
==== Front
Neuroimage Clin
Neuroimage Clin
NeuroImage : Clinical
2213-1582
Elsevier

S2213-1582(24)00104-9
10.1016/j.nicl.2024.103665
103665
Regular Article
Association between clinical features and decreased degree centrality and variability in dynamic functional connectivity in the obsessive–compulsive disorder
Teng Changjun a1
Zhang Wei a1
Zhang Da b
Shi XiaoMeng a
Wu Xin a
Qiao Huifen a
Zhang Ning zn6360@126.com
a⁎
Hu Xiao xiao.hu@njmu.edu.cn
b⁎⁎
Guan Chengbin guanchb@njmu.edu.cn
a⁎
a Department of Medical Psychology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
b Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
⁎ Corresponding author at: Department of Medical Psychology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China. zn6360@126.comguanchb@njmu.edu.cn
⁎⁎ Corresponding author at: Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China. xiao.hu@njmu.edu.cn
1 Changjun Teng and Wei Zhang contributed equally to this work.

07 9 2024
2024
07 9 2024
44 1036653 7 2024
28 8 2024
29 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Highlights

• Obsessive-compulsive disorder (OCD) was associated with decreased degree centrality (DC) in the bilateral thalamus, bilateral precuneus, and bilateral cuneus.

• The OCD patients showed decreased dynamic functional connectivity (dFC) variability between the left thalamus and left cuneus and right lingual gyrus, between bilateral cuneus and bilateral postcentral gyrus.

• OCD patients showed a nominal negative correlation with the average DC value of the left thalamus as well as the right thalamus, and a nominal positive correlation between the illness duration and variability in dFC between the left cuneus and left postcentral gyrus.

Neuroimaging studies have indicated widespread brain structural and functional disruptions in patients with obsessive–compulsive disorder (OCD). However, the underlying mechanism of these changes remains unclear. A total of 45 patients with OCD and 42 healthy controls (HC) were enrolled. The study investigated local degree centrality (DC) abnormalities and employed abnormal regions of DC as seeds to investigate variability in dynamic functional connectivity (dFC) in the whole brain using a sliding window approach to analyze resting-state functional magnetic resonance imaging. The relationship between abnormal DC and dFC as well as the clinical features of OCD were examined using correlation analysis. Our findings suggested decreased DC in the bilateral thalamus, bilateral precuneus, and bilateral cuneus in OCD patients and a nominally negative correlation between the DC value in the thalamus and illness severity measured using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). In addition, seed-based dFC analysis showed that compared to measurements in the HC, the patients had decreased dFC variability between the left thalamus and the left cuneus and right lingual gyrus, and between the bilateral cuneus and bilateral postcentral gyrus, and a nominally positive correlation between the duration of illness and dFC variability between the left cuneus and left postcentral gyrus. These results indicated that OCD patients had decreased hub importance in the bilateral thalamus and cuneus throughout the entire brain. This reduction was associated with impaired coupling with dynamic function in the visual cortex and sensorimotor network and provided novel insights into the neurophysiological mechanisms underlying OCD.

Keywords

Obsessive-compulsive disorder
Resting-state
Degree centrality
Dynamic functional connectivity
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pmc1 Introduction

Obsessive-compulsive disorder (OCD) is a prevalent psychiatric disorder marked by the recurrence of intrusive thoughts and compulsive behaviors. OCD affects 2–3 % of people with severe mental distress, causing major disruption to daily life, work, and social activity (Stein et al., 2019). However, the pathological mechanisms for these changes remain unclear. Functional magnetic resonance imaging (fMRI) may assist in further unraveling the potential mechanisms underlying this psychiatric disorder by identifying neuroimaging biomarkers and overcoming the difficulty of diagnosing the disorder by relying on self-reported symptoms. Findings from fMRI studies can significantly improve our understanding of neural circuit abnormalities in psychiatric disorders, and facilitate the identification of reliable neuroimaging biomarkers for precise diagnosis, and subtype classification, and even may inform personalized treatment strategies (Luo et al., 2022).

