Biological Psychiatry-Cognitive Neuroscience and Neuroimaging最新文献

{"title":"Mapping Neuroinflammation With Diffusion-Weighted Magnetic Resonance Imaging: A Randomized Crossover Study","authors":"Julia R. Plank ,&nbsp;Catherine A. Morgan ,&nbsp;Flavio Dell’Acqua ,&nbsp;Frederick Sundram ,&nbsp;Nicholas R. Hoeh ,&nbsp;Suresh Muthukumaraswamy ,&nbsp;Joanne C. Lin","doi":"10.1016/j.bpsc.2025.05.002","DOIUrl":"10.1016/j.bpsc.2025.05.002","url":null,"abstract":"<div><h3>Background</h3><div>The pathophysiology of neuroinflammation in psychiatric conditions remains poorly understood, highlighting the need for noninvasive tools that can measure neuroinflammation in vivo. We explored advanced diffusion-weighted magnetic resonance imaging (MRI) techniques for detection of low-level neuroinflammation induced by typhoid vaccine, with potential applications to psychiatric disorders.</div></div><div><h3>Methods</h3><div>Twenty healthy volunteers (10 males; median age 34, range 18–44 years) participated in a randomized, placebo-controlled, crossover design study. Participants underwent MRI before and after receiving placebo or vaccine in alternating sessions, separated by a washout period. Diffusion tensor (multishell and single shell), diffusion kurtosis, and neurite orientation dispersion and density imaging parameter maps were generated. Probabilistic tractography investigated differences in tract volume, fractional anisotropy, and mean diffusivity (MD) of the tracts. Thirteen tracts and 15 regions were analyzed using a region-of-interest (ROI) approach entered into linear mixed models to evaluate treatment effects.</div></div><div><h3>Results</h3><div>A treatment effect was observed on white matter tracts derived from XTRACT, with a global reduction in MD (<em>p</em> = .040). White matter tracts of interest showed increased axial kurtosis (<em>p</em> &lt; .001) while gray matter ROIs demonstrated increased mean and radial kurtosis (both <em>p</em>s = .038). Additionally, several correlations were found between the inflammatory marker interleukin 6 and diffusion parameters.</div></div><div><h3>Conclusions</h3><div>Our findings demonstrate that diffusion-weighted MRI may be sensitive to inflammation-induced microstructural changes in the brain. Future studies should integrate complementary techniques and clinical assessments to deepen our understanding of inflammatory pathophysiology and its implications for health outcomes in clinical populations.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 944-953"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transfer Learning of Deep Neural Networks Pretrained Using the ABCD Dataset for General Psychopathology Prediction in Korean Adolescents","authors":"Jundong Hwang ,&nbsp;Jae-eon Kang ,&nbsp;Soohyun Jeon ,&nbsp;Kyung Hwa Lee ,&nbsp;Jae-Won Kim ,&nbsp;Jong-Hwan Lee","doi":"10.1016/j.bpsc.2025.04.005","DOIUrl":"10.1016/j.bpsc.2025.04.005","url":null,"abstract":"<div><h3>Background</h3><div><span>In this study, we examined whether a deep neural network (DNN), trained to predict the general psychopathology factor (</span><em>p</em> factor) using functional magnetic resonance imaging (fMRI) data from adolescents in the ABCD (Adolescent Brain Cognitive Development) Study, would generalize to Korean adolescents.</div></div><div><h3>Methods</h3><div>We trained a scanner-generalization neural network (SGNN) to predict <em>p</em><span> factor scores from resting-state functional connectivity (RSFC) data of 6905 ABCD Study adolescents, controlling for MRI scanner–related confounds. Then, we transferred the pretrained SGNN to a DNN to predict </span><em>p</em> factor scores for 125 adolescents, including healthy individuals and individuals with major depressive disorder, using data from Seoul National University Hospital (SNUH). We compared the transferred DNN’s performance with that of kernel ridge regression (KRR) and a baseline DNN.</div></div><div><h3>Results</h3><div>The transferred DNN outperformed KRR (0.17 ± 0.16; 0.60 ± 0.07) and the baseline DNN (0.17 ± 0.16; 0.69 ± 0.11), with a higher Pearson’s correlation coefficient (0.29 ± 0.18) and lower mean absolute error (0.59 ± 0.09; <em>p</em><span> &lt; .005). We identified the default mode network (DMN) and visual network (VIS) as crucial functional networks for predicting </span><em>p</em> factors across both datasets. The dorsal attention network was specific to the ABCD Study dataset, while the cingulo-opercular and ventral attention networks were specific to the SNUH dataset.