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Default network connectivity as a vulnerability marker for obsessive compulsive disorder

Published online by Cambridge University Press:  04 September 2013

Z. W. Peng
Affiliation:
Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China Department of Psychology, South China Normal University, Guangzhou, People's Republic of China Guangzhou Psychiatry Hospital, Guangzhou, People's Republic of China
T. Xu
Affiliation:
Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China Key Laboratory of Behavioral Science, Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
Q. H. He
Affiliation:
Guangzhou Psychiatry Hospital, Guangzhou, People's Republic of China
C. Z. Shi
Affiliation:
Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, People's Republic of China
Z. Wei
Affiliation:
Guangzhou Psychiatry Hospital, Guangzhou, People's Republic of China
G. D. Miao
Affiliation:
Guangzhou Psychiatry Hospital, Guangzhou, People's Republic of China
J. Jing
Affiliation:
Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, Guangzhou, People's Republic of China
K. O. Lim
Affiliation:
Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
X. N. Zuo*
Affiliation:
Key Laboratory of Behavioral Science, Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
R. C. K. Chan*
Affiliation:
Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
*
*Address for correspondence: R. C. K. Chan, Ph.D. and Xi-Nian Zuo, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, People's Republic of China. (Email: rckchan@psych.ac.cn) [R.C.K.C.] (Email: zuoxn@psych.ac.cn) [X.N.Z.]
*Address for correspondence: R. C. K. Chan, Ph.D. and Xi-Nian Zuo, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, People's Republic of China. (Email: rckchan@psych.ac.cn) [R.C.K.C.] (Email: zuoxn@psych.ac.cn) [X.N.Z.]
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Abstract

Background

Aberrant functional connectivity within the default network is generally assumed to be involved in the pathophysiology of obsessive compulsive disorder (OCD); however, the genetic risk of default network connectivity in OCD remains largely unknown.

Method

Here, we systematically investigated default network connectivity in 15 OCD patients, 15 paired unaffected siblings and 28 healthy controls. We sought to examine the profiles of default network connectivity in OCD patients and their siblings, exploring the correlation between abnormal default network connectivity and genetic risk for this population.

Results

Compared with healthy controls, OCD patients exhibited reduced strength of default network functional connectivity with the posterior cingulate cortex (PCC), and increased functional connectivity in the right inferior frontal lobe, insula, superior parietal cortex and superior temporal cortex, while their unaffected first-degree siblings only showed reduced local connectivity in the PCC.

Conclusions

These findings suggest that the disruptions of default network functional connectivity might be associated with family history of OCD. The decreased default network connectivity in both OCD patients and their unaffected siblings may serve as a potential marker of OCD.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 

Introduction

Obsessive compulsive disorder (OCD) is a neuropsychiatric disorder associating with persistent intrusive thoughts (obsessions) and/or repetitive behaviors (compulsions), and the lifetime prevalence is estimated to be 2–3% worldwide (Weissman et al. Reference Weissman, Bland, Canino, Greenwald, Hwu, Lee, Newman, Oakley-Browne, Rubio-Stipec and Wickramaratne1994). Empirical findings from family studies have suggested that the first-degree relatives of patients with OCD have almost 3–12 times more risk than the general population of developing OCD (Pauls et al. Reference Pauls, Alsobrook, Goodman, Rasmussen and Leckman1995; Nestadt et al. Reference Nestadt, Samuels, Riddle, Bienvenu, Liang, LaBuda, Walkup, Grados and Hoehn-Saric2000; Hanna et al. Reference Hanna, Veenstra-VanderWeele, Cox, Boehnke, Himle, Curtis, Leventhal and Cook2002). The concordance rate for OCD is also greater among monozygotic twins (80–87%) than dizygotic twins (47–50%) (Inouye, Reference Inouye1965; O'Donnell, Reference O'Donnell1970).

