Psychiatry Research: Neuroimaging最新文献

{"title":"Changed ventral striatum structural covariance and grey matter volume in depression during a one-year follow-up","authors":"Yong-ming Wang ,&nbsp;Liang-liang Chen ,&nbsp;Cheng-lei Wang ,&nbsp;Chao Yan ,&nbsp;Guang-rong Xie ,&nbsp;Xin-hua Yang","doi":"10.1016/j.pscychresns.2024.111887","DOIUrl":"10.1016/j.pscychresns.2024.111887","url":null,"abstract":"<div><p>Empirical findings suggest reduced cortico-striatal structural connectivity in patients with major depressive disorder (MDD). However, the relationship between the abnormal structural covariance and one-year outcome of first-episode drug-naive patients has not been evaluated. This longitudinal study aimed to identify specific changes of ventral striatum-related brain structural covariance and grey matter volume in forty-two first-episode patients with major depression disorder compared with thirty-seven healthy controls at the baseline and the one-year follow-up conditions. At the baseline, patients showed decreased structural covariance between the left ventral striatum and the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), right supplementary motor area (SMA) and left precentral gyrus and increased grey matter volume at the left fusiform and left parahippocampus. At the one-year follow-up, patients showed decreased structural covariance between the left ventral striatum and the right SFG, right MFG, left precentral gyrus and left postcentral gyrus, and increased structural covariance between the right ventral striatum and the right amygdala, right hippocampus, right parahippocampus, right superior temporal pole, right insula and right olfactory bulb and decreased volume at the left SMA compared with controls. These findings suggest that specific ventral striatum connectivity changes contribute to the early brain development of the MDD.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111887"},"PeriodicalIF":2.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136466","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":"No significant alteration in white matter microstructure in first-degree relatives of patients with obsessive-compulsive disorder","authors":"Hirofumi Tomiyama ,&nbsp;Keitaro Murayama ,&nbsp;Kiyotaka Nemoto ,&nbsp;Kenta Kato ,&nbsp;Akira Matsuo ,&nbsp;Mingi Kang ,&nbsp;Kenta Sashikata ,&nbsp;Osamu Togao ,&nbsp;Tomohiro Nakao","doi":"10.1016/j.pscychresns.2024.111884","DOIUrl":"10.1016/j.pscychresns.2024.111884","url":null,"abstract":"<div><p>Obsessive-compulsive disorder (OCD) is characterized by structural alteration within white matter tissues of cortico-striato-thalamo-cortical, temporal and occipital circuits. However, the presence of microstructural changes in the white matter tracts of unaffected first-degree relatives of patients with OCD as a vulnerability marker remains unclear. Therefore, here, diffusion-tensor magnetic resonance imaging (DTI) data were obtained from 29 first-degree relatives of patients with OCD and 59 healthy controls. We investigated the group differences in FA using whole-brain analysis (DTI analysis). For additional regions of interest (ROI) analysis, we focused on the posterior thalamic radiation and sagittal stratum, shown in recent meta-analysis of patients with OCD. In both whole-brain and ROI analyses, using a strict statistical threshold (family-wise error rate [FWE] corrected <em>p</em>&lt;.05 for whole-brain analyses, and <em>p</em>&lt;.0125 (0.05/4) with Bonferroni correction for ROI analyses), we found no significant group differences in FA. Subtle reductions were observed in the anterior corona radiata, forceps minor, cingulum bundle, and corpus callosum only when a lenient statistical was applied (FWE corrected <em>p</em>&lt;.20). These findings suggest that alterations in the white matter microstructure of first-degree relatives, as potential vulnerability markers for OCD, are likely subtle.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111884"},"PeriodicalIF":2.1,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0925492724001070/pdfft?md5=ec23e326b0b39f3faccc171125d1a4aa&pid=1-s2.0-S0925492724001070-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136465","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":"Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability","authors":"Pankaj Kumar Sahu,&nbsp;Karan Jain","doi":"10.1016/j.pscychresns.2024.111886","DOIUrl":"10.1016/j.pscychresns.2024.111886","url":null,"abstract":"<div><p>Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activity observed in alpha-EEG recordings. The suggested research provides evidence of the reliability of alpha-EEG rhythm in a Gated-Recurrent-Unit-based deep-learning model for investigating SZ. This study suggests Rudiment Densely-Coupled Convolutional Gated Recurrent Unit (RDCGRU) for the various EEG-rhythm-based (gamma, beta, alpha, theta, and delta) diagnoses of SZ. The model includes multiple 1-D-Convolution (Con-1-D) folds with steps greater than 1, which enables the model to programmatically and effectively learn how to reduce the incoming signal. The Con-1-D layers and numerous Gated Recurrent Unit (GRU) layers comprise the Exponential-Linear-Unit activation function. This powerful activation function facilitates in-deep-network training and improves classification performance. The Densely-Coupled Convolutional Gated Recurrent Unit (DCGRU) layers enable RDCGRU to address the training accuracy loss brought on by vanishing or exploding gradients, and this might make it possible to develop intense, deep versions of RDCGRU for more complex problems. The sigmoid activation function is implemented in the digital (binary) classifier's output nodes. The RDCGRU deep learning model attained the most excellent accuracy, 88.88 %, with alpha-EEG rhythm. The research achievements: The RDCGRU deep learning model's GRU cells responded superiorly to the alpha-EEG rhythm in EEG-based verification of SZ.