Obsessive-compulsive disorder (OCD) is characterized by an excessive focus on upsetting or disturbing thoughts, feelings, and images that are internally-generated. Internally-focused thought processes are subserved by the “default mode network" (DMN), which has been found to be hyperactive in OCD during cognitive tasks. In healthy individuals, disengagement from internally-focused thought processes may rely on interactions between DMN and a fronto-parietal network (FPN) associated with external attention and task execution. Altered connectivity between FPN and DMN may contribute to the dysfunctional behavior and brain activity found in OCD.
The current study examined interactions between FPN and DMN during rest in 30 patients with OCD (17 unmedicated) and 32 control subjects (17 unmedicated). Timecourses from seven fronto-parietal seeds were correlated across the whole brain and compared between groups.
OCD patients exhibited altered connectivity between FPN seeds (primarily anterior insula) and several regions of DMN including posterior cingulate cortex, medial frontal cortex, posterior inferior parietal lobule, and parahippocampus. These differences were driven largely by a reduction of negative correlations among patients compared to controls. Patients also showed greater positive connectivity between FPN and regions outside DMN, including thalamus, lateral frontal cortex, and somatosensory/motor regions.
OCD is associated with abnormal intrinsic functional connectivity between large-scale brain networks. Alteration of interactions between FPN and DMN at rest may contribute to aspects of the OCD phenotype, such as patients' inability to disengage from internally-generated scenarios and thoughts when performing everyday tasks requiring external attention.
Citation: Stern ER, Fitzgerald KD, Welsh RC, Abelson JL, Taylor SF (2012) Resting-State Functional Connectivity between Fronto-Parietal and Default Mode Networks in Obsessive-Compulsive Disorder. PLoS ONE 7(5): e36356. https://doi.org/10.1371/journal.pone.0036356
Editor: Carles Soriano-Mas, Bellvitge Biomedical Research Institute-IDIBELL, Spain
Received: January 11, 2012; Accepted: April 3, 2012; Published: May 3, 2012
Copyright: © 2012 Stern et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Support for this research comes from National Institute of Mental Health (NIMH) R01 MH071821 awarded to SFT, NIMH F32 MH082573 and Brain and Behavior Foundation (formerly NARSAD) Young Investigator Award to ERS, and NIMH K23 MH082176 awarded to KDF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study.
Competing interests: The authors have declared that no competing interests exist.
Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts, feelings, or images (obsessions) and repetitive behaviors (compulsions) aimed at reducing anxiety associated with obsessions. Neuroimaging studies examining brain activation in OCD at rest, during symptom provocation, and in response to cognitive tasks have made critical advances in elucidating the neurobiological substrates of the disorder, pointing to dysfunction in several cortical and subcortical regions. While dysfunction in orbital, medial frontal, and striatal areas composing fronto-striatal circuits  has long been found to be contribute to the pathogenesis of OCD –, emerging evidence suggests there is broader cortical dysfunction in the disorder, including abnormality of dorsolateral prefrontal cortex, anterior insula, lateral and medial temporal lobe regions, and parietal cortex –. Such widespread alterations may be due to the diversity of tasks used to investigate OCD, which include response inhibition, habit formation, set switching/reversal, and performance monitoring, to name just a few. Contributing to the complexity of interpretation is the fact that the direction of group effects in the majority of these brain regions appears to differ depending on the task being used. The investigation of large-scale functional networks during rest in OCD has the advantage of identifying neural mechanisms that are not specific to the task employed, which will complement and extend findings from task-based studies.
A growing body of literature in neuroscience has begun to emphasize the importance of interactions between brain regions, due to the realization that a typical brain area is likely to support multiple cognitive functions and that unique functionality is most likely to emerge through inter-regional connectivity , . Resting-state functional connectivity analysis using functional magnetic resonance imaging (rs-fcMRI) examines correlations between low-frequency bold fluctuations (LFBFs) at rest, allowing for the identification of regions or systems showing agonistic interactions (identified by positive correlations) as well as antagonistic or competitive interactions (identified by negative correlations). Numerous rs-fcMRI studies have identified “intrinsic" large-scale brain networks that exhibit interactions at rest similar to those identified during task –. Despite being task-independent, resting-state network connectivity is modulated by the preceding task ,  and is related to task-evoked neural activity and behavior , , but with considerably more stability over time than task-related BOLD changes , . Evidence suggests that changes in rs-fcMRI reflect altered network functioning in several disease states , indicating that this marker of brain function can provide important information about neurocircuit abnormalities in psychiatric disorders.
Recent investigations of rs-fcMRI in OCD focusing on the striatum – have supported fronto-striatal theories by identifying altered functional coupling between striatum and multiple regions of frontal cortex. Zhang et al  found altered resting-state connectivity within a “top-down control network" including posterior temporal cortex, lateral frontal and cingulate cortex, and precuneus, regions that partially overlap with the fairly well-delineated fronto-parietal network (FPN) composed of anterior insula, medial frontal cortex, and lateral frontal and parietal regions . Although there are dissociable nodes within FPN , , as a whole this network is referred to as “task-positive" because it increases in activity when attention is directed to external stimuli in cognitive tasks , –. By contrast, the “default mode" network (DMN), composed of midline frontal and parietal areas, posterior inferior parietal lobule, and medial and lateral temporal lobe regions, often decreases in activity when attention is directed externally , , , but increases in response to a variety of introspectively-oriented cognitive processes including autobiographical memory, imagination, and thinking about the self , . While the relationship between FPN and DMN during task depends upon the paradigm employed and the goals of the subject , , reductions in DMN activity ,  and greater negative correlations between FPN and DMN  are associated with improved performance (and less “mind wandering") on tasks requiring externally-directed attention. FPN and DMN are also negatively correlated at rest, at least in healthy controls , , , suggesting that the unconstrained brain may be intrinsically organized to support competitive relationships between networks involved in external attention and internally-focused thought processes.
The investigation of competitive interactions between FPN and DMN at rest is particularly relevant for the study of OCD. Not only are nodes of these networks found to be abnormal during task-based studies of OCD, but the phenomenology of the disorder is consistent with the idea of a disrupted relationship between ongoing internal thought and external information, in that patients often excessively focus on internally-generated fears that are inconsistent with evidence present in the external environment . To test the possibility that OCD patients show alterations of the intrinsic functional relationship between fronto-parietal and default mode networks, the current study measured whole-brain rs-fcMRI in OCD patients and control subjects using seeds located in fronto-parietal network. We predicted that negative correlations between FPN and DMN would be evident in controls, replicating prior studies using rs-fcMRI, but reduced or absent in patients with OCD.
