Psychiatry Research: Neuroimaging最新文献

{"title":"Alterations of subcortical structural volume in pediatric bipolar disorder patients with and without psychotic symptoms.","authors":"Weijia Gao, Qingli Mu, Dong Cui, Ce Zhu, Qing Jiao, Linyan Su, Shaojia Lu, Rongwang Yang","doi":"10.1016/j.pscychresns.2025.111948","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2025.111948","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"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, Denise Ribeiro Gobbo, Rafael Conte, Raissa Mazzer de Sino, Natan Nascimento de Oliveira, Thiago Marques Fidalgo, João Ricardo Sato, Henrique Carrete Junior, Maria Lucia Oliveira Souza-Formigoni, Zhenhao Shi, João Ricardo N Vissoci, Corinde E Wiers, Isabel Cristina Céspedes","doi":"10.1016/j.pscychresns.2025.111946","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2025.111946","url":null,"abstract":"<p><p>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 (n = 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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"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, Manabu Kubota, Jun Miyata, Toshiya Murai","doi":"10.1016/j.pscychresns.2025.111947","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2025.111947","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"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":"","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, Yuan Huang, Siying Guo, Xiaoyi Chang, Yuqi Chen, Mingzhu Wang, Yingfang Wang, Shuai Ren","doi":"10.1016/j.pscychresns.2024.111928","DOIUrl":"10.1016/j.pscychresns.2024.111928","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"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, Mike Michael Schmitgen, Gudrun M Henemann, Marius Gerdes, Robert Christian Wolf","doi":"10.1016/j.pscychresns.2024.111903","DOIUrl":"10.1016/j.pscychresns.2024.111903","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":" ","pages":"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":"","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, Alireza Talesh Jafadideh, Asiyeh Rezaei Niyasar, Reza Rostami, Reza Khosrowabadi","doi":"10.1016/j.pscychresns.2024.111927","DOIUrl":"10.1016/j.pscychresns.2024.111927","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"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}

{"title":"Multimodal imaging of the amygdala in non-clinical subjects with high vs. low autistic-like social skills traits.","authors":"Niccolò Zovetti, Tina Meller, Ulrika Evermann, Julia-Katharina Pfarr, Jonas Hoffmann, Andrea Federspiel, Sebastian Walther, Sarah Grezellschak, Andreas Jansen, Ahmad Abu-Akel, Igor Nenadić","doi":"10.1016/j.pscychresns.2024.111910","DOIUrl":"10.1016/j.pscychresns.2024.111910","url":null,"abstract":"<p><p>Recent clinical and theoretical frameworks suggest that social skills and theory of mind impairments characteristic of autism spectrum disorder (ASD) are distributed in the general population on a continuum between healthy individuals and patients. The present multimodal study aimed at investigating the amygdala's function, perfusion, and volume in 56 non-clinical subjects from the general population with high (n = 28 High-SOC) or low (n = 28 Low-SOC) autistic-like social skills traits. Participants underwent magnetic resonance imaging to evaluate the amygdala's functional connectivity at rest, blood perfusion by means of arterial spin labelling, its activation during a face evaluation task and lastly grey matter volumes. The High-SOC group was characterised by higher blood perfusion in both amygdalae, lower volume of the left amygdala and higher activations of the right amygdala during processing of human faces with fearful value. Resting state analyses did not reveal any significant difference between the two groups. Overall, our results highlight the presence of overlapping morpho-functional alterations of the amygdala between healthy individuals and ASD patients confirming the importance of the amygdala in this disorder and in social and emotional processing. Our findings may help disentangle the neurobiological facets of ASD elucidating aetiology and the relationship between clinical symptomatology and neurobiology.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":" ","pages":"111910"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142547018","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":"Neuroanatomical alterations in young boys and adolescents with Klinefelter syndrome.","authors":"Lara C Foland-Ross, Tracy L Jordan, Matthew J Marzelli, Judith L Ross, Allan L Reiss","doi":"10.1016/j.pscychresns.2024.111929","DOIUrl":"10.1016/j.pscychresns.2024.111929","url":null,"abstract":"<p><p>Klinefelter syndrome (KS, 47,XXY) is a common sex chromosome aneuploidy in males that is characterized by pubertal developmental delays and a wide range of alterations in cognitive, social and emotional functioning. The neural bases of these behavioral symptoms, however, are unclear. A total of 130 boys and adolescents, including 67 males with KS (11.5 ± 2.8 years) and 63 typically developing (TD; control) males (10.6 ± 2.8 years) underwent MRI scanning and pubertal assessment. Group differences in