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111886"},"PeriodicalIF":2.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095867","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":"Atlas-based structural analysis of prefrontal cortex atrophy in major depressive disorder: Correlations with severity and episode frequency","authors":"Aybars Kokce ,&nbsp;Merve Şahin Can ,&nbsp;Omur Karaca ,&nbsp;Emrah Ozcan ,&nbsp;İlter Kuş","doi":"10.1016/j.pscychresns.2024.111885","DOIUrl":"10.1016/j.pscychresns.2024.111885","url":null,"abstract":"<div><h3>Background</h3><p>Current models of major depressive disorder (MDD) primarily focus on the structural and functional changes in key prefrontal areas responsible for emotional regulation. Among these regions some sections such as the dorsal prefrontal area, has received limited attention regarding its structural abnormalities in MDD. This study aims to evaluate volumetric abnormalities in brain regions associated with markers of depression severity and episode frequency.</p></div><div><h3>Methods</h3><p>The study included 33 MDD patients and 33 healthy subjects. Using an atlas-based method, we measured the volumes of several key brain regions based on MRI data. The regions of interest included prefrontal and posterior sections of the middle frontal gyrus (MFG) and superior frontal gyrus (SFG). Additionally, we evaluated the volumes of the dorsal anterior cingulate cortex (dACC), perigenual (rostral) anterior cingulate cortex (pgACC), subgenual cingulate cortex (sgACC), posterior cingulate cortex (PCC), hippocampus (HPC), and parahippocampus (paraHPC). Hamilton Depression Scale (HAM-D) scores and count of the depressive episodes of patients were also obtained. A regression analysis with sex as the confounding factor has been made.</p></div><div><h3>Results</h3><p>Analysis of covariances, controlling for sex, showed significant atrophy in the sgACC in the depression group: F(1, 63) = 4.013, p = 0.049 (left) and F(1, 63) = 8.786, <em>p &lt;</em> 0.004 (right). Poisson regression, also controlling for sex, found that each additional depressive episode was associated with a significant reduction in left posterior MFG volume (0.952 times, 95 % CI, 0.906 to 1.000; p = 0.049).</p></div><div><h3>Conclusions</h3><p>Findings in this study highlight the structural abnormalities in MDD patients in correlation to either current depression severity or chronicity of the disease.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111885"},"PeriodicalIF":2.1,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095439","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 changes of functional brain networks in major depressive disorder by graph theoretical analysis of resting-state fMRI","authors":"Elnaz Akbarpouri Agziyart,&nbsp;Karim Abbasian,&nbsp;Somaye Makouei,&nbsp;Sana Beyg Mohammadi","doi":"10.1016/j.pscychresns.2024.111880","DOIUrl":"10.1016/j.pscychresns.2024.111880","url":null,"abstract":"<div><h3>Background</h3><p>Major Depressive Disorder (MDD), as a chronic mental disorder, causes changes in mood, thoughts, and behavior. The pathophysiology of the disorder and its treatment are still unknown. One of the most notable changes observed in patients with MDD through fMRI is abnormal functional brain connectivity.</p></div><div><h3>Methods</h3><p>Preprocessed data from 60 MDD patients and 60 normal controls (NCs) were selected, which has been performed using the DPARSF toolbox. The whole-brain functional networks and topologies were extracted using graph theory-based methods. A two-sample, two-tailed <em>t</em>-test was used to compare the topological features of functional brain networks between the MDD and NCs groups using the DPABI-Net/Statistical Analysis toolbox.</p></div><div><h3>Results</h3><p>The obtained results showed a decrease in both global and local efficiency in MDD patients compared to NCs, and specifically, MDD patients showed significantly higher path length values. Acceptable p-values were obtained with a small sample size and less computational volume compared to the other studies on large datasets. At the node level, MDD patients showed decreased and relatively decreased node degrees in the sensorimotor network (SMN) and the dorsal attention network (DAN), respectively, as well as decreased node efficiency in the SMN, default mode network (DMN), and DAN. Also, MDD patients showed slightly decreased node efficiency in the visual networks (VN) and the ventral attention network (VAN), which were reported after FDR correction with <em>Q</em> &lt; 0.05.