Nature Mental Health

General distress cuts across psychiatric symptom domains, yet its computational correlates remain poorly defined. We examined whether drift rate--a core parameter indexing the efficiency of evidence accumulation--is more strongly associated with general distress than with domain-specific symptoms. In a cross-sectional online sample of 441 adults from the general population, participants completed a perceptual and value-based decision-making task, symptom assessments, and cognitive testing. Drift rates were estimated using hierarchical drift-diffusion modeling. Individuals with severe symptom elevations showed robust reductions in drift rate, particularly for value-based decisions. Mixed-effects models demonstrated that general distress, indexed by the Positive Symptom Distress Index, was more strongly associated with value-based than perceptual drift rate, even after accounting for all symptom domains. Value-based drift rate also explained variance in general distress beyond that accounted for by elevated symptoms across domains and selectively attenuated associations with somatization and paranoid symptoms. These findings suggest that value-based evidence accumulation captures a transdiagnostic component of distress-related impairment that is not reducible to symptom burden alone.

Language transforms subjective internal states into observable behavior, enabling investigation of the neurocognitive dynamics central to psychiatric conditions. Intense emotional and physiological responses to evocative drug-related contexts precipitate craving and drug seeking in substance use disorders, yet sensitive, accessible behavioral markers of the underlying neural dynamics remain elusive. In this fMRI study, we analyzed individuals unconstrained verbal recall of their subjective experiences after watching a drug-themed movie, including inpatients in treatment for heroin use disorder (HUD) and healthy controls, with speech recorded outside the scanner under minimal instructions. The semantic context of these accounts, assessed using transformer-based embeddings, effectively predicted both HUD diagnosis and treatment progression, with earlier treatment characterized by heightened self-reference and drug focus but less socially oriented recall. Semantic similarities between individuals reflected synchronized activation patterns in dorsal attention and visual networks during movie viewing, linking motivated attentional processing to later recall. With treatment, most HUD-biased semantic features shifted toward control-like patterns, while drug focus persisted; the semantic-neural link was attenuated though partially remained. These results suggest that spontaneous speech, collected offline, can provide a sensitive behavioral readout of both treatment effects and neural encoding of a complex, personally relevant, drug-related context. offering a scalable approach for monitoring neurocognitive dynamics in real-world settings.

Current psychiatric diagnoses are not defined by neurobiological measures which hinders the development of therapies targeting mechanisms underlying mental illness 1,2. Research confined to diagnostic boundaries yields heterogeneous biological results, whereas transdiagnostic studies often investigate individual symptoms in isolation. There is currently no paradigm available to comprehensively investigate the relationship between different clinical symptoms, individual disorders, and the underlying neurobiological mechanisms. Here, we propose a framework that groups clinical symptoms derived from ICD-10/DSM-V according to shared brain mechanisms defined by brain structure, function, and connectivity. The reassembly of existing ICD-10/DSM-5 symptoms reveal six cross-diagnostic psychopathology scores related to mania symptoms, depressive symptoms, anxiety symptoms, stress symptoms, eating pathology, and fear symptoms. They were consistently associated with multimodal neuroimaging components in the training sample of young adults aged 23, the independent test sample aged 23, participants aged 14 and 19 years, and in psychiatric patients. The identification of symptom groups of mental illness robustly defined by precisely characterized brain mechanisms enables the development of a psychiatric nosology based upon quantifiable neurobiological measures. As the identified symptom groups align well with existing diagnostic categories, our framework is directly applicable to clinical research and patient care.