Studies employing multimodal neuroimaging technologies have investigated the neurobiological mechanism underlying OCD, and have identified structural and functional abnormalities in several brain regions, including the dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), lateral temporal cortex, precuneus/cuneus, insula, thalamus, and striatum regions, as well as the precentral and postcentral gyrus (Liu et al., 2022, Yang et al., 2024). For example, a multimodal meta-analysis showed increased activity in the bilateral inferior frontal gyrus and bilateral mPFC/ACC as well as decreased activity in the bilateral paracentral lobule, bilateral cerebellum, left caudate nucleus, left inferior parietal gyrus and right precuneus cortex (Yang et al., 2024). In contrast, other meta-analyses reported contradictory (Li et al., 2023) or discrepant findings (Yu et al., 2022). The cortico-striato-thalamo-cortical (CSTC) circuit has long been considered a key model for the neurobiological mechanism of OCD (Gao et al., 2019, Shephard et al., 2022). Aberrant activity within CSTC circuits has been linked to impaired cognitive flexibility, visuospatial memory, response inhibition, and goal-directed behavior in patients with OCD (Gonçalves et al., 2016, Jalal et al., 2023). Large-scale brain network research has also suggested altered functional communications within and between intrinsic networks in OCD, including the cognitive executive network (CEN), default mode network (DMN), salience network (SN), and sensorimotor network (SMN) (Liu et al., 2022, Luo et al., 2021). However, a conclusive statement about the affected brain regions or circuits in OCD has not been achieved due to issues such as clinical heterogeneity and methodology. Therefore, further research is required.

Degree centrality (DC) is a graph theory-based local metric of the number of direct connections for a target node and indicates the relative importance and influence of nodes in the efficient integration and transmission of communication in the brain network. It is also a data-driven approach (Zuo et al., 2012). DC has been used to explore the neuromechanism of many mental disorders, such as major depressive disorder (MDD) (Yang et al., 2023), and panic disorder (Liu and Lai, 2022). Decreased or increased DC in the cortex-limbic areas have been found in OCD patients (Göttlich et al., 2015, Li et al., 2018, Xu et al., 2023), while some other studies have reported different results in patients with OCD (Luo et al., 2021, , 2023). Although these findings were inconclusive, they underscored the novelty and importance of graph modeling, showcasing its capacity to advance our understanding of brain alterations associated with OCD (Luo et al., 2023). Further research is therefore needed to determine the neuromechanism of OCD and identify clinically relevant abnormalities in brain nodes, thereby assisting in diagnosis and therapy by controlling confounding factors such as drugs, chronic illness, and recurrent features.

Previous studies on functional connectivity (FC) assumed a static brain and did not consider the crucial dynamics of brain activity that are important for cognitive, affective, and behavioral adaptability. Dynamic FC (dFC) reflects the temporal dynamic properties of brain region interactions, thereby providing deeper insight into the fundamental mechanisms of brain function (Zhao et al., 2022). Some researchers considered dFC as a potentially sensitive biomarker for neuropsychiatric disorders (Kundu et al., 2021, Peng et al., 2021). For example, functional alterations in dFC between the left superior temporal gyrus and the left cerebellum and left thalamus, and also between the right supplementary motor area (SMA) and right DLPFC and left precuneus were reported in OCD patients (Ding et al., 2023). A significant increase in the number of transitions of intrinsic connection networks, encompassing the CEN, DMN, and SN, was observed in individuals with OCD and this increase was positively correlated with the severity of the disease (Liu et al., 2021b). Although these findings have been confirmed (Luo et al., 2021), another study has shown that OCD patients spent more time in a more frequent, segregated state characterized by lower between-network and within-network connections, but no difference in the number of transitions (Peng et al., 2021). These findings indicated that OCD patients had abnormalities in dFC between different regions, but no consistent conclusion was reached.

Initial research predominantly focused on the static functional connections in OCD, neglecting dFC. Conversely, the present investigation employed a dual approach, combining local DC analysis with seed-based dFC analysis during resting-state fMRI. By identifying key nodes exhibiting altered DC values across the whole brain, we subsequently assessed whether these regions showed divergent dFC patterns in individuals with OCD. We proposed the following hypotheses: Firstly, the OCD patients would exhibit reduced DC in certain pivotal cortical and subcortical areas, suggesting a disruption in the integration and transmission of information. Secondly, this reduction in DC would correlate with irregular dFC variability within the cortical regions. We further theorized that the aberrant DC coupling with dFC might jointly contribute to the neurological basis of OCD, potentially linking to the clinical features.

