Observational Study Open Access
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Aug 19, 2025; 15(8): 107860
Published online Aug 19, 2025. doi: 10.5498/wjp.v15.i8.107860
Decreased inter- and intra-network connectivity after group cognitive behavioral therapy in patients with unmedicated obsessive-compulsive disorder
Zong-Feng Zhang, Yan He, Yu-Qiu Su, Ji-Meng Liu, Department of Psychiatry, The Affiliated Kangning Hospital of Ningbo University, Ningbo 315201, Zhejiang Province, China
Zong-Feng Zhang, Yan He, Yu-Qiu Su, Ji-Meng Liu, Department of Psychiatry, Ningbo Kangning Hospital, Ningbo 315201, Zhejiang Province, China
ORCID number: Zong-Feng Zhang (0000-0001-6097-0939); Ji-Meng Liu (0009-0005-8127-9801).
Co-first authors: Zong-Feng Zhang and Yan He.
Author contributions: Zhang ZF and He Y contributed to data analysis and manuscript drafting; Liu JM was responsible for research design and overall supervision; and Su YQ conducted the research implementation and sample evaluations; All authors advised upon, edited, and reviewed the manuscript.
Supported by the Pharmaceutical Science and Technology Project of Zhejiang Province, No. 2023RC266; and the Natural Science Foundation of Ningbo, No. 202003N4266.
Institutional review board statement: The study was approved by the Ethics Committee of the Affiliated Kangning Hospital of Ningbo University (NBKNYY-2021-LC-5).
Informed consent statement: All participants were signed informed consent forms.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Data sharing statement: The datasets utilized and examined in this investigation are available from the corresponding author upon reasonable request at 13216645323@163.com.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ji-Meng Liu, MD, Chief Physician, Department of Psychiatry, The Affiliated Kangning Hospital of Ningbo University, No. 1 Zhuangyu South Road, Zhuangshi Sub-District, Ningbo 315201, Zhejiang Province, China. 13216645323@163.com
Received: April 22, 2025
Revised: May 20, 2025
Accepted: June 13, 2025
Published online: August 19, 2025
Processing time: 108 Days and 1.4 Hours

Abstract
BACKGROUND

Group cognitive behavioral therapy (GCBT) is increasingly being used to treat obsessive-compulsive disorder (OCD) because of its high efficiency, economy, and interaction among group members. However, the changes in network functional connectivity (FC) in patients with OCD with GCBT remain unclear.

AIM

To investigate inter- and intra-network resting-state FC (rs-FC) abnormalities before and after GCBT in unmedicated patients with OCD and validate the efficacy of GCBT.

METHODS

Overall, 33 individuals with OCD and 26 healthy controls underwent resting-state functional magnetic resonance imaging. The patients were rescanned 12 weeks after GCBT. Four cognition-related networks-default mode network (DMN), dorsal attention network (DAN), salience network (SAN), and frontoparietal network (FPN)-were selected to examine FC abnormalities within and between OCD networks before and after GCBT. Neuropsychological assessments including memory, executive function, speech, attention, and visuospatial ability were reassessed following GCBT. Pearson’s correlations were used to analyze the relationship between aberrant FC in cognition-related networks and altered neuropsychological assessments in patients.

RESULTS

Rs-FC within the DMN and DAN decreased significantly. Additionally, rs-FC between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN also decreased. Significant improvements were observed in cognitive functions, such as memory, executive function, attention, and visuospatial ability. Furthermore, reduced rs-FC within the DMN correlated with visuospatial ability and executive function; DAN positively correlated with Shape Trails Test (STT)-A test elapsed time; DMN-DAN negatively correlated with Rey-Osterrieth Complex Figure (Rey-O) mimicry time and the three elapsed times of the tower of Hanoi; DMN-SAN negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time; and DMN-FPN negatively correlated with Auditory Word Learning Test N1 and N4 scores.

CONCLUSION

Decreased rs-FC within the DMN and DAN, which correlated with executive function post-treatment, has potential as a neuroimaging marker to predict treatment response to GCBT in patients with OCD.

Key Words: Cognitive networks; Default mode network; Dorsal attention network; Frontoparietal network; Group cognitive behavioral therapy; Obsessive-compulsive disorder; Resting-state functional connectivity; Salience network

Core Tip: This study demonstrated that group cognitive behavioral therapy (GCBT) reduced resting-state functional connectivity (rs-FC) within and between the default mode (DMN) and dorsal attention networks (DAN) in patients with unmedicated obsessive-compulsive disorder (OCD). These connectivity changes correlated with improved executive function, memory, and visuospatial abilities, suggesting reduced DMN/DAN rs-FC as a potential neuroimaging marker for predicting GCBT efficacy in OCD treatment.



INTRODUCTION

Obsessive-compulsive disorder (OCD) is a chronic and refractory disease characterized by intrusive thinking and repetitive behaviors, often accompanied by anxiety and depression, which severely affects social function and quality of life. Previous studies have demonstrated that cognitive-behavioral therapy (CBT) is as effective as pharmacotherapy in patients with OCD[1-3]. One meta-analysis suggested that group CBT (GCBT) may be effective in relieving OCD symptoms[4] in the long term[5]. Other studies have suggested that CBT elicits improvements in clinical symptoms by altering cognitive function[6,7]; however, the results have been inconsistent.

Recently, studies have documented abnormal functional connectivity (FC) in the prefrontostriatothalamo-cortical loop[8], with increasing evidence indicating altered network connectivity in OCD[9,10]. Based on convergent evidence from multiple studies, three networks-the default mode (DMN), frontoparietal (FPN), and salience (SAN)-are considered canonical[11,12]. The dorsal attention network (DAN) also exhibits increased FC with the FPN[10], explained by their interactive role in most cognitive functions. Abnormal functional organization of these networks and dynamic cross-network communication may underlie a wide range of psychiatric symptoms. The DMN comprises the bilateral medial prefrontal cortex (mPFC), superior frontal gyrus, inferior frontal gyrus, posterior cingulate, temporal lobe, and subparietal lobules. Furthermore, it is often defined as a task-negative activation network, as its primary functions include maintaining alertness, consolidating memories, monitoring surroundings, and self-reflection[13]. The DAN, which includes the dorsolateral prefrontal lobe, frontal eye fields, and precentral, supraoccipital, middle temporal, and supraparietal gyri, is associated with attentional function and provides top-down attentional orienting and sustained activity to ensure task completion[14]. The FPN is associated with goal-directed cognitive functions and includes the lateral prefrontal cortex, precuneus, anterior subparietal sulcus, medial-superior prefrontal cortex, and anterior insula[15]. Finally, the SAN comprises the anterior cingulate gyrus and anterior insula and is involved in executive functions, such as planning and decision-making[16].