Cognitive control supports adaptive responses in an ever-changing world. While alterations in cognitive control have been consistently observed in a range of psychiatric disorders, the neural mechanisms giving rise to this behavioral variation remain elusive. Here, we tested whether the ability to flexibly recruit recurring brain activation patterns (i.e., brain states) may serve as an intermediate phenotype supporting cognitive control in individuals with a spectrum of clinical symptoms. We leveraged machine learning and external validation to explore this question in three independent, transdiagnostic datasets (N>600), including participants with anxiety disorder, schizophrenia, mood disorder, substance use disorders, post-traumatic stress disorder, obsessive-compulsive disorder, and neurodevelopmental disorder. To capture the multifaceted nature of cognitive control, we assessed two of its components, inhibition and shift, using both task-based and questionnaire data. Flexible brain state engagement predicted all cognitive control metrics in previously unseen individuals transdiagnostically, regardless of which dataset was used for model training. Connectome-based predictive modeling also revealed that shared brain networks underpinned flexible brain state engagement in a transdiagnostic manner. Leveraging brain network dynamics, we further observed that moments of more flexible brain state engagement aligned with moments of network connectivity related to better cognitive control within the same individual. This temporal alignment was replicated in all three datasets with heterogeneous samples. Altogether, this study provides robust evidence that flexible engagement of brain state may support both inter- and intra-individual differences in cognitive control across individuals with diverse mental health profiles. Funding sources F31AA032179; R01MH121095

Interoception--the sensing and perception of the internal viscera--is widely cast as a transdiagnostic mechanism linking brain-body interaction to mental illness. Prevailing models propose that altered interoceptive ability reflects a core liability underlying diverse psychiatric symptoms. We tested this hypothesis in a large community sample (N = 547) using psychophysically optimised tasks spanning cardiac and respiratory domains, combined with hierarchical Bayesian modelling and comprehensive symptom profiling. Contrary to this central prediction, objective interoceptive sensitivity, precision, and metacognitive insight were largely unrelated to general symptom burden or specific mental health dimensions. In contrast, self-reported interoceptive sensibility showed moderate associations with symptoms, but semantic similarity analyses suggest these reflect conceptual rather than mechanistic overlap. These findings challenge the prevailing view that objective interoceptive sensitivity is a broad marker of psychopathology, prompting a reconsideration of how we measure interoception in mental health research.

Substance use disorders (SUD) are chronic conditions with devastating effects on brain health, functioning, and survival. In this study, we compared brain morphometry of 2,782 individuals with SUD to 1,951 controls and assessed the topographic overlap of these differences with brain connectivity and receptor architecture. Across SUD, we identified a morphometric signature involving frontal, parietal, temporal and limbic systems that overlapped with cortical hub regions and harbored cortical and subcortical disease epicenters. Findings were highly consistent across six substances and numerous robustness and generalizability analyses. Transdiagnostic comparisons showed high spatial overlap of SUD epicenters with those of schizophrenia and bipolar disorder, suggesting shared network-constrained cortical differences. Finally, multivariate mapping revealed that SUD brain differences aligned with two neurotransmitter axes contrasting cannabinoid-opioid and dopaminergic systems. These findings indicate that addiction-related brain differences are shaped by connectome and neurotransmitter architecture, positioning brain network and neurochemical organization as key principles of SUD-related brain alterations.

Brain imaging-derived phenotypes (IDPs) serve as underlying functional intermediates in psychiatric disorders, both of which are highly polygenic and heritable. Observational studies have elucidated the correlation between IDPs and psychiatric disorders, yet no systematic screening of IDPs to confer the causal liability in such disorders. We conducted a bidirectional two-sample Mendelian randomization framework to explore the causality of 1,901 IDPs on 10 psychiatric disorders and established the BrainMR database (http://brainmr.online/idp2psy/Index.php). We identified 17 causalities in forward MR analyses and 14 causalities in reverse MR analyses, which all rigorously examined them through various sensitivity analyses. The top significant relationship in forward was a unit lower volume of right central lateral of the thalamic nuclei, which was causally associated with an increased anorexia nervosa risk with an estimated OR of 0.52 (95% CI 0.41-0.64, P = 3.32 x 10-9). In reverse, the top significant IDP to be affected was the area of superior segment of the circular sulcus of the insula in the right hemisphere, which was increased by the reason of SCZ risk with an estimated association effect size of 0.068 (95% CI 0.046-0.090, P = 1.12 x 10-6). Overall, our study provides unique insights into causal pathways of psychiatric disorders at the imaging levels.