There is increasing evidence to suggest that OCD is associated with altered connectivity within the default mode network (DMN) (Harrison et al. Reference Harrison, Soriano-Mas, Pujol, Ortiz, Lopez-Sola, Hernandez-Ribas, Deus, Alonso, Yucel, Pantelis, Menchon and Cardoner2009; Fitzgerald et al. Reference Fitzgerald, Stern, Angstadt, Nicholson-Muth, Maynor, Welsh, Hanna and Taylor2010; Jang et al. Reference Jang, Kim, Jung, Choi, Jung, Lee, Choi, Kang and Kwon2010; Sakai et al. Reference Sakai, Narumoto, Nishida, Nakamae, Yamada, Nishimura and Fukui2010; Stern et al. Reference Stern, Fitzgerald, Welsh, Abelson and Taylor2012), which is thought to be the backbone of the intrinsic functional architecture (Vincent et al. Reference Vincent, Patel, Fox, Snyder, Baker, Van Essen, Zempel, Snyder, Corbetta and Raichle2007; Hagmann et al. Reference Hagmann, Cammoun, Gigandet, Meuli, Honey, Wedeen and Sporns2008; Biswal et al. Reference Biswal, Mennes, Zuo, Gohel, Kelly, Smith, Beckmann, Adelstein, Buckner, Colcombe, Dogonowski, Ernst, Fair, Hampson, Hoptman, Hyde, Kiviniemi, Kotter, Li, Lin, Lowe, Mackay, Madden, Madsen, Margulies, Mayberg, McMahon, Monk, Mostofsky, Nagel, Pekar, Peltier, Petersen, Riedl, Rombouts, Rypma, Schlaggar, Schmidt, Seidler, Siegle, Sorg, Teng, Veijola, Villringer, Walter, Wang, Weng, Whitfield-Gabrieli, Williamson, Windischberger, Zang, Zhang, Castellanos and Milham2010; Zuo et al. Reference Zuo, Ehmke, Mennes, Imperati, Castellanos, Sporns and Milham2012) and relevant to brain development (Dosenbach et al. Reference Dosenbach, Nardos, Cohen, Fair, Power, Church, Nelson, Wig, Vogel, Lessov-Schlaggar, Barnes, Dubis, Feczko, Coalson, Pruett, Barch, Petersen and Schlaggar2010; Power et al. Reference Power, Fair, Schlaggar and Petersen2010) and disorders (Broyd et al. Reference Broyd, Demanuele, Debener, Helps, James and Sonuga-Barke2009). This network is more active when the brain is at a ‘resting’ state and has been implicated in the cognitive functions associated with self-referential mental activity (Gusnard et al. Reference Gusnard, Akbudak, Shulman and Raichle2001), the extraction of episodic memory (Cabeza et al. Reference Cabeza, Dolcos, Graham and Nyberg2002), imagining the future (Schacter et al. Reference Schacter, Addis and Buckner2007) and mind wandering (Mason et al. Reference Mason, Norton, Van Horn, Wegner, Grafton and Macrae2007). DMN regions include the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex, ventral anterior cingulate cortex and lateral parietal cortex (Raichle et al. Reference Raichle, MacLeod, Snyder, Powers, Gusnard and Shulman2001). Several studies have shown that OCD patients demonstrate abnormal DMN functional connectivity (Harrison et al. Reference Harrison, Soriano-Mas, Pujol, Ortiz, Lopez-Sola, Hernandez-Ribas, Deus, Alonso, Yucel, Pantelis, Menchon and Cardoner2009; Fitzgerald et al. Reference Fitzgerald, Stern, Angstadt, Nicholson-Muth, Maynor, Welsh, Hanna and Taylor2010, Reference Fitzgerald, Welsh, Stern, Angstadt, Hanna, Abelson and Taylor2011; Jang et al. Reference Jang, Kim, Jung, Choi, Jung, Lee, Choi, Kang and Kwon2010; Sakai et al. Reference Sakai, Narumoto, Nishida, Nakamae, Yamada, Nishimura and Fukui2010; Hou et al. Reference Hou, Wu, Lin, Wang, Zhou, Guo, Gu, He, Ahmed, Hu, Qu and Li2012; Stern et al. Reference Stern, Fitzgerald, Welsh, Abelson and Taylor2012). For instance, Harrison et al. (Reference Harrison, Soriano-Mas, Pujol, Ortiz, Lopez-Sola, Hernandez-Ribas, Deus, Alonso, Yucel, Pantelis, Menchon and Cardoner2009) reported that OCD patients had increased functional connectivity along a ventral corticostriatal axis within the DMN and decreased functional connectivity in the dorsal striatum within the lateral prefrontal cortex and the ventral striatum within the midbrain ventral tegmental area by using the striatum seed regions. Jang et al. (Reference Jang, Kim, Jung, Choi, Jung, Lee, Choi, Kang and Kwon2010) found that OCD patients had less functional connectivity with the PCC in the anterior cingulate cortex, middle frontal gyrus, and putamen. Taken together, these findings suggest that abnormal functional connectivity of the DMN exists in OCD patients. However, the heritability property of functional connectivity within the DMN in OCD remains unclear.

Due to their high risk of developing OCD, unaffected siblings of patients with OCD can provide rich genetic information for OCD research, thus helping to disentangle state and trait characteristic of the illness. Thus an important next step in the identification of DMN connectivity as a putative biological marker is to examine the functional connectivity of the DMN in unaffected siblings of OCD patients, providing new insights into genetic risk factors for OCD.

The purpose of this study was to examine the profiles of functional connectivity of the DMN in patients with OCD, their unaffected siblings, and healthy controls. Given the high familial risk of OCD, we expected to observe in unaffected siblings a pattern of functional connectivity within the DMN intermediate between OCD patients and healthy controls.

Method

Participants

The subjects (see Table 1 for details) were recruited through the Guangzhou Psychiatry Hospital and included: (1) patients who met Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) criteria for OCD [OCD group; n = 15, 10 males; age (±s.d.) 26.7 ± 4.8 years]; (2) the unaffected siblings of individuals with OCD (SIB group; n = 15, seven males; age 30.0 ± 9.0 years); and (3) healthy control subjects (CON group; n = 28, 21 males; age 27.5 ± 8.4 years). All participants were from the Chinese Han population. Each unaffected sibling was compared with one OCD patient and they came from the same family. The individuals with OCD were all out-patients and had been stabilized on selective serotonin reuptake inhibitors for at least 4 weeks (see online Supplementary Material). Siblings were full siblings, based on self-report. The institutional research and ethics committee of Guangzhou Psychiatry Hospital approved all study protocols. All subjects gave written informed consent before participation.

Table 1. Demographic and clinical characteristics of study subjects

Data are given as mean (standard deviation).

OCD, Obsessive compulsive disorder; SIB, siblings of individuals with OCD; CON, healthy control subjects; IQ, intelligence quotient; YBOCS, Yale–Brown Obsessive Compulsive Scale; OCI-R, Obsessive Compulsive Inventory – Revised; BDI, Beck Depression Inventory; STAI, State-Trait Anxiety Inventory.

All subjects were diagnosed with DSM-IV criteria for OCD by using the Structured Clinical Interview (SCID) for DSM-IV-TR Axis I disorders (First et al. Reference First, Spitzer, Gibbon and Williams1996). The patients had no history of neurological disorder, Tourette's syndrome, head injury, serious medical condition, or history of drug or alcohol addiction. The SIB and CON subjects were screened by using the SCID for the DSM-IV-TR Axis I disorders, Research Version, Non-Patient edition (SCID-I/NP; First et al. Reference First, Spitzer, Gibbon and Williams2002). Healthy controls with a family history of Axis I or II psychiatric disorders were excluded.

