Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

{"title":"Transdiagnostic and Disorder-specific Neural Correlates of Emotion Processing in Major Depressive Disorder and Borderline Personality Disorder: Coordinate-based and Image-based Comparative Meta-Analyses.","authors":"Wanrong Peng, Suyao Liu, Jinyao Yi","doi":"10.1016/j.bpsc.2025.03.009","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.009","url":null,"abstract":"<p><strong>Background: </strong>Major Depressive Disorder (MDD) and Borderline Personality Disorder (BPD) involve substantial impairments in negative and positive emotions processing. This meta-analysis aims to identify both transdiagnostic and disorder-specific neural abnormalities during the processing of negative and positive stimuli for MDD and BPD.</p><p><strong>Methods: </strong>The current coordinate-based and image-based meta-analyses comprised 42 fMRI studies involving MDD (42 Negative studies vs. 22 Positive studies; 1,532 MDD patients vs. 1,481 healthy controls) and 25 involving BPD (23 Negative studies vs. 7 Positive studies; 522 BPD patients vs. 519 healthy controls).</p><p><strong>Results: </strong>Compared to healthy controls, MDD patients exhibited hyporeactivity in left precentral gyrus during negative emotion processing, and decreased activation in left temporal lobe, insula, and bilateral anterior cingulate cortex during positive emotion processing, while BPD patients displayed hyperreactivity in left hippocampus and amygdala and hyporeactivity in right inferior frontal gyrus during negative emotion processing. Compared to BPD, MDD exhibited greater hyporeactivity in bilateral anterior cingulate cortex during negative emotion processing and in left middle temporal gyrus during positive emotion processing. The transdiagnostic hyporeactivity of BPD and MDD was mainly located in left inferior and right middle frontal gyrus during negative emotion processing.</p><p><strong>Conclusions: </strong>Our findings highlight both distinct and transdiagnostic neural mechanisms of emotion processing for MDD and BPD.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ten Suggestions for Better Inference in Population Neuroscience Studies.","authors":"Wesley K Thompson, Chun-Chieh Fan, Evan White, Dedra Buchwald, Damien Fair, Terry Jernigan, Martin Paulus","doi":"10.1016/j.bpsc.2025.03.010","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.010","url":null,"abstract":"","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic updating of psychosis prediction models in individuals at ultra high-risk of psychosis.","authors":"Simon Hartmann, Dominic Dwyer, Isabelle Scott, Cassandra M J Wannan, Josh Nguyen, Ashleigh Lin, Christel M Middeldorp, Stephen J Wood, Alison R Yung, Patrick D McGorry, Barnaby Nelson, Scott R Clark","doi":"10.1016/j.bpsc.2025.03.006","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.006","url":null,"abstract":"<p><strong>Background: </strong>The performance of psychiatric risk calculators can deteriorate over time due to changes in patient population, referral pathways, and medical advances. Such temporal biases in existing models may lead to suboptimal decisions when translated into clinical practice. Methods are available to correct this bias, yet no research has been conducted to investigate their utility in psychiatry.</p><p><strong>Methods: </strong>We aimed to analyse the performance of model updating methods for predicting psychosis onset by one year in 784 individuals at ultra high-risk (UHR) of psychosis from the UHR 1000+ cohort - a longitudinal cohort of UHR individuals recruited to research studies at Orygen, Melbourne, Australia, between 1995 and 2020. Model updating was performed using a yearly adjusted model (recalibration), a continuously updated model (refitting), and a continuous Bayesian updating model (dynamic updating) and compared to a static logistic regression prediction model (original) regarding calibration, discrimination, and clinical net benefit.</p><p><strong>Results: </strong>The original model was poorly calibrated over the entire validation period. All three updating methods improved the predictive performance compared to the original model (recalibration: P= 0.014, refitting: P= 0.028, dynamic updating: P= 0.002). The dynamic updating method demonstrated the best predictive performance (Harrel's C-index = 0.70, 95% CI: [0.58, 0.81]), calibration slope (slope = 1.03, 95% CI: [0.38, 1.74]) and clinical net benefit over the entire validation period.</p><p><strong>Conclusions: </strong>Dynamic updating of psychosis prediction models may help to mitigate decreases in performance over time. Hence, existing psychosis prediction models need to be monitored for temporal biases to mitigate potentially harmful decisions.