Materials and Methods
This research was approved by the Institutional Review Board of the University of Michigan Medical School, following the principles set forth by the Declaration of Helsinki. All subjects provided written informed consent. Resting-state functional connectivity data were acquired for a total of 69 subjects. Seven subjects were excluded due to technical problems (failure during data acquisition: 1, corrupted data: 4, poor coregistration: 2), leaving a total of 62 participants including 30 OCD patients and 32 control subjects for further analysis. Seventeen OCD patients were unmedicated for a minimum of 6 months prior to study participation (uOCD) and 13 were medicated (mOCD), primarily with serotonin-reuptake inhibitors (SRIs, see Table S1). All patients met DSM-IV criteria for current OCD, excluding primary hoarding subtypes. Due to the high comorbidity between OCD and depression , we did not want to bias our sample by excluding patients with histories of depression or sub-threshold depressive symptoms. Thus, prior history of major depression was allowed if it was in partial or full remission (n = 14), as was depressive disorder not otherwise specified (NOS) and dysthymia (n = 6). Importantly, no subjects were in a major depressive episode. Other axis I disorders were also excluded unless they were clearly secondary to the diagnosis of OCD, which were relatively few in number (specific phobia: n = 5, panic disorder NOS: n = 1; panic disorder: n = 2; eating disorder NOS: n = 2; anorexia nervosa, n = 3, trichotillomania: n = 1; chronic motor tic disorder, n = 1; bipolar disorder NOS: n = 1).
The control group included 17 unmedicated healthy control subjects (uHC) without psychiatric diagnoses and 15 medicated patient controls (mPC). Subjects with any history of OCD were excluded from both control groups. Subjects in the mPC group were patients with remitted major depression who were on SRI medication (Table S1) and had few comorbidities (panic disorder: n = 1; attention deficit hyperactivity disorder: n = 1; anxiety disorder NOS: n = 2; impulse control disorder NOS: n = 1). As many OCD patients were taking SRIs and had histories of depression, the current design allowed us to better localize group differences to the presence of OCD by comparing the OCD group with a control group also containing medicated participants with histories of depression.
Subjects were evaluated by a trained clinician using the Structured Clinical Interview for DSM-IV (SCID; . Symptoms of anxiety and depression were quantified using Hamilton Ratings Scales for Anxiety (HAM-A;  and Depression (HAM-D; . Obsessive-compulsive (OC) symptom severity (current and lifetime) was quantified using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS, . Table 1 shows demographic and clinical information for the groups. Both OCD groups showed significantly more generalized anxiety and depression than either control group, as would be expected, but mOCD and uOCD patients were not different from each other. While OCD patients were not significantly different in age from the control group, they had attained fewer years of education at the time of testing.
Functional MRI Acquisition and Preprocessing
MRI scanning occurred on a GE 3T Signa scanner (LX [8.3] release). A T1-weighted image was acquired in the same prescription as functional images to facilitate co-registration. Functional images were acquired with a T2*-weighted, reverse spiral acquisition sequence (GRE, Repetition time [TR] = 2000 ms, Echo time [TE] = 30, Flip angle = 90, Field of view = 20, 40 slices, 3 mm thickness, skip = 0, matrix dia. 71 - equivalent to 64×64) sensitive to signal in ventral frontal regions . Data were acquired for 6 minutes while subjects fixated on a crosshair, resulting in 180 volumes (plus 4 initial discarded volumes). Following acquisition of functional data, a high resolution T1 SPGR scan was obtained for anatomic normalization.
Physiologic signals (heart rate and respiration) were removed from the data using RETROICOR . Data were then realigned and slice-time corrected using slicetimer (interpolated with an 8-point sinc kernel multiplied by a Hanning window) (FSL, Analysis Group, FMRIB, Oxford). Functional volumes were coregistered and resliced to 3 mm3, normalized to the template MNI152 brain (Montreal Neurological Institute), and smoothed with a 5 mm isotropic Gaussian smoothing kernel using the Statistical Parametric Mapping (SPM) 2 package (Wellcome Institute of Cognitive Neurology, London).
Functional Connectivity Analysis
Analysis of functional connectivity of LFBFs was carried out with the “conn" toolbox (www.nitrc.org/projects/conn, see ref. . This tool identifies principle components associated with segmented white matter (WM) and cerebrospinal fluid (CSF) images for each individual subject using the “CompCor" method . Critically, this method corrects for positivity biases arising from “noise correlations" related to non-neural sources (such as respiration or cardiac activity) without regressing out the global signal, which has been shown to lead to spurious negative correlations . Timecourses from the top three principle components associated with both WM and CSF were regressed out of whole-brain gray matter activity.
In addition to removing noise correlations present in WM and CSF, the addition of 12 motion regressors (6 realignment parameters and first derivatives) controlled for correlations due to movement. Data were filtered between .01 and .10 Hz. We examined connectivity patterns separately for seven different seed regions-of-interest (ROIs) located in FPN. Given abundant evidence of positive correlations among FPN nodes, the timecourses for these separate seeds are not likely to be completely orthogonal; thus we cannot make strong claims about distinct patterns of connectivity between the different seeds. Nevertheless, given recent evidence identifying dissociable cingulo-opercular and dorsolateral prefrontal and parietal systems within FPN , , , we feel that this approach is more informative than creating a global timecourse compiled from signals averaged across the entire network.
Coordinates (in MNI format) for these seeds were taken from prior studies, which have identified a “core" task-set network that includes bilateral dorsal anterior insula (Brodmann's area [BA] 13, x = −35, y = 14, z = 6; x = 36, y = 16, z = 5) and posterior medial frontal cortex (BA 6/32, x = −1, y = 8, z = 51) , and a central executive network consisting of bilateral dorsolateral prefrontal cortex (BA 8/9, x = −45, y = 16, z = −45; x = 45, y = 16, z = −45) and bilateral anterior regions of inferior parietal lobule (BA 40, x = −38, y = −53, z = 45; x = 54, y = −50, z = 50) . Timecourses representing the average within 6 mm-radius spheres located around these coordinates were correlated with all gray matter voxels over the 180 volumes using a Hanning window. Correlation coefficient images between FPN seeds and whole-brain gray matter were z-transformed, with one and two-sample t-tests examining within- and between-group connectivity. Significant clusters were defined using a voxelwise threshold of p<.005 and cluster-level corrected for multiple comparisons using familywise error (FWE) correction at a threshold of p<.05 as implemented in SPM8.
Although not our main focus of analysis, we also sought to investigate within-DMN patterns of connectivity, due to two prior reports of reduced connectivity in OCD , . We used seeds located in two regions thought to be core “hubs" of DMN, anterior medial prefrontal cortex (BA 10, x = −6, y = 52, z = −2) and posterior cingulate cortex (BA 31, x = −8, y = −56, z = 26) (coordinates taken from ref. 39). In order to restrict our analysis to connectivity within DMN, within- and between-group t-tests searched for effects in a mask of DMN, which consisted of regions showing positive connectivity with the posterior cingulate (PCC) seed in the uHC group at p<.05 (cluster-level corrected using FWE).