Measures

Clinical and neurocognitive assessments

Estimated intelligence quotient (IQ) was assessed with the Wechsler Adult Intelligence Scale-Revised (Wechsler, Reference Wechsler1981), and subjects with a total score of less than 80 were excluded. The Yale–Brown Obsessive Compulsive Scale (YBOCS) was used to assess illness severity (Goodman et al. Reference Goodman, Price, Rasmussen, Mazure, Fleischmann, Hill, Heninger and Charney1989). The Obsessive Compulsive Inventory – Revised (OCI-R) was used to characterize obsessive and compulsive phenomena, including obsessing, washing, checking, neutralizing, ordering and hoarding (Foa et al. Reference Foa, Huppert, Leiberg, Langner, Kichic, Hajcak and Salkovskis2002; Peng et al. Reference Peng, Yang, Miao, Jing and Chan2011). The Beck Depression Inventory (BDI; Beck & Steer, Reference Beck and Steer1984) was used to assess depressive symptoms, and the State-Trait Anxiety Inventory (STAI; Spielberger, Reference Spielberger1983) was used to measure anxiety symptoms. The Annett Handedness Inventory measured handedness information (Spreen & Strauss, Reference Spreen and Strauss1991). An experienced psychiatrist administered all clinical ratings.

Magnetic resonance imaging acquisition

All scans were performed on a Signa HDe 1.5-T GE Signa scanner (GE Medical Systems, USA) equipped with an eight-channel phased-array head coil at the First Affiliated Hospital of Jinan University. For each subject, 141 resting-state functional images (blood oxygenation level-dependent) were acquired with a single-shot echo-planar imaging sequence [repetition time (TR) = 2000 ms, echo time (TE) = 60 ms, matrix = 64 × 64, field of view (FOV) = 240 mm × 240 mm, 6 mm slice thickness, 22 axial slices, no gap, flip angle = 90°]. All subjects were instructed to relax, stay awake, lie still, keep their eyes closed and not to think of anything in particular. In order to assess the stability of the resting-state scans and the reproducibility of findings, the second resting-state scan (REST2) was obtained following the first resting-state scan (REST1) with the same parameters after 1-min break. We also acquired a high-resolution T1-weighted anatomical image for each subject using a three-dimensional fast spoiled gradient-recalled sequence with 128 contiguous slices (TR = 8 ms, TE = 1.7 ms, flip angle = 20°, FOV = 240 mm × 240 mm, matrix = 256 × 256, slice thickness = 1.0 mm).

Subject-level data pre-processing and connectivity analyses

Both structural and functional data pre-processing were conducted with the Connectome Computation System (http://lfcd.psych.ac.cn/ccs.html) developed by the Laboratory for Functional Connectome and Development (Zuo et al. Reference Zuo, Xu, Jiang, Yang, Cao, He, Zang, Castellanos and Milham2013) based on the ‘1000 Functional Connectomes Project’ scripts (Biswal et al. Reference Biswal, Mennes, Zuo, Gohel, Kelly, Smith, Beckmann, Adelstein, Buckner, Colcombe, Dogonowski, Ernst, Fair, Hampson, Hoptman, Hyde, Kiviniemi, Kotter, Li, Lin, Lowe, Mackay, Madden, Madsen, Margulies, Mayberg, McMahon, Monk, Mostofsky, Nagel, Pekar, Peltier, Petersen, Riedl, Rombouts, Rypma, Schlaggar, Schmidt, Seidler, Siegle, Sorg, Teng, Veijola, Villringer, Walter, Wang, Weng, Whitfield-Gabrieli, Williamson, Windischberger, Zang, Zhang, Castellanos and Milham2010), producing the resultant four-dimensional (4D) residual time series for subsequent subject-level functional connectivity analyses. All details of the data pre-processing can be found in our recent work (Wei et al. Reference Wei, Xu, Fan, Dong, Jiang, Li, Yang, Luo and Zuo2013; Zuo et al. Reference Zuo, Xu, Jiang, Yang, Cao, He, Zang, Castellanos and Milham2013). Of note, the Friston-24 model was employed to correct for individual in-scanner head motion (Yan et al. Reference Yan, Cheung, Kelly, Colcombe, Craddock, Di Martino, Li, Zuo, Castellanos and Milham2013). We examined resting-state functional connectivity (RSFC) associated with the hub of the default network (i.e. seed region of a sphere with 6 mm radius): the PCC (x = −8, y = −56, z = 26) in MNI152 standard space (Andrews-Hanna et al. Reference Andrews-Hanna, Reidler, Sepulcre, Poulin and Buckner2010). For each subject, we first transferred individual residual 4D data to the Montreal Neurological Institute (MNI152) 2 mm space and extracted the mean time series by averaging across all voxels in each seed region. Using this mean time series, we performed a whole-brain seed correlation analysis for each subject using the AFNI program 3dfim+, carried out in each individual's native space. This analysis produced subject-level correlation maps of all voxels in the brain that were positively or negatively correlated with the seed's time series. Finally, these correlation maps were converted into z value maps using Fisher's r-to-z transformation to improve the data normality.

Group-level default network connectivity analyses

Group-level analyses were implemented as a two-way (factors: group, scan) repeated-measure (scan) analysis of covariance using the Linear Mixed Effect (LME) Matlab toolbox in FreeSurfer 5.1 (Bernal-Rusiel et al. Reference Bernal-Rusiel, Greve, Reuter, Fischl and Sabuncu2012). Cluster-based statistical corrections for multiple comparisons were performed using Gaussian random field theory (z > 2.3; corrected p < 0.05). This group-level analysis produced thresholded z statistic maps showing brain regions with significantly detectable RSFC with the PCC seed regions for OCD, SIB and CON groups, respectively, as well as differences in default network RSFC (i.e. group difference maps indicating OCD versus SIB, SIB versus CON and OCD versus CON comparisons). Of note, according to previous studies showing age, sex, IQ and head micromovement-related changes of default network connectivity (Biswal et al. Reference Biswal, Mennes, Zuo, Gohel, Kelly, Smith, Beckmann, Adelstein, Buckner, Colcombe, Dogonowski, Ernst, Fair, Hampson, Hoptman, Hyde, Kiviniemi, Kotter, Li, Lin, Lowe, Mackay, Madden, Madsen, Margulies, Mayberg, McMahon, Monk, Mostofsky, Nagel, Pekar, Peltier, Petersen, Riedl, Rombouts, Rypma, Schlaggar, Schmidt, Seidler, Siegle, Sorg, Teng, Veijola, Villringer, Walter, Wang, Weng, Whitfield-Gabrieli, Williamson, Windischberger, Zang, Zhang, Castellanos and Milham2010; Tomasi & Volkow, Reference Tomasi and Volkow2012; Zuo et al. Reference Zuo, Ehmke, Mennes, Imperati, Castellanos, Sporns and Milham2012; Yan et al. Reference Yan, Cheung, Kelly, Colcombe, Craddock, Di Martino, Li, Zuo, Castellanos and Milham2013) and the wide age range of OCD patients in the present study, we modeled age, sex, IQ, and mean framewise displacement (Yan et al. Reference Yan, Cheung, Kelly, Colcombe, Craddock, Di Martino, Li, Zuo, Castellanos and Milham2013) as covariates in the group-level LME model.

