Psychiatry Research: Neuroimaging最新文献

{"title":"Antipsychotic exposure and regional brain volume changes in schizophrenia: Dose-related associations.","authors":"Khalilullah Arsyi, Artha M T Simanjuntak, Juwita Saragih, Rina Hastuti Lubis, Zulfa Zahra, Solaphat Hemrungrojn","doi":"10.1016/j.pscychresns.2026.112316","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2026.112316","url":null,"abstract":"<p><strong>Background: </strong>The long-term effects of antipsychotic treatment on brain structure in schizophrenia remain uncertain. Previous meta-analyses have primarily compared patients with controls rather than examining dose-related associations between cumulative exposure and brain structure.</p><p><strong>Objective: </strong>To quantify the association between cumulative antipsychotic exposure (chlorpromazine equivalents) and structural brain changes measured by MRI in patients with schizophrenia.</p><p><strong>Methods: </strong>Following prospective registration (PROSPERO CRD420261352526), 19 studies involving 1607 patients were included. Pearson's r or standardized β coefficients were pooled using random-effects models with the DerSimonian-Laird estimator. Subgroup analyses were conducted for the primary outcome.</p><p><strong>Results: </strong>Higher cumulative antipsychotic exposure was associated with lower global gray matter volume (10 studies, n = 993; r = -0.259, 95% CI -0.337 to -0.179; p < 0.001). Publication bias was detected for this outcome (Egger's test p = 0.00574). Negative associations were also observed for global cortical thickness (r = -0.293), frontal lobe volume (r = -0.339), temporal lobe volume (r = -0.351), and total brain volume (r = -0.310). Lateral ventricular volume showed a positive association (r = 0.228), whereas white matter volume was not significantly associated. The dose-related association with gray matter volume was consistent across study designs and illness stages, with no significant subgroup differences.</p><p><strong>Conclusions: </strong>Higher cumulative antipsychotic exposure was modestly associated with greater structural brain alterations. However, these observational findings do not establish causality because medication exposure is closely linked to illness progression. Interpretation is further limited by publication bias, the small number of studies, and heterogeneity across secondary outcomes. Well-designed prospective longitudinal studies are needed to better distinguish medication effects from disease-related changes.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"364 ","pages":"112316"},"PeriodicalIF":2.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148897667","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":"C-reactive protein-related cortical thickness changes and its association with resting-state functional connectivity alterations in major depressive disorder.","authors":"Youbin Kang, Minjee Jung, Jihoon Park, Daun Shin, Aram Kim, Woo-Suk Tae, Byung-Joo Ham, Kyu-Man Han","doi":"10.1016/j.pscychresns.2026.112314","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2026.112314","url":null,"abstract":"<p><strong>Background: </strong>C-reactive protein (CRP) has emerged as a promising peripheral biomarker of neuroinflammatory processes implicated in the pathophysiology of major depressive disorder (MDD). We combined structural magnetic resonance imaging (MRI) with resting-state functional MRI to examine plasma CRP-related cortical thickness and resting-state functional connectivity (RSFC) changes.</p><p><strong>Methods: </strong>Seventy-six patients with MDD and 65 healthy controls (HCs) were included in this study. The association between whole-brain cortical thickness and plasma CRP levels in the total sample (MDD+ HC, n = 141) was investigated. Seed-to-voxel RSFC analysis was performed using plasma CRP level-related cortical regions as seeds.</p><p><strong>Results: </strong>Compared to the HC group, the MDD group showed significantly higher plasma CRP levels (p = 0.039). Higher plasma CRP levels were associated with cortical thinning in the prefrontal cortices and precentral gyrus, and cortical thickening in the left postcentral and right medial orbitofrontal gyrus. RSFC analysis showed a lower RSFC between the left dorsolateral prefrontal cortex and bilateral insula and between the precentral gyrus and superior parietal cortex, and higher RSFC between the dorsomedial prefrontal cortex and postcentral gyrus in MDD compared to HCs.</p><p><strong>Conclusions: </strong>Our findings suggest that systemic inflammation may be associated with structural and functional disruption of emotion regulation and cognitive control networks in MDD.