inhibition and dysfunctional connectivity at rest in obsessive-compulsive disorder.
      ). Despite specific neural changes to be expected during the execution of the task, connectivity at rest appears to represent a functional predisposition that enables task execution. Indeed, our results suggest that the observed behavioral deficits depend on this trait-like predisposition, associated with objective behavioral measures heralding symptom manifestation. Thus, resting-state connectivity might serve as a biomarker predicting individual variability in behavioral performance, as shown here. Resting state is a promising practical tool, considering its relative ease and simplicity of data collection and its potential for providing reliable brain mapping from relatively short durations of scanning. We suggest that coupling of well-standardized behavioral indices and brain measures derived from an easily applicable resting-state sequence is a valuable approach for identifying neurobehavioral markers for severe psychiatric disorders, in line with the recent Research Domain Criteria initiative aimed at identifying the biological bases of mental disorders (
      • Insel T.
      • Cuthbert B.
      • Garvey M.
      • Heinssen R.
      • Pine D.S.
      • Quinn K.
      • et al.
      Research Domain Criteria (RDoC): Toward a new classification framework for research on mental disorders.
      ).
      In conclusion, the present data represent the first identification of discrete striatal-cortical circuits associated with key cognitive endophenotypes for OCD. The data extend the neurobiological model of OCD centered on dysfunction of frontostriatal brain circuits (
      • Graybiel A.M.
      • Rauch S.L.
      Toward a neurobiology of obsessive-compulsive disorder.
      ). Our study shows that these alterations have a direct link to cognitive processes severely impaired in OCD and of relevance for its symptoms and diagnosis.

      Acknowledgments and Disclosures

      This work was supported by a Wellcome Trust Senior Investigator Award Grant No. 104631/Z/14/Z (to TWR). Work was completed at the Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom, supported by a joint award from the Medical Research Council and Wellcome Trust Grant No. G00001354. MMV is supported by a Pinsent-Darwin Studentship in Mental Pathology and a Cambridge Home and European Union Scholarship Scheme studentship. PEV is supported by the Medical Research Council Grant No. MR/K020706/1. AMA-S is supported by the Wellcome Trust Grant above. VV is a Wellcome Trust Fellow.
      We thank all the patients and volunteers who took part in this study and members of the Wolfson Brain Imaging Centre for technical assistance in data collection.
      Presented in part at British Neuroscience Association, April 12, 2015, Edinburgh, Scotland; Bernstein Conference, September 20, 2015, Heidelberg, Germany; and the Society for Neuroscience, October 21, 2015, Chicago, Illinois.
      Dr. Robbins consults for Cambridge Cognition and in the past year for Lundbeck and Otsuka and receives royalties from Cambridge Cognition (for CANTAB) and editorial honoraria from Elsevier and Springer Verlag. Dr. Bullmore is employed half-time by the University of Cambridge and half-time by GlaxoSmithKline (GSK) and holds stock in GSK. Dr. Fineberg has received research support from Lundbeck, GSK, European College of Neuropsychopharmacology (ECNP), Servier, Cephalon, AstraZeneca, Medical Research Council (UK), National Institute for Health Research, Wellcome Foundation; has received honoraria for lectures at scientific meetings from Otsuka, Lundbeck, Servier, AstraZeneca, Jazz Pharmaceuticals, Bristol Myers Squibb, UK College of Mental Health Pharmacists, British Association for Psychopharmacology (BAP); has received financial support to attend scientific meetings from Janssen, Lundbeck, Servier, Novartis, Bristol Myers Squibb, Cephalon, International College of Obsessive-Compulsive Spectrum Disorders, International Society for Behavioural Addiction, ECNP, BAP, World Health Organization, Royal College of Psychiatrists; and has received financial royalties for publications from Oxford University Press and Taylor and Francis. Other than the above disclosures, the authors report no biomedical financial interests or potential conflicts of interest.

      Appendix A. Supplementary material

      References

        • Abramovitch A.
        • Abramowitz J.S.
        • Mittelman A.
