Psychiatry Research: Neuroimaging最新文献

{"title":"Correlation study between the microstructural abnormalities of medial prefrontal cortex and white matter hyperintensities with mild cognitive impairment patients: A diffusion kurtosis imaging study","authors":"Dongtao Liu ,&nbsp;Xiangke Ma ,&nbsp;Xinhui Li ,&nbsp;Kun Li ,&nbsp;Qiao Bu ,&nbsp;Lichun Zhou","doi":"10.1016/j.pscychresns.2025.111958","DOIUrl":"10.1016/j.pscychresns.2025.111958","url":null,"abstract":"<div><h3>Background</h3><div>Our study aimed to investigate the correlation between the microstructural changes of medial prefrontal cortex (m-PFC) and white matter hyperintensities (WMHs) with mild cognitive impairment (MCI) patients by Diffusion kurtosis imaging (DKI).</div></div><div><h3>Methods</h3><div>We retrospectively collected 68 patients, including 47 patients with WMHs and 21 age matched controls. WMHs patients were divided into with MCI (<em>n</em> = 30) and without MCI group (<em>n</em> = 17). The m-PFC was selected for regions of interests (ROIs). DKI parameters were measured and compared between each group. Correlations between DKI parameters and Montreal cognitive assessment (MoCA) score were also performed.</div></div><div><h3>Results</h3><div>1. Compared to controls, WMHs patients have lower MoCA score; WMHs with MCI patients have significant lower axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK) and fractional anisotropy (FA) in right anterior cingulate and paracingulate gyri (ACG) of m-PFC; and also have significant lower MK in left ACG. 2. Compared to WMHs without MCI patients, AK, FA and kurtosis fractional anisotropy (KFA) of WMHs with MCI patients were also significantly decreased. 3. AK were positively correlated with MoCA score in both ACG.</div></div><div><h3>Conclusions</h3><div>Patients with WMHs were related to MCI. DKI sequence has certain application value in evaluating whether WMHs with MCI patients have cognitive function impaired.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"348 ","pages":"Article 111958"},"PeriodicalIF":2.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143080760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple dimensions approach in polysubstance use: An ESEM analysis based on the RDoC framework","authors":"Laís da Silva Pereira-Rufino ,&nbsp;Denise Ribeiro Gobbo ,&nbsp;Rafael Conte ,&nbsp;Raissa Mazzer de Sino Romano ,&nbsp;Thays Cristina Silva Vissoto ,&nbsp;Marcelo Carvalho da Conceição ,&nbsp;João Ricardo Sato ,&nbsp;Henrique Carrete Junior ,&nbsp;Thiago Marques Fidalgo ,&nbsp;Maria Lucia Oliveira Souza-Formigoni ,&nbsp;Zhenhao Shi ,&nbsp;João Ricardo Nickenig Vissoci ,&nbsp;Corinde E. Wiers ,&nbsp;Isabel Cristina Céspedes","doi":"10.1016/j.pscychresns.2025.111959","DOIUrl":"10.1016/j.pscychresns.2025.111959","url":null,"abstract":"<div><div>Substance use disorders (SUD) are associated with cognitive alterations, influenced by genetic, neurodevelopmental, and environmental factors, and frequently co-occur with emotional disorders, complicating treatment strategies. Employing the Research Domain Criteria (RDoC) framework and Exploratory Structural Equation Modeling (ESEM), this study investigated the direct and indirect relationships between drug abuse, neurocognitive performance, emotional indicators, and structural changes in brain regions implicated in emotional regulation and executive functions in SUD patients and healthy controls. High-resolution magnetic resonance imaging (MRI) scans were acquired from patients with SUD (n=50) and healthy controls (HC=50). Group differences were assessed using voxel-based morphometry (VBM) and regions of interest (ROIs). Participants were evaluated for substance use (ASSIST) and completed a battery of cognitive tasks and emotional tests. The SUD group exhibited higher levels of depression and anxiety, as well as cognitive deficits, compared to the control group. Additionally, the SUD group showed significantly lower gray matter volume (GMV) in cortical and limbic areas. However, the ESEM analysis indicated that limbic areas indirectly and negatively impacted ASSIST scores. Thus, we can conclude that structural impairments in limbic areas strongly influenced substance use patterns, even when reductions in cortical volume and impaired cognitive performance were also present.