CBT and GCBT are considered the first-line treatments for OCD. Few functional neuroimaging studies have examined the potential neurobiological mechanisms and predictors of CBT response in patients with OCD and have found associations with frontostriatal circuitry or independent component networks[10,17-20]. A previous study reported that CBT normalized the aberrant resting-state FC (rs-FC) between the right orbitofrontal cortex and the left dorsolateral prefrontal cortex[17]. Another study showed that rs-FC within the DMN and visual network predicted the severity of OCD symptoms after CBT[18]. Greater pretreatment activation has also been reported within the right temporal lobe and rostral anterior cingulate cortex during cognitive control tasks, as well as within the ventromedial and lateral prefrontal cortices, orbitofrontal cortex, and amygdala during reward processing in patients with OCD[19]. Meanwhile, global network clustering coefficients and nodal clustering of the precuneus as well as the left lingual, middle temporal, and fusiform gyri, have been reported after CBT[21]; however, relatively few studies have focused on the effects of GCBT on FC in patients with OCD. The present study reported significantly decreased rs-FC within the DMN and DAN, and between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN after GCBT.

Patients with OCD have been reported to have memory, attention, and executive function dysfunctions[22], which can be improved with CBT[23-25]. Additional difficulties include persistent cognitive inhibition and motor responses, difficulty in shifting attention from one aspect of a stimulus to another, impaired executive planning and decision-making, difficulty in forming words in a limited amount of time, and reduced capacity to recall verbal information[26,27]. One study applied the Connectivity Test, Verbal/Nonverbal Fluency and Flexibility Test, Tower of London, Complex Images Test, and Conversion Test and found significant improvements after CBT, suggesting that CBT can improve thinking and cognitive flexibility and help patients implement more effective cognitive strategies[23]. Cognition-related network abnormalities that align with changes in cognitive functioning can provide clearer insights into the underlying mechanisms of CBT efficacy in patients with OCD.

In this study, we aimed to assess unmedicated patients with OCD who underwent 12 weeks of GCBT. Four seed networks (i.e., DMN, DAN, SAN, and FPN) were used to investigate inter- and intra-network FC abnormalities before and after GCBT, and neuropsychological assessments (i.e., attention, memory, executive functioning, speech, and verbal fluency) were conducted to validate the mechanisms underlying the efficacy of GCBT.

MATERIALS AND METHODS
Participants

Overall, 33 patients with OCD were recruited from an outpatient service, and 26 healthy controls were recruited through local advertisements from January 2022 to December 2023. All the participants were right-handed, aged 18-54 years, and had completed at least junior high school education or higher. Patients with OCD did not take psychotropic medications for at least 8 weeks. All patients were diagnosed by a trained psychiatrist according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) diagnostic criteria and screened using the Mini-International Neuropsychiatric Interview to exclude other psychiatric disorders. The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was used to assess symptom severity, and the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD) were used to assess anxiety and depression symptoms, respectively (Table 1). Exclusion criteria were as follows: (1) Diagnosis of pulmonary, cardiac, hepatic, neurological, endocrine, or metabolic disorders; (2) Current or past DSM-5 Axis I psychiatric disorders, other than OCD; (3) Severe suicidal ideation; and (4) Contraindications for magnetic resonance imaging (MRI), such as an implanted metal device. All participants provided written informed consent. The study protocol was approved by the Ethics Committee of the Affiliated Kangning Hospital of Ningbo University (No. NBKNYY-2021-LC-5).

Table 1 Comparison of general demographic information between groups.
mean ± SD
OCD (n = 33)
HC (n = 26)
t/χ2
P value
Sex (male)16110.150.78
Age32.24 ± 7.3828.23 ± 7.361.980.06
Education15.18 ± 2.0715.45 ± 1.76-0.930.61
Age at onset24.56 ± 9.15///
Duration (months)84.12 ± 79.15///
Y-BOCS total25.81 ± 4.78///
Y-BOCS obsession13.03 ± 2.91///
Y-BOCS compulsion12.88 ± 3.48///
HAMD12.94 ± 5.801.09 ± 1.4411.060.000b
HAMA9.42 ± 3.800.77 ± 1.1111.340.000b
Neuropsychological assessments

A series of neuropsychological assessments were conducted in the present study, including the Montreal Cognitive Assessment-Based Scale (MoCA-B), Auditory Verbal Learning Test (AVLT), Verbal Fluency Test, Digit Span Test, Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), Complex Figure Test, Trail Making Test, Stroop Color Word Test, California Card Sorting Test (CST), and the Tower of Hanoi. The assessments lasted approximately 45 minutes and were administered at baseline and after 12 weeks of treatment. Detailed descriptions of the neuropsychological assessments are provided in the online Supplementary material.

Functional MRI acquisition and preprocessing

Patients with OCD underwent functional MRI (fMRI) both before and after the treatment. The total scanning time was approximately 30 minutes and included both 3D-T1 (structural images) and resting-state (rs) fMRI scanning. A simultaneous multilayer scanning technique (multiband accel factor) and echo-planar imaging sequence were used to scan parallel to the anteroposterior joint line plane simultaneously. The scanning parameters were as follows: Echo time of 30 millisecond, repetition time of 2000 millisecond, field of view of 220 mm2, flip angle of 90°, automatic matrix coil mode, 4 mm layer thickness, 30 layers, 180 passes, and scanning time of 8 minutes and 30 seconds. The general preprocessing procedure was as follows: First, the first 10 time points of each participant’s rs fMRI data were excluded to allow participants to get used to the fMRI scanning noise. Second, the slices were timed to correct for differences in the acquisition time. Third, realignment was conducted to exclude participants with head translations of > 2 mm or rotations of > 2°. Fourth, spatial normalization was applied to align all selected participants to the standard Montreal Neurological Institute template with a sampling resolution of 3 mm × 3 mm × 3 mm. Finally, detrending was performed to reduce the signal drift caused by the banding of the receiver coil during scanning. Finally, a band-pass filter of 0.01-0.08 Hz was applied to remove interference from physiological noise signals and data were smoothed using a Gaussian kernel of 6 mm full width at half-maximum.

