Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

{"title":"Thalamic Nuclear Volumes in Fetal Alcohol Spectrum Disorders: from Adolescence to Middle-Age 20 Years Later.","authors":"Adolf Pfefferbaum, Edith V Sullivan, Manojkumar Saranathan, Kilian M Pohl, Amanda Bischoff-Grethe, Susan A Stoner, Edward P Riley","doi":"10.1016/j.bpsc.2025.04.002","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.04.002","url":null,"abstract":"<p><strong>Background: </strong>Midline orofacial and brain structures, including the multinucleated thalamus, may be differentially sensitive to prenatal alcohol exposure and vulnerable to accelerated aging.</p><p><strong>Methods: </strong>Two sets of MRI data separated by 20 years are reported for controls, individuals with fetal alcohol syndrome (FAS), and nondysmorphic individuals with heavy fetal alcohol exposure (FAE). MRI1 included 179 participants with 69 reassessed at MRI2. Segmentation produced estimates of bilateral thalamic volume and 10 bilateral nuclei, which were aggregated into Anterior, Ventral, Posterior, and Medial Volumes. Differences were assessed without and with correction for intracranial volume (ICV).</p><p><strong>Results: </strong>MRI1 revealed stepwise group differences in ICV, total thalamic volume, and Anterior and Ventral regions uncorrected for ICV, where Controls>FAE>FAS. Corrected for ICV, the smaller volumes endured in the Anterior and Ventral regions, although differences between FAE and FAS groups were attenuated. Nuclei volumes were selectively smaller in the alcohol-exposed groups than controls even after controlling for ICV. Longitudinally, thalamic volumes typically declined over time maintaining the stepwise effects and with little evidence for accelerated decline in the FAE or FAS groups.</p><p><strong>Conclusions: </strong>These novel data revealed stable deficits in thalamic nuclei of the groups with heavy fetal alcohol exposure. After 20 years, the deficits endured but without accelerated age-related decline and following the same aging pattern as controls. Despite parallel aging functions in all groups, ICV adjustment yielded volume deficits localized to the anterior and ventral thalamic nuclei, differing from patterns in the remaining thalamic nuclei and cortical brain structures.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014977","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":"Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs).","authors":"Najme Soleimani, Armin Iraji, Godfrey Pearlson, Adrian Preda, Vince D Calhoun","doi":"10.1016/j.bpsc.2025.03.015","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.015","url":null,"abstract":"<p><strong>Background: </strong>Mental illnesses extract personal and societal costs, leading to significant challenges in cognitive function, emotional regulation, and social behavior. These disorders are thought to result from disruptions in how different brain regions communicate with each other. Despite advances in neuroimaging, current methods are not always precise enough to fully understand the complexity of these disruptions. More advanced approaches are needed to better identify and characterize the specific brain network alterations linked to different psychiatric conditions.</p><p><strong>Methods: </strong>We employed a hierarchical approach to derive Double Functionally Independent Primitives (dFIPs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. dFIPs represent independent patterns of functional network connectivity (FNC) across the brain. Our study utilized a large multi-site dataset comprising 5805 individuals diagnosed with schizophrenia (SCZ), autism spectrum disorder (ASD), bipolar disorder (BPD), major depressive disorder (MDD), and healthy controls. We analyzed how combinations of dFIPs differentiate psychiatric diagnoses.</p><p><strong>Results: </strong>Distinct dFIP patterns emerged for each disorder. Schizophrenia was characterized by heightened cerebellar connectivity and reduced cerebellar-subcortical connectivity. In ASD, sensory domain hyperconnectivity was prominent. Some dFIPs displayed disorder-specific connectivity patterns, while others exhibited commonalities across multiple conditions. These findings underscore the utility of dFIPs in revealing neural connectivity alterations unique to each disorder, serving as unique fingerprints for different mental disorders.</p><p><strong>Conclusions: </strong>Our study demonstrates that dFIPs provide a novel, data-driven method for identifying disorder-specific functional connectivity patterns in psychiatric conditions. These distinct neural signatures offer potential biomarkers for mental illnesses, contributing to a deeper understanding of the neurobiological underpinnings of these disorders.