Test–retest reliability and reproducibility

Despite the reasonable test–retest reliability of the resting-state functional magnetic resonance imaging (R-fMRI) measures reported (Zuo et al. Reference Zuo, Kelly, Adelstein, Klein, Castellanos and Milham2010a ,Reference Zuo, Kelly, Di Martino, Mennes, Margulies, Bangaru, Grzadzinski, Evans, Zang, Castellanos and Milham b , Reference Zuo, Ehmke, Mennes, Imperati, Castellanos, Sporns and Milham2012), previous studies have shown the dynamic and unconstrained nature of R-fMRI (Yan et al. Reference Yan, Liu, He, Zou, Zhu, Zuo, Long and Zang2009; Chang & Glover, Reference Chang and Glover2010). We conducted careful stability analysis to evaluate the test–retest reliability of default network mapping across the two resting-state scans (see online Supplementary Material).

Relationship with clinical and neurocognitive variables

To examine whether default network connectivity can predict neurocognitive function and clinical symptom severity in OCD, we conducted partial correlation analysis by controlling for the effects of age, sex and estimated IQ. Across subjects in the patient group, RSFC in the regions showing high test–retest reliability and reproducibility (see online Supplementary material), OCD versus CON or SIB versus CON differences were averaged to correlate with YBOCS, BDI and STAI scores.

Results

Demographic data

One-way analysis of variance was used to examine if there were any differences in behavior measures among the three groups. The results are summarized in Table 1. Briefly, the three groups did not differ significantly in age, sex, and education or estimated IQ. All subjects were right handed. As a group, our OCD patients were mildly impaired [total YBOCS: 25.7 (s.d. = 6.0); OCI-R: 21.0 (s.d. = 10.2); BDI: 20.5 (s.d. = 13.7); state STAI: 55.1 (s.d. = 20.2); trait STAI: 57.9 (s.d. = 18.7)] compared with SIB and normal CON subjects.

Default network connectivity: OCD versus CON

Compared with healthy controls, OCD patients were found to have significantly decreased RSFC within the PCC. We also observed significantly increased RSFC in the right inferior frontal lobe, insula and superior temporal lobe. Of note, the right superior parietal cortex also showed increased RSFC. We employed the threshold of z > 2.3, corrected p < 0.05 for cluster level statistic in FSL (Oxford University, UK). The significant cluster was still there with the threshold at z > 3.1. These results are shown in Fig. 1.

Fig. 1. Group-level default network functional connectivity differences between obsessive compulsive disorder patients and healthy controls. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

Default network connectivity: OCD versus SIB

Compared with SIB subjects, OCD patients exhibited decreased RSFC in the right middle temporal gyrus (Fig. 2).

Fig. 2. Group-level default network functional connectivity differences between obsessive compulsive disorder patients and their first-degree siblings. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

Default network connectivity: SIB versus CON

With the PCC seed (Fig. 3), compared with CON subjects, SIB participants only showed a lower RSFC in the PCC and no increased RSFC was found.

Fig. 3. Group-level default network functional connectivity differences between obsessive compulsive disorder first-degree siblings and healthy controls. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

Test–retest reliable and reproducible findings

For PCC seeded RSFC maps, we measured the test–retest reliability of the default network connectivity across REST1 and REST2 with the intraclass correlation coefficient (ICC). There was fair (ICC = 0.4) to excellent (ICC = 0.9) reproducibility for RSFC within default network regions (online Supplementary Fig. S1).

Default network connectivity predicts clinical scores

To assess if the reduction of short-distance default network connectivity in both OCD patients and their siblings is associated with various clinical or neurocognitive measures, we extracted the mean RSFC within the overlap region for PCC seeds and correlated them with clinical scores. Our RSFC-symptom correlational analyses found that there was a significant negative correlation between RSFC in the overlap region for the PCC and YBOCS obsessive subscale scores (Pearson r = −0.49, p = 0.008).

Discussion

The goal of the present study was to examine differences in functional connectivity within the DMN in OCD patients, their unaffected siblings and matched controls to test the hypothesis that the disruptive connectivity of the DMN in OCD may be a putative marker for this disease. We observed reduced functional connectivity in the PCC within the DMN not only in patients with OCD but also in their unaffected siblings. These disrupted connectivity patterns were present in the two sequential scans with a 1-min interval, implying their test–retest reliability. The presence of abnormalities of the DMN in unaffected siblings suggests that these abnormalities are mainly due to genetic factors rather than to treatment or other secondary environmental factors. Taken together, these findings suggest that OCD is associated with disrupted functional connectivity within the DMN, and may provide new insights into the understanding of the pathophysiology of this disorder.