        The neuropsychology of adult obsessive-compulsive disorder: A meta-analysis.
        Clin Psychol Rev. 2013; 33: 1163-1171
        • Purcell R.
        • Maruff P.
        • Kyrios M.
        • Pantelis C.
        Cognitive deficits in obsessive-compulsive disorder on tests of frontal-striatal function.
        Biol Psychiatry. 1998; 43: 348-357
        • Purcell R.
        • Maruff P.
        • Kyrios M.
        • Pantelis C.
        Neuropsychological deficits in obsessive-compulsive disorder: A comparison with unipolar depression, panic disorder, and normal controls.
        Arch Gen Psychiatry. 1998; 55: 415-423
        • Alexander G.E.
        • DeLong M.R.
        • Strick P.L.
        Parallel organization of functionally segregated circuits linking basal ganglia and cortex.
        Annu Rev Neurosci. 1986; 9: 357-381
        • Middleton F.A.
        • Strick P.L.
        Basal ganglia output and cognition: Evidence from anatomical, behavioral, and clinical studies.
        Brain Cogn. 2000; 42: 183-200
        • Baxter Jr, L.R.
        • Phelps M.E.
        • Mazziotta J.C.
        • Guze B.H.
        • Schwartz J.M.
        • Selin C.E.
        Local cerebral glucose metabolic rates in obsessive-compulsive disorder. A comparison with rates in unipolar depression and in normal controls.
        Arch Gen Psychiatry. 1987; 44: 211-218
        • Saxena S.
        • Brody A.L.
        • Schwartz J.M.
        • Baxter L.R.
        Neuroimaging and frontal-subcortical circuitry in obsessive-compulsive disorder.
        Br J Psychiatry. 1998; : 26-37
        • Saxena S.
        • Rauch S.L.
        Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder.
        Psychiatr Clin North Am. 2000; 23: 563-586
        • Gillan C.M.
        • Papmeyer M.
        • Morein-Zamir S.
        • Sahakian B.J.
        • Fineberg N.A.
        • Robbins T.W.
        • de Wit S.
        Disruption in the balance between goal-directed behavior and habit learning in obsessive-compulsive disorder.
        Am J Psychiatry. 2011; 168: 718-726
        • Gillan C.M.
        • Apergis-Schoute A.M.
        • Morein-Zamir S.
        • Urcelay G.P.
        • Sule A.
        • Fineberg N.A.
        • et al.
        Functional neuroimaging of avoidance habits in obsessive-compulsive disorder.
        Am J Psychiatry. 2015; 172: 284-293
        • Graybiel A.M.
        • Rauch S.L.
        Toward a neurobiology of obsessive-compulsive disorder.
        Neuron. 2000; 28: 343-347
        • Gillan C.M.
        • Robbins T.W.
        Goal-directed learning and obsessive-compulsive disorder.
        Philos Trans R Soc Lond B Biol Sci. 2014; 369: 20130475
        • Harrison B.J.
        • Soriano-Mas C.
        • Pujol J.
        • Ortiz H.
        • López-Solà M.
        • Hernández-Ribas R.
        • et al.
        Altered corticostriatal functional connectivity in obsessive-compulsive disorder.
        Arch Gen Psychiatry. 2009; 66: 1189-1200
        • Chamberlain S.R.
        • Fineberg N.A.
        • Menzies L.A.
        • Blackwell A.D.
        • Bullmore E.T.
        • Robbins T.W.
        • Sahakian B.J.
        Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive-compulsive disorder.
        Am J Psychiatry. 2007; 164: 335-338
        • Delorme R.
        • Goussé V.
        • Roy I.
        • Trandafir A.
        • Mathieu F.
        • Mouren-Siméoni M.-C.
        • et al.
        Shared executive dysfunctions in unaffected relatives of patients with autism and obsessive-compulsive disorder.
        Eur Psychiatry. 2007; 22: 32-38
        • Chamberlain S.R.
        • Blackwell A.D.
        • Fineberg N.A.
        • Robbins T.W.
        • Sahakian B.J.
