Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is a risk factor for later brain disorders. Here, we characterize the relationship between ADHD status and white matter cellularity across development and examine associations with medication, using a novel biophysical diffusion MRI model in youth aged 9 to 14 years. Methods: The ABCD Study(R) is a longitudinal cohort study with three biennial waves of brain MRI collection. Twenty-seven white matter tracts were delineated using multi-shell diffusion-weighted imaging (DWI) and tractography. Intracellular isotropic (RNI) and directional (RND) diffusion were quantified using the Restriction Spectrum Imaging (RSI) model. Longitudinal linear mixed-effect models characterize the effects of ADHD status and medication use on white matter cellularity across three waves. Results: By wave: 9,426 participants at baseline (mean [SD] age: 9.92 [0.63] years; 48.7% Female; 12.2% with ADHD), 6745 participants at 2-year (11.95 [0.65] years; 46.8% Female; 11.3% with ADHD), and 2,483 participants at 4-year (14.07 [0.69] years; 46.0% Female; 11.8% with ADHD). ADHD was associated with decreased RNI in 20 tracts at age 9, with evidence of developmental trajectory differences suggesting attenuation over early adolescence. We found enduring ADHD-associated decreases in RND of 16 tracts spanning ages 9 to 14 years, with methylphenidate effects on 2 tracts. Low-motion sensitivity analyses confirmed robust RNI findings, but not RND findings. ConclusionsADHD was associated with reductions in isotropic diffusion in white matter tracts, and possibly with complementary reductions in directional diffusion of select tracts. Isotropic diffusion findings suggest atypical glial cellularity in white matter during late childhood.

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examined whether scalp electroencephalography (EEG) data features beyond spectral power, including waveform shape, broadband spectral structure, and signal complexity, provide complementary information for predicting cognitive and clinical outcomes. EEG was recorded from 200 adults spanning a broad range of neuropsychiatric symptom severity while they completed three WM task paradigms: Sternberg spatial WM (SWM), delayed face recognition (DFR), and dot pattern expectancy (DPX). Separate machine learning models were trained on EEG features from the encoding, delay, and probe phase of each task to predict participants task accuracy, reaction time (RT) variability, WM capacity, and psychopathology scores (Brief Psychiatric Rating Scale). A split-half analytic framework was used, with cross-validated model development in an exploratory dataset (N=100) and evaluation of statistically significant models in a held-out validation dataset (N=100). In the exploratory dataset, SWM task data best predicted WM capacity, DPX task data predicted RT variability, and DFR task data predicted psychopathology, suggesting that these three WM paradigms engage distinct neural processes relevant to different outcomes. No models reliably predicted task accuracy. Models incorporating features beyond spectral power generally outperformed power-only models, and task-derived features outperformed resting-state-derived features. However, only those models predicting WM capacity and RT variability generalized to the validation dataset; models predicting psychopathology did not. These findings demonstrate functional heterogeneity across WM paradigms, show that complementary EEG features enhance predictive modeling, and highlight the importance of rigorous validation for identifying robust brain-behavior relationships.

BackgroundNaturalistic fMRI provides an ecologically valid window into social brain function, yet binary diagnostic labels may obscure neural signatures linked to the continuous spectrum of social deficits. We investigated whether social brain alterations in autism spectrum disorder (ASD) follow a categorical, dimensional, or "dual-track" architecture. MethodsWe analyzed fMRI data from 428 youth (262 ASD, 166 typically developing; ages 5-22) watching two films: The Present and Despicable Me. Using Principal Component Analysis (PCA) to quantify primary (PC1) and secondary (PC2) synchronization, we employed variance partitioning to disentangle the contributions of categorical diagnosis from continuous symptom severity (Social Responsiveness Scale-2, SRS-2). ResultsDuring The Present, reduced synchronization was widespread. In social-motivational hubs (medial prefrontal cortex, caudate), reductions were largely explained by variance shared between diagnosis and SRS-2 scores. In contrast, the left amygdala exhibited a unique dimensional association with SRS-2 scores independent of categorical diagnosis. Secondary response patterns (PC2), reflecting complex temporal integration, revealed further unique dimensional effects in the cuneus. Notably, these signatures were stimulus-dependent, manifesting during the emotionally complex narrative of The Present but not during the slapstick-oriented Despicable Me. ConclusionsWhile core social-motivational hubs reflect overlapping diagnostic and dimensional deficits, the amygdala and secondary visual patterns provide distinct, dimension-specific signatures of social impairment. This variance partitioning approach supports a Research Domain Criteria (RDoC) framework, highlighting the necessity of integrating dimensional assessments and narrative complexity to characterize the neural architecture of autism.