The present study demonstrates that OCD patients are associated with abnormal functional connectivity in the PCC within the DMN. These findings are consistent with previous studies about resting-state functional connectivity in OCD. Fitzgerald et al. (Reference Fitzgerald, Stern, Angstadt, Nicholson-Muth, Maynor, Welsh, Hanna and Taylor2010) found that pediatric OCD patients exhibited less functional connectivity within the PCC during the resting state. In addition, previous studies have identified structural and functional abnormalities of the PCC in OCD patients. Neuroanatomically, recent studies demonstrated that OCD patients had reductions of gray matter volume in the PCC (Matsumoto et al. Reference Matsumoto, Ito, Takahashi, Ando, Fujimura, Nakayama, Okubo, Obata, Fukui and Suhara2010), as well as white matter reduction in the PCC (Cannistraro et al. Reference Cannistraro, Makris, Howard, Wedig, Hodge, Wilhelm, Kennedy and Rauch2007). Functionally, the PCC is important for cognitive inhibition (Rubia et al. Reference Rubia, Smith, Brammer, Toone and Taylor2005; Simmonds et al. Reference Simmonds, Pekar and Mostofsky2008) and flexibility (Fox et al. Reference Fox, Barense and Baxter2003; Chamberlain et al. Reference Chamberlain, Menzies, Hampshire, Suckling, Fineberg, del Campo, Aitken, Craig, Owen, Bullmore, Robbins and Sahakian2008; Pearson et al. Reference Pearson, Heilbronner, Barack, Hayden and Platt2011), which are the core cognitive dysfunctions in OCD and suggested as cognitive biological markers for OCD (Chamberlain et al. Reference Chamberlain, Fineberg, Menzies, Blackwell, Bullmore, Robbins and Sahakian2007; Menzies et al. Reference Menzies, Achard, Chamberlain, Fineberg, Chen, del Campo, Sahakian, Robbins and Bullmore2007). Most recently, two resting-state studies both found that OCD patients showed decreased functional connectivity within the DMN when using the PCC as seed, which is similar to our results (Jang et al. Reference Jang, Kim, Jung, Choi, Jung, Lee, Choi, Kang and Kwon2010; Stern et al. Reference Stern, Fitzgerald, Welsh, Abelson and Taylor2012). However, their results did not find that OCD patients had reduced connectivity in the PCC. This difference might be due to the differences of sample heterogeneity or seed selection. Specifically, one study included medicated and unmedicated patient samples (Stern et al. Reference Stern, Fitzgerald, Welsh, Abelson and Taylor2012), and another study defined the PCC seed region using a different labeled template (Jang et al. Reference Jang, Kim, Jung, Choi, Jung, Lee, Choi, Kang and Kwon2010). Relative to healthy controls, OCD patients also showed increased functional connectivity in the inferior frontal lobe and insula, which are core regions of the salience network involved in implementing and maintaining attention to external task demands and detecting salient events (Dosenbach et al. Reference Dosenbach, Fair, Miezin, Cohen, Wenger, Dosenbach, Fox, Snyder, Vincent, Raichle, Schlaggar and Petersen2007). Particularly, the insula may act as an integral hub in mediating dynamic interactions between externally oriented attentional networks and internally oriented self-related networks. In other words, this region is important for switching attention away from an internal focus toward the external environment after detecting potentially harmful situations (Menon & Uddin, Reference Menon and Uddin2010). Our results found that OCD patients had decreased functional connectivity in the DMN, but increased connectivity in the salient network. Based on the causal relationship between the salience network and the DMN (Chiong et al. Reference Chiong, Wilson, D'Esposito, Kayser, Grossman, Poorzand, Seeley, Miller and Rankin2013), it is natural to speculate that OCD patients have difficulties in disengaging from internal mental processes when needing to respond more appropriately to salient external information related to potential risk.

Intriguingly, our findings also demonstrated that the unaffected siblings exhibited impairments in functional connectivity within the PCC similar to OCD patients. Given that the unaffected siblings have not received any medication for the treatment of OCD symptoms, the similar functional connectivity patterns shown in them suggests that such a disrupted functional connection in their OCD probands was not secondary to medication or the effects of the illness. This finding is consistent with the findings of disrupted functional connectivity when the first-degree relatives of OCD patients were asked to perform a functional task. For instance, Chamberlain et al. (Reference Chamberlain, Fineberg, Menzies, Blackwell, Bullmore, Robbins and Sahakian2007, Reference Chamberlain, Menzies, Hampshire, Suckling, Fineberg, del Campo, Aitken, Craig, Owen, Bullmore, Robbins and Sahakian2008) demonstrated that relatives and OCD patients both showed impaired cognitive flexibility and motor inhibition, which were related to the PCC (Rubia et al. Reference Rubia, Smith, Brammer, Toone and Taylor2005; Pearson et al. Reference Pearson, Heilbronner, Barack, Hayden and Platt2011). However, future research is needed to elucidate the precise function and connectivity of the PCC in first-degree relatives. These findings may ultimately contribute to brain-based markers for OCD and aid in determining risk genes.

The observed decreased functional connectivity within the DMN may contribute to the core cognitive symptoms of OCD. The DMN has been implicated in cognitive functions associated with internal thought in contrast to stimulus-based perception (Buckner et al. Reference Buckner, Andrews-Hanna and Schacter2008). The reduced RSFC of the DMN in OCD patients may blur the normal boundary between internal thoughts and external perceptions. Based on difficulty in inhibiting the external stimuli (uncontrolled and recurrent thoughts, impulses or images), OCD patients might pay more attention to the distressing stimuli and attend less on internal thoughts. This may result in an ambiguous integration between one's own thoughts and feeling with external events. Furthermore, OCD patients would seem to be imbued with exaggerated perceptions of external stimuli for attempting to avoid or control the uncontrolled and recurrent thoughts. Indeed, the preoccupations were speculated on contributing to many symptoms of OCD for less sense of self-relevance (Fitzgerald et al. Reference Fitzgerald, Stern, Angstadt, Nicholson-Muth, Maynor, Welsh, Hanna and Taylor2010). Thus, abnormal functional connectivity of the DMN may be involved in the psychopathological symptoms of OCD.