Group cognitive behavioral therapy

The study was conducted by two registered psychotherapists who had undergone systematic professional training and formed a homogeneous closed group with live recordings. Each group consisted of 6-10 participants, and the treatment was conducted for 12 weeks, with each session being conducted once per week for 2 hours. Before treatment, the psychotherapist conducted one pre-treatment interview with each participant to exclude patients who were not suitable for GCBT (e.g., poor introspection and severe symptoms of depression and anxiety). The first three sessions were to introduce participants to each other; re-emphasize the treatment setup, treatment process, and concept of group therapy; re-introduce the concept of OCD and explain the concepts of “obsessive-compulsive thoughts” and “obsessive-compulsive behaviors” and the relationship between the two; discussion of the principles of graded exposure development; and assign homework. The next 4-10 sessions involved practice exposures within the group, while the final 11-12 sessions included feedback and summarization. The details of the treatment protocols are provided in the online Supplementary material.

Cognition-related brain networks

The DMN, DAN, FPN, and SAN were selected as the networks of interest, with 12 seeds regions selected based on a previous study[8] (Table 2).

Table 2 Seed points of the default mode, dorsal attention, frontoparietal, and salience networks.

Abbreviation
X (L/R)
Y (L/R)
Z (L/R)
DMN
    Dorsal medial prefrontal cortexdmPFC-85034
    Ventral medial prefrontal cortexvmPFC-244-12
    Posterior cingulate cortexPCC-2-4828
    PrecuneusPcu-2-6050
    Superior frontal gyrusSFG-8/1220/1862/62
    Inferior frontal gyrusIFG-42/5026/30-14/-6
DAN
    Frontal eye fieldsFEF-24/242/-262/56
    Superior occipital gyrusSOG-18/26-66/-6450/54
FPN
    Anterior inferior parietal lobuleaIPL-54/50-48/-4448/46
    Dorsolateral prefrontal cortexDLPFC-38/4432/4230/26
SAN
    Anterior insulaaINS-30/3220/20-2/-4
    Dorsal anterior cingulate cortexdACC63040
Statistical analysis

Clinical and neuropsychological data: Two-sample t tests and χ2 tests were used to compare clinical data using SPSS (version 22.0; IBM, Armonk, NY, United States).

fMRI data: fMRI data were processed using the MATLAB 2012a (MathWorks, Natick, MA, Unite States) software platform using the Data Processing Assistant. We conducted two-sample t tests on the FC values within and between the four networks extracted before and after the GCBT, with differences considered statistically significant at P < 0.05. To determine whether any changes in FC were consistent with changes in any of the neuropsychological assessments, Pearson’s correlations were calculated (P < 0.05 was considered statistically significant). All statistical analyses were conducted using the SPSS software. Additional details of the analyses are provided in the online Supplementary material.

RESULTS
Demographic information

A total of 33 patients with OCD and 26 healthy controls were enrolled in this study. There were no significant demographic differences between the two groups in terms of sex, age, or years of education. However, significant decreases were observed in the Y-BOCS score, HAMD, and HAMA after GCBT in the OCD group (Tables 1 and 3).

Table 3 Comparison of demographic information before and after group cognitive-behavioral therapy treatment.

Before (n = 33)
After (n = 21)
t
P value
Sex (male)1611//
Age32.24 ± 7.3832.50 ± 7.22-0.3150.75
Education15.18 ± 2.0716.04 ± 1.850.170.87
Age at onset24.56 ± 9.1524.32 ± 9.07-0.370.72
Y-BOCS total25.81 ± 4.7816.41 ± 6.706.650.000b
Y-BOCS obsession13.03 ± 2.918.59 ± 3.115.400.000b
Y-BOCS compulsion12.88 ± 3.487.82 ± 4.475.370.000b
HAMD12.94 ± 5.806.83 ± 4.502.910.005a
HAMA9.42 ± 3.805.11 ± 3.253.410.001a
Comparison of neuropsychological assessments between groups

Significant differences were observed between patients with OCD and healthy controls in MoCA-B, Complex Graphic Recall Score (Rey-O), Organization Score, Short Delayed Recall, and Long Delayed Recall on the ALVT, number of correct responses on the SDMT, number of correct responses on the PASAT, Shape Trails Test (STT) B, Tower of Hanoi, and Verbal Fluency Tests (Table 4).

Table 4 Comparison of neuropsychological assessment results between groups.