Exposure is considered the most active element of cognitive behavioral therapy (CBT) for pediatric anxiety, and its efficacy is theorized to depend on cognitive control and its supporting neural substrates (e.g., central executive [CEN], salience [SN], and default mode networks [DMN]). However, little work has identified how CBT, or exposure specifically, modulates intrinsic connectivity of these networks. Progress may be limited by heterogeneity in network connectivity in anxiety, which may obscure treatment-related effects in group-averaged analyses. This randomized clinical trial (RCT) leverages person-specific network modeling to test how exposure-focused CBT (EF-CBT) influences resting-state connectivity of cognitive control networks in pediatric anxiety, relative to an active control (relaxation mentorship training; RMT). Youth aged 7-18 years with an anxiety disorder (N = 104) or low/no anxiety (L/NA; N = 37) completed resting-state fMRI scans before being randomized to EF-CBT or RMT. Resting-state connectivity was reassessed following treatment (or commensurate time L/NA youth) in 113 participants. Changes in within-CEN, CEN-SN, and CEN-DMN density were examined using Group Iterative Multiple Model Estimation, which yields sparse, person-specific networks capturing both shared and individual connectivity structure. At baseline, anxious youth exhibited lower density within-CEN, between CEN-SN, and between CEN-DMN than L/NA youth. Treatment effects differed by intervention: EF-CBT selectively increased (i.e., normalized) CEN-SN density, whereas RMT increased within-CEN density. These findings demonstrate dissociable effects of exposure and relaxation on cognitive control network organization in pediatric anxiety. Exposure-focused CBT uniquely strengthens coordination between control and salience systems, consistent with a mechanism supporting top-down control of threat-related signals during exposure. Network-based measures of cognitive control may help identify mechanistic targets for optimizing and personalizing treatment. Clinical Trial NumberNCT02810171.

BackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) affects approximately 7.6% of children globally and exhibits heterogeneous cognitive and behavioral manifestations. Conventional group-level MRI analyses often obscure individual variability in brain structure, limiting understanding of personalized neuroanatomical profiles. ObjectiveThis study quantified individualized gray matter volume (GMV) deviations in children with ADHD using age- and sex-matched normative structural MRI references. MethodsStructural MRI data from 31 children with ADHD (16 males, 15 females; ages 7-15) and 413 typically developing controls (TDC; ages 7-22) were analyzed. Voxel-based morphometry extracted regional GMV across prefrontal cortex, striatal nuclei, and cerebellar vermis. Individual deviations were calculated as z-scores relative to normative distributions and categorized as typical, mild, moderate, strong, and extreme. ResultsLateral and orbital prefrontal regions exhibited the highest deviations: for females, the Lateral Orbital Gyrus (LOrG) showed 33.3% mild-to-strong deviations and 13.3% extreme deviations, while the Opercular Inferior Frontal Gyrus (OpIFG) had 73.3% mild-to-strong deviations. In males, the LOrG showed 31.2% moderate, 6.2% strong, and 18.8% extreme deviations. Striatal nuclei exhibited mixed patterns: female caudate volumes were typical in 33.3% of participants, moderate-to-extreme deviations occurred in 46.7%; male putamen was typical in 31.2%, with 37.5% showing strong or extreme deviations. Cerebellar vermis values were mostly typical (50-60%) with occasional mild-to-strong deviations. Medial and superior frontal regions remained largely typical (40-73%). ConclusionChildren with ADHD display heterogeneous and region-specific GMV deviations, most pronounced in lateral and orbital prefrontal cortex and select striatal regions. Individualized z-score profiling captures variability obscured in group averages, supporting personalized neuroanatomical assessment for understanding ADHD and guiding targeted treatment.