Relationships with symptom severity were examined by extracting connectivity values from regions showing group differences and correlating these with Y-BOCS scores (total score, obsessions subscale, and compulsions subscale) in the OCD group.
Several post-hoc analyses were performed to examine the impact of other variables on results (see Supporting information File S1). Multiple regressions examined the influence of diagnosis (OCD vs. controls) on extracted connectivity values when controlling for medication, generalized anxiety/depression, and education (as the latter two variables differed between the groups, see Table 1). These regressions were repeated for a restricted sample where patients and control groups were matched for head movement .
Connectivity with fronto-parietal network
There were several regions that showed significant group differences in connectivity with seeds in fronto-parietal network. For all of these regions, there was greater overall connectivity with FPN seeds in OCD patients as compared to controls, due in some cases to patterns of reduced negative correlations in patients and in other cases to patterns of increased positive correlations in patients (see Table 2 for direction of effects in each region).
For the left anterior insula seed, OCD patients exhibited greater connectivity with several areas of default mode network including PCC/precuneus extending into medial occipital lobe, right parahippocampus, left posterior regions of inferior parietal lobule (pIPL) and adjacent regions of posterior temporal cortex, and dorsomedial prefrontal cortex (DMPFC) (Figure 1). Patients also had greater connectivity between the left anterior insula seed and left pre-postcentral gyrus. Similarly, for the right anterior insula seed, patients exhibited greater connectivity with DMN regions including PCC/precuneus, parahippocampus, left pIPL, and DMPFC extending into anterior MFC (Figure 2). In addition, patients showed greater connectivity between the right anterior insula seed and right posterior insula as well as bilateral thalamus. There were no significant differences in connectivity with the posterior medial frontal seed.
a) OCD patients exhibited greater connectivity than controls between the left anterior insula seed and default mode network regions including parahippocampus, posterior cingulate cortex (PCC)/precuneus, posterior inferior parietal lobule (pIPL), and dorsomedial prefrontal cortex (DMPFC). Patients also showed greater connectivity with pre-postcentral gyrus. Numbers above images represent z-coordinate (MNI format) of axial slices. Images displayed at p<.005, corrected across whole-brain gray matter at p<.05, b) Connectivity maps with left anterior insula for both groups, displayed at p<.005 with 10 contiguous voxels. Black circles represent location of seed. Color bars represent t-scores.
a) OCD patients exhibited greater connectivity than controls between the right anterior insula seed and default mode network regions including posterior cingulate cortex (PCC)/precuneus, dorsomedial prefrontal cortex (DMPFC)/anterior medial frontal cortex (aMFC), posterior inferior parietal lobule (pIPL), and parahippocampus. Patients also showed greater connectivity with right posterior insula and bilateral thalamus. Images displayed at p<.005, corrected across whole-brain gray matter at p<.05, b) Connectivity maps with right anterior insula seed for both groups, displayed at p<.005 with 10 contiguous voxels. Black circles represent location of seed, c) Extracted connectivity values (y-axes show z-transformed correlation coefficients) in DMPFC/aMFC, rostral PCC/precuneus, right posterior insula, and right thalamus for unmedicated OCD patients (uOCD), medicated OCD patients (mOCD), unmedicated healthy controls (uHC), and medicated patient controls (mPC); uOCD>uHC and mOCD>mPC for all regions shown at p<.05 in multiple regressions controlling for generalized anxiety/depression and education (see File S1 and Table S2). Error bars represent standard error of the mean. Color bars represent t-scores. Coordinates are in MNI format.
Hyper-connectivity in OCD was also found with dorsolateral and anterior inferior parietal seeds of FPN, although differences with DMN were less robust than with anterior insula seeds. For the left dorsolateral prefrontal (DLPFC) seed, patients had greater connectivity with right anterior insula/frontal operculum – also a part of FPN – as well as ventral occipital lobe/cerebellum. For the right DLPFC seed, patients not only had greater connectivity with the posterior cingulate cortex in the DMN, but also showed increased coupling with right lateral frontal regions of FPN.
Fewer group differences emerged for connectivity with anterior inferior parietal seeds, with the left hemisphere exhibiting more connectivity with left pre-postcentral gyrus and the right hemisphere exhibiting more connectivity with PCC/precuneus for OCD patients as compared to controls.
Connectivity within default mode network
There were no regions within DMN that exhibited group differences in connectivity with anterior medial frontal (aMFC) or PCC seeds at the current threshold, which was corrected for multiple comparisons. However, as two prior studies have reported altered resting-state connectivity within DMN in OCD , , we examined connectivity between these seeds and regions of DMN at an uncorrected threshold (p<.005, k = 10). In contrast to results from FPN seeds, where all group differences were associated with less negative and/or more positive connectivity in patients, OCD patients showed less positive connectivity between the aMFC seed and an adjacent region of aMFC (BA 10, k = 12, x = 9, y = 57, z = 9) and with DMPFC (BA 9, k = 21, x = 0, y = 57, z = 27) compared to controls. Patients also showed reduced connectivity between the PCC seed and bilateral aMFC/DMPFC (BA 10, k = 14, x = 9, y = 69, z = 18; k = 10, x = −24, y = 63, z = 12). There were no areas where within-DMN connectivity was greater in OCD patients than controls, even at this lowered threshold.
Relationships with OC symptoms severity
Connectivity between the right anterior insula seed and right thalamus was significantly related to Y-BOCS scores, with greater severity of symptoms associated with reduced connectivity (total score: r = −0.50, p = 0.005, obsessions subscale: r = −.46, p = .011; compulsions subscale: r = −.45. p = .013). No other connectivity values were related to OC symptom severity.
Impact of other variables on effects of diagnosis
As is shown in the Supporting information (File S1), group differences persisted after controlling for the influence of medication status, generalized anxiety/depression, education, and head motion on connectivity. Comparisons between unmedicated OCD patients and healthy controls can be seen in Table S2.
Primary results from the current study revealed reduced negative connectivity between the fronto-parietal network and default mode network in OCD. Patients also showed more positive connectivity between fronto-parietal seeds and several areas outside DMN, including somato-motor areas (pre-postcentral gyrus and posterior insula) and other FPN regions (anterior insula/frontal operculum and lateral frontal cortex). However, not all group differences reflected increased connectivity in OCD, as patients showed less positive connectivity than control subjects within DMN itself, although these effects only emerged at lower levels of significance. Negative connectivity among controls was evident despite the fact that global normalization was not used in the analysis , and group differences were not due to head motion . Importantly, the factorial design gave us greater ability to control for confounding factors frequently co-occuring in OCD, such as the presence of medication and depression, and post-hoc multiple regression analyses indicated that these variables did explain group differences. Overall, these data suggest that intrinsic functional relationships between large-scale brain systems are altered in OCD, specifically pointing to a disruption of the competitive interactions typically found at rest between fronto-parietal and default mode networks.