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"348 ","pages":"Article 111959"},"PeriodicalIF":2.1,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143142393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased functional connectivity between brainstem substructures and cortex in treatment resistant depression","authors":"Anastasia Gaspert ,&nbsp;Rasmus Schülke ,&nbsp;Zeinab Houjaije ,&nbsp;Tabea Bätge ,&nbsp;Christopher Sinke ,&nbsp;Nima Mahmoudi ,&nbsp;Thorsten Folsche ,&nbsp;Alborz Bastami ,&nbsp;Alexandra Neyazi ,&nbsp;Mike P. Wattjes ,&nbsp;Tillmann H.C. Krüger ,&nbsp;Stefan Bleich ,&nbsp;Helge Frieling ,&nbsp;Hannah Benedictine Maier","doi":"10.1016/j.pscychresns.2025.111957","DOIUrl":"10.1016/j.pscychresns.2025.111957","url":null,"abstract":"<div><div>Previous functional magnetic resonance imaging (fMRI) studies showed an abnormal brainstem-to-cortex functional connectivity (FC) in major depressive disorder. However, only few studies analyzed brainstem substructures in treatment-resistant depression (TRD).</div><div>In this study, we analyzed resting-state seed-based FC between midbrain, pons, medulla oblongata and cortical/subcortical brain regions in patients with TRD (<em>n</em> = 24) and age- and sex-matched healthy controls (<em>n</em> = 24). FC was analyzed in each group and compared between groups. Correlation analyses assessed the relationship between FC strength and depressive symptom severity in regions showing significant group differences in seed-based connectivity.</div><div>Our findings reveal an increased FC in the midbrain and pons to the precentral gyrus, postcentral gyrus, and temporal gyrus in patients with TRD compared to healthy controls. Interestingly, in TRD patients, FC between midbrain and cortex was negatively correlated with BDI-II scores, indicating a relationship between altered connectivity and self-reported depression severity.</div><div>It is essential to note that our naturalistic, cross-sectional approach precludes causal conclusions regarding the relationship between FC and pathophysiology of TRD. The small sample size necessitates confirmation in a larger cohort.</div><div>Midbrain/pons-to-cortex FC was increased in patients with TRD compared to healthy controls. Future studies should explore the relationship between abnormal brainstem-to-cortex FC and depressive symptomatology in more detail.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"348 ","pages":"Article 111957"},"PeriodicalIF":2.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143142392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural indices of cognitive reappraisal impact the association between childhood trauma and suicide risk in adulthood","authors":"Kathryn C. Jenkins ,&nbsp;Lauren R. Khazem ,&nbsp;Shiane Toleson ,&nbsp;Kayla Kreutzer ,&nbsp;Craig J. Bryan ,&nbsp;Jagan Jimmy ,&nbsp;Stephanie M. Gorka","doi":"10.1016/j.pscychresns.2025.111949","DOIUrl":"10.1016/j.pscychresns.2025.111949","url":null,"abstract":"<div><h3>Background</h3><div>Childhood trauma exposure is a risk factor for suicide. However, not all trauma exposed individuals experience suicidal urges and core factors moderate this risk pathway. Individual differences in volitional emotion regulation capacity may be one key factor that shapes the association between childhood trauma and suicide; however, few studies have comprehensively investigated these associations using both subjective and objective indicators of emotion regulation. We therefore utilized a multimodal design with 80 adults reporting active suicidal urges.</div></div><div><h3>Methods</h3><div>Participants completed self-report forms capturing suicidogenic cognitions and severity of suicidal ideation. Volitional cognitive reappraisal was measured using self-report and prefrontal cortex activation (PFC; i.e., ventrolateral and dorsolateral) during instructed reappraisal with functional magnetic resonance imaging.</div></div><div><h3>Results</h3><div>Hierarchal linear regression analyses revealed evidence of childhood trauma by PFC activation interactions on suicide risk. At low levels of vlPFC activation, but not high levels, greater childhood trauma was associated with greater suicidal ideation severity and suicide cognitions. Similarly, at low levels of dlPFC activation, but not high levels, greater childhood trauma was associated with suicide cognitions.