Background. Major depressive disorder (MDD) is characterized by altered frontal alpha oscillations. Transcranial alternating current stimulation (tACS) can normalize aberrant oscillations in MDD, yet the daily dynamics of tACS target engagement of alpha oscillations in depression remain unclear. Methods. In a double-blind randomized controlled trial (NCT03994081), 20 participants with MDD received verum or sham 10 Hz tACS (40 min/day, 5 days) targeted to left and right dorsolateral prefrontal cortex (F3/F4). High-density EEG was collected pre/post-stimulation each day to quantify within-session and cumulative changes in alpha power and functional connectivity (wPLI). Results. Verum stimulation produced late-emerging, session-specific alpha power decreases compared to sham, with robust day (D)4 post-pre reductions at both IAF and 10 Hz across frontal and parietal regions (t=-2.42 to -3.82, p<0.05; parietal t=-3.82, pFDR<0.05). Whole-brain topographical analysis confirmed a distinct condition x D4 effect at left prefrontal cortex (t=2.9, pFWE<0.05, cluster permutation). Connectivity changes emerged earlier and more transiently, with D2 bilateral frontal wPLI reductions (t=-2.53, p<0.05). Cumulative analyses (change from D1) showed significant wPLI decreases on D2 and D3 (t=-2.65 and t=-2.46; p<0.05). Exploratory clinical correlations showed that the D4 IAF power decrease was associated with increased reward sensitivity (spearman rho= -0.6, p<0.05, cluster-corrected). Conclusions. Alpha-tACS produced a temporally distinct neural response: an early, transient decrease in functional connectivity on D2, which may have driven a later suppression of left prefrontal alpha power on D4, correlated with clinical and behavioral improvements. These results delineate target engagement and validation mechanisms in a multi-day tACS trial, supporting optimized dosing in future tACS interventions.

Deficits in inhibitory control are common across a wide range of psychiatric disorders and are closely linked to symptom severity, including emotional dysregulation, anxiety, substance misuse, and self-harm, making them an appealing target for intervention. Cognitive training offers a low-cost, scalable, and non-invasive strategy to strengthen inhibitory control; however, most existing paradigms target only a single facet of inhibition and rarely account for environmental influences, such as affective context. To address these gaps, we developed a computerized inhibitory control training paradigm to simultaneously engage three components of inhibition: preemptive, proactive, and reactive, while embedding trials within positive and negative affective contexts to assess the impact of emotional stimuli. Across two online experiments, participants completed the GAMBIT task in one session (Experiment 1, N = 300) or repeated over three sessions (Experiment 2, N = 65). The task included No-Go trials to train preemptive inhibition, stop-signal trials for reactive inhibition, and stop-signal anticipation trials to train proactive inhibition. Affective images of differing valence were presented as background stimuli to evaluate their impact on inhibitory performance. In Experiment 1, participants showed higher accuracy on No-Go versus reference Go trials ({beta}=1.45, SE=0.09, p<.001), confirming successful manipulation of preemptive inhibition. Reaction times were slower during anticipation trials across two different conditions ({beta}=0.16, SE=0.04, p<.001; {beta} = 0.07, SE = 0.04, p = 0.047), consistent with proactive slowing when anticipating a potential stop signal. Additionally, positive affective images ({beta} = 0.10, SE= 0.009, p < 0.001) further slowed RTs, indicating emotional interference with proactive control. In Experiment 2, the pattern of higher No-Go accuracy was replicated ({beta} = 0.91, SE = 0.11, p < .001) and accuracy generally improved over sessions ({beta} = 0.38, SE = 0.06, p < .001). In anticipation trials, RTs become shorter across sessions (session 2: {beta} = -0.25, SE = 0.06, p < .001; session 3: {beta} = -0.45, SE = 0.06, p < .001), reflecting practice-related gains, and SSRTs decreased over time (F(2,56) = 6.26, p = .004), consistent with enhanced reactive inhibition. Proactive inhibition was modulated by affective images, with both negative ({beta} = 0.04, SE = 0.02, p = .039) and positive ({beta} = 0.16, SE = 0.02, p < .001) affective images associated with slower RTs. Participants also reported reductions in self-assessed temper control by the last session (W = 25.5, p = .007, q = .037, d = -0.51) and usability ratings were high (all means [&ge;] 3.87/5). Together, these findings show that this paradigm recruits multiple forms of inhibitory control and yields training-related improvements in both performance and affective outcomes. This provides preliminary validation of a scalable, fully online inhibitory control training tool targeting multiple dissociable inhibitory processes within affective contexts. The approach holds promise as an accessible transdiagnostic intervention to support symptom improvement across psychiatric disorders, with future work needed to evaluate clinical efficacy in patient populations.