OCD (n = 33)
HC (n = 26)
t
P value
MoCA-BMoCA-B27.79 ± 1.5929.00 ± 0.87-3.250.002a
Visuospatial abilityRey-O emulation time (second)160 ± 80.67128.63 ± 48.441.670.100
Rey-O recall time (second)79.57 ± 40.1087.63 ± 25.01-0.840.404
Rey-O recall score15.26 ± 7.9721.27 ± 6.18-2.990.004a
Rey-O recall organization score4.53 ± 1.775.41 ± 1.10-2.270.027a
MemoryAVLT-N14.12 ± 1.604.36 ± 1.22-0.600.548
AVLT-N25.94 ± 2.017.18 ± 1.26-2.810.007a
AVLT-N37.00 ± 2.198.55 ± 1.99-2.650.011a
AVLT-N4 short-delayed recall5.73 ± 2.187.36 ± 2.01-2.810.007a
AVLT-N5 long-delayed recall5.30 ± 2.427.05 ± 2.06-2.770.008a
AVLT-N65.45 ± 2.477.36 ± 1.89-3.070.008a
AVLT-reaccreditation9.82 ± 2.1110.91 ± 1.07-2.520.015a
AttentionSDMT-correct count53.03 ± 12.4761.18 ± 7.71-2.990.004a
SDMT-error count0.30 ± 0.630.72 ± 1.24-1.470.150
PASAT-correct count32.79 ± 4.1335.77 ± 2.93-2.930.005a
DST-recite along9.61 ± 1.329.59 ± 1.010.050.964
DST-recite backwards5.94 ± 1.697.05 ± 1.79-2.320.024a
DST total score15.54 ± 2.6716.64 ± 2.42-1.540.129
Executive functionSCWT-A (second)21.27 ± 4.8319.96 ± 3.431.180.24
SCWT-B (second)34.27 ± 10.8628.32 ± 3.752.900.006a
SCWT-C (second)63.76 ± 22.3956.45 ± 9.931.440.157
SCWT-C error count0.46 ± 1.300.73 ± 2.33-0.560.581
STT-A practice (second)7.33 ± 3.277.09 ± 3.540.260.791
STT-A test (second)39.30 ± 12.5932.18 ± 8.802.300.025a
STT-B practice (second)13.18 ± 5.0410.59 ± 1.992.670.011a
STT-B test (second)85.21 ± 22.7970.96 ± 13.622.900.005a
CCST spontaneous classification4.36 ± 1.246.22 ± 1.02-5.830.000b
CCST classification of leads8.79 ± 1.537.86 ± 1.811.970.056
CCST total classification13.15 ± 2.0914.09 ± 2.07-1.630.107
Tower of Hanoi: Three discs moving steps12.31 ± 4.468.82 ± 2.383.720.001a
Time (second)40.50 ± 20.3523.36 ± 17.393.220.002a
Tower of Hanoi: Four discs moving steps23.97 ± 5.9922.09 ± 6.931.060.293
Time (second)82.03 ± 33.9362.04 ± 32.242.170.035a
Tower of Hanoi: Five discs moving steps52.42 ± 9.6742.23 ± 6.294.320.000b
Time (second)171.16 ± 58.92111.91 ± 29.404.810.000b
SpeechSurname and city alternate correct number26.81 ± 5.8534.18 ± 5.79-4.560.000b
Surname correct number13.22 ± 3.4717.77 ± 4.43-4.230.000b
City correct number13.59 ± 3.9116.41 ± 4.46-2.460.017a
Number of errors1.22 ± 2.150.91 ± 1.630.570.570
Repetition number2.91 ± 4.601.36 ± 2.171.650.106
Animal and fruit alternate correct number15.97 ± 3.4018.14 ± 3.06-2.410.020a
Number of errors0.21 ± 0.480.55 ± 0.91-1.570.127
Repetition number0.09 ± 0.290.41 ± 1.10-1.320.197
Changes in neuropsychological assessments after GCBT treatment

The Rey-O imitation time and recall score, AVLT-N1, AVLT-N2, AVLT-N3, AVLT-N4, AVLT-N5, AVLT-N6, number of correct SDMT, STT-A elapsed time, CCST, number of steps, and elapsed time of the four discs of the Tower of Hanoi were significantly different in the OCD group compared to the control group (Table 5).

Table 5 Changes in neuropsychological assessments before and after treatment.
Cognitive function
Test
Before GCBT
After GCBT
t
P value
Visuospatial abilityRey-O emulation time (second)160.73 ± 80.6787.56 ± 21.482.670.000b
Rey-O recall score15.26 ± 7.9721.00 ± 5.45-2.030.049
MemoryALVT-N14.12 ± 1.606.11 ± 1.62-3.310.002
ALVT-N25.94 ± 2.017.56 ± 1.94-2.150.038
ALVT-N37.00 ± 2.199.22 ± 1.64-2.820.007
ALVT-N45.73 ± 2.188.56 ± 1.67-3.600.001
ALVT-N55.30 ± 2.428.11 ± 1.69-3.260.002
ALVT-N65.45 ± 2.488.33 ± 1.73-3.260.002
AttentionSDMT correct number53.03 ± 12.4763.33 ± 12.07-2.210.033
Executive functionSTT-A time (second)39.30 ± 12.5929.89 ± 10.002.070.045
CCST total score13.15 ± 2.0915.22 ± 1.30-2.810.008
Time taken to move four discs (second)82.03 ± 33.9333.44 ± 11.296.860.000b
Changes in cognition-related networks after GCBT

After GCBT, a significant decrease in rs-FC within the DMN and DAN, and a weakened FC between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN was observed (Table 6, Figure 1).

Figure 1
Figure 1 Comparison of default mode network, dorsal attention network, frontoparietal network, and salience network intra- and inter-network functional connectivity after group cognitive behavioral therapy. DMN: Default mode network; DAN: Dorsal attention network; FPN: Frontoparietal network; SAN: Salience network; dmPFC: Dorsomedial prefrontal; vmPFC: Ventral medial prefrontal; PCC: Posterior cingulate cortex; Pcu: Precuneus; SFG: Superior frontal gyrus; IFG: Inferior frontal gyrus; FEF: Frontal eye field; SOG: Superior occipital gyrus; aIPL: Inferior parietal lobule; DLPFC: Dorsolateral prefrontal cortex; aINS: Anterior insula; dACC: Dorsal anterior cingulate cortex; L: Left; R: Right.
Table 6 Comparison of default mode network, dorsal attention network, frontoparietal network, and salience network intra- and inter-network functional connectivity before and after group cognitive-behavioral therapy.

Before-GCBT
After-GCBT
t
P value
Intra-network
    DMN
        dmPFC-vmPFC0.38 ± 0.240.22 ± 0.232.370.022
        vmPFC-LSFG0.22 ± 0.200.09 ± 0.202.180.035
        vmPFC-LIFG0.33 ± 0.240.13 ± 0.262.680.010
        Pcu-RIFG0.23 ± 0.220.06 ± 0.202.700.010
        LIFG-RIFG0.62 ± 0.250.43 ± 0.183.000.004
    DAN
        LFEF-LSOG0.50 ± 0.280.35 ± 0.242.040.047
        LFEF-RSOG0.37 ± 0.260.15 ± 0.253.010.003a
Inter-network
    DMN-DAN
        vmPFC-RFEF0.13 ± 0.22-0.04 ± 0.162.990.004a
        vmPFC-RSOG0.16 ± 0.220.04 ± 0.152.170.035
        RIFG-LFEF0.20 ± 0.260.04 ± 0.242.030.048
        RIFG-RFEF0.25 ± 0.270.10 ± 0.192.170.035
        RIFG-RSOG0.22 ± 0.210.08 ± 0.212.260.028
    DMN-FPN
        LSFG-LDLPFC0.03 ± 0.24-0.13 ± 0.232.260.029
        RIFG-RaIPL0.20 ± 0.26-0.01 ± 0.262.620.012
        RIFG-LDLPFC0.24 ± 0.28-0.00 ± 0.263.020.004
        RIFG-RDLPFC0.04 ± 0.21-0.19 ± 0.213.850.000b
        RIFG-RDLPFC0.04 ± 0.21-0.19 ± 0.213.850.000b
    DMN-SAN
        LSFG-dACC0.20 ± 0.250.03 ± 0.212.470.017
        LIFG-LaINS0.24 ± 0.240.11 ± 0.192.110.040
        RIFG-LaINS0.07 ± 0.170.34 ± 0.285.130.000b
        RIFG-RaINS0.34 ± 0.280.09 ± 0.193.530.001a
        RIFG-dACC0.34 ± 0.290.09 ± 0.263.130.003a
    DAN-SAN
        RFEF-RaINS0.34 ± 0.200.20 ± 0.132.910.005a
        LSOG-LaINS0.29 ± 0.230.12 ± 0.262.380.022
        LSOG-RaINS0.24 ± 0.200.11 ± 0.232.090.043
Analysis of altered FC of cognitive-related networks with neuropsychological assessments after GCBT