regional gray matter volume was examined using voxel-based morphometry while controlling for age at scan and total gray matter volume. Thresholded statistical significance maps indicated widespread reductions in frontal and temporal and cerebellar gray matter in males with KS relative to TD males, as well as increases in parietal and occipital gray matter. Secondary analyses explored potential associations between GMV in these regions and pubertal development. Lower testicular volume was a significant predictor of reduced GMV in frontal, temporal and cerebellar subregions, even after accounting for group status (KS, TD). Taken together, these findings add support for a neuroanatomical phenotype of KS and provide initial evidence for a role of pubertal development in KS-associated differences in gray matter structure. Future studies that examine the influence of testosterone supplementation on GMV in males with KS are warranted.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"346 ","pages":"111929"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142786763","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":"Objective outcome prediction in depression through functional MRI brain network dynamics.","authors":"Jesper Pilmeyer, Stefan Rademakers, Rolf Lamerichs, Vivianne van Kranen-Mastenbroek, Jacobus Fa Jansen, Marcel Breeuwer, Svitlana Zinger","doi":"10.1016/j.pscychresns.2024.111945","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2024.111945","url":null,"abstract":"<p><strong>Research purpose: </strong>Subjective clinical decision-making in major depressive disorder (MDD) may result in low treatment effectiveness. This study aims to identify objective predictors of MDD outcome using resting-state functional MRI scans, acquired from 25 MDD patients at baseline. Over a year, patients were assessed every 3 months, labeled as positive or negative outcome (change in depression severity). Group independent component analysis (GICA) identified (sub)networks at different orders, from which static and dynamic (wavelet) fMRI features were extracted. Binary classifiers performed MDD outcome prediction at each follow-up.</p><p><strong>Principal results: </strong>The total coherence feature, reflecting network interactivity, yielded the highest performance (area under the curve (AUC) of 0.70). In the positive outcome group, total coherence between the default mode network and ventral salience network was increased at all follow-ups. Classification using this feature alone further demonstrated its discriminating capability (AUC of 0.76 ± 0.10 over all follow-ups). These results suggest that a higher switching capability between internal and external brain states predicts symptom improvement. Higher GICA orders, where major networks are divided into subnetworks, yielded optimal classification performance.</p><p><strong>Major conclusions: </strong>Total coherence, a dynamic fMRI measure, achieved the highest classification performance. These findings contribute to the identification of prognostic biomarkers in MDD.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"111945"},"PeriodicalIF":2.1,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142932502","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 changes in volumes of the limbic system and hypothalamic-subnuclei in patients with depression.","authors":"Daun Shin, Kyu-Man Han, Sun-Uk Lee, Byung-Jo Kim, Sung-Bom Pyun, Woo Suk Tae, Byung-Joo Ham","doi":"10.1016/j.pscychresns.2024.111942","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2024.111942","url":null,"abstract":"<p><strong>Background: </strong>Depression is consistently linked to changes in the hypothalamus, HPA axis, and limbic system, though the specific substructures involved remain unclear. This study aims to explore the relationship between depression and the volumes of specific nuclei within these brain regions. Understanding these connections could provide deeper insights into the biological mechanisms underlying depression.</p><p><strong>Methods: </strong>Seventy-three healthy individuals and 39 patients with depression were assessed using the Beck Depression Inventory or Hamilton Depression Rating Scale. All participants underwent 3.0T MRI, and the volumes of subnuclei in the hypothalamus and limbic system were measured.</p><p><strong>Results: </strong>The results revealed increased volumes in both the inferior tubular areas of the hypothalamus and the left hypothalamus in the patient group with depression. Moreover, the left infTub volume initially increased during the first three years of depression, followed by a decrease, suggesting distinct structural changes between early and chronic stages of the illness.</p><p><strong>Conclusions: </strong>Alterations in the left inferior tubular area volume suggest a connection between the hypothalamus and the chronicity of depressive symptoms. Further exploration of specific nuclei in the hypothalamus promises deeper insights into depression's biological mechanisms.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"347 ","pages":"111942"},"PeriodicalIF":2.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143010504","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}