</div></div><div><h3>Conclusion</h3><div>Hypoactivation of regulatory PFC regions during volitional emotion regulation may contribute to increased suicide risk amongst individuals with a history of childhood trauma.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"348 ","pages":"Article 111949"},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143041306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alterations of subcortical structural volume in pediatric bipolar disorder patients with and without psychotic symptoms","authors":"Weijia Gao ,&nbsp;Qingli Mu ,&nbsp;Dong Cui ,&nbsp;Ce Zhu ,&nbsp;Qing Jiao ,&nbsp;Linyan Su ,&nbsp;Shaojia Lu ,&nbsp;Rongwang Yang","doi":"10.1016/j.pscychresns.2025.111948","DOIUrl":"10.1016/j.pscychresns.2025.111948","url":null,"abstract":"<div><h3>Background</h3><div>Pediatric bipolar disorder (PBD) with psychotic symptoms may predict more severe impairment in social functioning, but the underlying biological mechanisms remain unclear. The aim of this study was to investigate alterations in subcortical structural volume in PBD with and without psychotic symptoms.</div></div><div><h3>Methods</h3><div>We recruited 24 psychotic PBD (P-PBD) patients, 24 non-psychotic PBD (NP-PBD) patients, and 18 healthy controls (HCs). All participants underwent scanning with a 3.0 T Siemens Trio scanner. The FreeSurfer 7.4.0 software was employed to calculate the volume of each subcortical structure. An analysis of covariance (ANCOVA) was performed to identify brain regions with significant volume differences among the three groups, and then the inter-group comparisons were calculated. Partial correlation analyses were conducted to identify relationships between subcortical structural volumes and clinical features. Finally, receiver operating characteristic curve (ROC) analysis was employed to verify the capacity to distinguish between P-PBD and NP-PBD, P-PBD and HCs, and NP-PBD and HCs.</div></div><div><h3>Results</h3><div>ANCOVA revealed significant differences in the volumes of bilateral lateral ventricles, third ventricle, left thalamus, and right pallidum among three groups. Compared with HC, the third ventricle volume was increased in both groups of PBD patients, whereas the left thalamus and right pallidum volumes were decreased, and the bilateral lateral ventricles were enlarged in P-PBD patients. In contrast, only the third ventricle showed further enlargement in the group of P-PBD patients compared with NP-PBD patients. Partial correlation analyses revealed that episode times were associated with the third ventricle volume in P-PBD patients. Furthermore, ROC analyses indicated that volume in the left lateral ventricle exhibited the greatest capacity to distinguish between the P-PBD and NP-PBD, and the third ventricle performed best in distinguishing both the P-PBD group from HCs and the NP-PBD group from HCs. The combined metrics demonstrated greater diagnostic value in two-by-two comparisons.</div></div><div><h3>Conclusion</h3><div>Current research suggests that PBD with psychotic symptoms may have more extensive lateral and third ventricular volume enlargement. Bilateral lateral ventricles may serve as potential neurobiomarkers to distinguish P- PBD patients from NP-PBD patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"Article 111948"},"PeriodicalIF":2.1,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduced gray matter volume in limbic and cortical areas is associated with anxiety and depression in alcohol use disorder patients","authors":"Laís da Silva Pereira-Rufino ,&nbsp;Denise Ribeiro Gobbo ,&nbsp;Rafael Conte ,&nbsp;Raissa Mazzer de Sino ,&nbsp;Natan Nascimento de Oliveira ,&nbsp;Thiago Marques Fidalgo ,&nbsp;João Ricardo Sato ,&nbsp;Henrique Carrete Junior ,&nbsp;Maria Lucia Oliveira Souza-Formigoni ,&nbsp;Zhenhao Shi ,&nbsp;João Ricardo N. Vissoci ,&nbsp;Corinde E. Wiers ,&nbsp;Isabel Cristina Céspedes","doi":"10.1016/j.pscychresns.2025.111946","DOIUrl":"10.1016/j.pscychresns.2025.111946","url":null,"abstract":"<div><div>Alcohol use disorder (AUD) is a multifactorial disease closely related to neurodevelopment and environmental factors that influence behavior. This study explored the relationships between brain volume and behavior from an Exploratory Structural Equation Modeling (ESEM) based on the Research Domain Criteria. High-resolution magnetic resonance imaging scans were acquired from recent patients with AUD (<em>n</em> = 