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144048458","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":"Current status of EEG microstate in psychiatric disorders: a systematic review and meta-analysis.","authors":"Ágota Vass, Kinga Farkas, Orsolya Lányi, Tamás Kói, Gábor Csukly, János M Réthelyi, Máté Baradits","doi":"10.1016/j.bpsc.2025.04.001","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.04.001","url":null,"abstract":"<p><strong>Background: </strong>EEG microstates are promising biomarkers for psychiatric conditions, though prior meta-analyses mainly focused on schizophrenia and mood disorders. This study expands the analysis to a wider range of mental disorders, examining microstate variations across the psychosis and mood spectra and assessing medication effects on schizophrenia.</p><p><strong>Methods: </strong>Following PRISMA guidelines, we conducted a comprehensive literature search, identifying 24 studies meeting inclusion criteria. Analyses were performed across two psychiatric subgroups: psychotic disorders and mood disorders. We further conducted a subgroup analysis within the schizophrenia spectrum to examine differences in microstate properties between medicated and unmedicated patients.</p><p><strong>Results: </strong>Microstate C demonstrated significant increase in coverage, and occurrence in patients with schizophrenia, first episode psychosis and high risk for psychosis, and increased duration in schizophrenia. The absence of increased occurrence in medicated schizophrenia patients suggests that this feature may be state-dependent or modulated by treatment. In contrast, microstate D exhibited significant decreases in duration and coverage in unmedicated schizophrenia patients, indicating potential links with acute psychotic states.</p><p><strong>Conclusions: </strong>Our findings suggest that microstates C and D could serve as potential biomarkers in schizophrenia, with microstate D alterations linked to acute psychotic symptoms and microstate C potentially reflecting a chronic course or treatment effects. These results emphasize the clinical potential of microstate analysis in psychotic disorder diagnosis and treatment monitoring. The literature on microstate variations in neurodevelopmental and mood disorders is limited, highlighting the need for further research to determine their biomarker potential in these conditions.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144059834","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":"Beyond the Surface: Deep TMS Efficacy in Reducing Craving in Addictive Disorders. A Systematic Review and Meta-analysis.","authors":"Lilia Del Mauro, Alessandra Vergallito, Francantonio Devoto, Gaia Locatelli, Gabriel Hassan, Leonor J Romero Lauro","doi":"10.1016/j.bpsc.2025.03.012","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.012","url":null,"abstract":"<p><strong>Background: </strong>Substance use disorders (SUDs) and Gambling Disorder (GD) are addictive diseases with a chronic course. Due to the limited efficacy of conventional treatments, there is growing interest in alternative approaches targeting the altered neural circuits underlying these disorders. Deep Transcranial Magnetic Stimulation (dTMS) has emerged as a promising neuromodulation technique capable of reaching deep and bilateral brain regions. However, no definite recommendation for its use in addiction treatment exists. This study systematically reviewed and quantitatively analyzed dTMS effects in SUDs and GD.</p><p><strong>Methods: </strong>Following the PRISMA guidelines, we screened four electronic databases up to February 2024 and selected relevant English-written original research articles. Seventeen papers were included in the systematic review. As only a minority of studies employed a sham-controlled design, we ran the meta-analysis on a subset of 12 studies, computing the pre-post real stimulation standardized mean change (SMCC) as the effect size, using self-reported craving scores as the dependent variable.</p><p><strong>Results: </strong>The results showed a significant and large effect of real dTMS in reducing craving scores (SMCC = - 1.26, 95% CI [-1.67, - 0.86], p <.001). High heterogeneity across studies was found at both quantitative and qualitative levels.</p><p><strong>Conclusions: </strong>Results provide preliminary evidence supporting the effectiveness of dTMS for SUDs treatment. Current limitations and future directions are critically discussed, highlighting the need for further rigorous research to refine the therapeutic potential and develop consensus-based guidelines for dTMS clinical application.