2 Methods

2.1 Participants

Ethical approval for this study, encompassing all associated methodologies, was granted by the Research Ethics Committee of Nanjing Brain Hospital, affiliated with Nanjing Medical University, with the research carried out by the principles outlined in the Helsinki Declaration. Informed consent forms were provided and signed by all the participants before the commencement of the experiment.

A total of 45 patients diagnosed with a first-episode of OCD were recruited from the inpatient and outpatient departments of the Medical Psychology Department at the Nanjing Brain Hospital. The diagnosis of OCD was confirmed by a consensus of two psychiatrists using the criteria outlined in the DSM-5. The severity of the OCD symptoms, anxiety, and depression was assessed using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS), Hamilton Anxiety Rating Scale (HARS), and Hamilton Depression Rating Scale (HDRS), respectively. Inclusion criteria for the patients included a total score of Y-BOCS≥16 and a score of HDRS score ≤ 18. The enrollment criteria of the patients were as follows: (1) no psychiatric comorbidities or psychotic symptoms; (2) no history of aggression or suicidal tendencies; (3) not be on antipsychotic or antidepressant medication; (4) no visible cognitive or communication disabilities; (5) no family history of psychiatric disorders in first-degree relatives; and (6) a BMI within the normal range. Of the OCD patients, 36 were first-episode treatment-naïve, 7 had intermittently taken antidepressant drugs in the previous 6 months, while 2 had taken antidepressant drugs irregularly about 1 year ago. None of the patients had obtained any relief from their medication.

Forty-two healthy controls (HC), matched for age, gender, and educational status, were recruited through poster advertisements and recommendations from nearby communities. All these participants were Han Chinese, aged 18 to 45 years, and right-handed. Exclusion criteria for the HC included: (1) the presence of any serious somatic diseases or organic brain diseases; (2) a history of substance abuse, including alcohol or drugs; (3) a contraindication to MRI scanning; and (4) pregnancy or breastfeeding status.

2.2 Imaging scanning and preprocessing

Imaging data were acquired using a 3.0 Tesla GE MRI scanner at the Nanjing Brain Hospital affiliated with Nanjing Medical University. To minimize noise and head motion, the participants wore earplugs and were secured with a standard restraining foam pad. The participants were instructed to remain awake, relaxed, and with their eyes closed throughout the scanning session. T1-weighted structural images were acquired by a 3D magnetization-prepared rapid acquisition gradient echo (MPRAGE) sequence, with the following parameters: repetition/echo Time (TR/TE) = 8200 ms/3.2 ms, flip angle = 9°, 200 slices, field of view (FOV) = 240 mm x 240 mm; matrix = 256 mm x 256 mm, slice thickness /gap = 1 mm/0 mm. Resting-state fMRI images were obtained using a gradient recalled echo-planar imaging (GRE-EPI) sequence, with the following parameters: TR/TE=2000 ms/30 ms, flip angle = 90°, FOV=240 mm × 240 mm, matrix = 64 × 64, thickness/gap = 4.0 mm/4.0 mm, 40 slices, time points = 240.

The original image preprocessing was carried out using the DPABI package (https://rfmri.org/DPABI). After removing the initial 10 volumes for each participant, the data with a maximal displacement over 2.5 mm or maximal rotation over 2.5° were discarded following the correction for slice timing and head motion. Then, the images were spatially normalized to the Montreal Neurological Institute (MNI) space by applying a new segment to the structural images and then resampled to a voxel size of 3 mm x 3 mm x 3 mm. A 6-mm full width at half-maximum (FWHM) Gaussian kernel was performed for smoothing, with the covariates Friston-24 parameter, cerebrospinal fluid, and white matter removed. At last, the data were linearly detrended and filtered to 0.01–0.08 Hz.