Research on DMN has garnered much interest since the initial observation of reduced blood flow within several anatomically-widespread brain regions during cognitive tasks versus passive viewing . Subsequent studies have associated this network with a core set of regions including PCC/precuneus, ventral and dorsal medial frontal cortex, posterior inferior parietal cortex, and medial and lateral temporal cortex . Activation in these regions not only decreases during externally-directed attention, but also increases when attention is directed inward, such as when subjects think about their own personal qualities and take the perspective of others (theory of mind/mentalizing), remember personal episodes from their past, imagine future events, and construct scenes , , , . Experiments investigating the relationship between fronto-parietal network regions involved in executive/control processes and DMN indicate that efficient processing of external stimuli requires the suspension of introspectively-oriented cognition , , and that this inverse pattern of activity appears even when the brain is at rest , , .
Recent evidence has identified dissociable sub-networks within FPN, with dorsal regions of anterior insula and medial frontal cortex forming a “core" network involved in implementing and maintaining attention to external task demands and detecting salient events , and lateral frontal and parietal regions performing more “executive" functions such as working memory, planning, and cognitive control , . Right insula in particular may function as a “switch" between modes of processing, triggering the activation of executive regions and suppression of default mode regions when salient external events are detected , . While anterior insula may respond somewhat generally to external task demands, it does appear to be particularly sensitive to stimuli signaling potential risk ; as such, this area may be important for switching attention away from an internal focus toward the external environment after detecting potentially harmful situations. Though speculative, the current findings of attenuated negative connectivity between anterior insula and DMN suggest a potential neural basis for the difficulty OCD patients may have in efforts to disengage from internal mental processes in order to respond more appropriately to salient external information related to potential risk (such as that informing them that dreaded events have not or will not occur). These findings extend work identifying greater connectivity between anterior insula and VMPFC during task  to include alterations in connectivity with several regions of DMN at rest, and raise the possibility that abnormal intrinsic connectivity contributes to the DMN hyperactivity found in OCD during cognitive tasks , , , .
Connectivity differences with FPN occurred across a number of DMN regions, including PCC, pIPL, DMPFC/aMFC, and parahippocampus. Despite the consistent activation of these brain regions across several different tasks involving internally-directed cognition , there appears to be some measure of dissociation between different nodes within DMN, particularly between anterior medial frontal and posterior parietal/temporal regions , , . Although the current study was not aimed at distinguishing among different DMN subsystems, the findings of aberrant connectivity between FPN and several DMN regions suggests that altered resting-state connectivity in OCD is not specific to a particular DMN subsystem.
OCD patients also showed greater positive interactions between FPN seeds and several areas outside of DMN, including pre-postcentral gyrus and posterior insula, which are part of a somatosensory/interoceptive and motor network . Increased connectivity between fronto-parietal regions and somato-motor network could contribute to obsessive-compulsive symptoms involving sensitivity to physical sensations, particularly those related to disgust or internal urges, although such interpretations need to be tested directly. The finding of hyper-connectivity between anterior insula and thalamus is also of interest given the importance of the fronto-striatal-thalamic circuitry in OCD –. Whereas positive connectivity between these regions was greater in the patient group overall, it was inversely related to OC symptom severity, suggesting a compensatory mechanism because patients with lesser severity of symptoms showed the greatest difference from controls. However, this finding should be interpreted with caution as we did not correct for the number of tests that were performed to examine correlations with symptom severity.
Although the general absence of correlations with Y-BOCS scores might seem surprising, this may indicate that group differences reflect stable biomarkers of OCD not sensitive to symptom severity differences, similar to the mechanism suggested for the error-related negativity . The current analysis focused on identifying connectivity patterns where OCD patients differed from both healthy controls and remitted depressed subjects (see Figure 2c and Table S2). However, the current data cannot address whether similar disturbances would be found in patients with active major depression, or whether remitted depressed patients would show differences in connectivity compared to healthy controls in brain regions other than those explored in the current analysis.
Unlike group differences found with FPN seeds, OCD patients showed less positive connectivity than controls subjects within DMN, a finding that was not due to differential motion. Although this effect was found only at a lowered threshold, it is consistent with two prior reports , , and is intriguing given the finding that negative affect reduces connectivity within DMN . These results suggest that OCD may be characterized by a complex pattern of hyper- and hypo-connectivity among large-scale networks.
To our knowledge, this is the first report of altered intrinsic connectivity between distributed regions of fronto-parietal and default mode networks in OCD. However, there are several limitations of the current study, many of which could be addressed by future research. Given that results were not corrected for multiple seed comparisons, replications using a larger sample size are necessary. In addition, OCD and controls groups were not matched on generalized depression/anxiety and education levels. Although post-hoc inclusion of these factors in multiple regressions indicated that these effects were not driving the reported group differences in connectivity, future studies would benefit from investigating the effects of these variables on brain connectivity. Of particular interest for the study of psychopathology, hyperactivity in DMN has been identified in other psychiatric disorders (for a review, see ), and the current investigation cannot address whether the findings are specific to OCD. It is possible that changes in DMN across a range of dysfunction could be due to abnormal relationships between FPN and DMN, which would be consistent with the emerging recognition that overlapping physiological mechanisms are found among comorbid disorders . Many anxiety disorders , including OCD , , , , are characterized by increased activation of anterior insula; as such, the hyper-connectivity between insula and DMN revealed by the current study may be more related to an anxiety phenotype than other psychopathologies, although direct comparisons between disorders will be needed to test this hypothesis. In addition, although we did not have enough subjects to examine different symptom dimensions in OCD, it is likely that some DMN-based cognitive processes (e.g., scene construction and imagination) are more directly related to certain OCD subtypes (e.g., those involving intrusive imagery) than others (e.g., those with symmetry/ordering concerns). Future work should be aimed at obtaining a large and diverse cohort of patients to determine whether these alterations in rs-fcMRI differ based on symptom dimension. Finally, although interpretations regarding the functional significance of resting-state interactions rely on a large body of literature in cognitive neuroscience, it will be necessary to directly test the relationship between rs-fcMRI and behavior as well as task-evoked activity in order to elucidate the cognitive processes associated with these abnormal interactions. In particular, assessment of subjects' thoughts or feelings during rest will improve the ability to link resting-state connectivity to behavior. Despite these issues, the current results highlight the importance of inter-regional interactions between large-scale networks in OCD, revealing alterations of connectivity that may provide promising leads for the development of novel treatments using behavioral training or neuromodulation to target specific patterns of dysfunctional connectivity. Future work will be aimed at replicating and extending the current findings in order to determine the generality of the effect and its behavioral significance.