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Difficult to Treat Anxiety: A neurocomputational framework.","authors":"Martin P Paulus, Murray B Stein","doi":"10.1016/j.bpsc.2025.03.008","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.008","url":null,"abstract":"<p><p>Anxiety disorders, affecting approximately one in nine individuals globally, impose significant socioeconomic and health burdens, with many individuals failing to achieve symptom remission despite standard treatments. Difficult-to-Treat Anxiety (DTA) encompasses a broad spectrum of persistent anxiety disorders that remain refractory to conventional interventions, necessitating a shift from rigid response-based criteria to a mechanistically driven framework integrating computational psychiatry and systems neuroscience. Central to DTA is dysregulated approach-avoidance decision-making, where heightened punishment sensitivity, inflexible belief updating, and uncertainty misestimation drive persistent avoidance behaviors and reinforce maladaptive anxiety cycles. Computational modeling of reinforcement learning tasks reveals exaggerated Pavlovian biases and impaired exploratory learning, while predictive processing models highlight overestimation of threat and rigidity in safety learning, perpetuating chronic anxiety. Neural dysfunction in default mode and negative affective networks, characterized by hyperstable attractor states in the amygdala and impaired top-down regulation by the prefrontal cortex, further sustains maladaptive anxiety states. Novel interventions targeting these dysfunctions-such as neuromodulation, precision pharmacotherapy, and personalized digital therapeutics-offer potential breakthroughs in managing DTA. This review synthesizes current evidence on computational, neural, and behavioral mechanisms underlying DTA, proposing an integrative, process-targeted approach to assessment and treatment. Future research must refine biomarker-driven subtyping and individualized interventions, moving beyond trial-and-error approaches toward mechanistically informed, precision psychiatry for persistent anxiety disorders.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Limbic-Sensorimotor Tug of War for the Hippocampus: Dynamic Functional Connectivity as a Transdiagnostic Vulnerability Marker in Offspring of Emotion Dysregulation Patients.","authors":"Luigi F Saccaro, Farnaz Delavari, Ben Meuleman, Nader Perroud, Dimitri Van De Ville, Camille Piguet","doi":"10.1016/j.bpsc.2025.03.007","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.007","url":null,"abstract":"<p><strong>Background: </strong>Emotion dysregulation (ED) is a key transdiagnostic symptom in several psychiatric disorders such as borderline personality disorder (BPD), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). These disorders, here defined as ED disorders (EDD), share similarities in symptoms, comorbidity, and heritability, emphasizing the importance of a transdiagnostic approach to identify markers of vulnerability to EDD in high-risk populations, such as EDD patients' offspring (EDDoff). The hippocampus, central to ED, exhibits alterations across EDD.</p><p><strong>Methods: </strong>We employed a state-of-the-art approach (micro-co-activation patterns, μCAPs) to study the transdiagnostic dynamic functional connectivity (dFC) of hippocampal subregions from resting-state functional MRI of 201 participants (74 EDD patients, 57 EDDoff, 70 controls). μCAPs provide a data-driven differentiation within the seed region.</p><p><strong>Results: </strong>DFC between the sensorimotor network (SMN) and the hippocampal body was lower in EDD patients (p_FDR=0.0002) and EDDoff (p_FDR=0.01) compared to controls, with EDDoff displaying an intermediate pattern between EDD patients and controls. dFC between the limbic network (LN) and the hippocampal head was higher in EDD patients than in controls (p_FDR=0.01) and in EDDoff (p_FDR=0.01). A negative correlation was found between ED and SMN (p_FDR=0.01), suggesting increasing ED with decreasing SMN dFC with the hippocampus.</p><p><strong>Conclusions: </strong>Increased dFC between the hippocampal head and the LN, at the expense of the SMN, may represent a marker of disease in EDD patients. Lower dFC between the SMN and the hippocampal body may represent a marker of vulnerability to EDD in EDDoff, correlating with ED. Such a transdiagnostic construct represents a clinically relevant target for early interventions aimed at reducing vulnerability to EDD in high-risk populations.