        The neuropsychology of obsessive compulsive disorder: The importance of failures in cognitive and behavioural inhibition as candidate endophenotypic markers.
        Neurosci Biobehav Rev. 2005; 29: 399-419
        • Shallice T.
        Specific impairments of planning.
        Philos Trans R Soc Lond B Biol Sci. 1982; 298: 199-209
        • Chamberlain S.R.
        • Fineberg N.A.
        • Blackwell A.D.
        • Clark L.
        • Robbins T.W.
        • Sahakian B.J.
        A neuropsychological comparison of obsessive-compulsive disorder and trichotillomania.
        Neuropsychologia. 2007; 45: 654-662
        • van den Heuvel O.A.
        • Veltman D.J.
        • Groenewegen H.J.
        • Cath D.C.
        • van Balkom A.J.
        • van Hartskamp J.
        • et al.
        Frontal-striatal dysfunction during planning in obsessive-compulsive disorder.
        Arch Gen Psychiatry. 2005; 62: 301-309
        • Gillan C.M.
        • Morein-Zamir S.
        • Urcelay G.P.
        • Sule A.
        • Voon V.
        • Apergis-Schoute A.M.
        • et al.
        Enhanced avoidance habits in obsessive-compulsive disorder.
        Biol Psychiatry. 2014; 75: 631-638
        • Haber S.N.
        The primate basal ganglia: Parallel and integrative networks.
        J Chem Neuroanat. 2003; 26: 317-330
        • Draganski B.
        • Kherif F.
        • Kloppel S.
        • Cook P.A.
        • Alexander D.C.
        • Parker G.J.M.
        • et al.
        Evidence for segregated and integrative connectivity patterns in the human basal ganglia.
        J Neurosci. 2008; 28: 7143-7152
        • Iversen S.D.
        • Mishkin M.
        Perseverative interference in monkeys following selective lesions of the inferior prefrontal convexity.
        Exp Brain Res. 1970; 11: 376-386
        • Dias R.
        • Robbins T.W.
        • Roberts A.C.
        Dissociation in prefrontal cortex of affective and attentional shifts.
        Nature. 1996; 380: 69-72
        • Hampshire A.
        • Owen A.M.
        Fractionating attentional control using event-related fMRI.
        Cereb Cortex. 2006; 16: 1679-1689
        • Baker S.C.
        • Rogers R.D.
        • Owen A.M.
        • Frith C.D.
        • Dolan R.J.
        • Frackowiak R.S.
        • Robbins T.W.
        Neural systems engaged by planning: A PET study of the Tower of London task.
        Neuropsychologia. 1996; 34: 515-526
        • Haber S.N.
        • Knutson B.
        The reward circuit: Linking primate anatomy and human imaging.
        Neuropsychopharmacology. 2009; 35: 4-26
        • Biswal B.
        • Yetkin F.Z.
        • Haughton V.M.
        • Hyde J.S.
        Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.
        Magn Reson Med. 1995; 34: 537-541
        • Bullmore E.
        • Sporns O.
        Complex brain networks: graph theoretical analysis of structural and functional systems.
        Nat Rev Neurosci. 2009; 10: 186-198
        • Hoddes E.
        • Zarcone V.
        • Smythe H.
        • Phillips R.
        • Dement W.C.
        Quantification of sleepiness: A new approach.
        Psychophysiology. 1973; 10: 431-436
        • Cox R.W.
        AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages.
        Comput Biomed Res Int J. 1996; 29: 162-173
        • Kundu P.
        • Brenowitz N.D.
        • Voon V.
        • Worbe Y.
        • Vértes P.E.
        • Inati S.J.
        • et al.
        Integrated strategy for improving functional connectivity mapping using multiecho fMRI.
        Proc Natl Acad Sci U S A. 2013; 110: 16187-16192
        • Lynall M.-E.
        • Bassett D.S.
        • Kerwin R.
        • McKenna P.J.
        • Kitzbichler M.
        • Muller U.
        • Bullmore E.
        Functional connectivity and brain networks in schizophrenia.