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"364 ","pages":"112314"},"PeriodicalIF":2.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148897665","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":"Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.","authors":"Baoxiang Wang, Fulai Yuan, Wei Zhou, Yizhi Pan","doi":"10.1016/j.pscychresns.2026.112308","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2026.112308","url":null,"abstract":"<p><strong>Background: </strong>Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized.</p><p><strong>Methods: </strong>A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets.</p><p><strong>Results: </strong>Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways.</p><p><strong>Conclusions: </strong>By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"363 ","pages":"112308"},"PeriodicalIF":2.4,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875905","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":"Graph neural network-based modeling of functional brain connectivity in autism spectrum disorder using the ABIDE-I and II datasets.","authors":"Ji-Won Lee, Hassan Shayan, Han-Gue Jo","doi":"10.1016/j.pscychresns.2026.112310","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2026.112310","url":null,"abstract":"<p><p>Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by atypical large-scale brain network organization. Using the comprehensive Autism Brain Imaging Data Exchange (ABIDE-I and ABIDE-II; n = 2013 participants), this study systematically evaluated three representative graph neural network (GNN) architectures for ASD classification based on resting-state functional MRI. The Graph Convolutional Network (GCN), Graph Attention Network (GAT), and Self-Attention Graph Pooling (SAGPool) models were applied to graph representations of functional connectivity among 200 brain regions, following standardized preprocessing and ComBat harmonization. Across 100 repetitions of 10-fold stratified cross-validation, all three models achieved consistent and reproducible accuracy (∼61% balanced accuracy), establishing a robust performance benchmark for connectome-based ASD classification. Permutation-based feature importance analysis revealed convergent brain regions across models, including the bilateral thalamus, right superior temporal gyrus, right middle occipital gyrus, and bilateral precuneus, which are involved in sensory integration, social cognition, and default mode network functioning. These findings indicate that distinct GNN architectures converge on common neurobiological signatures of ASD, highlighting their potential for reliable brain network modeling and biomarker discovery in psychiatry research.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"363 ","pages":"112310"},"PeriodicalIF":2.4,"publicationDate":"2026-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148888470","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":"Functional brain networks involved in fluid intelligence in bipolar disorder.","authors":"Mavis Kusi, Riley Zurrin, Samantha Tze Sum Wong, Chantal Percival, Meighen M Roes, Todd S Woodward, Vina M Goghari","doi":"10.1016/j.pscychresns.2026.112309","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2026.112309","url":null,"abstract":"<p><p>fMRI data were collected during the Raven's Standard Progressive Matrices (RSPM) to investigate the networks involved in fluid intelligence (Gf) in people with bipolar disorder (BD), compared to community controls. Brain networks were extracted using a multidimensional analysis method that provides network anatomical and temporal information about task-induced BOLD signal changes. Four networks were elicited. Two networks matched the multiple demand network (MDN), one of which consisted of the MDN desynchronized with all other networks and peaked earliest in the trial (∼ 6 s). The other network (MDN/DN-B) involved MDN activation synchronized with default mode network (DMN) deactivation, with a later, more protracted peak (∼ 9-12 s). Another network comprised activations in motor response (RESP) regions and peaked later in the trial (∼ 11-14 s). A fourth network (RE-EV/DN-A) peaked the latest (∼ 14 s) and comprised activations in regions involved in the re-evaluation (RE-EV) of responses and DMN deactivation. The BD and control groups did not differ in RSPM task performance or network activity. These null results might indicate heterogeneity in Gf in BD, with a subgroup of BD patients without Gf deficits.