Childhood and adolescence represent a critical period in which neurodevelopmental psychiatric conditions emerge; traditional case-control approaches often underestimate the complexity and co-occurrence of psychiatric conditions, calling for a transdiagnostic approach as a complementary measure. Open-access data sharing initiatives provide an opportunity to decipher structural- and functional-based organisational constraints on the relationship between brain connectivity and psychopathology. Using a highly heterogenous and comorbid neurodevelopmental sample of children and adolescents aged between 6 and 17 years old at-risk of neurodevelopmental conditions (N = 174, 114 males, mean age 10.72 {+/-} 2.21 years), and age-matched neurotypical controls (N = 27, 12 males, mean age 10.65 {+/-} 2.07 years), we identified a multivariate association, or latent variable, between resting-state functional connectivity and psychopathology. We extensively benchmarked this latent construct to develop a more parsimonious account of childhood psychopathology though an analytical framework spanning biological maps, brain connectivity, and behaviour. Participant-level expression of this latent brain-behaviour association differed by diagnostic burden and symptomatology, and pre-empted longitudinal psychopathology. Whilst diagnostic status was useful for interpretation, the latent construct transcended traditional diagnostic borders, revealing a neurotypical-neurodivergent continuum. The relationship between functional connectivity and neurodevelopmental psychopathology was circumscribed by functional connectivity networks (visual, fronto-parietal, and dorsal attention) and cytoarchitectonic class (primary/secondary sensory and primary sensory cortices). The latent variable aligned with magnetoencephalography-defined electrophysiological alpha (), high-gamma ({gamma}), and theta ({theta}) frequency bands, and was enriched across cortical distributions of astrocytes and excitatory neurones. The connectivity signature was significantly aligned with the archetypal sensorimotor-to-association axis and validated in an independent sample of pre-adolescents (N = 3504), with the strongest alignment with the principal component of gene expression and myelination and were relatively less enriched in cortical regions related to language, indicating a protective effect, and more positively enriched in regions related to executive functioning, conferring greater risk of psychopathology. Together, our findings suggest that the predictive link between functional connectivity and common symptoms of neurodevelopmental psychopathology are circumscribed by underlying macroscale anatomical, functional, and cognitive-related hierarchies.

Human social interactions rely on the ability to reflect on ones own and others internal states and traits--a process known as mentalizing. Impaired or altered mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total N=390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas, respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based mentalizing about self and others--present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions. Author NoteThis work was funded by a Starting Grant from the European Research Council (ERC, 101041087) to LKo, a German Academic Exchange Service (DAAD) doctoral grant and a Network of European Neuroscience Schools (NENS) exchange fellowship to DA, an R01 grant from the U.S. National Institutes of Mental Health (R01MH125414-01) to JAH and DAS, a Junior Leader Fellowship from "la Caixa" Foundation (LCF/BQ/PR22/11920017) to PFC, a Consolidator Grant from the European Research Council (ERC, 648082) to LKr, R37, R01 support from the U.S. National Institutes of Mental Health (R37MH076136 to TDW, MH116026 to TDW and L. Chang [PI], R01EB026549 to TDW and M. Lindquist [MPIs]), an NIMH grant (P50MH094258-01A1) to R. Adolphs, and a CIC Brain and Mental Health Chair from the Neurodis foundation to AT. LvdM acknowledges a European Science Foundation EURYI grant (044035001) that funded her doctoral studies (PI: A. Aleman). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. The funders had no role in study design, data analysis, manuscript preparation, or publication decisions.