Medications taken by OCD patients (mOCD) and medicated control subjects (mPC). SSRIs = selective-serotonin reuptake inhibitors; SNRIs = serotonin-norepinephrine reuptake inhibitors; TCAs = tricycle antidepressants. All subjects except 1 mOCD patient were taking a serotonin reuptake inhibitor (SSRI or SNRI). Two mOCD and 3 mPC subjects were taking more than one medication (not including benzodiazepines, which were taken as needed and omitted on the day of testing).
Significance of diagnosis in predicting connectivity separately for unmedicated and medicated participants. Results obtained from multiple regressions also including generalized anxiety/depression and education as predictors. PCC = posterior cingulate cortex; pIPL = posterior inferior parietal lobule; DMPFC = dorsomedial prefrontal cortex; aMFC = anterior medial frontal cortex; aI/fO = anterior insula/frontal operculum.
Conceived and designed the experiments: ERS KDF RCW JLA SFT. Performed the experiments: ERS. Analyzed the data: ERS. Wrote the paper: ERS.
- 1. Alexander GE, Delong MR, Strick PL (1986) Parallel Organization of Functionally Segregated Circuits Linking Basal Ganglia and Cortex. Annu Rev Neuroscience 9: 357–381.GE AlexanderMR DelongPL Strick1986Parallel Organization of Functionally Segregated Circuits Linking Basal Ganglia and Cortex.Annu Rev Neuroscience9357381
- 2. Saxena S, Rauch SL (2000) Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder. Psychiat Clin N Am 23: 563–86.S. SaxenaSL Rauch2000Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder.Psychiat Clin N Am2356386
- 3. Rauch SL, Whalen PJ, Curran T, Shin LM, Coffey BJ, et al. (2001) Probing striato-thalamic function in obsessive-compulsive disorder and Tourette syndrome using neuroimaging methods. Adv Neurol 85: 207–224.SL RauchPJ WhalenT. CurranLM ShinBJ Coffey2001Probing striato-thalamic function in obsessive-compulsive disorder and Tourette syndrome using neuroimaging methods.Adv Neurol85207224
- 4. Menzies L, Chamberlain SR, Laird AR, Thelen SM, Sahakian BJ, et al. (2008) Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: the orbitofronto-striatal model revisited. Neurosci Biobehav Rev 32: 525–549.L. MenziesSR ChamberlainAR LairdSM ThelenBJ Sahakian2008Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: the orbitofronto-striatal model revisited.Neurosci Biobehav Rev32525549
- 5. Ursu S, Carter CS (2009) An initial investigation of the orbitofrontal cortex hyperactivity in obsessive-compulsive disorder: Exaggerated representations of anticipated aversive events? Neuropsychologia 47: 2145–2148.S. UrsuCS Carter2009An initial investigation of the orbitofrontal cortex hyperactivity in obsessive-compulsive disorder: Exaggerated representations of anticipated aversive events?Neuropsychologia4721452148
- 6. Ursu S, Stenger VA, Shear MK, Jones MR, Carter CS (2003) Overactive action monitoring in obsessive-compulsive disorder: Evidence from functional magnetic resonance imaging. Psychol Sci 14: 347–353.S. UrsuVA StengerMK ShearMR JonesCS Carter2003Overactive action monitoring in obsessive-compulsive disorder: Evidence from functional magnetic resonance imaging.Psychol Sci14347353
- 7. Remijnse PL, Nielen MMA, van Balkom AJLM, Cath DC, van Oppen P, et al. (2006) Reduced orbitofrontal-striatal activity on a reversal learning task in obsessive-compulsive disorder. Arch Gen Psych 63: 1225–1236.PL RemijnseMMA NielenAJLM van BalkomDC CathP. van Oppen2006Reduced orbitofrontal-striatal activity on a reversal learning task in obsessive-compulsive disorder.Arch Gen Psych6312251236
- 8. Stern ER, Welsh RC, Gonzalez R, Fitzgerald KD, Abelson JL, et al. (2012) Subjective uncertainty and limbic hyperactivation in obsessive-compulsive disorder. ER SternRC WelshR. GonzalezKD FitzgeraldJL Abelson2012Subjective uncertainty and limbic hyperactivation in obsessive-compulsive disorder.Hum Brain Mapp E-pub ahead of print. Hum Brain Mapp E-pub ahead of print.
- 9. Stern ER, Welsh RC, Fitzgerald KD, Gehring WJ, Lister JJ, et al. (2011) Hyperactive error responses and altered connectivity in ventromedial and frontoinsular cortices in obsessive-compulsive disorder. Biol Psychiat 69: 583–591.ER SternRC WelshKD FitzgeraldWJ GehringJJ Lister2011Hyperactive error responses and altered connectivity in ventromedial and frontoinsular cortices in obsessive-compulsive disorder.Biol Psychiat69583591
- 10. Rotge JY, Guehl D, Dilharreguy B, Cuny E, Tignol J, et al. (2008) Provocation of obsessive-compulsive symptoms: a quantitative voxel-based meta-analysis of functional neuroimaging studies. J Psychiatry Neurosci 33: 405–412.JY RotgeD. GuehlB. DilharreguyE. CunyJ. Tignol2008Provocation of obsessive-compulsive symptoms: a quantitative voxel-based meta-analysis of functional neuroimaging studies.J Psychiatry Neurosci33405412
- 11. Rauch SL, Wedig MM, Wright CI, Martis B, McMullin KG, et al. (2007) Functional magnetic resonance imaging study of regional brain activation during implicit sequence learning in obsessive-compulsive disorder. Biol Psychiat 61: 330–336.SL RauchMM WedigCI WrightB. MartisKG McMullin2007Functional magnetic resonance imaging study of regional brain activation during implicit sequence learning in obsessive-compulsive disorder.Biol Psychiat61330336
- 12. Page LA, Rubia K, Deeley Q, Daly E, Toal F, et al. (2009) A functional magnetic resonance imaging study of inhibitory control in obsessive-compulsive disorder. Psychiat Res-Neuroim 174: 202–209.LA PageK. RubiaQ. DeeleyE. DalyF. Toal2009A functional magnetic resonance imaging study of inhibitory control in obsessive-compulsive disorder.Psychiat Res-Neuroim174202209
- 13. Jung WH, Kang DH, Han JY, Jang JH, Gu BM, et al. (2011) Aberrant ventral striatal responses during incentive processing in unmedicated patients with obsessive-compulsive disorder. Acta Psychiat Scand 123: 376–386.WH JungDH KangJY HanJH JangBM Gu2011Aberrant ventral striatal responses during incentive processing in unmedicated patients with obsessive-compulsive disorder.Acta Psychiat Scand123376386