Limitations and future work

Given different OCD symptom dimensions relating to distinct neural mechanisms (Mataix-Cols et al. Reference Mataix-Cols, Wooderson, Lawrence, Brammer, Speckens and Phillips2004), we were unable to divide the OCD patient sample into different subtypes because of the relatively small sample. Second, OCD patients in this study were mostly treated with antidepressants and had long average illness duration, so the effects of the illness duration and medication cannot completely be ruled out in our results. Further studies using different subtypes and drug-naive cohorts are required to confirm our preliminary results. Finally, from a methodological perspective, the current study only focused on the examination of the default network connectivity and may be enhanced with high-resolution full-brain network explorations to gain more insights of brain function under such a psychiatric condition.

Conclusion

In the present study, we used the resting-state functional connectivity approach to show the default networks in OCD patients and their unaffected siblings during rest. The current study provides a unique opportunity to understand the pathophysiology of, and the susceptibility to, OCD. Our findings support the hypothesis that OCD is associated with abnormal functional connectivity of the DMN. The similar abnormal connectivity in the PCC with the DMN in both OCD patients and their unaffected siblings may serve as a neuroimaging marker for the development of OCD. Future studies combining R-fMRI with structural MRI techniques will be vital to explore how the functional alterations shown in this study are related to structural changes, and whether these changes could be used for early screening markers, or detecting disease progression and medication effects in OCD patients.

Supplementary material

For supplementary material accompanying this paper visit http://dx.doi.org/10.1017/S0033291713002250.

Declaration of Interest

None.

