Psychoradiology最新文献

{"title":"Age- and sex-related glymphatic differences and hemispheric asymmetry in healthy adults at 7.0T magnetic resonance imaging.","authors":"Yumei Yue, Xiaocui Tang, Ting Shen, Boyi Qu, Wen Lv, Wenying Zhang, Shengzhong Feng, Hsin-Yi Lai","doi":"10.1093/psyrad/kkag012","DOIUrl":"10.1093/psyrad/kkag012","url":null,"abstract":"<p><strong>Background: </strong>The glymphatic system plays a critical role in cerebral waste clearance and has been implicated in neurodegenerative and cerebrovascular disorders. However, normative variations in glymphatic structure and function across age, sex, and hemispheric organization in healthy adults remain incompletely characterized.</p><p><strong>Methods: </strong>Using ultra-high-field 7.0T MRI, we quantitatively assessed structural and functional glymphatic markers in 80 healthy adults. Perivascular space (PVS) number and volume were measured in the basal ganglia (BG) and midbrain (Mid), and glymphactic function was evaluated using the diffusion tensor imaging-analysis along the perivascular space (DTI-ALPS) index. Participants were stratified by age and sex. False discovery rate (FDR) correction was applied to control for multiple comparisons.</p><p><strong>Results: </strong>Robust age-related effects were observed. Older participants exhibited significantly greater PVS burden in the BG and Mid and lower right-hemispheric DTI-ALPS indices compared with younger adults. Age correlated positively with PVS number and left BG PVS volume, and negatively with the right DTI-ALPS index. Several sex effects did not survive FDR correction but showed moderate-to-large effect sizes in age-stratified analyses, suggesting potential sex-by-age interactions. Hemispheric analyses revealed a consistent right-dominant PVS burden in the midbrain, evident across age groups, whereas BG PVS burden and DTI-ALPS indices were largely symmetric.</p><p><strong>Conclusion: </strong>These findings demonstrate that glymphatic structure and function in healthy adults are strongly influenced by aging, exhibit age-dependent sex-related trends, and show region-specific hemispheric asymmetry. This study provides high-resolution normative reference data for glymphatic imaging and informs future investigations of early or subclinical glymphatic dysfunction.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag012"},"PeriodicalIF":7.4,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13153705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147870992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent developments in imaging transcriptomics for psychiatric disorders.","authors":"Juan Liu, Xian Ma, Wanze Xu, Xiaoyi Zhang, Feifei Liang, Jing Li, Yu Dou","doi":"10.1093/psyrad/kkag010","DOIUrl":"10.1093/psyrad/kkag010","url":null,"abstract":"<p><p>Mental disorders refer to abnormal states that affect an individual's thinking, emotion, behavior, and perception, and are generally associated with dysregulation of brain function. They exhibit genetic heterogeneity as well as multi-level structural and functional abnormalities of the brain. Magnetic resonance imaging has been widely applied to detect macroscopic neurophenotypic alterations in patients with psychiatric disorders; however, it remains limited in directly revealing the underlying molecular and cellular mechanisms. Imaging transcriptomics, by integrating whole-brain gene expression atlases with neuroimaging features, offers a novel paradigm for exploring the associations between microscopic genetic expression and macroscopic neuroimaging phenotypes. This review systematically summarizes the methodological framework of imaging transcriptomic association studies and highlights recent advances in their application to psychiatric disorders such as depression. A growing body of evidence has revealed spatial coupling between structural and functional abnormalities in disease-related brain regions and gene expression in synaptic transmission, ion channels, neurodevelopment, and immune signaling. Imaging transcriptomics not only facilitates a multiscale understanding of the pathophysiological mechanisms of psychiatric disorders but also provides potential pathways for disease classification, targeted intervention, and precision diagnosis and treatment. Future research should further promote the integration of longitudinal imaging omics and spatial transcriptomic data to construct translatable multimodal models, thereby accelerating the translation of psychiatric neuroimaging from mechanistic research to clinical application.