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intrinsic functional connectivity of right dorsolateral prefrontal cortex and hippocampus subregions relates to emotional and sensory-perceptual properties of intrusive trauma memories.","authors":"Quentin Devignes, Kevin J Clancy, Boyu Ren, Yara Pollmann, Justin T Baker, Isabelle M Rosso","doi":"10.1016/j.bpsc.2025.03.004","DOIUrl":"10.1016/j.bpsc.2025.03.004","url":null,"abstract":"<p><strong>Background: </strong>Trauma-related intrusive memories (TR-IMs) are core symptoms of posttraumatic stress disorder (PTSD). Prior research links reexperiencing symptoms with resting-state functional coupling between the right dorsolateral prefrontal cortex (dlPFC) and right hippocampus. However, prior work has not examined whether this negative coupling relates to TR-IMs, nor differentiated between the anterior and posterior hippocampus (aHPC/pHPC). This study examined relationships of TR-IM frequency and properties with resting-state negative coupling between the right dlPFC and right aHPC/pHPC in symptomatic trauma-exposed individuals with TR-IMs.</p><p><strong>Methods: </strong>Participants (N=109; 88 female) completed two weeks of ecological momentary assessments capturing TR-IM frequency and properties (intrusiveness, emotional intensity, vividness, visual properties, and reliving). Using resting-state functional magnetic resonance imaging, participant-specific 4-mm spheres were placed at the right dlPFC voxel most anticorrelated with the right aHPC and pHPC. Quasi-Poisson and linear mixed-effects models assessed relationships of TR-IM frequency and properties with right dlPFC-right aHPC and pHPC anticorrelation.</p><p><strong>Results: </strong>TR-IM emotional intensity was positively associated with right dlPFC-aHPC connectivity, while vividness and visual properties correlated with right dlPFC-pHPC connectivity. These associations remained significant after controlling for PTSD symptom severity and time since trauma. No significant associations emerged between TR-IM frequency, intrusiveness, or reliving, and anticorrelation with either hippocampal subregion.</p><p><strong>Conclusions: </strong>This study provides novel insights into the neural correlates of TR-IMs, highlighting the relevance of intrinsic negative coupling between the right dlPFC and aHPC/pHPC to their phenomenology. Further research on this circuit could advance understanding of component processes of trauma reexperiencing, a severe and treatment-refractory PTSD symptom.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliable multimodal brain signatures predict mental health outcomes in children.","authors":"Kathryn Y Manning, Alberto Llera, Catherine Lebel","doi":"10.1016/j.bpsc.2025.03.003","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.003","url":null,"abstract":"<p><strong>Background: </strong>Inter-individual brain differences likely precede the emergence of mood and anxiety disorders, however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health.</p><p><strong>Methods: </strong>In a large population-based cohort of children from the Adolescent Brain Cognitive Development (ABCD) study (N > 10K), we applied data-driven linked independent component analysis to identify linked variations in cortical structure and white matter microstructure that together predict longitudinal behavioural and mental health symptoms. Brain differences were examined in a sub-sample of twins depending on the presence of at-risk behaviours.</p><p><strong>Results: </strong>Two multimodal brain signatures at age 9-10y predicted longitudinal mental health symptoms from 9-12y, with small effect sizes. Cortical variations in association, limbic and default mode regions linked with peripheral white matter microstructure together predicted higher depression and anxiety symptoms across two independent split-halves. The brain signature differed amongst depression and anxiety symptom trajectories and related to emotion-regulation network functional connectivity. Linked variations of subcortical structures and projection tract microstructure variably predicted behavioural inhibition, sensation seeking, and psychosis symptom severity over time in male participants. These brain patterns were significantly different between pairs of twins discordant for self-injurious behaviour.</p><p><strong>Conclusions: </strong>Our results demonstrate reliable, multimodal brain patterns in childhood, before mood and anxiety disorders tend to emerge, that lay the foundation for long-term mental health outcomes and offer targets for early identification of children at-risk.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latent Profiles of Impulsivity and Emotion Regulation in Children with Externalizing Disorders are Associated with Alterations in Striatocortical Connectivity.","authors":"Joseph Aloi, Tahlia E Korin, Olivia K Murray, Kathleen I Crum, Katherine LeFevre, Mario Dzemidzic, Leslie A Hulvershorn","doi":"10.1016/j.bpsc.2025.02.013","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.02.013","url":null,"abstract":"<p><strong>Introduction: </strong>Children with externalizing disorders (EDs) often have difficulties with impulsivity and emotion regulation. These constructs have been associated with dysfunction in the recruitment of reward processing circuits and striatal connectivity with cortical networks. However, it is unclear to what extent co-presentations of impulsivity and emotion regulation are associated with differences in striatocortical connectivity.