Cocaine use disorder (CUD) detrimentally impacts personal health, social relationships, and economic opportunity. Here, we assess CUD-associated shifts in brain dynamics using Network Control Theory and examine how they align with previously identified changes in neurological systems and behavioral profiles of people with CUD. The SUDMEX CONN dataset consists of multi-modal MRI, cocaine use metrics, behavioral measures, and demographics of individuals with CUD (N=132, 71 CUD). We identified recurring brain activity states and used NCT to calculate the transition energy (TE) between pairs of states. ANCOVAs examined global and regional TE associations with drug use group (CUD vs controls (NC)), years of CUD, and risk-taking behaviors. We identified potential mechanisms driving the differences by correlating CUD-related regional TE effects with neurotransmitter/receptor systems. People with CUD had significantly lower global TE and default mode, dorsal attention and limbic network TE compared to non-user controls, particularly in regions enriched for noradrenaline and mu opioid receptors. Longer duration of CUD was associated with more decreased global TE, top-down TE, default mode, control and ventral attention network TE, and regional TE enriched for excitatory neurotransmitters and receptors. People with CUD needed to expend more global and top-down TE to perform better on a risk-taking task (the Iowa Gambling task), an effect which was not found in NCs. Our analysis of whole-brain activity dynamics provides a link between the effects of upstream glutamatergic excitotoxicity and/or opioid receptor dysfunction, and downstream weakening of inhibitory control that is central to CUD.

Psychotic-like experiences (PLEs) include a range of sub-threshold symptoms that resemble aspects of psychosis but do not necessarily indicate the presence of psychiatric illness. These experiences are highly prevalent in youth and are associated with developmental disruptions across social, academic, and emotional domains. While not all youth who report PLEs develop psychosis, many develop other psychiatric illnesses during adolescence and adulthood. As such, PLEs are theorized to represent early markers of poor mental health. Here, we characterized the similarities and differences in the neurobiological underpinnings of childhood PLEs across the sexes using a large sample from the ABCD Study (n=5,260), revealing sex-specific associations between functional networks connectivity and PLEs. We find that although the networks associated with PLEs overlap to some extent across the sexes, there are also crucial differences. In females, PLEs are associated with dispersed cortical and non-cortical connections, whereas in males, they are primarily associated with functional connections within limbic, temporal parietal, somato/motor, and visual networks. These results suggest that early transdiagnostic markers of psychopathology may be distinct across the sexes, further emphasizing the need to consider sex in psychiatric research as well as clinical practice.

ObjectiveTo delineate the phenotype of juvenile myoclonic epilepsy (JME) with a focus on obsessive-compulsive personality disorder (OCPD) using multimodal psychiatric, neuropsychological, quantitative EEG (qEEG), and structural MRI markers within a predictive-processing/free-energy framework. MethodsWe prospectively studied 65 patients with JME and 68 matched healthy controls (HC). Participants completed DSM-IV SCID I/II interviews and a neuropsychological battery assessing working memory, psychomotor speed, mental flexibility, divided attention, inhibition, and phasic/tonic alertness; standard EEG and high-resolution structural MRI were acquired. Groups comprised HC and JME subgroups without psychiatric comorbidity, with non-OCPD Axis I/II diagnoses, and with OCPD. Welchs t-tests (FDR-corrected) and Hedges g quantified neuropsychological and alpha-band coherence differences. Surface-based analyses assessed cortical thickness/surface area. Exploratory regressions tested associations of OCPD, seizure freedom, and antiseizure medication (ASM) load with cognition; Kendalls tau tested coherence-cognition associations. ResultsCompared with HC, JME showed broad executive-attentional impairment, most pronounced in patients with psychiatric comorbidity. The OCPD subgroup exhibited particularly large slowing in psychomotor speed, inhibition (reaction time), and tonic alertness versus HC, while OCPD versus non-OCPD JME differences did not survive multiple-comparison correction. qEEG showed increased interhemispheric frontal and decreased temporal alpha coherence in JME, with temporal hypo-coherence strongest in those with psychiatric comorbidity; within JME, OCPD was linked to increased left fronto-temporal alpha coherence. In the MRI subsample, JME-OCPD demonstrated increased cortical thickness in left medial orbitofrontal and anterior cingulate regions (vs HC and vs JME without OCPD) and additional posterior occipito-temporal clusters versus HC. Regression and coherence-cognition associations were weak and non-significant after FDR correction. SignificanceJME features syndrome-level executive-attentional dysfunction and altered fronto-temporal network organization. Comorbid OCPD marks a subgroup with accentuated cognitive slowing and distinct medial prefrontal/cingulate structural and left fronto-temporal connectivity signatures, aligning with predictive-processing accounts of rigid, over-precise high-level priors. Key pointsJME is linked to broad executive-attentional impairment versus healthy controls. Psychiatric comorbidity amplifies cognitive deficits in JME. JME with OCPD shows particularly large slowing/inhibitory-control deficits versus controls, while OCPD vs non-OCPD differences within JME are modest. Alpha-band EEG coherence indicates altered network organization in JME and an OCPD-related increase in left fronto-temporal coherence within JME Surface-based MRI suggests an OCPD-related structural phenotype in JME, involving medial orbitofrontal/anterior cingulate cortical thickening