50) and healthy controls (HC=50). Group differences were assessed by means of voxel-based morphometry (VBM) and regions of interest (ROIs). Participants completed a battery of neurocognitive tasks and emotional tests. When controlling for age, education levels, and total intracranial volume, we found lower gray matter volume in cortical and limbic areas, as well as significant impairments in the AUD group on cognition and affective status. This study demonstrated the importance of multifactorial analysis and complex models in order to better understand substance use disorders. The brain losses may have been the result of neurodevelopmental impairments due to biological and environmental factors that predisposed to AUD or the result of drug abuse. The ESEM indicated that limbic areas indirectly affected the alcohol severity through emotional dysfunction. These results suggest a more relevant involvement of limbic regions for the severity of alcohol use, showing a more significant association between AUD and mood disorders.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"Article 111946"},"PeriodicalIF":2.1,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143010512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Left posterior superior temporal gyrus and its structural connectivity in schizophrenia","authors":"Hitoshi Sasaki ,&nbsp;Manabu Kubota ,&nbsp;Jun Miyata ,&nbsp;Toshiya Murai","doi":"10.1016/j.pscychresns.2025.111947","DOIUrl":"10.1016/j.pscychresns.2025.111947","url":null,"abstract":"<div><div>The left posterior superior temporal gyrus (pSTG) is thought to be involved in the pathophysiology and core symptoms of schizophrenia, although its structural connectivity has not yet been systematically investigated. Here, we aimed to evaluate its white matter (WM) connectivity with Broca's area, the thalamus, and the right pSTG. Eighty-three patients with schizophrenia and 141 healthy controls underwent diffusion-weighted imaging and T1-weighted three-dimensional magnetic resonance imaging. Probabilistic tractography was performed from the left pSTG to the Broca area, the left thalamus, and the right pSTG. Group comparison of WM fractional anisotropy (FA) in these pathways, as well as its correlations with the pSTG volume and clinical characteristics in the patient group, were examined. Patients showed significantly lower FA in the left pSTG-Broca and left-right pSTG pathways, but not in the left pSTG-thalamus pathway. Patients also revealed a trend toward a smaller left pSTG volume. Significant negative correlations were found in patients between FA in the left-right pSTG pathway and the left pSTG volume, and between FA in the left pSTG-Broca pathway and positive symptom severity. The present results suggest fiber-specific alterations in structural connectivity linked to the left pSTG, possibly supporting the “inner speech” and “interhemispheric disconnection” hypotheses of schizophrenia.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"Article 111947"},"PeriodicalIF":2.1,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of studies on constructing classification models to identify mental illness using brain effective connectivity","authors":"Fangfang Huang ,&nbsp;Yuan Huang ,&nbsp;Siying Guo ,&nbsp;Xiaoyi Chang ,&nbsp;Yuqi Chen ,&nbsp;Mingzhu Wang ,&nbsp;Yingfang Wang ,&nbsp;Shuai Ren","doi":"10.1016/j.pscychresns.2024.111928","DOIUrl":"10.1016/j.pscychresns.2024.111928","url":null,"abstract":"<div><div>Brain effective connectivity (EC) is a functional measurement that reflects the causal effects and topological relationships of neural activities. Recent research has increasingly focused on the classification for mental illnesses and healthy controls using brain EC; however, no comprehensive reviews have synthesized these studies. Therefore, the aim of this review is to thoroughly examine the existing literature on constructing diagnosis model for mental illnesses using brain EC. We first conducted a systematical literature search and thirty-five papers met the inclusion criteria. Subsequently, we summarized the approaches for estimating EC, the classification and validation methods used, the accuracies of models, and the main findings. Finally, we discussed the limitations of current research and the challenges in future research. These summaries and discussion provide references for future research on mental illnesses identification based on brain EC.