</p><p><strong>Methods: </strong>In Study 1, a latent profile analysis (LPA) was conducted in a sample of 198 youths with EDs (Oppositional Defiant Disorder and/or Conduct Disorder) to investigate co-presentation of impulsivity and emotion regulation symptoms. Participants completed the UPPS Impulsivity Scale (UPPS) and the Emotion Regulation Checklist (ERC). LPA was applied to the subscales of the UPPS and ERC. In Study 2, we examined 169 participants who completed a resting state fMRI scan to examine differences in striatocortical connectivity between profiles.</p><p><strong>Results: </strong>The LPA identified three profiles: Moderate Impulsivity (IMP)/Moderate Emotion Regulation, High IMP/Low Emotion Regulation (ER), and High IMP/Moderate Emotion Regulation. The two High IMP profiles were associated with greater connectivity between the posterior caudate nucleus and parietal cortex. The High IMP/Low ER profile was associated with increased connectivity between the anterior caudate and anterior insula.</p><p><strong>Discussion: </strong>The current data indicate that the profiles associated with high impulsivity are associated with greater caudate-parietal cortex connectivity while the profile associated with high impulsivity and impaired emotion regulation showed increased anterior caudate-AIC connectivity. The current work contributes to the literature by examining the relationship between heterogeneity of externalizing symptoms and functional connectivity.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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, Ines Aitsahalia, Krishan Kumar, Tobias Atkin, Kiyohito Iigaya","doi":"10.1016/j.bpsc.2025.02.014","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.02.014","url":null,"abstract":"<p><p>Anticipation of future experiences is a crucial cognitive function impacted in various psychiatric conditions. Despite significant research advancements, the mechanisms underlying altered anticipation remain poorly understood, and effective targeted treatments are largely lacking. This review proposes an integrated computational psychiatry approach to address 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 eating disorders, and summarizing the insights gained from extensive research using self-report scales and task-based neuroimaging, despite notable limitations. We then 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.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microstructural alterations in superficial white matter associated with anhedonia and suicidal ideation in major depressive disorder.","authors":"Yichen Zhang, Guorong Wu, Sara De Witte, Chris Baeken","doi":"10.1016/j.bpsc.2025.02.010","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.02.010","url":null,"abstract":"<p><strong>Background: </strong>Major depressive disorder (MDD) is characterized by impaired emotional and cognitive functions. Previous studies have focused on the long-range white matter bundles within the deep white matter connecting distant cortices. Less is known about the superficial white matter (SWM), which consists of short bundles connecting adjacent and precise cortices. We therefore investigated the differences in SWM between MDD patients and healthy controls (HCs) and its relationship with core clinical depressive symptoms.</p><p><strong>Methods: </strong>Probabilistic tractography was used to generate the SWM bundles in 62 antidepressant-free MDD patients and 77 HCs. Diffusion tensor imaging (DTI) and Neurite orientation dispersion and density imaging (NODDI) were used to compare the microstructural differences of SWM between two groups. correlations were calculated between the diffusion metrics in the SWM showing significant between-group differences and core clinical depressive symptoms.</p><p><strong>Results: </strong>Compared with HCs, MDD patients showed DTI metric changes in the SWM bundles connecting frontal-parietal-temporal-occipital cortices. For the NODDI metrics, MDD patients showed lower neurite density index in the SWM bundles connecting frontal-parietal-temporal cortices. Here, the neurite density index in the SWM bundles connecting prefrontal-insula regions was significantly negatively correlated with anhedonia and suicidal ideation. MDD patients displayed higher orientation dispersion index in the SWM bundles connecting parietal, occipital and posterior cingulate cortices.</p><p><strong>Conclusions: </strong>SWM plays a crucial role in the neuropathology of MDD. The decreased neurite density in the SWM connecting prefrontal-insula regions may underlie anhedonia and suicidal ideation. Furthermore, NODDI metrics may offer more specific detection of SWM microstructural abnormalities than DTI metrics.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}