2.3 Degree centrality analysis

DC was used to calculate the number of direct connections for a given node and other nodes based on graph theory, with a Pearson’s correlation coefficient of 2.5 above the threshold indicating a direct connection. The analysis was performed using the DPABI toolbox. The DC values were calculated by summing the number of positive functional connections between each voxel and all other voxels within the brain network. The individual level DC was then normalized to a Z-score map based on the mean and standard deviation, followed by spatial smoothing with a 6 mm FWHM Gaussian kernel.

2.4 Seed-based dynamic functional connectivity analysis

Dynamic FC was extracted for each participant using a sliding time-window approach implemented in the DynamicBC toolkit (https://www.restfmri.net/forum/DynamicBC). To examine the characteristics of dFC, the sliding window length was set to 30TR (60 s) with a shifting step of 3TR (6 s), which generated a total of 67 windows. For FC mapping, the FC values between the thalamus or cuneus and all other voxels within the whole-brain mask were computed for each window. This process produced a set of sliding window FC maps of each subject. The temporal variability of each FC value was quantified by calculating its variance over time. We used Fisher’s Z score transformation to convert the correlation FC maps and improved the normality by subtracting the mean values divided by the standard deviation of all values within the brain mask. The dFC variability, indicative of FC value fluctuations over time, was determined by assessing the standard deviation of the dFC maps for each individual across the sliding time windows (Ding et al., 2023, Zhou et al., 2021). To evaluate the consistency and validity of the dFC analysis at different window sizes relative to the 30TR window used, we also examined the data using a 20TR (40 s) window size with a shifting step of 1TR (2 s) to repeat the above analyses. Findings using the 30TR window were well replicated in this validation analysis (details in Supplementary Material).

2.5 Statistical analysis

The demographic data, including sex distraction, education years, age, and scores on the HDRS, HARS, and Y-BOCS, were analyzed using SPSS 21.0 and included sex distraction, education years, age, and HDRS, HARS, and Y-BOCS scores. A two-sample t-test was performed to assess the differences between the OCD and HC groups. Analyses of differences in DC and dFC between the OCD and HC groups were performed using the DPABI toolbox, with a two-sample t-test used to evaluate the significance. Between-group differences were considered significant at a voxel level of p＜0.01 with the Gaussian random field (GRF) corrected for multiple comparisons at a cluster level of p＜0.05. To explore clinical correlations in OCD patients, Pearson correlation analysis was performed between Y-BOCS, HARS scores, duration, and brain regions. In these exploratory analyses, we set p＜0.05 as indicating nominal significance and interpreted them as suggestive or descriptive rather than conclusive.

3 Results

3.1 Demographic and clinical variables

Table 1 presents a comparative analysis of demographic and clinical characteristics between the OCD and HC groups. There was no significant difference in sex distribution, education years, age, or HDRS scores between the two groups. However, the scores on Y-BOCS and HARS of the OCD patients were significantly higher than those of the HCs.Table 1 Demographic data and clinical information of patients with OCD and healthy controls.

Variable	OCD(n = 45)	HC(N=42)	t/χ2	p	
Age (years), mean ± SDa	26.400 ± 5.132	24.976 ± 5.506	1.248	0.215	
Sex, males (%) b	23（51.11 %）	21（50.00 %)	0.011	0.918	
Education (years)a	15.067 ± 2.178	15.048 ± 1.975	0.043	0.966	
Duration of illness(months)	63.867 ± 58.680	NA	NA	NA	
Y-BOCS	28.311 ± 6.007	NA	NA	NA	
HDRS	11.000 ± 2.892	NA	NA	NA	
HARS	12.089 ± 3.189	NA	NA	NA	
Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; SD: standard deviations; Y-BOCS: Yale-Brown Obsessive Compulsive Scale; HDRS: Hamilton Depression Rating Scale; HARS: Hamilton Anxiety Rating Scale; aBoth t and p-value were obtained by two-sample t-tests; b Both χ2 and p-value were obtained by Chi square test; * Statistically significant.