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"363 ","pages":"112309"},"PeriodicalIF":2.4,"publicationDate":"2026-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866685","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":"Retraction notice to Corrigendum to ''Analysis of the Application Value of Multi-slice Spiral CT and Multimodal MRI in Screening Patients with Bipolar Disorder'' Psychiatry research. Neuroimaging, 358, 112178 [Psychiatry Research: Neuroimaging 360 (2026) 112218].","authors":"Yandong Si, Yan Yu, Hongfeng Fan, Zhiqiang Xing","doi":"10.1016/j.pscychresns.2026.112287","DOIUrl":"10.1016/j.pscychresns.2026.112287","url":null,"abstract":"","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":" ","pages":"112287"},"PeriodicalIF":2.4,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148621207","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":"Brain functional network dynamics in women with alleged mediumship: a controlled study","authors":"Jéssica Plácido ,&nbsp;Marco Aurélio Vinhosa Bastos Jr. ,&nbsp;Paulo Roberto Haidamus de Oliveira Bastos ,&nbsp;Thaise G.L. de O. Toutain ,&nbsp;José Garcia Vivas Miranda","doi":"10.1016/j.pscychresns.2026.112164","DOIUrl":"10.1016/j.pscychresns.2026.112164","url":null,"abstract":"<div><h3>Introduction</h3><div>The Brain Functional Networks (BFN) approach integrates Electroencephalography, Graph Theory, and Motif Synchronization to identify brain regions that are functionally connected over time, even if spatially distant. This contrasts with previous studies on mediumship.</div></div><div><h3>Objective</h3><div>To analyze BFN topological indices during mediumistic trance.</div></div><div><h3>Method</h3><div>Secondary data collected in Campo Grande, Brazil, were analyzed. Twenty-eight women participated, divided into two groups: Mediums Group (MG, <em>n</em> = 14) and Control Group (CG, <em>n</em> = 14). Both groups performed a pre-trance task (resting condition). MG performed a mediumship trance task, while CG engaged in a prayer task (listening and praying). EEG data were processed to construct networks for Delta, Theta, Alpha, Beta, and all-frequency bands.</div></div><div><h3>Results</h3><div>Significant differences in brain connectivity indices were observed: MG showed changes in delta (<em>p</em> = 0.002), theta (<em>p</em> = 0.006), and alpha (<em>p</em> = 0.035) bands. CG showed changes in the beta band (<em>p</em> = 0.008).</div></div><div><h3>Discussion</h3><div>These results suggest that the tasks influenced brain activity patterns. Mediumistic trance appears to be an altered state of consciousness distinct from sleep.</div></div><div><h3>Conclusion</h3><div>The results reinforce the notion of mediumship as an altered, non-pathological brain state, distinct from schizophrenia and non-dominant temporal lobe syndrome.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"358 ","pages":"Article 112164"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146258918","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":"Investigating the neuroanatomical underpinnings of complex PTSD in people with psychosis","authors":"Peter Panayi ,&nbsp;Filippo Varese ,&nbsp;Emmanuelle Peters ,&nbsp;Richard Bentall ,&nbsp;Amy Hardy ,&nbsp;Katherine Berry ,&nbsp;William Sellwood ,&nbsp;Raphael Underwood ,&nbsp;Craig Steel ,&nbsp;Liam Mason ,&nbsp;Rebecca Elliott","doi":"10.1016/j.pscychresns.2026.112182","DOIUrl":"10.1016/j.pscychresns.2026.112182","url":null,"abstract":"<div><div>Childhood maltreatment and complex post-traumatic stress disorder (cPTSD) are common among people with psychosis. Traumatic life experiences may contribute to the neural substrates of psychosis. Affective pathways to psychosis outline the role of post-traumatic sequelae, but no studies have explored the neurobiological underpinnings of cPTSD in this population. We compared two groups meeting criteria for schizophrenia-spectrum disorders, with (<em>n</em> = 58) and without (<em>n</em> = 50) comorbid cPTSD. Region of interest (ROI) analysis was used to assess structural differences in ROIs identified by meta-analyses as overlapping between PTSD and psychosis. The cPTSD group showed enlarged limbic regions, including the bilateral anterior insula and left parahippocampus, and smaller prefrontal regions, including the left medial orbitofrontal cortex (mOFC). In the right mOFC, specific voxel volumes were larger, and others smaller, in the cPTSD group. All differences, aside from hippocampal volume, survived whole-brain analysis corrected for multiple comparisons. Post-hoc analyses indicated trends suggesting bilateral insula and mOFC volume correlated positively, whereas parahippocampal volume correlated negatively, with cPTSD symptom severity. To conclude, in people with comorbid cPTSD and psychosis, post-traumatic sequelae may be underpinned by anatomical differences in regions implicated in emotion regulation, especially the regulation of fear, supporting the neural characterisation of affective psychosis pathways.