- 14. Gu BM, Park JY, Kang DH, Lee SJ, Yoo SY, et al. (2008) Neural correlates of cognitive inflexibility during task-switching in obsessive-compulsive disorder. Brain 131: 155–164.BM GuJY ParkDH KangSJ LeeSY Yoo2008Neural correlates of cognitive inflexibility during task-switching in obsessive-compulsive disorder.Brain131155164
- 15. Roth RM, Saykin AJ, Flashman LA, Pixley HS, West JD, et al. (2007) Event-related functional magnetic resonance imaging of response inhibition in obsessive-compulsive disorder. Biol Psychiat 62: 901–909.RM RothAJ SaykinLA FlashmanHS PixleyJD West2007Event-related functional magnetic resonance imaging of response inhibition in obsessive-compulsive disorder.Biol Psychiat62901909
- 16. Anderson ML, Brumbaugh J, Suben A (2010) Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods. In: Chaovalitwongse A, Pardalos PM, Xanthopoulos P, editors. Computational Neuroscience: Springer. pp. 31–42.ML AndersonJ. BrumbaughA. Suben2010Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods.A. ChaovalitwongsePM PardalosP. XanthopoulosComputational Neuroscience: Springer3142
- 17. Anderson ML (2010) Neural reuse: a fundamental organizational principle of the brain. Behav Brain Sci 33: 245–266.ML Anderson2010Neural reuse: a fundamental organizational principle of the brain.Behav Brain Sci33245266
- 18. Greicius MD, Krasnow B, Reiss AL, Menon V (2003) Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A 100: 253–258.MD GreiciusB. KrasnowAL ReissV. Menon2003Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.Proc Natl Acad Sci U S A100253258
- 19. Harrison BJ, Pujol J, Lopez-Sola M, Hernandez-Ribas R, Deus J, et al. (2008) Consistency and functional specialization in the default mode brain network. Proc Natl Acad Sci U S A 105: 9781–9786.BJ HarrisonJ. PujolM. Lopez-SolaR. Hernandez-RibasJ. Deus2008Consistency and functional specialization in the default mode brain network.Proc Natl Acad Sci U S A10597819786
- 20. Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, et al. (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27: 2349–2356.WW SeeleyV. MenonAF SchatzbergJ. KellerGH Glover2007Dissociable intrinsic connectivity networks for salience processing and executive control.J Neurosci2723492356
- 21. Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, et al. (2009) Correspondence of the brain's functional architecture during activation and rest. Proc Natl Acad Sci U S A 106: 13040–13045.SM SmithPT FoxKL MillerDC GlahnPM Fox2009Correspondence of the brain's functional architecture during activation and rest.Proc Natl Acad Sci U S A1061304013045
- 22. Hasson U, Nusbaum HC, Small SL (2009) Task-dependent organization of brain regions active during rest. Proc Natl Acad Sci U S A 106: 10841–10846.U. HassonHC NusbaumSL Small2009Task-dependent organization of brain regions active during rest.Proc Natl Acad Sci U S A1061084110846
- 23. Lewis CM, Baldassarre A, Committeri G, Romani GL, Corbetta M (2009) Learning sculpts the spontaneous activity of the resting human brain. Proc Natl Acad Sci U S A 106: 17558–17563.CM LewisA. BaldassarreG. CommitteriGL RomaniM. Corbetta2009Learning sculpts the spontaneous activity of the resting human brain.Proc Natl Acad Sci U S A1061755817563
- 24. Fox MD, Snyder AZ, Vincent JL, Raichle ME (2007) Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron 56: 171–184.MD FoxAZ SnyderJL VincentME Raichle2007Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior.Neuron56171184
- 25. Mennes M, Kelly C, Zuo XN, Di Martino A, Biswal BB, et al. (2010) Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity. Neuroimage 50: 1690–1701.M. MennesC. KellyXN ZuoA. Di MartinoBB Biswal2010Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity.Neuroimage5016901701
- 26. Grigg O, Grady CL (2010) Task-related effects on the temporal and spatial dynamics of resting-state functional connectivity in the default network. PLoS One 5: e13311.O. GriggCL Grady2010Task-related effects on the temporal and spatial dynamics of resting-state functional connectivity in the default network.PLoS One5e13311
- 27. Shehzad Z, Kelly AM, Reiss PT, Gee DG, Gotimer K, et al. (2009) The resting brain: unconstrained yet reliable. Cereb Cortex 19: 2209–2229.Z. ShehzadAM KellyPT ReissDG GeeK. Gotimer2009The resting brain: unconstrained yet reliable.Cereb Cortex1922092229
- 28. Rosazza C, Minati L (2011) Resting-state brain networks: literature review and clinical applications. Neurol Sci 32: 773–85.C. RosazzaL. Minati2011Resting-state brain networks: literature review and clinical applications.Neurol Sci3277385
- 29. Fitzgerald KD, Welsh RC, Stern ER, Angstadt M, Hanna GL, et al. (2011) Developmental alterations of frontal-striatal-thalamic connectivity in obsessive compulsive disorder. J Am Acad Child Psy 50: 938–948.KD FitzgeraldRC WelshER SternM. AngstadtGL Hanna2011Developmental alterations of frontal-striatal-thalamic connectivity in obsessive compulsive disorder.J Am Acad Child Psy50938948
- 30. Harrison BJ, Soriano-Mas C, Pujol J, Ortiz H, Lopez-Sola M, et al. (2009) Altered corticostriatal functional connectivity in obsessive-compulsive disorder. Arch Gen Psychiat 66: 1189–1200.BJ HarrisonC. Soriano-MasJ. PujolH. OrtizM. Lopez-Sola2009Altered corticostriatal functional connectivity in obsessive-compulsive disorder.Arch Gen Psychiat6611891200
- 31. Sakai Y, Narumoto J, Nishida S, Nakamae T, Yamada K, et al. (2010) Corticostriatal functional connectivity in non-medicated patients with obsessive-compulsive disorder. Eur Psychiat 26: 463–9.Y. SakaiJ. NarumotoS. NishidaT. NakamaeK. Yamada2010Corticostriatal functional connectivity in non-medicated patients with obsessive-compulsive disorder.Eur Psychiat264639
- 32. Zhang TJ, Wang JH, Yang YC, Wu QZ, Li B, et al. (2011) Abnormal small-world architecture of top-down control networks in obsessive-compulsive disorder. J Psychiat Neurosci 36: 23–31.TJ ZhangJH WangYC YangQZ WuB. Li2011Abnormal small-world architecture of top-down control networks in obsessive-compulsive disorder.J Psychiat Neurosci362331
- 33. Vincent JL, Kahn I, Snyder AZ, Raichle ME, Buckner RL (2008) Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J Neurophysiol 100: 3328–3342.JL VincentI. KahnAZ SnyderME RaichleRL Buckner2008Evidence for a frontoparietal control system revealed by intrinsic functional connectivity.J Neurophysiol10033283342