The results of the Pearson analyses suggested that reduced FC within the DMN was negatively correlated with Rey-O recall scores, number of correct responses on the SDMT, and CCST total scores after GCBT. This reduction was also positively correlated with the elapsed time of the STT-A test and the Tower of Hanoi. DAN rs-FC was positively correlated with the STT-A test elapsed time, whereas DMN-DAN rs-FC was negatively correlated with the Rey-O mimicry time and the three elapsed times of the Tower of Hanoi. The rs-FC of DMN-SAN was negatively correlated with Rey-O imitation time and positively correlated with STT-A test elapsed time, whereas the rs-FC of DMN-FPN was negatively correlated with AVLT-N1 and N4 scores (Table 7).

Table 7 Correlations between functional connectivity and neuropsychological assessments after group cognitive-behavioral therapy.
dmPFC-vmPFC
VmPFC-RSOG
LIFG-LaINS
RIFG-LDLPFC
vmPFC-LIFG
LFEF-LSOG
LSOG-LaINS
LIFG-RIFG
DMN
DMN-DAN
DMN-SAN
DMN-FPN
DMN
DAN
DAN-SAN
DMN
r
P value
r
P value
r
P value
r
P value
r
P value
r
P value
r
P value
r
P value
Rey-O emulation time-0.840.010-0.870.005a
Rey-O recall score-0.730.042a-0.860.006a
AVLT-N1-0.870.005a
AVLT-N4-0.790.019a
SDMT correct number-0.760.028a-0.770.025a
STT-A test0.700.0500.780.022a0.770.024a
CCST score-0.800.016a-0.760.024a
Tower of Hanoi: Three discs moving steps-0.730.040a-0.890.003a0.740.036a
Time taken to move the three discs (second)0.860.006a
Tower of Hanoi: Four discs moving steps0.770.024a
Time taken to move the four discs (second)0.850.007a
DISCUSSION

In the present study, we conducted a seed-based FC analysis assessing 12 specific seeds from four cognitive networks (i.e., DMN, SAN, FPN, and SAN) to investigate intrinsic connectivity alterations at baseline and after GCBT treatment in patients with OCD. We found decreased rs-FC within the DMN and DAN as well as between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN after GCBT, suggesting that abnormalities in the FC of these large-scale brain networks are implicated in the pathogenesis of OCD. Additionally, GCBT improved cognitive function in patients with OCD. We also observed a correlation between altered FC and neuropsychological assessments after GCBT, suggesting functional changes attributable to GCBT in patients with OCD.

We found significantly decreased rs-FC within the DMN and DAN as well as between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN in patients with OCD after GCBT. Previous studies have demonstrated that the DMN is overactivated in patients with OCD[28,29], which is consistent with our results showing reduced network connectivity after treatment. Del Casale et al[30] found enhanced FC among the DMN, FPN, and SAN; aberrant FC between the SAN and SAN-dCEN; and correlations between SAN-dCEN FC and trait anxiety levels in patients with OCD. Another study reported significantly reduced FC between the anterior mPFC and the anterior insular cortex (regions within the DMN and SAN) in patients with OCD compared to healthy controls. Notably, reduced DMN-SAN FC has been associated with an increased severity of OCD symptoms and decreased sustained attention[31]. Furthermore, patients with OCD exhibit altered FC between the FPN and DMN[32]. These studies focused on baseline internetwork connectivity without treatment; however, several other studies have reported alterations in the connectivity of brain networks after treatment. Following 4 weeks of high-intensity CBT, a significant increase in FC between the cerebellum and caudate nucleus as well as between the dorsolateral and ventral prefrontal cortex[33] was observed in patients with OCD. Increased FC is associated with symptomatic improvement in obsessions, suggesting that CBT mechanisms are connected to enhanced cross-network integration within the CCST. Another study suggested increased FC within the DAN and between the DAN and FPN after 12 weeks of escitalopram treatment[10]. While there is a lack of research on the brain network changes before and after GCBT, our findings help bridge this lack of understanding. Previous studies have also suggested that decreased FC within and between networks may be the underlying mechanism of the efficacy of GCBT[29,34].

In this study, we reported improvements in multiple domains of cognitive function, including visuospatial ability (Rey-O imitation time and recall score), memory (AVLT-N1, AVLT-N2, AVLT-N3, AVLT-N4, AVLT-N5, and AVLT-N6), attention (number of correct responses on the SDMT), and executive function (time elapsed in STT-A, CSC, total score, number of steps, and elapsed time in the four Hanoi Tower discs) after GCBT treatment. These findings are consistent with those of previous studies, suggesting that CBT can improve cognitive dysfunction in patients with OCD[23,25]. Time and group effects on non-verbal memory, switching trials, and self-supervised behaviors were observed in patients with OCD after CBT, and the group with greater symptom improvement performed better than the group with less symptom improvement in the immediate and delayed recall of complex images[23]. However, one study found no significant changes in the neurocognitive assessments before and after CBT in patients with OCD[35]. This discrepancy may be attributed to differences in sample characteristics of the studies (OCD vs comorbidities), strategy and setting of CBT, researchers, and different methods of statistical analysis. Combining most research findings, we recommend the use of GCBT to improve cognitive dysfunction in patients with OCD.