</p></div><div><h3>Limitations</h3><p>All participants were Chinese.</p></div><div><h3>Conclusions</h3><p>Collectively, increased path length, decreased global and local efficiency, and also decreased nodal degree and efficiency in the SMN, DAN, DAN, VN, and VAN were found in patients compared to NCs.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111880"},"PeriodicalIF":2.1,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095868","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":"Impact of excessive abdominal obesity on brain microstructural abnormality in schizophrenia","authors":"Shinichi Yamada ,&nbsp;Shun Takahashi ,&nbsp;Daniel Keeser ,&nbsp;Katriona Keller-Varady ,&nbsp;Thomas Schneider-Axmann ,&nbsp;Florian J. Raabe ,&nbsp;Peter Dechent ,&nbsp;Thomas Wobrock ,&nbsp;Alkomiet Hasan ,&nbsp;Andrea Schmitt ,&nbsp;Peter Falkai ,&nbsp;Sohei Kimoto ,&nbsp;Berend Malchow","doi":"10.1016/j.pscychresns.2024.111878","DOIUrl":"10.1016/j.pscychresns.2024.111878","url":null,"abstract":"<div><p>Significant evidence links obesity and schizophrenia (SZ), but the brain associations are still largely unclear. 48 people with SZ were divided into two subgroups: patients with lower waist circumference (SZ-LWC: <em>n</em> = 24) and patients with higher waist circumference (SZ-HWC: <em>n</em> = 24). Healthy controls (HC) were included for comparison (HC: <em>n</em> = 27). Using tract-based spatial statistics, we compared fractional anisotropy (FA) of the whole-brain white matter skeleton between these three groups (SZ-LWC, SZ-HWC, HC). Using Free Surfer, we compared whole-brain cortical thickness and the selected subcortical volumes between the three groups. FA of widespread white matter and the mean cortical thickness in the right temporal lobe and insular cortex were significantly lower in the SZ-HWC group than in the HC group. The FA of regional white matter was significantly lower in the SZ-LWC group than in the HC group. There were no significant differences in mean subcortical volumes between the groups. Additionally, the cognitive performances were worse in the SZ-HWC group, who had more severe triglycerides elevation. This study provides evidence for microstructural abnormalities of white matter, cortical thickness and neurocognitive deficits in SZ patients with excessive abdominal obesity.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111878"},"PeriodicalIF":2.1,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122730","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":"Amygdala connectivity is associated with withdrawn/depressed behavior in a large sample of children from the Adolescent Brain Cognitive Development (ABCD) Study®","authors":"Elina Thomas ,&nbsp;Anthony Juliano ,&nbsp;Max Owens ,&nbsp;Renata B. Cupertino ,&nbsp;Scott Mackey ,&nbsp;Robert Hermosillo ,&nbsp;Oscar Miranda-Dominguez ,&nbsp;Greg Conan ,&nbsp;Moosa Ahmed ,&nbsp;Damien A. Fair ,&nbsp;Alice M. Graham ,&nbsp;Nicholas J. Goode ,&nbsp;Uapingena P. Kandjoze ,&nbsp;Alexi Potter ,&nbsp;Hugh Garavan ,&nbsp;Matthew D. Albaugh","doi":"10.1016/j.pscychresns.2024.111877","DOIUrl":"10.1016/j.pscychresns.2024.111877","url":null,"abstract":"<div><p>Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRS_D), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9–11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111877"},"PeriodicalIF":2.1,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0925492724001008/pdfft?md5=96d7f041b16dd36054f088964e2dc21f&pid=1-s2.0-S0925492724001008-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142130247","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":"Functional magnetic resonance imaging studies in bipolar disorder in resting state: A coordinates-based meta-analysis","authors":"Xia Nan ,&nbsp;Wenling Li ,&nbsp;Lin Wang","doi":"10.1016/j.pscychresns.2024.111869","DOIUrl":"10.1016/j.pscychresns.2024.111869","url":null,"abstract":"<div><p>Exploring changes in the intrinsic activity of the brain in people with bipolar disorder (BD) is necessary. However, the findings have not yet led to consistent conclusions. In this regard, this paper aims to extract more obvious differential brain areas and neuroimaging markers, for the purpose of providing assistance for early clinical diagnosis and subsequent treatment. We conducted a meta-analysis of whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) studies using seed-based d-mapping software that examined differences in amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) between patients with BD and healthy controls (HCs). Seed-based d-Mapping (formerly <em>Signed Differential Mapping</em>) with Permutation of Subject Images, or SDM-PSI, is a statistical technique for meta-analyzing studies of differences in brain activity or structure. A total of 16 articles involving 1112 individuals were included in this study for meta-analysis. This paper confidently analyzes the correlation between the clinical scales HAMD, HAMA, and YMRS, and the area of difference. We found significant changes that increased activation in the anterior connective and left lens nucleus, the nucleus of the shell, and BA 48 in BD patients compared with HC (<em>P</em> &lt; 0.05, uncorrected), as well as a significant correlation between HAMD and the left superior frontal gyrus (after FWE correction <em>P</em> &lt; 0.05). Therefore, basal ganglia and frontal cortex may have important significance in the pathogenesis and pathological basis of BD, making it an important issue to be attached importance to.