Neuroimaging markers that capture interindividual differences may aid diagnosis and patient stratification, whereas those sensitive to intraindividual variation may inform prognosis and treatment monitoring. Yet, most machine-learning research in ADHD has emphasised interindividual prediction, leaving open whether neuroimaging can predict within-person cognitive changes in ADHD. Using a longitudinal ADHD-enriched dataset, the Oregon ADHD-1000 study (n = 594; 1,053 annual timepoints), we developed multimodal markers from resting-state functional and structural MRI to predict cognitive functioning. These markers showed good out-of-sample accuracy (r =.459) and performed comparably in children with and without ADHD. They explained 29.09% of interindividual variance in cognitive functioning, 33.48% of intraindividual cognitive trajectories, and 60.87% of intraindividual age-related cognitive development. They also accounted for substantial portions of the association between cognitive functioning and hyperactivity (58.79%) and inattention (25.99%). Together, these findings provide foundational evidence that f/sMRI-based markers can longitudinally track cognitive functioning, underscoring their potential, once further developed, for prognosis and treatment monitoring.

Background: Major depressive disorder (MDD) is associated with altered brain structure and evidence of accelerated brain aging. However, previous studies have been limited by clinical samples with mixed medication status and multiple mood states, modest sample sizes, small percentage of MDD individuals older than 65 years of age, and/or reliance on summary-level data. Methods: Harmonized T1-weighted MRI from MDD (n = 645), all medication-free and in a current depressive episode, and matched healthy controls (n = 645), segmented into 145 regional volumes, from 11 sites in COORDINATE-MDD consortium. Brain age gap (BAG) was estimated using gradient boosting regression with nested cross-validation. Group differences in BAG (and age-corrected BAG [cBAG]) were examined across age strata. Regional contributions were evaluated using Shapley Additive exPlanations. Results: MDD was associated with significantly elevated cBAG compared with healthy controls (mean difference + 2.01 years). Age-stratified analyses showed no differences before mid-30s, with progressively larger gaps thereafter, reaching +6.85 years in MDD aged 55 and older. cBAG differed across neuroanatomical phenotypes associated with differential antidepressant response, cognitive impairment, increased adverse life events, increased self-harm and suicide attempts, and a pro-atherogenic metabolic profile. Key contributing regions included lateral and medial prefrontal regions, middle temporal gyrus, putamen, supplementary motor cortex, central operculum, and cerebellum. Conclusions: Accelerated structural brain aging in MDD is age-dependent and is most pronounced in a neuroanatomical phenotype associated with worse key clinical outcomes. The findings support neuroprogression models of MDD while demonstrating that cBAG is not a uniform feature of MDD and seem to be more strongly expressed in a specifically clinically vulnerable disease phenotype.

IntroductionLactate plays dual roles in neuronal energy metabolism and signalling. The dorsal anterior cingulate cortex (dACC), a region with high baseline glycolytic activity implicated in psychiatric disorders, may exhibit dynamic lactate responses to graded cognitive-emotional demands. Because mitochondrial function declines with age, aging may model whether fMRS-derived lactate dynamics can detect latent neurometabolic vulnerabilities. MethodsUsing fMRS, we monitored dACC metabolite changes in 34 healthy participants (aged 21-69) during an emotional face-processing task with escalating cognitive-emotional workload. The paradigm comprised a 2-minute baseline, 10-minute task of increasing intensity, and 10-minute recovery. ResultsdACC lactate increased significantly, tracking task intensity and peaking 19.5% above baseline at maximum cognitive load (z = 2.66, p = 0.004). The response showed both linear task-related increases (z = 2.08, p = 0.02) and a quadratic inverted-U profile (z = 2.72, p = 0.004). Total creatine, total NAA and Glx (Glutamate+Glutamine) exhibited no task-dependent changes. Age influenced task-period lactate AUC (z = 2.19, p = 0.014). Participants over 40 exhibited greater peak responses (54% vs 28%), steeper upslopes (14% vs 7% per block), and larger AUC (155% vs 16%) than those under 40. Sex differences were also observed. Baseline lactate did not correlate with age. ConclusionsdACC lactate dynamics are sensitive to cognitive-emotional demand, with evidence of age-and sex-dependent modulation. The dissociation between static and dynamic measures establishes a metabolic stress-testing paradigm for detecting latent neuroenergetic vulnerabilities, supporting fMRS utility for probing mitochondrial function in health and psychiatric disorders.