References

Andrews-Hanna, JR, Reidler, JS, Sepulcre, J, Poulin, R, Buckner, RL (2010). Functional–anatomic fractionation of the brain's default network. Neuron 65, 550562.Google Scholar
Beck, AT, Steer, RA (1984). Internal consistencies of the original and revised Beck Depression Inventory. Journal of Clinical Psychology 40, 13651367.Google Scholar
Bernal-Rusiel, JL, Greve, DN, Reuter, M, Fischl, B, Sabuncu, MR (2012). Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models. Neuroimage 66C, 249260.Google Scholar
Biswal, BB, Mennes, M, Zuo, XN, Gohel, S, Kelly, C, Smith, SM, Beckmann, CF, Adelstein, JS, Buckner, RL, Colcombe, S, Dogonowski, AM, Ernst, M, Fair, D, Hampson, M, Hoptman, MJ, Hyde, JS, Kiviniemi, VJ, Kotter, R, Li, SJ, Lin, CP, Lowe, MJ, Mackay, C, Madden, DJ, Madsen, KH, Margulies, DS, Mayberg, HS, McMahon, K, Monk, CS, Mostofsky, SH, Nagel, BJ, Pekar, JJ, Peltier, SJ, Petersen, SE, Riedl, V, Rombouts, SA, Rypma, B, Schlaggar, BL, Schmidt, S, Seidler, RD, Siegle, GJ, Sorg, C, Teng, GJ, Veijola, J, Villringer, A, Walter, M, Wang, L, Weng, XC, Whitfield-Gabrieli, S, Williamson, P, Windischberger, C, Zang, YF, Zhang, HY, Castellanos, FX, Milham, MP (2010). Toward discovery science of human brain function. Proceedings of the National Academy of Sciences USA 107, 47344739.CrossRefGoogle ScholarPubMed
Broyd, SJ, Demanuele, C, Debener, S, Helps, SK, James, CJ, Sonuga-Barke, EJ (2009). Default-mode brain dysfunction in mental disorders: a systematic review. Neuroscience and Biobehavioral Reviews 33, 279296.Google Scholar
Buckner, RL, Andrews-Hanna, JR, Schacter, DL (2008). The brain's default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences 1124, 138.CrossRefGoogle ScholarPubMed
Cabeza, R, Dolcos, F, Graham, R, Nyberg, L (2002). Similarities and differences in the neural correlates of episodic memory retrieval and working memory. Neuroimage 16, 317330.Google Scholar
Cannistraro, PA, Makris, N, Howard, JD, Wedig, MM, Hodge, SM, Wilhelm, S, Kennedy, DN, Rauch, SL (2007). A diffusion tensor imaging study of white matter in obsessive–compulsive disorder. Depression and Anxiety 24, 440446.CrossRefGoogle ScholarPubMed
Chamberlain, SR, Fineberg, NA, Menzies, LA, Blackwell, AD, Bullmore, ET, Robbins, TW, Sahakian, BJ (2007). Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive–compulsive disorder. American Journal of Psychiatry 164, 335338.Google Scholar
Chamberlain, SR, Menzies, L, Hampshire, A, Suckling, J, Fineberg, NA, del Campo, N, Aitken, M, Craig, K, Owen, AM, Bullmore, ET, Robbins, TW, Sahakian, BJ (2008). Orbitofrontal dysfunction in patients with obsessive–compulsive disorder and their unaffected relatives. Science 321, 421422.Google Scholar
Chang, C, Glover, GH (2010). Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 50, 8198.Google Scholar
Chiong, W, Wilson, SM, D'Esposito, M, Kayser, AS, Grossman, SN, Poorzand, P, Seeley, WW, Miller, BL, Rankin, KP (2013). The salience network causally influences default mode network activity during moral reasoning. Brain 136, 19291941.CrossRefGoogle ScholarPubMed
Dosenbach, NU, Fair, DA, Miezin, FM, Cohen, AL, Wenger, KK, Dosenbach, RA, Fox, MD, Snyder, AZ, Vincent, JL, Raichle, ME, Schlaggar, BL, Petersen, SE (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences USA 104, 1107311078.Google Scholar
Dosenbach, NU, Nardos, B, Cohen, AL, Fair, DA, Power, JD, Church, JA, Nelson, SM, Wig, GS, Vogel, AC, Lessov-Schlaggar, CN, Barnes, KA, Dubis, JW, Feczko, E, Coalson, RS, Pruett, JR Jr., Barch, DM, Petersen, SE, Schlaggar, BL (2010). Prediction of individual brain maturity using fMRI. Science 329, 13581361.Google Scholar
First, MB, Spitzer, RL, Gibbon, M, Williams, JB (1996). Structured Clinical Interview for DSM-IV Axis I Disorder, Research Version, Patient Edition (SCID-I/P,Version 2.0). Biometrics Research Department, New York State Psychiatric Institute: New York.Google Scholar
First, MB, Spitzer, RL, Gibbon, M, Williams, JB (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition (SCID-I/NP). Biometrics Research Department, New York State Psychiatric Institute: New York.Google Scholar
Fitzgerald, KD, Stern, ER, Angstadt, M, Nicholson-Muth, KC, Maynor, MR, Welsh, RC, Hanna, GL, Taylor, SF (2010). Altered function and connectivity of the medial frontal cortex in pediatric obsessive–compulsive disorder. Biological Psychiatry 68, 10391047.Google Scholar
Fitzgerald, KD, Welsh, RC, Stern, ER, Angstadt, M, Hanna, GL, Abelson, JL, Taylor, SF (2011). Developmental alterations of frontal–striatal–thalamic connectivity in obsessive–compulsive disorder. Journal of the American Academy of Child Adolescent Psychiatry 50, 938948.e3.CrossRefGoogle ScholarPubMed
Foa, EB, Huppert, JD, Leiberg, S, Langner, R, Kichic, R, Hajcak, G, Salkovskis, PM (2002). The Obsessive–Compulsive Inventory: development and validation of a short version. Psychological Assessment 14, 485496.CrossRefGoogle ScholarPubMed
Fox, MT, Barense, MD, Baxter, MG (2003). Perceptual attentional set-shifting is impaired in rats with neurotoxic lesions of posterior parietal cortex. Journal of Neuroscience 23, 676681.Google Scholar
Goodman, WK, Price, LH, Rasmussen, SA, Mazure, C, Fleischmann, RL, Hill, CL, Heninger, GR, Charney, DS (1989). The Yale–Brown Obsessive Compulsive Scale. I. Development, use, and reliability. Archives of General Psychiatry 46, 10061011.Google Scholar
Gusnard, DA, Akbudak, E, Shulman, GL, Raichle, ME (2001). Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proceedings of the National Academy of Sciences USA 98, 42594264.Google Scholar
Hagmann, P, Cammoun, L, Gigandet, X, Meuli, R, Honey, CJ, Wedeen, VJ, Sporns, O (2008). Mapping the structural core of human cerebral cortex. PLoS Biology 6, e159.CrossRefGoogle ScholarPubMed
Hanna, GL, Veenstra-VanderWeele, J, Cox, NJ, Boehnke, M, Himle, JA, Curtis, GC, Leventhal, BL, Cook, EH Jr. (2002). Genome-wide linkage analysis of families with obsessive–compulsive disorder ascertained through pediatric probands. American Journal of Medical Genetics 114, 541552.CrossRefGoogle ScholarPubMed
Harrison, BJ, Soriano-Mas, C, Pujol, J, Ortiz, H, Lopez-Sola, M, Hernandez-Ribas, R, Deus, J, Alonso, P, Yucel, M, Pantelis, C, Menchon, JM, Cardoner, N (2009). Altered corticostriatal functional connectivity in obsessive–compulsive disorder. Archives of General Psychiatry 66, 11891200.Google Scholar
Hou, J, Wu, W, Lin, Y, Wang, J, Zhou, D, Guo, J, Gu, S, He, M, Ahmed, S, Hu, J, Qu, W, Li, H (2012). Localization of cerebral functional deficits in patients with obsessive–compulsive disorder: a resting-state fMRI study. Journal of Affective Disorders 138, 313321.Google Scholar
Inouye, E (1965). Similar and dissimilar manifestations of obsessive–compulsive neuroses in monozygotic twins. American Journal of Psychiatry 121, 11711175.CrossRefGoogle ScholarPubMed
Jang, JH, Kim, JH, Jung, WH, Choi, JS, Jung, MH, Lee, JM, Choi, CH, Kang, DH, Kwon, JS (2010). Functional connectivity in fronto-subcortical circuitry during the resting state in obsessive–compulsive disorder. Neuroscience Letters 474, 158162.Google Scholar