        J Neurosci. 2010; 30: 9477-9487
        • Newman M.E.J.
        Communities, modules and large-scale structure in networks.
        Nat Phys. 2012; 8: 25-31
        • Blondel V.D.
        • Guillaume J.-L.
        • Lambiotte R.
        • Lefebvre E.
        Fast unfolding of communities in large networks.
        J Stat Mech Theory Exp. 2008; 2008: P10008
        • Rubinov M.
        • Sporns O.
        Complex network measures of brain connectivity: Uses and interpretations.
        NeuroImage. 2010; 52: 1059-1069
        • Rogers R.
        • Andrews T.
        • Grasby P.
        • Brooks D.
        • Robbins T.
        Contrasting cortical and subcortical activations produced by attentional-set shifting and reversal learning in humans.
        J Cogn Neurosci. 2000; 12: 142-162
        • Monchi O.
        • Petrides M.
        • Petre V.
        • Worsley K.
        • Dagher A.
        Wisconsin Card Sorting Revisited: Distinct neural circuits participating in different stages of the task identified by event-related functional magnetic resonance imaging.
        J Neurosci. 2001; 21: 7733-7741
        • Morris L.S.
        • Kundu P.
        • Dowell N.
        • Mechelmans D.J.
        • Favre P.
        • Irvine M.A.
        • et al.
        Fronto-striatal organization: Defining functional and microstructural substrates of behavioural flexibility.
        Cortex. 2015; 74: 118-133
        • Chamberlain S.R.
        • Fineberg N.A.
        • Blackwell A.D.
        • Robbins T.W.
        • Sahakian B.J.
        Motor inhibition and cognitive flexibility in obsessive-compulsive disorder and trichotillomania.
        Am J Psychiatry. 2006; 163: 1282-1284
        • Watkins L.H.
        • Sahakian B.J.
        • Robertson M.M.
        • Veale D.M.
        • Rogers R.D.
        • Pickard K.M.
        • et al.
        Executive function in Tourette’s syndrome and obsessive–compulsive disorder.
        Psychol Med. 2005; 35: 571-582
        • Clarke H.F.
        • Walker S.C.
        • Crofts H.S.
        • Dalley J.W.
        • Robbins T.W.
        • Roberts A.C.
        Prefrontal serotonin depletion affects reversal learning but not attentional set shifting.
        J Neurosci. 2005; 25: 532-538
        • Rogers R.D.
        • Blackshaw A.J.
        • Middleton H.C.
        • Matthews K.
        • Hawtin K.
        • Crowley C.
        • et al.
        Tryptophan depletion impairs stimulus-reward learning while methylphenidate disrupts attentional control in healthy young adults: Implications for the monoaminergic basis of impulsive behaviour.
        Psychopharmacology (Berl). 1999; 146: 482-491
        • Selemon L.D.
        • Goldman-Rakic P.S.
        Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey.
        J Neurosci. 5. 1985: 776-794
        • Vaghi M.M.
        • Hampshire A.
        • Fineberg N.A.
        • Brühl A.B.
        • Sahakian B.J.
        • Chamberlain S.R.
        • Robbins T.W.
        Hypoactivation of a fronto-striatal loop in OCD associated with goal-directed planning.
        Society for Neuroscience, Washington, 19 November 2014. 2014;
        • Beucke J.C.
        • Sepulcre J.
        • Talukdar T.
        • Linnman C.
        • Zschenderlein K.
        • Endrass T.
        • et al.
        Abnormally high degree connectivity of the orbitofrontal cortex in obsessive-compulsive disorder.
        JAMA Psychiatry. 2013; 70: 619-629
        • Davis F.C.
        • Knodt A.R.
        • Sporns O.
        • Lahey B.B.
        • Zald D.H.
        • Brigidi B.D.
        • Hariri A.R.
        Impulsivity and the modular organization of resting-state neural networks.
        Cereb Cortex. 2013; 23: 1444-1452
        • Menzies L.
        • Williams G.B.
        • Chamberlain S.R.
        • Ooi C.
        • Fineberg N.A.