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag010"},"PeriodicalIF":7.4,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13048277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147624743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impaired connectivity between the thalamus and the visual pathway in schizophrenia: a multimodal magnetic resonance imaging study.","authors":"Changyue Hou, Meihua Yan, Sisi Jiang, Yuting Deng, Lang Zhang, Hechun Li, Mingjun Duan, Yafeng Wang, Gang Yao, Hui He, Roberto Rodríguez-Labrada, Dezhong Yao, Cheng Luo","doi":"10.1093/psyrad/kkag008","DOIUrl":"10.1093/psyrad/kkag008","url":null,"abstract":"<p><strong>Background: </strong>Schizophrenia is a severe psychiatric disorder characterized by cognitive deficits as well as positive and negative symptoms. It is considered a disorder of widespread network dysconnectivity, including aberrant connectivity between the thalamus and the visual pathway. However, the relationships between the thalamus and various regions of the dorsal and ventral visual pathways in schizophrenia, and how the thalamus affects interactions among these visual regions, remain unclear.</p><p><strong>Methods: </strong>Resting-state functional magnetic resonance imaging, task-state functional magnetic resonance imaging, and diffusion tensor imaging data were acquired to examine the neural activity within the thalamus and the visual pathway, along with the relationships between them (i.e. functional connectivity, structural connectivity, and structure-function coupling). We also correlated the altered imaging parameters with clinical characteristics. Furthermore, based on previous molecular imaging in healthy controls, we explored the spatial associations between altered imaging parameters and receptor/transporter distributions.</p><p><strong>Results: </strong>We found significantly decreased neural activity and widespread altered thalamo-visual pathway connectivity in both dorsal and ventral pathways in schizophrenia patients. Moreover, schizophrenia patients exhibited altered mediation effects within the thalamo-dorsal visual pathway, involving MT, V1, V2, and V3. Abnormal neural activity and connectivity were related to disease duration and positive symptom severity. Altered neural activity of MT was correlated with the density of multiple neurotransmitters.</p><p><strong>Conclusions: </strong>Our findings further expand our understanding of thalamo-visual pathway dysconnectivity and primary information-processing deficits in schizophrenia, which may be related to clinical symptoms. Our findings may provide more potential insights for non-invasive intervention treatments.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag008"},"PeriodicalIF":7.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023046/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain entropy as a biomarker of major depression in adolescents and young adults: insights from multimodal resting-state functional magentic resonance imaging.","authors":"Ruoxi Lu, Jianyu Li, Yiran Li, Xinglin Zeng, Yan Guo, Danian Li, Ying Cui, Xinyu Liang, Hanyue Zhang, Jing Wang, Baohua Cheng, Yujie Liu, Ze Wang, Shijun Qiu","doi":"10.1093/psyrad/kkag009","DOIUrl":"10.1093/psyrad/kkag009","url":null,"abstract":"<p><strong>Background: </strong>Major depressive disorder (MDD) in adolescents and young adults is increasingly prevalent, yet accurate diagnosis remains challenging due to the limitations of conventional neuroimaging metrics. Traditional resting-state functional magnetic resonance imaging (rs-fMRI) measures such as amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity density (FCD) primarily capture static aspects of brain activity and may overlook critical neural dynamics. Brain entropy (BEN), which quantifies temporal irregularity in rs-fMRI signals, may offer a complementary approach to better characterize neural alterations in MDD.</p><p><strong>Methods: </strong>We analyzed multimodal rs-fMRI data from 204 individuals aged 12-24 years (119 with MDD and 85 healthy controls). BEN was computed alongside ALFF, ReHo, and FCD to extract region-wise features across the brain. A support vector machine with recursive feature elimination (SVM-RFE) was used to classify MDD and healthy controls based on various feature combinations. Classification performance was evaluated using repeated cross-validation and permutation testing. Additionally, partial Spearman correlations were performed between selected brain features and clinical measures including depression severity, childhood trauma, sleep quality, and cognitive control.