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"Article 111928"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142771605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning based classification of excessive smartphone users via neuronal cue reactivity","authors":"Jailan Oweda ,&nbsp;Mike Michael Schmitgen ,&nbsp;Gudrun M. Henemann ,&nbsp;Marius Gerdes ,&nbsp;Robert Christian Wolf","doi":"10.1016/j.pscychresns.2024.111903","DOIUrl":"10.1016/j.pscychresns.2024.111903","url":null,"abstract":"<div><div>Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data and machine learning techniques to classify ESU and non-excessive smartphone users (n-ESU) based on their neural Cue-Reactivity (CR) signatures. By conducting a CR task and analyzing brain activation patterns, we identified spatial similarities between addictive smartphone use and established addictive disorders. Our approach involved employing Support Vector Machines (SVM) for classification, enhanced with feature selection methods such as Recursive Feature Elimination (RFE) and Model-based Selection and dimensionality reduction methods such as and Principal Component Analysis (PCA) to mitigate the challenges posed by limited dataset size and high dimensionality of fMRI data. The results demonstrate the effectiveness of our classification model, achieving accuracies of up to 79.9 %. Furthermore, we observed region-specific activations contributing significantly to classification accuracy, highlighting the potential biomarkers associated with ESU. External validation on longitudinal data revealed the necessity for larger training datasets to improve model generalizability. Additionally, feature selection techniques proved crucial for optimizing model performance, particularly in datasets with combined information from multiple sources. Our findings underscore the importance of incorporating more data to enhance model stability and generalizability, with implications for advancing the understanding and treatment of ESU and related disorders. Overall, our study demonstrates the promise of machine learning approaches in elucidating neural correlates of ESU and informing targeted interventions for affected individuals.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"Article 111903"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142473275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered brain network stability in OCD following rTMS intervention: Insights from structural balance theory","authors":"Maryam Ansari Esfeh ,&nbsp;Alireza Talesh Jafadideh ,&nbsp;Asiyeh Rezaei Niyasar ,&nbsp;Reza Rostami ,&nbsp;Reza Khosrowabadi","doi":"10.1016/j.pscychresns.2024.111927","DOIUrl":"10.1016/j.pscychresns.2024.111927","url":null,"abstract":"<div><div>Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising intervention for Obsessive-Compulsive Disorder (OCD). However, understanding brain network changes following rTMS remains limited, despite its potential to enhance treatment efficacy. In this retrospective study, we investigated brain network reorganization in OCD patients after rTMS, using structural balance theory as a framework. We hypothesized that rTMS-induced functional plasticity would alter brain network topology, particularly affecting triadic associations, and leading to increased balance energy levels, indicative of a less stable network state. Brain functional networks were constructed from resting-state EEGs of OCD patients, with phase lag indexes calculated both before and after rTMS treatment. These networks were analyzed by comparing global parameters, including positive and negative links, triadic interactions (balanced/unbalanced), hub formation tendencies, and balance energy levels. We observed a significant decrease in weak-balanced triads and an increase in strong-unbalanced triads within the Beta І frequency band (12–15 Hz). Additionally, there was a notable reduction in the tendency of negative links to form hubs across certain frequency bands. These changes led to an increase in the network's balanced energy level, pushing it toward a less stable state. We hope these findings will refine rTMS strategies by facilitating brain network reorganization.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"Article 111927"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}