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"358 ","pages":"Article 112182"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147322090","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":"Insights into changes in glutaminergic metabolites in the anterior cingulate cortex: A systematic review and meta-analysis of magnetic resonance spectroscopy in schizophrenia","authors":"Mercedes Simh-Peh Chan,&nbsp;Pek-Yee Tang,&nbsp;Zhi-Kuan Chua,&nbsp;Wan-Ling Cheong,&nbsp;Siew-Ying Mok","doi":"10.1016/j.pscychresns.2026.112175","DOIUrl":"10.1016/j.pscychresns.2026.112175","url":null,"abstract":"<div><div>Dysregulation of glutamatergic metabolites—glutamate (GLU), glutamine (GLN), and the combined metabolite glutamine–glutamate (GLX)—has been implicated in schizophrenia, but interpreting these metabolites using magnetic resonance spectroscopy is challenging due to regional brain variation. This systematic review and meta-analysis investigate GLU, GLN, and GLX levels in the anterior cingulate cortex (ACC), a region critical for cognitive and emotional regulation. Database searches identified 51 case-control studies comparing schizophrenia patients to healthy controls. Data were analyzed using random-effects models, pooling Hedges' g effect sizes. Overall, no significant differences in glutamatergic metabolites were found between groups. However, after excluding one study in a leave-one-out analysis, a significant increase in GLX was observed. Subgroup analyses revealed that treatment-resistant schizophrenia (TRS) patients had higher GLU and GLX levels, indicating more pronounced glutamatergic dysregulation in TRS. Higher GLX levels were observed in medicated patients, and removal of the TRS cohort made GLX non-significant and reduced GLU, suggesting these variations were driven by TRS. Further meta-regression showed that GLX variation in TRS was linked to age of onset and disease severity, but not illness duration, pointing to a distinct neurochemical profile. These findings highlight the potential of targeting glutamatergic systems as a therapeutic strategy, particularly for treatment-resistant cases.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"358 ","pages":"Article 112175"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146214114","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":"TMN: Learning multi-timescale functional connectivity for identifying brain disorders","authors":"Jinlong Hu ,&nbsp;Jianmiao Luo ,&nbsp;Jiatong Huang ,&nbsp;Shoubin Dong ,&nbsp;Bin Liao","doi":"10.1016/j.pscychresns.2026.112156","DOIUrl":"10.1016/j.pscychresns.2026.112156","url":null,"abstract":"<div><h3>Background</h3><div>Functional connectivity (FC) has been used to identify brain disorders. The present study aimed to identify brain disorders by FC across multiple timescales.</div></div><div><h3>Methods</h3><div>We first segmented the resting-state fMRI signals to construct multiple timescale functional connectivity (mFC) between brain regions. Next, we developed a deep multiple instance learning (MIL) approach, namely the Two-stage Multi-stream Network (TMN), to capture spatio-temporal patterns from the mFC. We evaluated the TMN in the ABIDE I dataset and the REST-Meta-MDD dataset. Furthermore, we proposed using the inputXgrad to explain the important features in the model.</div></div><div><h3>Results</h3><div>We achieved the best performance using the TMN model with mFC. Our findings indicated that mFC outperformed both static FC and the combination of static and dynamic FC in identification tasks. The model's explanation revealed that FC across all timescales contributed to the identification of brain disorders and highlighted the important FC that are strongly associated with these conditions.</div></div><div><h3>Limitations</h3><div>The techniques used for data preprocessing can influence the model's performance, and this study requires further validation with a larger patient cohort and a broader range of brain disorders.</div></div><div><h3>Conclusions</h3><div>The experimental results demonstrate that brain disorders can be effectively identified using the proposed TMN with mFC.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"358 ","pages":"Article 112156"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102594","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}