</p><p><strong>Results: </strong>Models incorporating BEN consistently outperformed those using traditional rs-fMRI features alone. The combination of BEN, ALFF, and FCD achieved the highest classification accuracy (AUC = 0.877, permutation test <i>P</i> < 0.001). The most frequently selected brain regions contributing to MDD classification included the putamen, paracentral lobule, cuneus, middle frontal gyrus, and rectus. BEN features also showed preliminary correlations with clinical variables such as childhood trauma and sleep quality, suggesting functional relevance.</p><p><strong>Conclusions: </strong>This study demonstrates that BEN provides complementary diagnostic information to traditional rs-fMRI features in classifying adolescent and young adult MDD. BEN-related alterations in brain activity may reflect underlying neurobiological disruptions and show potential as a functional neuroimaging biomarker for depression during a critical stage of brain development.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag009"},"PeriodicalIF":7.4,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13092983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered dynamic functional connectivity of orbitofrontal cortex underlies olfactory and cognitive impairment in late-life depression.","authors":"Ben Chen, Shuang Liang, Ting Su, Youxuan Zheng, Wei He, Huarong Zhou, Qiang Wang, Mingfeng Yang, Gaohong Lin, Danyan Xu, Yunheng Chen, Jiafu Li, Qin Liu, Kexin Yao, Zhangying Wu, Min Zhang, Le Hou, Yueyang Zhang, Xiaomei Zhong, Yuping Ning","doi":"10.1093/psyrad/kkag002","DOIUrl":"10.1093/psyrad/kkag002","url":null,"abstract":"<p><strong>Background: </strong>Late-life depression (LLD) and odor identification (OI) dysfunction are risk factors for dementia, but the underlying neural mechanisms remain unclear. This study investigated dynamic functional connectivity (dFC) in olfactory brain regions of LLD patients with and without OI dysfunction and examined how dFC moderates the OI-cognition link.</p><p><strong>Methods: </strong>Resting-state functional magnetic resonance imaging data were acquired from 51 LLD patients with OI deficits (LLD-OID), 59 LLD patients without deficits (LLD-noOID), and 51 healthy controls (HC). A sliding-window approach (50 TR width, 1 TR step) was used to estimate dFC variability between the orbitofrontal cortex (OFC) and the whole brain. Bayesian regression and moderation analyses assessed associations among OFC dFC, OI scores, and cognitive measures. Results were robust across window sizes.</p><p><strong>Results: </strong>Compared to LLD-noOID and HC, LLD-OID showed decreased OFC-left inferior frontal gyrus dFC variability (<i>P</i> < 0.01) and increased OFC-right middle frontal gyrus (MFG) variability (<i>P</i> < 0.001). Higher OFC-MFG variability was associated with worse OI and cognitive performance and significantly moderated the OI-global cognition relationship (β = 1.06, <i>P</i> = 0.027, 95% CI [0.12, 2.0]). No group differences were found in primary olfactory regions.</p><p><strong>Conclusion: </strong>LLD patients with OI dysfunction exhibited more disrupted dFC in secondary olfactory regions compared with those without OI dysfunction. Dynamic OFC-MFG disconnectivity may index vulnerability to cognitive decline and dementia risk in LLD patients.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag002"},"PeriodicalIF":7.4,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12916006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive neural signature of internet gaming disorder severity revealed by cross-network connectivity.","authors":"Yi-Hao Hu, Meiting Wei, Xin Luo, Xuefeng Xu, Shuang Li, Anhang Jiang, Guang-Heng Dong","doi":"10.1093/psyrad/kkag006","DOIUrl":"10.1093/psyrad/kkag006","url":null,"abstract":"<p><strong>Background: </strong>While internet gaming disorder (IGD) correlates with regional brain responses and functional connectivity, the brain network architecture underlying addiction severity remains poorly characterized.</p><p><strong>Methods: </strong>Using resting-state functional magentic resonance imaging data and addiction severity metrics from 586 participants (443 IGD, 143 recreational game users), we employed connectome-based predictive modeling (CPM) with leave-one-out cross-validation to identify neural networks predictive of IGD severity. The resulting network was evaluated for replicability in independent datasets, with key predictive networks and nodes further analyzed.</p><p><strong>Results: </strong>CPM identified a replicable addiction severity network. CPM significantly predicted individual gaming addiction scores (<i>r</i> = 0.19, <i>P</i> < 0.001), with features selected using a threshold of <i>P</i> < 0.01. Predictive power primarily derived from internetwork connectivity linking the subcortical, subvisual, and frontoparietal networks. Validation in independent data showed a directional trend (<i>r </i>= 0.17, <i>P </i>= 0.011).