        • Suckling J.
        • et al.
        White matter abnormalities in patients with obsessive-compulsive disorder and their first-degree relatives.
        Am J Psychiatry. 165. 2008: 1308-1315
        • Anticevic A.
        • Hu S.
        • Zhang S.
        • Savic A.
        • Billingslea E.
        • Wasylink S.
        • et al.
        Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder.
        Biol Psychiatry. 2014; 75: 595-605
        • Menzies L.
        • Chamberlain S.R.
        • Laird A.R.
        • Thelen S.M.
        • Sahakian B.J.
        • Bullmore E.T.
        Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: The orbitofronto-striatal model revisited.
        Neurosci Biobehav Rev. 2008; 32: 525-549
        • Bostan A.C.
        • Dum R.P.
        • Strick P.L.
        The basal ganglia communicate with the cerebellum.
        Proc Natl Acad Sci. 2010; 107: 8452-8456
        • Hoshi E.
        • Tremblay L.
        • Féger J.
        • Carras P.L.
        • Strick P.L.
        The cerebellum communicates with the basal ganglia.
        Nat Neurosci. 2005; 8: 1491-1493
        • Doyon J.
        • Gaudreau D.
        • Laforce Jr, R.
        • Castonguay M.
        • Bédard P.J.
        • Bédard F.
        • Bouchard J.P.
        Role of the striatum, cerebellum, and frontal lobes in the learning of a visuomotor sequence.
        Brain Cogn. 1997; 34: 218-245
        • Posner J.
        • Marsh R.
        • Maia T.V.
        • Peterson B.S.
        • Gruber A.
        • Simpson H.B.
        Reduced functional connectivity within the limbic cortico-striato-thalamo-cortical loop in unmedicated adults with obsessive-compulsive disorder.
        Hum Brain Mapp. 2013; 35: 2852-2860
        • Sakai Y.
        • Narumoto J.
        • Nishida S.
        • Nakamae T.
        • Yamada K.
        • Nishimura T.
        • Fukui K.
        Corticostriatal functional connectivity in non-medicated patients with obsessive-compulsive disorder.
        Eur Psychiatry. 2011; 26: 463-469
        • Cole M.W.
        • Bassett D.S.
        • Power J.D.
        • Braver T.S.
        • Petersen S.E.
        Intrinsic and task-evoked network architectures of the human brain.
        Neuron. 2014; 83: 238-251
        • Kang D.-H.
        • Jang J.H.
        • Han J.Y.
        • Kim J.-H.
        • Jung W.H.
        • Choi J.-S.
        • et al.
        Neural correlates of altered response inhibition and dysfunctional connectivity at rest in obsessive-compulsive disorder.
        Prog Neuropsychopharmacol Biol Psychiatry. 2013; 40: 340-346
        • Insel T.
        • Cuthbert B.
        • Garvey M.
        • Heinssen R.
        • Pine D.S.
        • Quinn K.
        • et al.
        Research Domain Criteria (RDoC): Toward a new classification framework for research on mental disorders.
        Am J Psychiatry. 2010; 167: 748-751
        • Montgomery S.A.
        • Asberg M.
        A new depression scale designed to be sensitive to change.
        Br J Psychiatry. 1979; 134: 382-389
        • Foa E.B.
        • Huppert J.D.
        • Leiberg S.
        • Langner R.
        • Kichic R.
        • Hajcak G.
        • Salkovskis P.M.
        The Obsessive-Compulsive Inventory: Development and validation of a short version.
        Psychol Assess. 2002; 14: 485-496
        • Spielberger C.D.
        Manual for the State-Trait Anxiety Inventory STAI (Form Y).
        Mind Garden, Palo Alto, CA1983
        • Goodman W.K.
        • Price L.H.
        • Rasmussen S.A.
        • Mazure C.
        • Fleischmann R.L.
        • Hill C.L.
        • et al.
        The Yale-Brown Obsessive Compulsive Scale. I. Development, use, and reliability.
        Arch Gen Psychiatry. 1989; 46: 1006-1011