In addition, the correlation analysis between altered FC and neuropsychological assessments after GCBT in our study suggested that reduced FC within the DMN was significantly associated with visuospatial, attentional, and executive functions. Similarly, reduced FC within the DAN was associated with executive functions. Reductions in FCs between the DMN-DAN as well as DMN-SAN were significantly associated with visuospatial and executive functions, while reduced FC between the DMN-FPN was significantly associated with memory functions These findings are consistent with the findings of previous studies[30,36]. The dorsomedial PFC (dmPFC) and ventral medial PFC act as key hubs for internal and conceptual thoughts, especially in normalization of self-monitoring. Overactive dmPFC is associated with pathological self-focusing, and treatment may restore its balance with other nodes of the default network[37]. The observed reduction in FC within DMN may reflect enhanced cognitive control in patients with OCD following GCBT. This is consistent with previous findings by Guo et al[38], who reported reduced rs-FC within the core subsystem of DMN in patients with OCD. This reduction may represent a characteristic neurobiological feature of OCD and could potentially serve as a biomarker for obsession severity. Another previous study reported enhanced activation in the middle/precuneus cortex, thalamus, basal ganglia, and inferior frontal gyrus/frontal lobe cap in OCD, along with impairments in visuospatial ability, memory, attention, executive functioning, and speech. Improvements in executive function after treatment suggest that changes in the brain network connectivity during treatment contribute to improved neuropsychological performance[39]. Moreover, sustained attention is lower in patients with OCD than in healthy controls, and sustained attention deficits in OCD are negatively correlated with impaired function of the left superior frontal gyrus of the right mPFC within the DMN, and FC between the left mPFC and the right parietal lobe. This suggests that the interactions between the DMN and the FPN are closely related to attentional function[40]. The DMN, SAN, and CST loops in patients with OCD are associated with conversion task responses and executive function[41]. Further research replicated previous research on cognitive inflexibility in OCD and provided neural correlates associated with task-switching deficits in the condition, suggesting that impaired task-switching ability in OCD may be associated with an imbalance in brain activation between the dorsal and ventral frontal striatal circuits[42,43]. Taken together, these findings suggest that GCBT improves both the intra- and internetwork FC within cognitive networks and affects cognitive function in patients with OCD, which was verified by neuropsychological assessment. In addition, reductions in rs-FC within the DMN may represent a promising neuroimaging biomarker for predicting therapeutic response to GCBT in patients with OCD.

This paper has some limitations. First, the sample size of the present study was not large enough to examine the neuroimaging findings associated with the symptom dimensions. Second, this study did not use a blinded design. Third, follow-up data were not available for healthy controls, and future longitudinal studies with healthy controls are warranted. Fourth, the FC analyses were exploratory in nature, which limits the strength of the conclusions. Future replication with pre-registered hypotheses and rigorous statistical corrections is warranted. Finally, the study did not incorporate baseline FC analysis of cognitive-related networks between patients with OCD and healthy controls.

CONCLUSION

We reported significantly decreased rs-FC within the DMN and DAN, as well as reduced rs-FC between the DMN-DAN, DMN-FPN, DMN-SAN, and DAN-SAN. Additionally, we observed significant improvements in memory, executive function, attention, and visuospatial abilities. Our results further showed that reduced rs-FC of inter- and intra-cognitive networks was correlated with visuospatial ability, executive function, memory, and attention, suggesting that decreased rs-FC within the DMN and DAN, which is correlated with executive function post-treatment, can potentially serve as neuroimaging markers for predicting the therapeutic response to GCBT in patients with OCD.

ACKNOWLEDGEMENTS

The authors sincerely thank all the participants for their contributions to this study.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Psychiatry