</p><p><strong>Conclusions: </strong>Individual variability in subcortical-subvisual-frontoparietal network connectivity predicts IGD addiction severity, highlighting these circuits as potential targets for neuromodulation interventions.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag006"},"PeriodicalIF":7.4,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13103295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain-predicted age difference is associated with the progression of subthreshold depression: evidence from the UK Biobank.","authors":"Haowei Dai, Lijing Niu, Qingzi Zhu, Yuanyuan Zeng, Yutong Ying, Xueping Yin, Xiangyi Liang, Xingqin Wang, Bihua Zhou, Qing Ma, Ruibin Zhang","doi":"10.1093/psyrad/kkag005","DOIUrl":"10.1093/psyrad/kkag005","url":null,"abstract":"<p><strong>Background: </strong>Previous studies have reported accelerated brain aging in individuals with major depressive disorder (MDD) compared to healthy controls. However, these findings are based primarily on cross-sectional data, limiting dynamic association between brain aging and MDD. Here, we examined the relationship between brain aging and MDD progression by focusing on subthreshold depression, a prodromal stage of MDD, and aimed to determine whether quantitative markers of brain aging exhibit a stable association with disease progression.</p><p><strong>Methods: </strong>Using neuroimaging data from the UK Biobank and a support vector regression (SVR) model, we predicted brain age in individuals who exhibited subthreshold depressive symptoms at baseline but showed divergent mental status at follow-up, and then conducted between-group comparisons. Logistic regression was then applied to assess whether brain-predicted age difference (Brain-PAD) stably associates with the progression of subthreshold depression after adjusting for covariates.</p><p><strong>Results: </strong>Individuals with subthreshold depression showed a higher risk of progression to MDD compared to healthy controls. Those whose condition worsened from subthreshold depression to MDD exhibited greater brain aging than those who remained subthreshold or recovered. Importantly, Brain-PAD remained significantly and stably associated with this progression after controlling for sex, ethnicity, lifestyle, and socioeconomic factors.</p><p><strong>Conclusions: </strong>This study supports an association between brain aging and MDD progression and demonstrates a robust association between an increased Brain-PAD and the conversion from subthreshold depression to MDD. These findings enhance our understanding of MDD's developmental trajectory and suggest that Brain-PAD may facilitate early detection and intervention targeting brain aging.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag005"},"PeriodicalIF":7.4,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12947158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic brain lateralization patterns in Chinese naturalistic language comprehension and association with sex differences: a 7T functional magnetic resonance imaging study.","authors":"Ruohan Zhang, Shujie Geng, Xiaoqing Zheng, Wanwan Guo, Chun-Yi Zac Lo, Jiaying Zhang, Xiao Chang, Xinran Wu, Yufeng Zhang, Jie Zhang, Miao Cao, Jianfeng Feng","doi":"10.1093/psyrad/kkag003","DOIUrl":"10.1093/psyrad/kkag003","url":null,"abstract":"<p><strong>Background: </strong>Although language is traditionally regarded as unique to humans and predominantly left-lateralized in the brain, the dynamic interplay between cerebral hemispheres during language processing remains poorly understood.</p><p><strong>Methods: </strong>Using 400 functional magnetic resonance imaging scans acquired with a 7T scanner under diverse narrative stimuli, this study examined whole-brain functional dynamic lateralization patterns during Chinese language processing and explored potential sex differences.</p><p><strong>Results: </strong>We identified two distinct dynamic lateralization states. While core language regions consistently showed left-lateralization, other brain regions displayed reversed lateralization. These two states-characterized by higher-level functional regions lateralizing either left or right-corresponded to the processing of rational and emotional content, respectively. Notably, males showed a stronger tendency toward the former state, whereas females inclined toward the latter, particularly during the processing of rational content. Genetic analyses further suggested that sex differences in these lateralization states may be influenced by sex hormones.