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111869"},"PeriodicalIF":2.1,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141988734","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 study of somatization symptoms and low-frequency amplitude fluctuations of emotional memory in adolescent depression","authors":"Daming Mo ,&nbsp;Hongyu Zheng ,&nbsp;Wen Zheng Li ,&nbsp;Long Chen ,&nbsp;Rui Tao ,&nbsp;Hui Zhong ,&nbsp;Huanzhong Liu","doi":"10.1016/j.pscychresns.2024.111867","DOIUrl":"10.1016/j.pscychresns.2024.111867","url":null,"abstract":"<div><p>Studies have revealed that somatization symptoms are associated with emotional memory in adolescents with depressive disorders. This study investigated somatization symptoms and emotional memory among adolescents with depressive disorders using low-frequency amplitude fluctuations (ALFF). Participants were categorized into the somatization symptoms (FSS) group, non-FSS group and healthy control group (HC). The correctness of negative picture re-recognition was higher in the FFS and HC group than in the non-FSS group. The right superior occipital gyrus and right inferior temporal gyrus were significantly larger in the FSS group than those in the non-FSS and HC groups. Additionally, the ALFF in the superior occipital and inferior temporal gyrus were positively correlated with CSI score. Furthermore, the ALFF values in the temporal region positively correlated with correct negative image re-recognition. The negative image re-recognition rate was positively correlated with the ALFF in the left and right middle occipital gyri. These findings indicated that somatization symptoms in adolescent depression are associated with the superior occipital gyrus and inferior temporal gyrus. Notably, somatization symptoms play a role in memory bias within depressive disorders, with middle occipital and inferior temporal gyri potentially serving as significant brain regions.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111867"},"PeriodicalIF":2.1,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0925492724000908/pdfft?md5=3655c7bd141477ccb55f3baf42d8a0bb&pid=1-s2.0-S0925492724000908-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141996285","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":"Investigating the association between symptoms and functional activity in brain regions in schizophrenia: A cross-sectional fmri-based neuroimaging study","authors":"Indranath Chatterjee ,&nbsp;Bisma Hilal","doi":"10.1016/j.pscychresns.2024.111870","DOIUrl":"10.1016/j.pscychresns.2024.111870","url":null,"abstract":"<div><p>Schizophrenia is a persistent neurological disorder profoundly affecting cognitive, emotional, and behavioral functions, prominently characterized by delusions, hallucinations, disordered speech, and abnormal motor activity. These symptoms often present diagnostic challenges due to their overlap with other forms of psychosis. Therefore, the implementation of automated diagnostic methodologies is imperative. This research leverages Functional Magnetic Resonance Imaging (fMRI), a neuroimaging modality capable of delineating functional activations across diverse brain regions. Furthermore, the utilization of evolving machine learning techniques for fMRI data analysis has significantly progressive. Here, our study stands as a novel attempt, focusing on the comprehensive assessment of both classical and atypical symptoms of schizophrenia. We aim to uncover associated changes in brain functional activity. Our study encompasses two distinct fMRI datasets (1.5T and 3T), each comprising 34 schizophrenia patients for the 1.5T dataset and 25 schizophrenia patients for the 3T dataset, along with an equal number of healthy controls. Machine learning algorithms are applied to assess data subsets, enabling an in-depth evaluation of the current functional condition concerning symptom impact. The identified voxels contribute to determining the brain regions most influenced by each symptom, as quantified by symptom intensity. This rigorous approach has yielded various new findings while maintaining an impressive classification accuracy rate of 97 %. By elucidating variations in activation patterns across multiple brain regions in individuals with schizophrenia, this study contributes to the understanding of functional brain changes associated with the disorder. The insights gained may inform differential clinical interventions and provide a means of assessing symptom severity accurately, offering new avenues for the management of schizophrenia.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"344 ","pages":"Article 111870"},"PeriodicalIF":2.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0925492724000933/pdfft?md5=cbee441f2db4e8a546fdaa9b23048a71&pid=1-s2.0-S0925492724000933-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141978969","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}