3.2 Degree centrality analysis

The OCD patients had significantly decreased DC values in the bilateral thalamus compared to those measured in the HCs, with the peak coordinate located in the left thalamus (MNI: −9, −24, 12; voxels:132; t = -4.212; p＜0.01, GRF corrected), and the bilateral precuneus and bilateral cuneus (extending to the bilateral lingual gyrus) with the peak coordinate located in the right cuneus (MNI: 18, −75, 18; voxels:734; t = -5.736; p＜0.01, GRF corrected) (Fig. 1).Fig. 1 Degree centrality (DC) analysis between OCD and HC. Brain regions with significant differences in OCD. The area in a cold color tone represents a significantly decreased DC value. The color bar indicates the t values from two-sample t-tests (the level of statistical significance was set at voxel p＜0.01 with GRF correction for cluster p＜0.05.) Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; DC: Degree centrality; GRF: Gaussian random field.

3.3 Seed-based dynamic functional connectivity analysis

For the left thalamus seed, in comparison to the HCs, the OCD cohort exhibited significantly decreased dFC variability in the left cuneus (MNI:-9, −81, 24; voxels:162; t = -4.046) and right lingual gyrus (MNI:18, −78, 0; voxels:127; t = -4.031) (Fig. 2) (p＜0.01, GRF corrected). For the right thalamus seed, no remarked difference in variability in dFC between the OCD and HC groups was observed. For the left cuneus seed, the OCD group exhibited a significant reduction in dFC variability in the bilateral postcentral gyrus (left: MNI: −42, −39, 60; voxels:168; t = -4.328; right: MNI:36, −39, 60; voxels:89; t = -3.783) (Fig. 3) (p＜0.01, GRF corrected). Similarly, for the right cuneus seed, the OCD group also presented with a significant decrease in dFC variability in the bilateral postcentral gyrus (left: MNI: −36, −39, 63; voxels:366; t = -4.811; right: MNI:33, −45, 63; voxels:212; t = -4.606) (Fig. 4) (p＜0.01, GRF corrected).Fig. 2 Group differences in dFC variability of left thalamus between OCD and HC. Brain regions with a significant difference in OCD from two-sample t-tests (p＜0.01, GRF correction) Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; dFC: dynamic functional connectivity; THA.L: left thalamus; CUN.L: left Cuneus; LING.R: right lingual gyrus; GRF: Gaussian random field.

Fig. 3 Group differences in dFC variability of left cuneus between OCD and HC. Brain regions with a significant difference in OCD from two-sample t-tests (p＜0.01, GRF correction) Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; dFC: dynamic functional connectivity; CUN.L: left Cuneus; PoCG.L: left postcentral gyrus; PoCG.R: right postcentral gyrus; GRF: Gaussian random field.

Fig. 4 Group differences in dFC variability of right cuneus between OCD and HC. Brain regions with a significant difference in OCD from two-sample t-tests (p＜0.01, GRF correction). Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; dFC: dynamic functional connectivity; CUN.R: right cuneus; PoCG.L: left postcentral gyrus; PoCG.R: right postcentral gyrus; GRF: Gaussian random field.

3.4 Correlation analysis

Brain regions exhibiting significant differences in DC and dFC variability were further examined for potential correlations with clinical variables at a nominal statistical significance level of p＜0.05. Correlational analyses revealed a nominal negative correlation with the average DC value of the left thalamus (r = -0.377, p = 0.011, Fig. 5 A), as well as the right thalamus (r = -0.297, p = 0.048, Fig. 5 B). We also identified a nominal positive correlation between the illness duration and variability in dFC between the left cuneus and left postcentral gyrus (r = 0.363, p = 0.014, Fig. 5 C).Fig. 5 Brain regions showing abnormal node DC and dFC variability in brain functional networks and their relationships with clinical variables in OCD patients. (A) negative correlations between the DC value of the left thalamus and Y-BOCS score in OCD patients; (B) negative correlations between the DC value of the right thalamus and Y-BOCS score in OCD patients; (C) positive correlations between dFC variability between the left cuneus and the left postcentral gyrus and the duration of the illness. The threshold was set at a significance level of p＜0.05. Note: OCD: Obsessive-Compulsive disorder; HC: Healthy controls; DC: degree centrality; dFC: dynamic functional connectivity; Y-BOCS: Yale-Brown Obsessive Compulsive Scale; THA.L: left thalamus; THA.R: right thalamus; CUN.L left cuneus; PoCG.L: left postcentral gyrus.