</p><p><strong>Conclusion: </strong>This study offers novel insights into the dynamic organization of cerebral lateralization during Chinese language processing.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag003"},"PeriodicalIF":7.4,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12947159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroradiological features across major psychiatric disorders and behavioral variant of Alzheimer's disease: a concise multimodal synthesis.","authors":"Sina Dindarian, Joga Chaganti, Nazanin Rafiei, Scott H Faro","doi":"10.1093/psyrad/kkag004","DOIUrl":"10.1093/psyrad/kkag004","url":null,"abstract":"<p><p>Psychiatric disorders are complex, disabling conditions that continue to rely on subjective diagnostic criteria due to the absence of objective biological markers. Neuroradiology has become a critical discipline for examining the structural, functional, and biochemical underpinnings of these disorders through advanced brain imaging. This review synthesizes findings from five major psychiatric conditions including major depressive disorder, schizophrenia, autism spectrum disorder, obsessive-compulsive disorder, and generalized anxiety disorder, and briefly discusses the behavioral variant of Alzheimer's disease, a variant with neuropsychological overlay, across multiple imaging modalities, including structural magnetic resonance imaging (MRI), diffusion tensor imaging, functional MRI, magnetic resonance spectroscopy, functional near-infrared spectroscopy, and positron emission tomography. We present a comparative overview of cross-condition and modality-specific findings, highlighting converging disruptions in frontolimbic and temporoparietal circuits, alongside unique neurobiological features in each disorder. We also acknowledge key confounds such as medication effects, comorbidities, and methodological variability that limit direct transdiagnostic inference. We further discuss methodological limitations, emerging trends such as multimodal integration and machine learning, and future directions for translating imaging data into clinically meaningful biomarkers.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag004"},"PeriodicalIF":7.4,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12947160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized functional network connectivity abnormalities in chronic insomnia disorder.","authors":"Xiaoxuan Li, Yiran Zhai, Tianwei Qin, Zhiwei Zhang, Zixi Zhao, Hanbin Deng, Siqi Yang, Jiang Zhang, Liang Gong","doi":"10.1093/psyrad/kkag001","DOIUrl":"10.1093/psyrad/kkag001","url":null,"abstract":"<p><strong>Background: </strong>Chronic insomnia disorder (CID) is associated with disrupted functional brain networks, yet prior research has focused primarily on group-level analyses. This study employed personalized functional network mapping to identify connectivity abnormalities in CID.</p><p><strong>Methods: </strong>Resting-state functional magentic resonance imaging (rs-fMRI) data were collected from 86 CID patients and 38 good sleeper controls (GSCs). Using non-negative matrix factorization (NMF), we derived individualized large-scale brain networks for each participant to uncover subject-specific connectivity changes in CID. We also constructed functional network connectivity (FNC) matrices using Pearson correlation coefficients and compared global and local graph-theory metrics across groups based on these individualized networks.</p><p><strong>Results: </strong>FNC analysis revealed significant differences between CID patients and GSCs within the default mode network (DMN), ventral attention network, visual network (VIS), and other key brain regions. CID exhibited altered global network topology and significant differences in local topological properties. At the global level, CID demonstrated significantly higher small-worldness (Sigma) and normalized clustering coefficient (Gamma). At the nodal level, CID showed increased local efficiency and clustering coefficient, as well as decreased nodal efficiency in the DMN, along with increased degree centrality in the VIS.</p><p><strong>Conclusion: </strong>By focusing on individualized functional connectivity, this approach reveals unique \"fingerprint\" alterations in CID. These findings provide novel insights into CID's neurobiological mechanisms and underscore the value of personalized network approaches for understanding and treating sleep disorders.</p>","PeriodicalId":93496,"journal":{"name":"Psychoradiology","volume":"6 ","pages":"kkag001"},"PeriodicalIF":7.4,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12947161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}