BackgroundAlpha oscillations are dominant rhythms in the human brain, supporting inhibitory control and coordination of neural activity. Altered alpha dynamics are observed across many neuropsychiatric and neurodevelopmental disorders, including Fragile X syndrome (FXS), the most common monogenic cause of autism and intellectual disability. FXS exhibits paradoxical alpha power: elevated absolute but reduced relative power. To resolve this incongruity, we considered that conventional power metrics, relying on averaging, may obscure the underlying critical temporal dynamics of such neural rhythms. MethodsHere, we investigate alpha oscillations in FXS as a model to decompose nonspecific alpha abnormalities into underlying temporal features. We used cycle-by-cycle (bycycle) alpha burst analysis from source-localized resting-state EEG of 70 individuals with FXS (20.5{+/-}10.0 years; 32 females, 38 males) and 71 age- and sex-matched typically developing controls (22.2{+/-}10.7 years; 30 females, 41 males). Statistical modeling examined group, sex, and regional differences in alpha burst features using generalized linear mixed-effects models. ResultsWe reveal that alpha bursts in FXS show reduced count only in males, prolonged periods across sexes, and elevated amplitudes, particularly in males. Spatial mapping identified differential circuit vulnerability: timing-associated dysregulation in cognitive-control regions and amplitude elevations in sensory cortices. Within the FXS group, global alpha burst amplitude correlated with hyperactivity symptoms and inversely with general intelligence scores, and burst count correlated with age. LimitationsThis study is limited by its resting-state design and cross-sectional nature. Future studies should explore task-based modulation of alpha burst features and longitudinal trajectories in FXS. Additionally, fragile X messenger ribonucleoprotein (FMRP) was not quantified for participants, limiting potential stratification by molecular severity. ConclusionsThese findings resolve paradoxical alpha power in FXS into features consistent with interneuron dysfunction, demonstrating the potential for burst-level decomposition in mechanistic hypothesis generation and biomarker development across neurodevelopmental and neuropsychiatric disorders.

Intermittent explosive disorder (IED) is associated with impulsive aggression in ambiguous social contexts. Prior neuroimaging studies have treated IED as a homogenous group, but identical social situations may elicit divergent responses across IED individuals. Here, we test the hypothesis that IED is characterized by idiosyncratic neural responses to social cues during naturalistic social-emotional processing. IED individuals and healthy controls completed a validated paradigm where they were presented with video vignettes of interpersonal interactions while undergoing fMRI. We computed the intersubject correlation (ISC) in neural time courses between pairs of participants to quantify neural similarity, and assessed whether similarity differed between Healthy-Healthy and IED-IED dyads using Bayesian multilevel models, controlling for self-reported emotional responses and intention attributions for each vignette. Healthy-Healthy dyads showed significantly higher ISC than IED-IED dyads, indicating that neural responses to the videos were similar among healthy participants, but idiosyncratic in IED individuals. These effects were observed in regions in the default mode and salience networks, including the precuneus, medial prefrontal cortex, superior temporal sulcus, insula, and dorsal anterior cingulate cortex. Individuals with IED exhibited idiosyncratic neural responses during naturalistic social-emotional processing, even after accounting for differences in emotional reaction and intention attribution. This neural idiosyncrasy may reflect atypical integration of social cues, giving rise to maladaptive interpretations and impulsive aggression. Assessing neural synchrony during ecologically valid paradigms offers a promising tool for identifying neural markers of interpersonal dysfunction and informing targeted interventions.