4 Discussion

This study in patients with OCD showed decreased DC in the bilateral thalamus, bilateral precuneus, and bilateral cuneus, and reduced dFC variability between the left thalamus and left cuneus, left thalamus and right lingual gyrus, left cuneus and bilateral postcentral gyrus, and right cuneus and bilateral postcentral gyrus. We also observed that these abnormal functional activities were nominally associated with clinical features. Our results highlight the presence of functional alterations in critical neural hubs and their dynamic interactions during rest in OCD patients, findings that may serve as a neural basis for OCD symptoms.

Decreased DC in the bilateral thalamus in OCD patients was a major finding in this study. The thalamus, recognized as a pivotal relay station nucleus, integrates sensory inputs from the periphery and relays them to the cortex, thereby playing a critical role in perceptual and cognitive processing, motor coordination, and executive functions (Li et al., 2019, Weeland et al., 2022). It has been implicated in the pathophysiology of OCD, with some studies suggesting its involvement in behavioral inhibition and compulsive behavior (Gonçalves et al., 2011). Several reviews and meta-analyses have reported an increased grey matter volume in OCD patients (Eng et al., 2015, Yang et al., 2024), as well as increased thalamic activity (Picó-Pérez et al., 2020, Yang et al., 2024). Elevated thalamic metabolism has correlated with the severity of symptoms in OCD (Perani et al., 1995). Furthermore, studies utilizing diverse neuroimaging metrics have revealed that diminished glutamatergic signaling in the right thalamus inversely correlated with compulsive behaviors (Zhu et al., 2015), and decreased regional homogeneity (ReHo) of the thalamus was associated with disordered thinking, including aggressive/checking and unusual perceptual symptoms (Xia et al., 2020).

Our study also showed decreased DC in the bilateral precuneus and cuneus cortex, extending to the bilateral lingual gyrus, in proximity to the temporo-parieto-occipital junction. This observation is in concordance with prior research (Lv et al., 2021). Previous studies have reported a decreased grey matter volume in the precuneus of OCD patients (van den Heuvel et al., 2009; Yang et al., 2024) and increased activity (Jones and Bhattacharya, 2013; Tang et al., 2023), although a recent meta-analysis indicated a decreased activity (Yang et al., 2024). Additionally, a reduced ALFF was noted in the cuneus, lingual, postcentral, and precentral gyrus, yet these alterations did not correlate with symptom severity, suggesting that such changes in ALFF could serve as potential biomarkers for OCD (Zhao et al., 2017). Similar findings were reported by Niu et al. (2022), while Liu et al. (2021a) proposed that dynamic ALFF in the cuneus and middle occipital cortex could distinguish OCD patients from HCs. Ma et al. (2021) demonstrated an increased ALFF in the lingual gyrus following cognitive-copying therapy. Our findings align with these previous studies. The decreased DC in the precuneus, a region implicated in self-consciousness and self-referential processing, may be linked to an impaired ability to self-distract from obsessive and distressing thoughts in OCD patients. This reduction has been hypothesized to underlie the neural mechanism of thought-action fusion in OCD (Jones and Bhattacharya, 2013). Pieces of evidence also suggest that the cuneus and lingual gyrus, as components of the visual cortex connected to the thalamus, are involved in visual-spatial processing, face and object recognition, and attention, affective, and perceptual processing, all of which are known to be disrupted or altered in OCD (Ljungberg et al., 2017; Stern et al., 2017). These alterations can influence behaviors such as excessive visual attention to local details and a tendency to focus on minute details in the environment. Furthermore, our study revealed a reduced variability in dFC between the left thalamus and left cuneus and right lingual gyrus, which diverges from previous studies. A recent systematic review and meta-analysis indicated that OCD patients exhibit hypoconnectivity between the thalamus and striatum (mainly caudate and putamen) and hyperconnectivity between the cuneus and nucleus accumbens (Liu et al., 2022). Another study reported reduced connectivity between the visual network and DMN and SN, with connectivity between the lateral occipital cortex and lateral parietal cortex (associated with the DMN) positively correlating with symptom severity (Geffen et al., 2022). However, these discrepancies may be attributed to subject heterogeneity and variations in neuroimaging methodologies.