</div></div><div><h3>Conclusions</h3><div>The transferred SGNN successfully generalized to Korean adolescents. Altered RSFC in the DMN and VIS may serve as promising biomarkers for <em>p</em> factor prediction across diverse populations, addressing heterogeneity in demographics, diagnoses, and MRI scanner characteristics.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 926-935"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144045071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2451-9022(25)00230-7","DOIUrl":"10.1016/S2451-9022(25)00230-7","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Page A1"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144997632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging Inflammation and Brain Microstructure: Diffusion Magnetic Resonance Imaging as a Window Into Psychiatric Neurobiology","authors":"Lena K.L. Oestreich","doi":"10.1016/j.bpsc.2025.06.006","DOIUrl":"10.1016/j.bpsc.2025.06.006","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 900-902"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144997692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered Neural Responses to Punishment Learning in Conduct Disorder","authors":"Erik M. Elster ,&nbsp;Ruth Pauli ,&nbsp;Graeme Fairchild ,&nbsp;Maria McDonald ,&nbsp;Sarah Baumann ,&nbsp;Justina Sidlauskaite ,&nbsp;Stephane De Brito ,&nbsp;Christine M. Freitag ,&nbsp;Kerstin Konrad ,&nbsp;Veit Roessner ,&nbsp;Inti A. Brazil ,&nbsp;Patricia L. Lockwood ,&nbsp;Gregor Kohls","doi":"10.1016/j.bpsc.2025.01.003","DOIUrl":"10.1016/j.bpsc.2025.01.003","url":null,"abstract":"<div><h3>Background</h3><div>Conduct disorder (CD) is associated with deficits in the use of punishment for reinforcement learning (RL) and subsequent decision making, contributing to reckless, antisocial, and aggressive behaviors. Here, we used functional magnetic resonance imaging (fMRI) to examine whether differences in behavioral learning rates derived from computational modeling, particularly for punishment, are reflected in aberrant neural responses in youths with CD compared with typically developing control participants (TDCs).</div></div><div><h3>Methods</h3><div>A total of 75 youths with CD and 99 TDCs (9–18 years, 47% girls) performed a probabilistic RL task with punishment, reward, and neutral contingencies. Using fMRI data in conjunction with computational modeling indices (learning rate α), we investigated group differences for the 3 learning conditions in whole-brain and region of interest (ROI) analyses, including the ventral striatum and insula.</div></div><div><h3>Results</h3><div>Whole-brain analysis revealed typical neural responses for RL in both groups. However, linear regression models for the ROI analyses revealed that only the response pattern of the (anterior) insula during punishment learning was different in participants with CD compared with TDCs.</div></div><div><h3>Conclusions</h3><div>Youths with CD have atypical neural responses to learning from punishment (but not from reward), specifically in the insula. This suggests a selective dysfunction of RL mechanisms in CD that contributes to punishment insensitivity/hyposensitivity as a hallmark of the disorder. Because the (anterior) insula is involved in avoidance behaviors related to negative affect or arousal, insula dysfunction in CD may contribute to inappropriate behavioral decision making, which increases the risk for reckless, antisocial, and aggressive behaviors in affected youth.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 936-943"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing Altered Anticipation as a Transdiagnostic Target Through Computational Psychiatry","authors":"Pradyumna Sepúlveda ,&nbsp;Ines Aitsahalia ,&nbsp;Krishan Kumar ,&nbsp;Tobias Atkin ,&nbsp;Kiyohito Iigaya","doi":"10.1016/j.bpsc.2025.02.014","DOIUrl":"10.1016/j.bpsc.2025.02.014","url":null,"abstract":"<div><div>Anticipation of future experiences is a crucial cognitive function impacted in various psychiatric conditions<span>. Despite significant research advancements, the mechanisms that underlie altered anticipation remain poorly understood, and effective