BackgroundCytoskeletal structure and neuronal function are heavily intertwined, and altered pyramidal neuron morphology (e.g., reduced dendritic arbors) has been consistently identified in the neocortex of individuals with psychiatric disorders. A missense mutation in Kalrn (Kalrn-PT) enhances activation of RhoA, a cytoskeletal regulator, and leads to adolescent-onset dendritic regression in supragranular auditory cortex. To investigate the relationship between this spatiotemporally altered cytoskeletal structure and psychiatric-relevant dysfunction, we examine the functional impacts of this genetic mutation, focusing on mismatch negativity - a common biomarker of altered sensory integration that matures across adolescence. MethodsIn Kalrn-PT and littermate wild-type mice, pyramidal dendritic morphology was assessed across primary visual cortex (V1) layers using Golgi staining (n=172 neurons/26 mice). Local field potentials (LFPs) and neuronal spiking were recorded during a visual oddball sequence (n=25 mice). Deviance detection - the rodent neural analogue of mismatch negativity - was analyzed across V1 layers. ResultsKalrn-PT mice exhibit reductions in V1 dendritic length specific to layer 2/3, mirroring observations in post-mortem samples from people with psychiatric disorders. Deviance detection was reduced in LFPs from Kalrn-PT mice and absent in layer 2/3 neurons, despite typical feature selectivity and firing rates. These deficits were accompanied by reduced functional connectivity between visual and frontal areas. ConclusionsThese results highlight alterations in higher-level sensory cortical integration in Kalrn-PT mice and demonstrate that adolescent-onset, disease-relevant structural and functional phenotypes can be linked by a common upstream effector. Further, these alterations appear restricted to supragranular layers, demonstrating an outsized role for Kalrn, particularly longer isoforms, in superficial neocortex.

BackgroundTheta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. MethodSixty male participants with OUD were randomized to receive 20 minutes of active or sham 6 Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using timexgroup interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. Results(1) A significant Time x Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected =0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement ({beta}=2.63, p=0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum ({beta}=1.99, p=0.037) and left medial amygdala ({beta}=1.97, p=0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r=0.43, p=0.02). ConclusionTogether, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction. Significance StatementAddiction is linked to imbalances in cortico-subcortical brain circuits that control reward processing and craving. This study tested whether a non-invasive brain stimulation method-- theta-band transcranial alternating current stimulation (tACS)--can rebalance these circuits in people with opioid use disorder. Using advanced brain imaging, we found that tACS strengthened communication within frontoparietal brain regions involved in self-control while reducing their connections with reward and emotion centers. These brain changes were linked to reduced craving responses to drug cues. Our results demonstrate that dual-site, network-targeted tACS modulates neural activity and task-dependent engagement of brain circuits during drug cue reactivity in addiction, supporting its potential as a novel therapeutic approach.

The identification of objective, dimensional indices of mental health is of central importance in the pursuit of transdiagnostic multi-dimensional frameworks of psychopathology. Altered visual processing occupies a specific domain of interest and motivated the present investigation aimed to quantify the visuocortical impact of affective naturalistic distractor cues on limited capacity attentional resources in obsessive-compulsive disorder (OCD). The current investigation examined the extent to which attentional resources are allocated toward task cues under affective and disorder-relevant distraction in participants with OCD (N = 33) and control participants (N = 31). Steady-state visual evoked potentials (ssVEPs) in response to task-relevant cues were examined using a foreground task where participants detected coherent motion in a flickering random dot kinematogram (RDK) overlaid on naturalistic distractor pictures ranging in emotional content (pleasant, neutral, unpleasant, and OCD-evoking pictures). Amplitude envelopes of ssVEPs in response to the motion stimulus served as an index of visuocortical engagement with task-relevant cues. Data were also fitted to the distraction under competition model (DUC), a computational framework of attention selection. Group differences emerged with stronger visuocortical competition effects (attenuated task engagement) for the OCD group, driven largely by the unpleasant pictures, followed by the OCD-evoking pictures. Furthermore, the DUC model fit well in both groups, demonstrated the dominance of the visuocortical competition observed in response to the unpleasant pictures, and revealed the presence of substantial competition in response to the OCD-evoking pictures in the OCD group.