Complex clinical presentations are common in youth seeking mental health treatment, complicating attempts to identify specific biological underpinnings to guide precision psychiatry. We defined four classes of such youth based on their symptom profiles and identified unique patterns of amygdala functional connectivity in each class. Subjects were 215 youth who varied along major symptom dimensions commonly associated with pediatric affective psychopathology: depression, irritability, anxiety, and attention-deficit/hyperactivity (ADHD). We used latent profile analysis to identify classes of symptom patterns. Functional MRI data were obtained while subjects completed a gender identification task of face-emotions that varied in emotion type and intensity. We used generalized psychophysiological interaction analysis to examine associations between the probability of being in each symptom class and amygdala functional connectivity. The likelihood of being in the class with high parent-reported irritability and ADHD symptoms was associated with amygdala connectivity to the insula and superior temporal gyrus while processing high-intensity angry and fearful faces; to the precuneus while processing intensity across emotions; and to the ventrolateral prefrontal cortex across all task conditions. The likelihood of being in the class with high anxious and depressive symptoms was negatively associated with amygdala-thalamic connectivity across task conditions. This is the first study to identify distinct associations between symptom profile classes and amygdala connectivity in a transdiagnostic sample of youth. These neural correlates provide external validity to latent classes derived from symptom clusters. This is an essential first step toward identifying the biological basis of common transdiagnostic symptom presentations in youth.

Understanding the neurobiological basis of mental health disorders and their symptoms is a central goal of research in psychiatry. Yet, identifying robust brain-psychopathology associations with neuroimaging remains difficult, in part due to substantial heterogeneity within and comorbidity between diagnostic categories. Transdiagnostic latent factor models aim to address this structure by separating shared and unique symptom variance. This can potentially yield more reliable and neurobiologically-relevant dimensions of psychopathology. However, the extent to which latent factor models improve brain-psychopathology associations remains largely unclear. Using two large developmental cohorts, we compared transdiagnostic bifactor models, correlated factor models, and typical summary scores derived from the Child Behaviour Checklist (CBCL) in their reliability and multivariate associations with whole-brain structure (MRI) and function (resting-state fMRI). We found no consistent evidence that latent factors (bifactor or correlated factor models) strengthened reliability or brain-psychopathology associations, relative to summary scores. Whole-brain predictive models revealed broadly distributed neural signatures that were highly similar between corresponding factor and summary score constructs, with general psychopathology factors and total problem summary scores approaching numerical equivalence. Bifactor scores did, however, display more distinct neural signatures between general, internalising, and externalising dimensions than did summary or correlated factor scores. These results suggest that phenotypic modelling of psychopathology alone does not systematically strengthen the predictive utility of psychiatric neuroimaging, possibly reflecting fundamental limits on the amount of explainable symptom variance by brain features. While latent factor models may aid in distinguishing neural correlates between constructs, improving phenotypic assessment may be necessary for improvements to brain-psychopathology association strength.