- 34. Dosenbach NU, Fair DA, Miezin FM, Cohen AL, Wenger KK, et al. (2007) Distinct brain networks for adaptive and stable task control in humans. Proc Natl Acad Sci U S A 104: 11073–11078.NU DosenbachDA FairFM MiezinAL CohenKK Wenger2007Distinct brain networks for adaptive and stable task control in humans.Proc Natl Acad Sci U S A1041107311078
- 35. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, et al. (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102: 9673–9678.MD FoxAZ SnyderJL VincentM. CorbettaDC Van Essen2005The human brain is intrinsically organized into dynamic, anticorrelated functional networks.Proc Natl Acad Sci U S A10296739678
- 36. Sridharan D, Levitin DJ, Menon V (2008) A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci U S A 105: 12569–12574.D. SridharanDJ LevitinV. Menon2008A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks.Proc Natl Acad Sci U S A1051256912574
- 37. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, et al. (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98: 676–682.ME RaichleAM MacLeodAZ SnyderWJ PowersDA Gusnard2001A default mode of brain function.Proc Natl Acad Sci U S A98676682
- 38. Shulman GL, Fiez JA, Corbetta M, Buckner RL, Miezin FM, et al. (1997) Common blood flow changes across visual tasks: II. Decreases in cerebral cortex. J Cogn Neurosci 9: 648–663.GL ShulmanJA FiezM. CorbettaRL BucknerFM Miezin1997Common blood flow changes across visual tasks: II. Decreases in cerebral cortex.J Cogn Neurosci9648663
- 39. Andrews-Hanna JR, Reidler JS, Sepulcre J, Poulin R, Buckner RL (2010) Functional-anatomic fractionation of the brain's default network. Neuron 65: 550–562.JR Andrews-HannaJS ReidlerJ. SepulcreR. PoulinRL Buckner2010Functional-anatomic fractionation of the brain's default network.Neuron65550562
- 40. Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 1124: 1–38.RL BucknerJR Andrews-HannaDL Schacter2008The brain's default network: anatomy, function, and relevance to disease.Ann N Y Acad Sci1124138
- 41. Smallwood J, Brown K, Baird B, Schooler JW (2011) Cooperation between the default mode network and the frontal-parietal network in the production of an internal train of thought. Brain Res 1428: 60–70.J. SmallwoodK. BrownB. BairdJW Schooler2011Cooperation between the default mode network and the frontal-parietal network in the production of an internal train of thought.Brain Res14286070
- 42. Spreng RN, Stevens WD, Chamberlain JP, Gilmore AW, Schacter DL (2010) Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition. Neuroimage 53: 303–317.RN SprengWD StevensJP ChamberlainAW GilmoreDL Schacter2010Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition.Neuroimage53303317
- 43. Stawarczyk D, Majerus S, Maquet P, D'Argembeau A (2011) Neural correlates of ongoing conscious experience: both task-unrelatedness and stimulus-independence are related to default network activity. PLoS One 6: e16997.D. StawarczykS. MajerusP. MaquetA. D'Argembeau2011Neural correlates of ongoing conscious experience: both task-unrelatedness and stimulus-independence are related to default network activity.PLoS One6e16997
- 44. Weissman DH, Roberts KC, Visscher KM, Woldorff MG (2006) The neural bases of momentary lapses in attention. Nat Neurosci 9: 971–978.DH WeissmanKC RobertsKM VisscherMG Woldorff2006The neural bases of momentary lapses in attention.Nat Neurosci9971978
- 45. Kelly AM, Uddin LQ, Biswal BB, Castellanos FX, Milham MP (2008) Competition between functional brain networks mediates behavioral variability. Neuroimage 39: 527–537.AM KellyLQ UddinBB BiswalFX CastellanosMP Milham2008Competition between functional brain networks mediates behavioral variability.Neuroimage39527537
- 46. Fransson P (2005) Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis. Hum Brain Mapp 26: 15–29.P. Fransson2005Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis.Hum Brain Mapp261529
- 47. O'Connor K, Aardema F (2003) Fusion or confusion in obsessive compulsive disorder. Psychol Rep 93: 227–232.K. O'ConnorF. Aardema2003Fusion or confusion in obsessive compulsive disorder.Psychol Rep93227232
- 48. Overbeek T, Schruers K, Vermetten E, Griez E (2002) Comorbidity of obsessive-compulsive disorder and depression: prevalence, symptom severity, and treatment effect. J Clin Psychiatry 63: 1106–1112.T. OverbeekK. SchruersE. VermettenE. Griez2002Comorbidity of obsessive-compulsive disorder and depression: prevalence, symptom severity, and treatment effect.J Clin Psychiatry6311061112
- 49. First M, Spitzer R, Gibbon M, Williams J (1996) Structured Clinical Interview for DSM-IV Axis Disorders (SCID), Clinician Version: User's Guide. Washington, D.C.: American Psychiatric Press. M. FirstR. SpitzerM. GibbonJ. Williams1996Structured Clinical Interview for DSM-IV Axis Disorders (SCID), Clinician Version: User's GuideWashington, D.C.American Psychiatric Press
- 50. Hamilton M (1959) The assessment of anxiety states by rating. Br J Med Psychol 32: 50–55.M. Hamilton1959The assessment of anxiety states by rating.Br J Med Psychol325055
- 51. Hamilton M (1960) A rating scale for depression. J Neurol Neurosurg Psychiatry 23: 56–62.M. Hamilton1960A rating scale for depression.J Neurol Neurosurg Psychiatry235662
- 52. Goodman WK, Price LH, Rasmussen SA, Mazure C, Fleischmann RL, et al. (1989) The Yale-Brown Obsessive Compulsive Scale. I. Development, use, and reliability. Arch Gen Psychiat 46: 1006–1011.WK GoodmanLH PriceSA RasmussenC. MazureRL Fleischmann1989The Yale-Brown Obsessive Compulsive Scale. I. Development, use, and reliability.Arch Gen Psychiat4610061011
- 53. Yang Y, Gu H, Zhan W, Xu S, Silbersweig DA, et al. (2002) Simultaneous perfusion and BOLD imaging using reverse spiral scanning at 3T: characterization of functional contrast and susceptibility artifacts. Magn Reson Med 48: 278–289.Y. YangH. GuW. ZhanS. XuDA Silbersweig2002Simultaneous perfusion and BOLD imaging using reverse spiral scanning at 3T: characterization of functional contrast and susceptibility artifacts.Magn Reson Med48278289