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143999085","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":"Accelerated aging of white matter in late-life depression: evidence from ¹⁸F-flutemetamol PET imaging.","authors":"Akihiro Takamiya, Thomas Vande Casteele, Filip Bouckaert, Margot Ga Van Cauwenberge, Maarten Laroy, François-Laurent De Winter, Patrick Dupont, Jan Van den Stock, Michel Koole, Koen Van Laere, Louise Emsell, Mathieu Vandenbulcke","doi":"10.1016/j.bpsc.2025.03.013","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.013","url":null,"abstract":"<p><strong>Background: </strong>Late-life depression (LLD) is associated with white matter (WM) alterations. Current evidence indicates amyloid PET tracers as sensitive and reliable markers for evaluating normal-appearing WM (NAWM) on magnetic resonance imaging (MRI), showing an association between lower uptake and Alzheimer's disease pathology and higher uptake with age-related changes. Utilizing this novel and reliable technique, we aimed to distinguish two hypothetical models for neurobiology of LLD: the pathological neurodegenerative model and the accelerated aging model.</p><p><strong>Methods: </strong>In this monocentric cross-sectional study, a total of 103 participants, including 61 patients with LLD (age 73.8±7.0 years, 41 female) and 42 healthy controls (age 72.5±7.6 years, 28 female), underwent PET imaging with ¹⁸F-flutemetamol, MRI, and clinical assessment. T2-weighted fluid-attenuated inversion recovery (FLAIR) images were segmented into WM hyperintensities (WMH) and NAWM.</p><p><strong>Results: </strong>¹⁸F-flutemetamol standardized uptake value ratio (SUVR) in WMH was significantly lower than that in NAWM (t=7.8, df=102, p<0.001). Compared to healthy controls, patients with LLD exhibited higher ¹⁸F-flutemetamol SUVR in both NAWM (p<0.001, Cohen's d=0.91) and WMH (p=0.005, d=0.56), even after controlling for age and ¹⁸F-flutemetamol SUVR in cortical gray matter.</p><p><strong>Conclusions: </strong>Our result of elevated ¹⁸F-flutemetamol uptake in NAWM does not align with the pathological neurodegenerative aging pattern observed in Alzheimer's disease but is in line with patterns of age-related changes. This distinction is crucial for the development of future targeted treatments.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065359","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":"Multiscale heterogeneity of white matter morphometry in psychiatric disorders.","authors":"Ashlea Segal, Robert E Smith, Sidhant Chopra, Stuart Oldham, Linden Parkes, Kevin Aquino, Seyed Mostafa Kia, Thomas Wolfers, Barbara Franke, Martine Hoogman, Christian F Beckmann, Lars T Westlye, Ole A Andreassen, Andrew Zalesky, Ben J Harrison, Christopher G Davey, Carles Soriano-Mas, Narcís Cardoner, Jeggan Tiego, Murat Yücel, Leah Braganza, Chao Suo, Michael Berk, Sue Cotton, Mark A Bellgrove, Andre F Marquand, Alex Fornito","doi":"10.1016/j.bpsc.2025.03.014","DOIUrl":"https://doi.org/10.1016/j.bpsc.2025.03.014","url":null,"abstract":"<p><strong>Background: </strong>Inter-individual variability in the neurobiological and clinical characteristics of mental illnesses are often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear.</p><p><strong>Methods: </strong>We applied Warped Bayesian Linear Regression normative models to T1-weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter-regional connections, specific brain regions, and spatially extended brain networks.</p><p><strong>Results: </strong>The specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions, and large-scale networks in up to 69% of individuals.</p><p><strong>Conclusions: </strong>The prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism, but not other disorders.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055402","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":"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 J White, Dedra Buchwald, Damien A Fair, Terry Jernigan, Martin P Paulus","doi":"10.1016/j.bpsc.2025.03.010","DOIUrl":"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":"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, but no research has been conducted to investigate their utility in psychiatry.</p><p><strong>Methods: </strong>We aimed to analyze the performance of model updating methods for predicting psychosis onset by 1 year in 780 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 with 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 3 updating methods improved the predictive performance compared with the original model (recalibration: p = .009; refitting: p = .020; dynamic updating: p = .001). The dynamic updating method demonstrated the best predictive performance (Harrell's C-index = 0.71; 95% CI, 0.60 to 0.82), calibration slope (slope = 1.12; 95% CI, 0.46 to 1.87), 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. Therefore, 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}