BackgroundNormative modeling of brain development has gained traction for quantifying individual deviations in maturation. The brain age gap (BAG), the difference between predicted age from MRI features and chronological age, offers a potential individualized normative metric of neurodevelopment. However, consistent patterns across psychiatric disorders remain elusive, and no studies have examined whether BAG can predict developmental trajectories within an inclusive continuous model of youths cognition and behavior. MethodsUsing longitudinal data from the Adolescent Brain Cognitive Development Study (ages 9-15, n=9,074), we built 8 region-specific brain age models using volumes, thicknesses, and surface areas of parcels from the Brainnetome adolescent atlas. We derived psychiatric diagnoses from a parental questionnaire. Multivariate linear regression was used to assess case-control differences and cross-sectional continuous cognitive/behavioral profiles. We modeled cognitive/behavioral trajectories using a multivariate joint latent-class mixed model and assessed the relationship with BAG values using multinomial logistic regression. ResultsChildren with ADHD showed delayed maturation across multiple regions (Cohens d: - 0.12 to -0.08), while subcortical BAG emerged as a transdiagnostic indicator of delayed development (d: -0.07, pfdr = 0.024). Accelerated maturation characterized the high cognition and low symptom profile, while the inverse was found for the low cognition profile. Three developmental trajectories were identified: stable, towards externalizing behaviors, or internalizing behaviors. Widespread accelerated maturation predicted evolution towards internalizing behaviors but was protective against the externalizing trajectory. ConclusionsIntegrating BAG with continuous cognitive and behavioral profiles yielded a plausible framework for early identification of atypical trajectories, potentially contributing to personalized medicine in psychiatry.

1Psychopathy is a multifaceted construct encompassing affective, interpersonal, behavioural, and antisocial traits. Intrinsic brain organization, captured via functional connectivity, is widely used to map brain-behaviour relationships and to characterize the neural underpinnings of psychopathology. Prior work reports associations between psychopathic traits and altered connectivity in the frontoparietal control, default mode, and salience networks. However, current evidence is constrained by small sample sizes and the reliance on Western, Educated, Industrialized, Rich, and Democratic populations. Therefore, cross-cultural predictive modeling is crucial for identifying robust and generalizable biomarkers linked to psychopathic traits. To address these gaps, we tested whether resting-state functional connectivity (rsFC) predicts psychopathic traits in a non-Western community cohort. Participants (n=97, 52 females, community sample, Japan) completed the Self-Reported Psychopathy Scale-Short Form (SRP-SF) and underwent structural and resting-state functional magnetic resonance imaging. Connectome-based Predictive Modeling (CPM) with cross-validation was applied, and generalizability was evaluated in an independent dataset (n=107, 68 females, community sample, Germany). Across both cohorts, CPM failed to predict psychopathy scores out-of-sample, regardless of model parameters, psychopathic subdimensions, or potential sex differences. Post-hoc analyses indicated, however, that individuals with higher psychopathy scores exhibited more homogeneous rsFC patterns, whereas those with lower scores showed greater variability, suggesting score-dependent heterogeneity in brain-behaviour mapping. These findings highlight key challenges for predictive modeling and point to several future directions, including larger samples, the use of non-linear models, and potentially a shift toward individual-level connectome characterization to better capture heterogeneous neural substrates of similar behavioural phenotypes.

Attention-deficit/hyperactivity disorder and anxiety disorders are highly prevalent in youth and are characterized by substantial heterogeneity and frequent co-occurrence. This transdiagnostic complexity challenges conventional diagnostic frameworks that rely on symptom-based categories, which often obscure underlying dimensional and neurobiological mechanisms and offer limited neurobiological specificity. To address these issues, we developed a deep learning-based brain-behavior modeling framework that integrates clinically salient functional connectivity with cognitive and behavioral measures to identify interpretable dimensions and biologically grounded subtypes (biotypes). We applied our model to the Adolescent Brain Cognitive Development (ABCD) dataset comprising 3,508 children aged 9-11 years and revealed two reproducible brain-behavior dimensions that captured variation in cognitive control and emotion-attention regulation. These dimensions further yielded three distinct biotypes, each exhibiting unique symptom profiles and distinct brain development. We tested the robustness and generalizability of the dimensions and corresponding biotypes in an independent cohort of 224 age-matched participants from the Healthy Brain Network (HBN) and documented their early expression before symptom onset during adolescence. These findings highlight the utility of brain-behavior dimensions for elucidating heterogeneous psychiatric presentations and advance a biologically grounded framework for early classification and potential clinical translation in youth mental health.