targeted treatments are largely lacking. In this review, we propose an integrated computational psychiatry<span><span> approach to addressing these challenges. We begin by outlining how altered anticipation presents across different psychiatric conditions, including schizophrenia, major depressive disorder, anxiety disorders, substance use disorders, and </span>eating disorders<span>, and summarizing the insights that have been gained from extensive research using self-report scales and task-based neuroimaging despite notable limitations. Then, we explore how emerging computational modeling approaches, such as reinforcement learning and anticipatory utility theory, could overcome these limitations and offer deeper insights into underlying mechanisms and individual variations. We propose that integrating these interdisciplinary methodologies can offer comprehensive transdiagnostic insights, aiding the discovery of new therapeutic targets and advancing precision psychiatry.</span></span></span></div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 903-917"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aberrant Aversive Learning Signals in the Habenula in Remitted Patients With Recurrent Depression","authors":"Jessica M. de Klerk-Sluis ,&nbsp;Hanneke Geugies ,&nbsp;Roel J.T. Mocking ,&nbsp;Caroline A. Figueroa ,&nbsp;Paul F.C. Groot ,&nbsp;Jan-Bernard C. Marsman ,&nbsp;Philip F.P. van Eijndhoven ,&nbsp;Dirk E.M. Geurts ,&nbsp;Henricus G. Ruhé","doi":"10.1016/j.bpsc.2025.04.006","DOIUrl":"10.1016/j.bpsc.2025.04.006","url":null,"abstract":"<div><h3>Background</h3><div>Hypersensitivity to punishment is one of the core features of major depressive disorder (MDD). Hypersensitivity to punishment has been proposed to originate from aberrant aversive learning. One of the key areas in aversive learning is the habenula. Although evidence for dysfunctional aversive learning in patients with depression is well established, whether this dysfunction and its neural correlates persist during symptomatic remission of depression remains largely unexplored.</div></div><div><h3>Methods</h3><div>Functional magnetic resonance imaging data from 36 medication-free remitted patients with recurrent MDD and 27 healthy control participants participating in a Pavlovian classical conditioning task were assessed within a computational modeling framework to evaluate temporal difference–related activation of the habenula during aversive learning. Furthermore, generalized psychophysiological interaction analyses were performed to assess functional connectivity of the temporal difference signal with the habenula as an a priori region of interest.</div></div><div><h3>Results</h3><div>Relative to healthy control participants, patients showed significantly increased temporal difference–related aversive learning activation in the bilateral habenula. This activation was correlated with residual symptoms in the remitted MDD group. Furthermore, patients exhibited decreased functional connectivity between the habenula and the ventral tegmental area compared with control participants.</div></div><div><h3>Conclusions</h3><div>The increased habenula activity during aversive learning, particularly during the expectation of punishment, together with decreased functional habenula–ventral tegmental area connectivity in remitted patients with MDD, reflect hypersensitivity to and/or inability to regulate the impact of aversive environmental cues and punishment.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 978-987"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 Clinical Prediction Models in Psychopathology: Can Transfer Learning Fix the “Illusory Generalizability” Problem?","authors":"Jason Smucny","doi":"10.1016/j.bpsc.2025.06.004","DOIUrl":"10.1016/j.bpsc.2025.06.004","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 9","pages":"Pages 897-899"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144997691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multivariate Association Between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders","authors":"Ju-Chi Yu ,&nbsp;Colin Hawco ,&nbsp;Lucy Bassman ,&nbsp;Lindsay D. Oliver ,&nbsp;Miklos Argyelan ,&nbsp;James M. Gold ,&nbsp;Sunny X. Tang ,&nbsp;George Foussias ,&nbsp;Robert W. Buchanan ,&nbsp;Anil K. Malhotra ,&nbsp;Stephanie H. Ameis ,&nbsp;Aristotle N. Voineskos ,&nbsp;Erin W. Dickie","doi":"10.1016/j.bpsc.2024.09.001","DOIUrl":"10.1016/j.bpsc.2024.09.001","url":null,"abstract":"<div><h3>Background</h3><div>Schizophrenia spectrum disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in unimodal (e.g., visual, auditory) and multimodal (e.g., default mode and frontoparietal) cortical networks. However, little is known about how such dysconnectivity is related to social and nonsocial cognition and how such brain-behavior relationships associate with clinical outcomes of SSDs.