BackgroundPerinatal mood and anxiety disorders (PMADs) are among the most common and consequential complications of pregnancy. The perinatal period is also characterized by profound hormonal fluctuations and large-scale brain plasticity. However, the mechanisms linking these neurobiological changes to psychiatric risk are poorly understood. Prospective, clinically informed studies are needed to identify quantitative biomarkers and clarify pathways linking perinatal neurobiology to PMADs risk. MethodsThis report describes the design of a prospective, longitudinal cohort study integrating multimodal neuroimaging, biofluid sampling, and deep clinical phenotyping to enable precision characterization of neurobiological trajectories of PMADs risk. Twenty-five individuals at elevated risk for PMADs will be recruited prior to conception and followed across six in-person timepoints spanning the menstrual cycle, pregnancy, and early postpartum, with additional remote follow-ups through the first postpartum year. Data collection includes high-resolution structural MRI, functional brain mapping using multi-echo resting-state fMRI, diffusion MRI, arterial spin labeling, ultra-high field MR-based techniques for measuring glutamate (GluCEST and 1HMRS), biofluid sampling, and comprehensive clinical, behavioral, and cognitive assessments. Structured clinical interviews assess categorical diagnoses while dimensional symptom measures capture heterogeneity and transdiagnostic features of perinatal psychopathology. Longitudinal analyses will model nonlinear trajectories of brain and symptom change across the perinatal period as well as evaluate whether preconception network features and menstrual cycle-related brain changes are associated with subsequent perinatal symptom emergence. DiscussionThis cohort study establishes a longitudinal, multimodal framework for investigating neurobiological changes across the transition to pregnancy in individuals at elevated risk for PMADs. By anchoring pregnancy-related brain changes to preconception and menstrual cycle-related variability within the same individuals, this study is designed to evaluate associations between preconception hormone sensitivity, pregnancy-induced neuroplasticity, and PMADs risk. The resulting dataset will provide a deeply phenotyped longitudinal resource for investigating brain-behavior relationships across the perinatal period. Findings are expected to inform future larger-scale studies aimed at advancing mechanistic understanding of PMADs, improving individualized risk stratification, and supporting development of personalized preventive and neuromodulatory interventions.

BackgroundHIV and cocaine use (CU) each relate to cognitive deficits and brain abnormalities, yet their combined impact on brain aging remains unclear. This study examined how comorbid HIV and CU relate to brain aging and cognitive impairment. MethodsWe trained a morphometry-based brain-age model using harmonized Human Connectome Project-Aging data (HCP-A; n=725) with Gaussian Process Regression. The model was applied to an independent cohort with varying HIV/CU burden (HIV-/CU-, n=34; one disorder [HIV+/CU- or HIV-/CU+], n=72; HIV+/CU+, n=80). Brain age gap (BAG; predicted minus chronological age) was examined in relation to comorbidity burden and neurocognitive impairment (NCI; NIH Toolbox), adjusting for age, sex, education, depression, and image-quality indices. Analyses on SHapley Additive exPlanation (SHAP) values characterized network-wise feature-level contributions to brain age estimates. ResultsA dose-dependent effect of comorbidity burden on BAG was observed, with the HIV+/CU+ group showing the highest BAG. Greater BAG was associated with increased likelihood of NCI, and BAG partially mediated the relationship between comorbidity burden and NCI, with a stronger mediation effect in the two-disorder group than in the one-disorder group. Structural contributors to elevated BAG in the HIV/CU cohort included cortical thickness in the visual, ventral attention, and frontoparietal networks, and sulcal depth in the sensorimotor network. ConclusionComorbid HIV/CU is linked to accelerated structural brain aging. BAG may reflect brain-level alterations underlying the association between comorbid HIV/CU and cognitive impairment, and may help identify network-specific targets for intervention.

BackgroundSchizophrenia is marked by impairments in emotional processing and social cognition, yet traditional neuroimaging paradigms often lack the ecological validity to capture these deficits in real-world contexts. MethodsIn this study, we used intersubject correlation (ISC) analysis of functional MRI data to examine shared neural representations of naturalistic visual narratives in individuals with schizophrenia and healthy controls. Participants viewed short films designed to evoke happy, sad, and emotionally neutral responses, allowing us to compare how synchronized brain activity varied with emotional content across and within groups. ResultsHealthy controls showed greater ISC in regions associated with affective salience, emotion recognition, and social understanding, including the amygdala, insula, and temporal cortices. In contrast, participants with schizophrenia displayed higher synchrony in visual, subcortical, and frontal areas, suggesting a reliance on perceptual and executive systems. To isolate the effects of emotion from general visual processing, we compared ISC during emotional clips relative to neutral videos. This revealed significantly reduced synchrony in the bilateral amygdala in patients, highlighting a core dysfunction in affective engagement. Interestingly, neutral stimuli elicited unexpectedly strong synchronization in frontal and limbic regions in the schizophrenia group, possibly reflecting altered salience attribution to ambiguous or emotionally ambiguous content. ConclusionsThese results point to a functional reorganization of affective processing in schizophrenia, where impaired limbic recruitment is accompanied by compensatory engagement of perceptual and cognitive control networks. ISC during naturalistic stimulation emerges as a powerful tool for capturing subtle disruptions in shared emotional experience in psychiatric populations.