OCD has been characterized by recent data as a disorder of cognition. Recent data also show pathology in prefrontal-subcortical networks. We leveraged cross-species prefrontal-subcortical cytoarchitectonic homologies in order to parse anatomical abnormalities in people with OCD into higher resolution areas and neuronal networks. We established that the anatomical abnormalities associated with OCD predominantly reside in a neuronal network associated with emotional processing. We further provide evidence that current tests do not accurately dissociate emotion from cognition and so relying on them risks mis-stating the role of prefrontal-subcortical networks. Taken together, these findings reveal the neglect of the role of emotion in the pathophysiology of OCD. BackgroundRecent advances in the cytoarchitectonic parcellation of the human brain have significant implications for major psychiatric conditions such as obsessive-compulsive disorder (OCD). Brodmanns areas have remained in use as the histological map of the human brain, framing its functional correlates in health and disease. However, cytological research has continued to refine these divisions in some cases substantially. For instance, the 16 areas in Brodmanns prefrontal cortex have expanded to 63, delivering a four-fold increase in granular resolution. These contemporary cytoarchitectonic areas have been parcellated into distinct prefrontal-striatal networks responsible for (i) the control of emotions and visceral organs, (ii) mental representation and classification of external objects, and (iii) the control of visual attention. Interacting pathology across prefrontal-striatal circuits makes OCD a paradigmatic condition upon which to apply these advances. The enhanced granular and network resolution this provides could transform human brain imaging from the original divisions of 1909 to higher resolution delineations, for example, providing precise mediolateral partitioning of the orbitofrontal cortex, thereby distilling the substrates of obsessions and compulsions. AdvancesHere we provide a meta-review of existing reports of thousands of people with OCD to reveal impairments spanning sensory integration, affective arousal, cognitive control, and motor action selection. Behavioral data previously interpreted as implicating only cognitive abnormalities have failed to detect cognitive impairment in children and adolescents with OCD casting doubt on the sensitivity of conventional tests and the temporal relationship between apparent pathology in adults and OCD symptoms. Therefore, by relying on that behavioral evidence alone we risk mis-characterizing OCD solely as a disorder of cognition. Moreover, the presence of sensorimotor and neuroimaging abnormalities in young people with OCD indicate the chronological primacy of undifferentiated abnormalities in neuronal structure and function. Neuronal correlates of OCD symptoms were found to map evenly into emotional-visceral and object assessment networks; within the visual attention network only the premotor cortex had substantive abnormality. Tasks reported as measuring cognition also distributed equally across networks further calling into question the physiological fidelity of these tasks. In contrast, tasks reported as measuring emotion mapped faithfully onto the emotional-visceral network. Volumetric changes in people with OCD also implicated the emotional-visceral network, in which the number of abnormalities were double those in the object assessment network. OutlookAlthough conventional behavioral tasks characterize OCD as a cognitive disorder, associated anatomical abnormalities are, in fact, distributed across two distinct neuronal networks responsible for (i) the control of emotions and visceral organs and (ii) the representation of external objects. The predominance of abnormalities in an emotional-visceral neuronal network contrasts with the paucity of research on emotional processing in OCD relative to tasks reported to test cognition, showing an inflated attribution of cognitive relative to emotional dysfunction in the pathophysiology of OCD. The histologically derived orbital and medial prefrontal cortex subregions, shown here as selectively affected in people with OCD, provide higher resolution candidate treatment targets for neurostimulation and other therapeutics. Extending our current work to other conditions could identify transdiagnostic neural signatures of psychiatric symptoms. One-Sentence SummaryStructural brain changes in people with OCD reside predominantly in a neuronal network responsible for emotional control. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/22280808v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@15834f1org.highwire.dtl.DTLVardef@1fbf666org.highwire.dtl.DTLVardef@eddd00org.highwire.dtl.DTLVardef@48568f_HPS_FORMAT_FIGEXP M_FIG C_FIG OCD as a pathology of cytoarchitectureNeuronal networks derived from cross-species studies of cell structure, projections, and function transform the granular resolution of human brain imaging analysis to reveal the role of an emotional-visceral network in the pathophysiology of OCD.