</div></div><div><h3>Methods</h3><div>We analyzed cognitive (nonsocial and social) measures and resting-state functional magnetic resonance imaging data from the SPINS [Social Processes Initiative in Neurobiology of the Schizophrenia(s)] study (247 stable participants with SSDs and 172 healthy control participants, ages 18–55 years). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSD group.</div></div><div><h3>Results</h3><div>The SSD group showed significantly lower differentiation on all 3 gradients. The first PLSC dimension explained 68.53% (<em>p</em> &lt; .001) of the covariance and showed a significant difference between the SSD and the control group (bootstrap <em>p</em> &lt; .05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (gradient 1); auditory, sensorimotor, and visual networks (gradient 2); and perceptual networks and the striatum (gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSD group.</div></div><div><h3>Conclusions</h3><div>These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 8","pages":"Pages 833-845"},"PeriodicalIF":4.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Analysis Reveals Hippocampal Subfield Vulnerabilities to Chronic Cortisol Overexposure: Evidence From Cushing’s Disease","authors":"Guosong Shang ,&nbsp;Tao Zhou ,&nbsp;Xinyuan Yan ,&nbsp;Kunyu He ,&nbsp;Bin Liu ,&nbsp;Zhebin Feng ,&nbsp;Junpeng Xu ,&nbsp;Xinguang Yu ,&nbsp;Yanyang Zhang","doi":"10.1016/j.bpsc.2024.12.015","DOIUrl":"10.1016/j.bpsc.2024.12.015","url":null,"abstract":"<div><h3>Background</h3><div>Chronic cortisol overexposure plays a significant role in the development of neuropathological changes associated with neuropsychiatric and neurodegenerative disorders. The hippocampus, the primary target of cortisol, may exhibit characteristic regional responses due to its internal heterogeneity. In this study, we explored structural and functional alterations of hippocampal (HP) subfields in Cushing’s disease (CD), an endogenous model of chronic cortisol overexposure.</div></div><div><h3>Methods</h3><div>Utilizing structural and resting-state functional magnetic resonance imaging data from 169 participants (86 patients with CD and 83 healthy control participants [HCs]) recruited from a single center, we investigated specific structural changes in HP subfields and explored the functional connectivity alterations driven by these structural abnormalities. We also analyzed potential associative mechanisms between these changes and biological attributes, neuropsychiatric representations, cognitive function, and gene expression profiles.</div></div><div><h3>Results</h3><div>Compared with HCs, patients with CD exhibited significant bilateral volume reductions in multiple HP subfields. Notably, volumetric decreases in the left HP body and tail subfields were significantly correlated with cortisol levels, Montreal Cognitive Assessment scores, and quality of life measures. Disrupted connectivity between the structurally abnormal HP subfields and the ventromedial prefrontal cortex may impair reward-based decision making and emotional regulation, with this dysconnectivity being linked to structural changes in right HP subfields. Another region that exhibited dysconnectivity was located in the left pallidum and putamen. Gene expression patterns associated with synaptic components may underlie these macrostructural alterations.</div></div><div><h3>Conclusions</h3><div>Our findings elucidate the subfield-specific effects of chronic cortisol overexposure on the hippocampus, enhancing understanding of shared neuropathological traits linked to cortisol dysregulation in neuropsychiatric and neurodegenerative disorders.</div></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"10 8","pages":"Pages 865-876"},"PeriodicalIF":4.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}