Country of origin: China

Peer-review report’s classification

Scientific Quality: Grade B, Grade C

Novelty: Grade B, Grade C

Creativity or Innovation: Grade B, Grade B

Scientific Significance: Grade C, Grade C

P-Reviewer: Fluyau D; Khalifeh H S-Editor: Li L L-Editor: A P-Editor: Zhao S

References
1.  Del Casale A, Sorice S, Padovano A, Simmaco M, Ferracuti S, Lamis DA, Rapinesi C, Sani G, Girardi P, Kotzalidis GD, Pompili M. Psychopharmacological Treatment of Obsessive-Compulsive Disorder (OCD). Curr Neuropharmacol. 2019;17:710-736.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 47]  [Cited by in RCA: 98]  [Article Influence: 19.6]  [Reference Citation Analysis (0)]
2.  McKay D, Sookman D, Neziroglu F, Wilhelm S, Stein DJ, Kyrios M, Matthews K, Veale D. Efficacy of cognitive-behavioral therapy for obsessive-compulsive disorder. Psychiatry Res. 2015;225:236-246.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 120]  [Cited by in RCA: 101]  [Article Influence: 10.1]  [Reference Citation Analysis (0)]
3.  Reid JE, Laws KR, Drummond L, Vismara M, Grancini B, Mpavaenda D, Fineberg NA. Cognitive behavioural therapy with exposure and response prevention in the treatment of obsessive-compulsive disorder: A systematic review and meta-analysis of randomised controlled trials. Compr Psychiatry. 2021;106:152223.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 47]  [Cited by in RCA: 104]  [Article Influence: 26.0]  [Reference Citation Analysis (0)]
4.  Pozza A, Dèttore D. Drop-out and efficacy of group versus individual cognitive behavioural therapy: What works best for Obsessive-Compulsive Disorder? A systematic review and meta-analysis of direct comparisons. Psychiatry Res. 2017;258:24-36.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 34]  [Cited by in RCA: 38]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
5.  Braga DT, Manfro GG, Niederauer K, Cordioli AV. Full remission and relapse of obsessive-compulsive symptoms after cognitive-behavioral group therapy: a two-year follow-up. Braz J Psychiatry. 2010;32:164-168.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 19]  [Cited by in RCA: 20]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
6.  Elliott SJ, Marshall D, Morley K, Uphoff E, Kumar M, Meader N. Behavioural and cognitive behavioural therapy for obsessive compulsive disorder (OCD) in individuals with autism spectrum disorder (ASD). Cochrane Database Syst Rev. 2021;9:CD013173.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 4]  [Cited by in RCA: 9]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
7.  Reddy YCJ, Arumugham SS, Balachander S. Cognitive-behavioral and related therapies for obsessive-compulsive and related disorders. Curr Opin Psychiatry. 2021;34:467-476.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1]  [Cited by in RCA: 1]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
8.  Soriano-Mas C. Functional Brain Imaging and OCD. Curr Top Behav Neurosci. 2021;49:269-300.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5]  [Cited by in RCA: 11]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
9.  Luo L, Li Q, You W, Wang Y, Tang W, Li B, Yang Y, Sweeney JA, Li F, Gong Q. Altered brain functional network dynamics in obsessive-compulsive disorder. Hum Brain Mapp. 2021;42:2061-2076.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 46]  [Cited by in RCA: 43]  [Article Influence: 10.8]  [Reference Citation Analysis (0)]
10.  Bakay H, Ulasoglu-Yildiz C, Kurt E, Demiralp T, Tükel R. Hyperconnecitivity between dorsal attention and frontoparietal networks predicts treatment response in obsessive-compulsive disorder. Psychiatry Res Neuroimaging. 2024;337:111763.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 2]  [Reference Citation Analysis (0)]
11.  Uddin LQ, Betzel RF, Cohen JR, Damoiseaux JS, De Brigard F, Eickhoff SB, Fornito A, Gratton C, Gordon EM, Laird AR, Larson-Prior L, McIntosh AR, Nickerson LD, Pessoa L, Pinho AL, Poldrack RA, Razi A, Sadaghiani S, Shine JM, Yendiki A, Yeo BTT, Spreng RN. Controversies and progress on standardization of large-scale brain network nomenclature. Netw Neurosci. 2023;7:864-905.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 27]  [Cited by in RCA: 43]  [Article Influence: 21.5]  [Reference Citation Analysis (0)]
12.  Ciric R, Nomi JS, Uddin LQ, Satpute AB. Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks. Sci Rep. 2017;7:6537.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 35]  [Cited by in RCA: 38]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
13.  Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008;1124:1-38.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 6342]  [Cited by in RCA: 6969]  [Article Influence: 409.9]  [Reference Citation Analysis (0)]
14.  Vossel S, Geng JJ, Fink GR. Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist. 2014;20:150-159.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 700]  [Cited by in RCA: 949]  [Article Influence: 79.1]  [Reference Citation Analysis (0)]
15.  Marek S, Dosenbach NUF. The frontoparietal network: function, electrophysiology, and importance of individual precision mapping. Dialogues Clin Neurosci. 2018;20:133-140.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 273]  [Cited by in RCA: 479]  [Article Influence: 68.4]  [Reference Citation Analysis (0)]
16.  Schimmelpfennig J, Topczewski J, Zajkowski W, Jankowiak-Siuda K. The role of the salience network in cognitive and affective deficits. Front Hum Neurosci. 2023;17:1133367.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 49]  [Cited by in RCA: 105]  [Article Influence: 52.5]  [Reference Citation Analysis (0)]
17.  Li P, Yang X, Greenshaw AJ, Li S, Luo J, Han H, Liu J, Zhong Z, Guo Z, Xiong H, Yao S, Chen Y, Sun J, Li Z. The effects of cognitive behavioral therapy on resting-state functional brain network in drug-naive patients with obsessive-compulsive disorder. Brain Behav. 2018;8:e00963.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 30]  [Cited by in RCA: 29]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
18.  Reggente N, Moody TD, Morfini F, Sheen C, Rissman J, O'Neill J, Feusner JD. Multivariate resting-state functional connectivity predicts response to cognitive behavioral therapy in obsessive-compulsive disorder. Proc Natl Acad Sci U S A. 2018;115:2222-2227.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 93]  [Cited by in RCA: 91]  [Article Influence: 13.0]  [Reference Citation Analysis (0)]
19.  Norman LJ, Mannella KA, Yang H, Angstadt M, Abelson JL, Himle JA, Fitzgerald KD, Taylor SF. Treatment-Specific Associations Between Brain Activation and Symptom Reduction in OCD Following CBT: A Randomized fMRI Trial. Am J Psychiatry. 2021;178:39-47.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 19]  [Cited by in RCA: 31]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
20.  Huang FF, Wang PC, Yang XY, Luo J, Yang XJ, Li ZJ. Predicting responses to cognitive behavioral therapy in obsessive-compulsive disorder based on multilevel indices of rs-fMRI. J Affect Disord. 2023;323:345-353.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 6]  [Reference Citation Analysis (0)]
21.  Cao R, Yang X, Luo J, Wang P, Meng F, Xia M, He Y, Zhao T, Li Z. The effects of cognitive behavioral therapy on the whole brain structural connectome in unmedicated patients with obsessive-compulsive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2021;104:110037.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 11]  [Cited by in RCA: 18]  [Article Influence: 4.5]  [Reference Citation Analysis (0)]
22.  Robbins TW. Cognitive flexibility, OCD and the brain. Brain. 2022;145:814-815.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Reference Citation Analysis (0)]