Eating disorders (EDs) are complex psychiatric conditions that often emerge during adolescence, and affected individuals frequently demonstrate high rates of psychiatric comorbidity, particularly with depressive and anxiety disorders. Although risk for EDs reflects both genetic and neurobiological factors, knowledge of how genetic risk for EDs relates to neurobiology and psychiatric symptoms during critical developmental periods remains limited. We therefore implemented a novel multivariate framework, which sought to advance knowledge of the etiology of EDs by simultaneously estimating associations between genetic risk, brain structure and ED-related psychopathology symptoms in over 4,500 adolescents of European ancestry from the Adolescent Brain and Cognitive Development study (M(SD)age=119.29(7.49) months). Polygenic scores for anorexia nervosa (AN PGS) and body mass index (BMI PGS) were generated and related to three morphometric brain features-- cortical thickness, surface area and subcortical grey matter volume--and to latent psychopathology factors using structural equation modeling. We identified a three-factor structure of ED-related psychopathology symptoms: eating, distress and fear factors. Increased BMI PGS were uniquely associated with greater eating factor scores, whereas AN PGS were unrelated to psychopathology factors. Moreover, genetic risk for high BMI and for AN had distinct neural correlates, where greater BMI PGS predicted widespread increases in cortical thickness and reductions in surface area while AN PGS were nominally related to reduced caudate volume. Altered default mode and visual network thickness was associated with greater eating factor scores, whereas distress and fear factor scores reflected a shared reduction in somatomotor network thickness. Our novel findings indicate that greater genetic risk for high BMI and altered cortical thickness of canonical brain networks underpin ED symptomatology in early adolescence. As neurobiological factors appear to shape disordered eating earlier in the life course than previously thought, these results underscore the need for early detection and intervention efforts for EDs.

Posttraumatic stress disorder (PTSD) is a highly heterogeneous psychiatric disorder, complicating efforts to identify consistent biological markers and develop targeted treatments for individuals exposed to trauma. Recent research has identified a distinct intrusive-hypervigilant (IH) phenotype, which is characterized by heightened intrusive reexperiencing and hypervigilance symptoms along with elevated levels of pituitary adenylate cyclase-activating polypeptide (PACAP), a neuropeptide involved in stress response via amygdala signaling. In an independent sample of 172 symptomatic trauma-exposed adults, we replicated this IH phenotype using latent profile analysis of Clinician-Administered PTSD Scale for DSM-5 symptom severity ratings and expanded its biological characterization using resting-state functional magnetic resonance imaging (rs-fMRI). Consistent with prior work, the identified IH group demonstrated more severe intrusive reexperiencing and hypervigilance symptoms and higher PACAP levels compared to groups with generally High or Low symptom severity. Additionally, the IH phenotype exhibited stronger functional connectivity of the centromedial, but not basolateral, amygdala with regions in the occipital cortex, precuneus, and medial prefrontal cortex - areas primarily within the Default Mode and Visual Networks. Meta-analytic decoding linked these regions to mental imagery, memory processing, fear, and threat perception. These findings support the existence of an IH phenotype of posttraumatic stress that may exhibit a distinct biological profile, characterized by exaggerated interactions between memory, threat, and arousal systems that may be mediated by PACAP and its effects of amygdala connectivity. This phenotype may serve as a promising target for precision psychiatry approaches, including pharmacological and neurotherapeutic interventions that modulate PACAP signaling and amygdala connectivity.