- 54. Glover GH, Li TQ, Ress D (2000) Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med 44: 162–167.GH GloverTQ LiD. Ress2000Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR.Magn Reson Med44162167
- 55. Whitfield-Gabrieli S, Moran JM, Nieto-Castanon A, Triantafyllou C, Saxe R, et al. (2011) Associations and dissociations between default and self-reference networks in the human brain. Neuroimage 55: 225–232.S. Whitfield-GabrieliJM MoranA. Nieto-CastanonC. TriantafyllouR. Saxe2011Associations and dissociations between default and self-reference networks in the human brain.Neuroimage55225232
- 56. Behzadi Y, Restom K, Liau J, Liu TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37: 90–101.Y. BehzadiK. RestomJ. LiauTT Liu2007A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.Neuroimage3790101
- 57. Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA (2009) The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage 44: 893–905.K. MurphyRM BirnDA HandwerkerTB JonesPA Bandettini2009The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?Neuroimage44893905
- 58. Fitzgerald KD, Stern ER, Angstadt M, Nicholson-Muth KC, Maynor MR, et al. (2010) Altered function and connectivity of the medial frontal cortex in pediatric obsessive-compulsive disorder. Biol Psychiat 68: 1039–1047.KD FitzgeraldER SternM. AngstadtKC Nicholson-MuthMR Maynor2010Altered function and connectivity of the medial frontal cortex in pediatric obsessive-compulsive disorder.Biol Psychiat6810391047
- 59. Jang JH, Kim JH, Jung WH, Choi JS, Jung MH, et al. (2010) Functional connectivity in fronto-subcortical circuitry during the resting state in obsessive-compulsive disorder. Neurosci Lett 474: 158–162.JH JangJH KimWH JungJS ChoiMH Jung2010Functional connectivity in fronto-subcortical circuitry during the resting state in obsessive-compulsive disorder.Neurosci Lett474158162
- 60. Van Dijk KRA, Sabuncu MR, Buckner RL (2012) The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59: 431–438.KRA Van DijkMR SabuncuRL Buckner2012The influence of head motion on intrinsic functional connectivity MRI.Neuroimage59431438
- 61. Spreng RN, Mar RA, Kim AS (2009) The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis. J Cogn Neurosci 21: 489–510.RN SprengRA MarAS Kim2009The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis.J Cogn Neurosci21489510
- 62. Menon V, Uddin LQ (2010) Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct 214: 655–667.V. MenonLQ Uddin2010Saliency, switching, attention and control: a network model of insula function.Brain Struct Funct214655667
- 63. Preuschoff K, Quartz SR, Bossaerts P (2008) Human insula activation reflects risk prediction errors as well as risk. J Neurosci 28: 2745–2752.K. PreuschoffSR QuartzP. Bossaerts2008Human insula activation reflects risk prediction errors as well as risk.J Neurosci2827452752
- 64. Fitzgerald KD, Welsh RC, Gehring WJ, Abelson JL, Himle JA, et al. (2005) Error-related hyperactivity of the anterior cingulate cortex in obsessive-compulsive disorder. Biol Psychiat 57: 287–294.KD FitzgeraldRC WelshWJ GehringJL AbelsonJA Himle2005Error-related hyperactivity of the anterior cingulate cortex in obsessive-compulsive disorder.Biol Psychiat57287294
- 65. Laird AR, Eickhoff SB, Li K, Robin DA, Glahn DC, et al. (2009) Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling. J Neurosci 29: 14496–14505.AR LairdSB EickhoffK. LiDA RobinDC Glahn2009Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling.J Neurosci291449614505
- 66. Uddin LQ, Kelly AM, Biswal BB, Xavier Castellanos F, Milham MP (2009) Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp 30: 625–637.LQ UddinAM KellyBB BiswalF. Xavier CastellanosMP Milham2009Functional connectivity of default mode network components: correlation, anticorrelation, and causality.Hum Brain Mapp30625637
- 67. Tomasi D, Volkow ND (2011) Association between Functional Connectivity Hubs and Brain Networks. Cereb Cortex 21: 2003–13.D. TomasiND Volkow2011Association between Functional Connectivity Hubs and Brain Networks.Cereb Cortex21200313
- 68. Olvet DM, Hajcak G (2008) The error-related negativity (ERN) and psychopathology: Toward an endophenotype. Clin Psychol Rev 28: 1343–1354.DM OlvetG. Hajcak2008The error-related negativity (ERN) and psychopathology: Toward an endophenotype.Clin Psychol Rev2813431354
- 69. Harrison BJ, Pujol J, Ortiz H, Fornito A, Pantelis C, et al. (2008) Modulation of brain resting-state networks by sad mood induction. PLoS One 3: e1794.BJ HarrisonJ. PujolH. OrtizA. FornitoC. Pantelis2008Modulation of brain resting-state networks by sad mood induction.PLoS One3e1794
- 70. Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, et al. (2009) Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev 33: 279–296.SJ BroydC. DemanueleS. DebenerSK HelpsCJ James2009Default-mode brain dysfunction in mental disorders: a systematic review.Neurosci Biobehav Rev33279296
- 71. Sanislow CA, Pine DS, Quinn KJ, Kozak MJ, Garvey MA, et al. (2010) Developing Constructs for Psychopathology Research: Research Domain Criteria. J Abnorm Psychol 119: 631–639.CA SanislowDS PineKJ QuinnMJ KozakMA Garvey2010Developing Constructs for Psychopathology Research: Research Domain Criteria.J Abnorm Psychol119631639
- 72. Paulus MP, Stein MB (2006) An insular view of anxiety. Biol Psychiat 60: 383–387.MP PaulusMB Stein2006An insular view of anxiety.Biol Psychiat60383387
- 73. Schienle A, Schafer A, Stark R, Walter B, Vaitl D (2005) Neural responses of OCD patients towards disorder-relevant, generally disgust-inducing and fear-inducing pictures. Int J Psychophysiol 57: 69–77.A. SchienleA. SchaferR. StarkB. WalterD. Vaitl2005Neural responses of OCD patients towards disorder-relevant, generally disgust-inducing and fear-inducing pictures.Int J Psychophysiol576977
- 74. Shapira NA, Liu YJ, He AG, Bradley MM, Lessig MC, et al. (2003) Brain activation by disgust-inducing pictures in obsessive-compulsive disorder. Biol Psychiat 54: 751–756.NA ShapiraYJ LiuAG HeMM BradleyMC Lessig2003Brain activation by disgust-inducing pictures in obsessive-compulsive disorder.Biol Psychiat54751756