Synthesizing our findings, we infer that the observed decreased DC within the thalamus and occipital cortex, coupled with diminished dFC variability between these regions, may correlate with deficits in the integrative processing of cognitive, behavioral, and visual information. Such deficits are hypothesized to be instrumental in the manifestation of obsessive–compulsive symptoms and associated behaviors. The observed nominally negative correlation with symptom severity in OCD patients indicates that increased illness severity may exacerbate the efficiency of the information integration mechanisms.

The postcentral gyrus, a component of the SMN, involves the synthesis of sensory information and the regulation of motor behaviors (Kropf et al., 2019). Our study, in alignment with several others, has revealed a reduction in activity (Gan et al., 2023, Li et al., 2023, Norman et al., 2016) and grey matter volume (Yang et al., 2024) within the postcentral gyrus of OCD patients. However, it is noteworthy that these findings are not universally consistent, with some studies reporting opposing outcomes (Park et al., 2023; Tang et al., 2016). Compulsive behaviors in OCD are not only triggered by emotional states of fear or anxiety (Shephard et al., 2021) but also by sensory phenomena, such as aversive tactile sensations or perception disturbances, often described as “not-just-right” experiences (Ferrão et al., 2012, Shephard et al., 2021). The postcentral gyrus has been implicated in the neural substrates that underpin compulsive behaviors, with its abnormal activity correlating with these behaviors (Brown et al., 2019, Shephard et al., 2021). Our research further identified a nominally positive correlation between the illness duration and the variability of dFC between the left cuneus and left postcentral gyrus, suggesting a link between the chronicity of OCD and the fluctuating activation patterns within these brain regions. We speculate that deficits in information integration and compromised visual attention bias may contribute to the progression of perceptual dysfunction in OCD patients. As the disorder progresses, the spectrum of obsessive symptoms broadens, potentially leading to the establishment of entrenched compulsive behavioral habits (Shephard et al., 2021).

Some of the results of our study were inconsistent with those of previous studies. Previous studies in OCD patients reported decreased DC in the bilateral amygdala and bilateral hippocampus (Göttlich et al., 2015), left SMA (Li et al., 2022), and right superior temporal gyrus (Xu et al., 2023), and increased DC in the right middle frontal gyrus (Göttlich et al., 2015) and right SMA (Li et al., 2018). Luo et al. (2021) showed that the decreased dynamics of DC in the precuneus and right middle frontal gyrus correlated negatively with the duration of the illness and the severity of obsession symptoms in OCD patients, whereas Liu et al., (2021a) noted a negative correlation between illness duration and dynamic ALFF in the right inferior parietal lobule. The inconsistencies observed in our study may stem from a multitude of factors, including the heterogeneity of the participant cohort, variations in sample size, and different methodologies.

It is noteworthy that the thalamus, precuneus, cuneus and lingual gyrus are integral components of the DMN (Chen et al., 2015, Xu et al., 2022), which is implicated in a spectrum of executive functions such as cognitive control, self-referential thought, and the monitoring of the internal and external environments, with communicating with SN and CEN to regulate self-monitoring and goal-directed behavior (Smallwood et al., 2021, Weber et al., 2022). Larger-scale brain network studies in OCD have revealed aberrations in the connectivity patterns between the DMN and other intrinsic networks, including the SMN (Stern et al., 2022, Wu et al., 2022), the CSTC circuit (Hou et al., 2013), and the CEN (de Vries et al., 2019). Empirical evidence suggests that heightened activity within the SMN and the DMN is correlated with heightened error signals and self-referential error processing (Grützmann et al., 2021). Taking all these findings into consideration, our study’s findings point towards impaired visual processing and diminished cognitive information integration and transmission efficiency as potential neural substrates of OCD at the network-level, which may collectively contribute to the development of obsessive thoughts and compulsive behaviors. The observed correlations between clinical metrics and neuroimaging features in our OCD cohort did not survive after the multiple comparisons, possibly attributable to factors such as the modest sample size, a predominantly youthful demographic, and brief illness duration. The reliability of univariate correlation analyses, particularly in small samples, has been increasingly questioned (Vieira et al., 2024). In response, multivariate correlation analyses that map the interplay between the brain and behavior are gaining traction to mitigate bias risks (Vieira et al., 2024), especially with the emergence of large-scale, publicly accessible imaging datasets in psychiatry research that include comprehensive behavioral assessments. Canonical correlation analysis (CCA) and partial least squares (PLS) methods are the most popular techniques (Vieira et al., 2024), and have been successfully applied in MDD patients (Mihalik et al., 2020, Li et al., 2024). To identify the most salient features and delineate the nature and magnitude of the associations, future research endeavors should adopt an integrative multivariate modeling approach to assess the covariation between functional brain markers and clinical variables holistically, encompassing symptoms, cognitive profiles, and clinical history.