BackgroundImpaired glymphatic clearance, the perivascular system supporting cerebrospinal and interstitial fluid exchange, has been implicated in neurodegenerative and psychiatric disorders. Diffusion tensor imaging along the perivascular space (DTI-ALPS) provides a non-invasive proxy for glymphatic-related processes, yet its role in psychiatric conditions remains uncertain. MethodsFollowing PRISMA guidelines, we systematically searched PubMed, PsycNET, and Embase for articles published up to September 25th, 2025. The protocol was pre-registered in PROSPERO (CRD420251155430). Studies reporting diffusion-based indices of glymphatic function in psychiatric populations were included. Standardised mean differences (Hedges g) were calculated for patient-control comparisons and pooled using random-effects models. Heterogeneity, methodological moderators, and risk of bias were assessed. ResultsThirty-two studies met inclusion criteria for the systematic review, covering major psychiatric groups including mood disorders, autism spectrum disorder, ADHD, psychosis, sleep disorders, and substance-related conditions. Twenty-four studies (n = 2,855; 1,503 patients, 1,352 controls) reporting bilateral DTI-ALPS measures were included in the meta-analysis. The pooled random-effects model revealed a significant transdiagnostic reduction in DTI-ALPS index in psychiatric populations compared with healthy controls (Hedges g = -0.78, 95% CI -1.01 to -0.55, p < 0.0001). Between-study heterogeneity was substantial (I{superscript 2} = 86.3%), and there was evidence of small-study effects. ConclusionsBilateral DTI-ALPS index showed a robust but heterogeneous reduction across psychiatric disorders. Together, these results suggest that impairments of perivascular diffusion, as indexed by DTI-ALPS, may reflect a shared transdiagnostic vulnerability across psychiatric conditions. Harmonised imaging pipelines and multimodal validation are needed to clarify the biological and clinical significance of these findings. SIGNIFICANCE STATEMENTThe search for reliable transdiagnostic biomarkers remains a central challenge in contemporary psychiatry, where heterogeneous symptom profiles often obscure shared biological pathways. The glymphatic system, a glia-dependent network regulating cerebrospinal and interstitial fluid exchange, has recently been proposed as a key mechanism linking vascular, immune, and metabolic pathways to mental illness. Diffusion tensor imaging along the perivascular space (DTI-ALPS) offers a non-invasive proxy for glymphatic function, yet its specificity and clinical relevance remain debated. This systematic review and meta-analysis provide, to our knowledge, the first quantitative synthesis of DTI-ALPS findings across psychiatric disorders, critically evaluating methodological assumptions and evidence for shared pathophysiological mechanisms. By clarifying the strengths and limitations of diffusion-based glymphatic imaging, this work establishes a mechanistic framework for future translational, interventional, and biomarker research in psychiatry.

Catatonia is a severe psychomotor syndrome that occurs across psychiatric diagnoses and is increasingly conceptualized as reflecting neurodevelopmental vulnerability. The anterior cingulate cortex (ACC) plays a central role in motor initiation and cognitive-affective integration and displays substantial interindividual variability in its sulcal morphology, which is established prenatally and remains stable across life. In this MRI study, we examined whether ACC sulcal patterns represent a structural trait marker of catatonia. We analyzed high-resolution T1-weighted images from a hospital-based cohort comprising patients with catatonia (N = 109), psychiatric patients without catatonia (N = 323), and healthy controls (N = 91). The presence of the paracingulate sulcus (PCS) in each hemisphere was determined through blinded visual inspection, and regression analyses tested associations with diagnostic group, adjusting for age, sex, scanner type, intracranial volume, and benzodiazepine and antipsychotic exposure. Patients with catatonia exhibited a significantly reduced prevalence of the left PCS and diminished hemispheric asymmetry compared with both non-catatonic patients and healthy controls. These effects were independent of whether catatonia occurred within psychotic or mood disorders. PCS size did not differ across groups, and sulcal pattern did not correlate with catatonia severity among affected individuals. The findings demonstrate that ACC sulcal deviations are specifically associated with catatonia across diagnostic categories, supporting a neurodevelopmental etiology and reinforcing ACC involvement in its pathophysiology. Early-determined sulcal morphology may represent a trait-level marker contributing to vulnerability for catatonia, with implications for early identification, risk stratification, and targeted intervention strategies.