Mason, MF, Norton, MI, Van Horn, JD, Wegner, DM, Grafton, ST, Macrae, CN (2007). Wandering minds: the default network and stimulus-independent thought. Science 315, 393395.Google Scholar
Mataix-Cols, D, Wooderson, S, Lawrence, N, Brammer, MJ, Speckens, A, Phillips, ML (2004). Distinct neural correlates of washing, checking, and hoarding symptom dimensions in obsessive–compulsive disorder. Archives of General Psychiatry 61, 564576.CrossRefGoogle ScholarPubMed
Matsumoto, R, Ito, H, Takahashi, H, Ando, T, Fujimura, Y, Nakayama, K, Okubo, Y, Obata, T, Fukui, K, Suhara, T (2010). Reduced gray matter volume of dorsal cingulate cortex in patients with obsessive–compulsive disorder: a voxel-based morphometric study. Psychiatry and Clinical Neurosciences 64, 541547.CrossRefGoogle ScholarPubMed
Menon, V, Uddin, LQ (2010). Saliency, switching, attention and control: a network model of insula function. Brain Structure and Function 214, 655667.Google Scholar
Menzies, L, Achard, S, Chamberlain, SR, Fineberg, N, Chen, CH, del Campo, N, Sahakian, BJ, Robbins, TW, Bullmore, E (2007). Neurocognitive endophenotypes of obsessive–compulsive disorder. Brain 130, 32233236.Google Scholar
Nestadt, G, Samuels, J, Riddle, M, Bienvenu, OJ 3rd, Liang, KY, LaBuda, M, Walkup, J, Grados, M, Hoehn-Saric, R (2000). A family study of obsessive–compulsive disorder. Archives of General Psychiatry 57, 358363.Google Scholar
O'Donnell, TJ (1970). New dimensions in legal and ethical concepts for human research. 1. Ethical and legal base lines for professions and community. Fundamental and changing moral concepts. Annals of the New York Academy of Sciences 169, 316318.Google Scholar
Pauls, DL, Alsobrook, JP 2nd, Goodman, W, Rasmussen, S, Leckman, JF (1995). A family study of obsessive–compulsive disorder. American Journal of Psychiatry 152, 7684.Google Scholar
Pearson, JM, Heilbronner, SR, Barack, DL, Hayden, BY, Platt, ML (2011). Posterior cingulate cortex: adapting behavior to a changing world. Trends in Cognitive Science 15, 143151.Google Scholar
Peng, ZW, Yang, WH, Miao, GD, Jing, J, Chan, RC (2011). The Chinese version of the Obsessive–Compulsive Inventory-Revised scale: replication and extension to non-clinical and clinical individuals with OCD symptoms. BMC Psychiatry 11, 129.Google Scholar
Power, JD, Fair, DA, Schlaggar, BL, Petersen, SE (2010). The development of human functional brain networks. Neuron 67, 735748.Google Scholar
Raichle, ME, MacLeod, AM, Snyder, AZ, Powers, WJ, Gusnard, DA, Shulman, GL (2001). A default mode of brain function. Proceedings of the National Academy of Sciences USA 98, 676682.CrossRefGoogle ScholarPubMed
Rubia, K, Smith, AB, Brammer, MJ, Toone, B, Taylor, E (2005). Abnormal brain activation during inhibition and error detection in medication-naive adolescents with ADHD. American Journal of Psychiatry 162, 10671075.CrossRefGoogle ScholarPubMed
Sakai, Y, Narumoto, J, Nishida, S, Nakamae, T, Yamada, K, Nishimura, T, Fukui, K (2010). Corticostriatal functional connectivity in non-medicated patients with obsessive–compulsive disorder. European Psychiatry 26, 463469.CrossRefGoogle ScholarPubMed
Schacter, DL, Addis, DR, Buckner, RL (2007). Remembering the past to imagine the future: the prospective brain. Nature Reviews Neuroscience 8, 657661.Google Scholar
Simmonds, DJ, Pekar, JJ, Mostofsky, SH (2008). Meta-analysis of Go/No-go tasks demonstrating that fMRI activation associated with response inhibition is task-dependent. Neuropsychologia 46, 224232.CrossRefGoogle ScholarPubMed
Spielberger, DC (1983). Manual for the State-Trait Anxiety Inventory (STAI). Consulting Psychologists Press: Palo Alto, CA.Google Scholar
Spreen, O, Strauss, E (1991). A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary. Oxford University Press: New York.Google Scholar
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, e36356.Google Scholar
Tomasi, D, Volkow, ND (2012). Gender differences in brain functional connectivity density. Human Brain Mapping 33, 849860.Google Scholar
Vincent, JL, Patel, GH, Fox, MD, Snyder, AZ, Baker, JT, Van Essen, DC, Zempel, JM, Snyder, LH, Corbetta, M, Raichle, ME (2007). Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447, 8386.Google Scholar
Wechsler, D (1981). Wechsler Adult Intelligence Scale-Revised. Psychological Corporation: San Antonio.Google Scholar
Wei, GX, Xu, T, Fan, FM, Dong, HM, Jiang, LL, Li, HJ, Yang, Z, Luo, J, Zuo, XN (2013). Can taichi reshape the brain? A brain morphometry study. PLOS ONE 8, e61038.Google Scholar
Weissman, MM, Bland, RC, Canino, GJ, Greenwald, S, Hwu, HG, Lee, CK, Newman, SC, Oakley-Browne, MA, Rubio-Stipec, M, Wickramaratne, PJ (1994). The cross national epidemiology of obsessive compulsive disorder. The Cross National Collaborative Group. Journal of Clinical Psychiatry 55 (Suppl.), 510.Google Scholar
Yan, C, Liu, D, He, Y, Zou, Q, Zhu, C, Zuo, X, Long, X, Zang, Y (2009). Spontaneous brain activity in the default mode network is sensitive to different resting-state conditions with limited cognitive load. PLoS One 4, e5743.CrossRefGoogle ScholarPubMed
Yan, CG, Cheung, B, Kelly, C, Colcombe, S, Craddock, RC, Di Martino, A, Li, Q, Zuo, XN, Castellanos, FX, Milham, MP (2013). A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 76, 183201.CrossRefGoogle ScholarPubMed
Zuo, XN, Ehmke, R, Mennes, M, Imperati, D, Castellanos, FX, Sporns, O, Milham, MP (2012). Network centrality in the human functional connectome. Cerebral Cortex 22, 18621875.Google Scholar
Zuo, XN, Kelly, C, Adelstein, JS, Klein, DF, Castellanos, FX, Milham, MP (2010 a). Reliable intrinsic connectivity networks: test–retest evaluation using ICA and dual regression approach. Neuroimage 49, 21632177.Google Scholar
Zuo, XN, Kelly, C, Di Martino, A, Mennes, M, Margulies, DS, Bangaru, S, Grzadzinski, R, Evans, AC, Zang, YF, Castellanos, FX, Milham, MP (2010 b). Growing together and growing apart: regional and sex differences in the lifespan developmental trajectories of functional homotopy. Journal of Neuroscience 30, 1503415043.CrossRefGoogle ScholarPubMed
Zuo, XN, Xu, T, Jiang, L, Yang, Z, Cao, XY, He, Y, Zang, YF, Castellanos, FX, Milham, MP (2013). Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space. Neuroimage 65, 374386.Google Scholar
Figure 0

Table 1. Demographic and clinical characteristics of study subjects

Figure 1

Fig. 1. Group-level default network functional connectivity differences between obsessive compulsive disorder patients and healthy controls. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

Figure 2

Fig. 2. Group-level default network functional connectivity differences between obsessive compulsive disorder patients and their first-degree siblings. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

Figure 3

Fig. 3. Group-level default network functional connectivity differences between obsessive compulsive disorder first-degree siblings and healthy controls. LH, Left hemisphere; PCC, posterior cingulate cortex; RSFC, resting-state functional connectivity; RH, right hemisphere.

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