This study had some limitations. Firstly, the modest sample size constrained our capacity to stratify the patient cohort based on symptomatology or other clinical characteristics, thereby limiting our statistical power to detect more subtle effects which could potentially impact the robustness of our findings. Secondly, there is no consensus on the optimal length of slide windows using dynamic functional connectivity, which may have harmed the results. Thirdly, while all participants were medication-naïve during the study period, the influence of prior antidepressant use by nine patients cannot be entirely discounted, as medication is known to affect brain activity and connectivity. Fourthly, DC highlights its local metric but ignores the global metric (Zuo et al., 2012), such as eigenvector centrality (EC), and the most suitable metrics for brain network analysis remain a subject of ongoing debate (Bullmore and Sporns, 2009). Both DC and EC have specific limitations in their application (Eijlers et al., 2019, , 2023), and there is a growing interest in EC (You et al.,2022). Future research is warranted to explore the concordance between DC and EC and to assess the comprehensive functional integrity of brain connectivity at both local and global levels. Lastly, the patient’s age distribution in our study was skewed toward younger individuals, leading to a shorter disease duration compared to a normally distributed population. These factors may have exerted confounding influences on our outcomes, and thus, the findings should be interpreted with due consideration of these limitations.

5 Conclusion

The current study integrated DC and dFC analyses to examine functional alterations in patients with OCD. The study showed reduced DC in the bilateral thalamus and cuneus across the entire brain, decreased dFC variability between the thalamus and visual processing cortex, and also the DMN and SMN in patients with OCD. These results offer novel insights into the neurophysiological mechanisms underlying OCD and underscore the critical involvement of the thalamus, visual processing cortex, and sensorimotor networks in this disorder.

6 Statement of ethics

This research was approved by the Medical Research Ethics Committee of The Affiliated Brain Hospital of Nanjing Medical University in accordance with the World Medical Association Declaration of Helsinki. Written informed consent of the patients was obtained from their legally authorizedrepresentative, while the control subjects provided written, informed consent themself after totally understanding the purpose of our study.

Funding support

This work was supported by National Science Foundation of China (NSFC) (No.81701671), Health Science and Technology Development of Nanjing (YKK22134, YKK23145); Young Talents Project of Nanjing Brain Hospital(23‑25‑1R8‑1).

CRediT authorship contribution statement

Changjun Teng: Writing – original draft, Resources, Project administration, Funding acquisition, Formal analysis, Data curation, Conceptualization. Wei Zhang: Writing – original draft, Resources, Methodology, Formal analysis, Data curation. Da Zhang: Writing – review & editing, Supervision, Methodology, Conceptualization. XiaoMeng Shi: Resources, Formal analysis, Data curation. Xin Wu: Resources, Formal analysis, Data curation. Huifen Qiao: Resources, Data curation. Ning Zhang: Writing – review & editing, Supervision, Methodology, Conceptualization. Xiao Hu: Writing – review & editing, Supervision, Resources, Methodology, Funding acquisition, Data curation. Chengbin Guan: Writing – review & editing, Supervision, Resources, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Data availability

Data will be made available on request.

Acknowledgement

The authors are grateful to all the patients and the healthy volunteers for their participation and cooperation in our study. We sincerely thank Zonghong Li for assistance with fMRI data collection (Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University). The authors would like to express their gratitude to EditSprings (https://www.editsprings.com) for the expert linguistic services provided.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.nicl.2024.103665.
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