23.  Katrin Kuelz A, Riemann D, Halsband U, Vielhaber K, Unterrainer J, Kordon A, Voderholzer U. Neuropsychological impairment in obsessive-compulsive disorder--improvement over the course of cognitive behavioral treatment. J Clin Exp Neuropsychol. 2006;28:1273-1287.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 44]  [Cited by in RCA: 44]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
24.  Vandborg SK, Hartmann TB, Bennedsen BE, Pedersen AD, Thomsen PH. Are there reliable changes in memory and executive functions after cognitive behavioural therapy in patients with obsessive-compulsive disorder? Cogn Neuropsychiatry. 2015;20:128-143.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 6]  [Cited by in RCA: 10]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
25.  Vandborg SK, Hartmann TB, Bennedsen BE, Pedersen AD, Thomsen PH. Can memory and executive functions in patients with obsessive-compulsive disorder predict outcome of cognitive behavioural therapy? Nord J Psychiatry. 2016;70:183-189.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5]  [Cited by in RCA: 8]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
26.  Manarte L, Andrade AR, do Rosário L, Sampaio D, Figueira ML, Morgado P, Sahakian BJ. Executive functions and insight in OCD: a comparative study. BMC Psychiatry. 2021;21:216.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 3]  [Cited by in RCA: 12]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
27.  Robbins TW, Vaghi MM, Banca P. Obsessive-Compulsive Disorder: Puzzles and Prospects. Neuron. 2019;102:27-47.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 203]  [Cited by in RCA: 305]  [Article Influence: 50.8]  [Reference Citation Analysis (0)]
28.  Gonçalves ÓF, Soares JM, Carvalho S, Leite J, Ganho-Ávila A, Fernandes-Gonçalves A, Pocinho F, Carracedo A, Sampaio A. Patterns of Default Mode Network Deactivation in Obsessive Compulsive Disorder. Sci Rep. 2017;7:44468.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 22]  [Cited by in RCA: 43]  [Article Influence: 5.4]  [Reference Citation Analysis (0)]
29.  Raposo-Lima C, Moreira P, Magalhães R, Ferreira S, Sousa N, Picó-Pérez M, Morgado P. Differential patterns of association between resting-state functional connectivity networks and stress in OCD patients. Prog Neuropsychopharmacol Biol Psychiatry. 2022;118:110563.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 7]  [Reference Citation Analysis (0)]
30.  Del Casale A, Rapinesi C, Kotzalidis GD, De Rossi P, Curto M, Janiri D, Criscuolo S, Alessi MC, Ferri VR, De Giorgi R, Sani G, Ferracuti S, Girardi P, Brugnoli R. Executive functions in obsessive-compulsive disorder: An activation likelihood estimate meta-analysis of fMRI studies. World J Biol Psychiatry. 2016;17:378-393.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 45]  [Cited by in RCA: 46]  [Article Influence: 5.1]  [Reference Citation Analysis (0)]
31.  Posner J, Song I, Lee S, Rodriguez CI, Moore H, Marsh R, Blair Simpson H. Increased functional connectivity between the default mode and salience networks in unmedicated adults with obsessive-compulsive disorder. Hum Brain Mapp. 2017;38:678-687.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 48]  [Cited by in RCA: 68]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
32.  Stern ER, Fitzgerald KD, Welsh RC, Abelson JL, Taylor SF. Resting-state functional connectivity between fronto-parietal and default mode networks in obsessive-compulsive disorder. PLoS One. 2012;7:e36356.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 167]  [Cited by in RCA: 189]  [Article Influence: 14.5]  [Reference Citation Analysis (0)]
33.  Moody TD, Morfini F, Cheng G, Sheen C, Tadayonnejad R, Reggente N, O'Neill J, Feusner JD. Mechanisms of cognitive-behavioral therapy for obsessive-compulsive disorder involve robust and extensive increases in brain network connectivity. Transl Psychiatry. 2017;7:e1230.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 33]  [Cited by in RCA: 47]  [Article Influence: 5.9]  [Reference Citation Analysis (0)]
34.  Yazdi-Ravandi S, Akhavanpour H, Shamsaei F, Matinnia N, Ahmadpanah M, Ghaleiha A, Khosrowabadi R. Differential pattern of brain functional connectome in obsessive-compulsive disorder versus healthy controls. EXCLI J. 2018;17:1090-1100.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in RCA: 4]  [Reference Citation Analysis (0)]
35.  Braga DT, Abramovitch A, Fontenelle LF, Ferrão YA, Gomes JB, Vivan AS, Ecker KK, Bortoncello CF, Mittelman A, Miguel EC, Trentini CM, Cordioli AV. Neuropsychological predictors of treatment response to cognitive behavioral group therapy in obsessive-compulsive disorder. Depress Anxiety. 2016;33:848-861.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 8]  [Cited by in RCA: 14]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
36.  Li H, Li B, Cao L, Jiang J, Chai S, Zhou H, Gao Y, Zhang L, Zhou Z, Hu X, Bao W, Biswal BB, Gong Q, Huang X. Dysregulated connectivity configuration of triple-network model in obsessive-compulsive disorder. Mol Psychiatry. 2025;.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 2]  [Reference Citation Analysis (0)]
37.  Koban L, Gianaros PJ, Kober H, Wager TD. The self in context: brain systems linking mental and physical health. Nat Rev Neurosci. 2021;22:309-322.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 35]  [Cited by in RCA: 104]  [Article Influence: 26.0]  [Reference Citation Analysis (0)]
38.  Guo Q, Zhu R, Zhou H, Ma Z, He Y, Wang D, Zhang X. Reduced resting-state functional connectivity of default mode network subsystems in patients with obsessive-compulsive disorder. J Affect Disord. 2025;369:1108-1114.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 3]  [Reference Citation Analysis (0)]
39.  Woon FL, Allen MD, Miller CH, Hedges DW. The functional magnetic resonance imaging-based verbal fluency test in obsessive-compulsive disorder. Neurocase. 2012;18:424-440.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 8]  [Cited by in RCA: 10]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
40.  Fan J, Gan J, Liu W, Zhong M, Liao H, Zhang H, Yi J, Chan RCK, Tan C, Zhu X. Resting-State Default Mode Network Related Functional Connectivity Is Associated With Sustained Attention Deficits in Schizophrenia and Obsessive-Compulsive Disorder. Front Behav Neurosci. 2018;12:319.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 20]  [Cited by in RCA: 32]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
41.  Remijnse PL, Nielen MM, van Balkom AJ, Hendriks GJ, Hoogendijk WJ, Uylings HB, Veltman DJ. Differential frontal-striatal and paralimbic activity during reversal learning in major depressive disorder and obsessive-compulsive disorder. Psychol Med. 2009;39:1503-1518.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 104]  [Cited by in RCA: 104]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
42.  Gu BM, Park JY, Kang DH, Lee SJ, Yoo SY, Jo HJ, Choi CH, Lee JM, Kwon JS. Neural correlates of cognitive inflexibility during task-switching in obsessive-compulsive disorder. Brain. 2008;131:155-164.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 144]  [Cited by in RCA: 180]  [Article Influence: 10.0]  [Reference Citation Analysis (0)]
43.  Vaghi MM, Vértes PE, Kitzbichler MG, Apergis-Schoute AM, van der Flier FE, Fineberg NA, Sule A, Zaman R, Voon V, Kundu P, Bullmore ET, Robbins TW. Specific Frontostriatal Circuits for Impaired Cognitive Flexibility and Goal-Directed Planning in Obsessive-Compulsive Disorder: Evidence From Resting-State Functional Connectivity. Biol Psychiatry. 2017;81:708-717.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 171]  [Cited by in RCA: 218]  [Article Influence: 27.3]  [Reference Citation Analysis (0)]