Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

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.

Importance: 22q11.2 deletion syndrome (22q11DS) is among the strongest genetic risk factors for neuropsychiatric disorders and has marked effects on brain structure. Yet, it remains unclear which neuroanatomical features reflect uniform effects of the deletion versus inter-individual biological processes relevant to psychiatric outcomes. Identifying these features is critical for developing targeted treatments and interventions. Objective: To identify brain regions where 22q11DS exerts its most consistent and most variable impacts, and to test whether these patterns align with normative neurotransmitter receptor distributions and cortical growth trajectories. Design: Multisite cross-sectional case-control study. Setting: T1-weighted brain MRI data were obtained across 15 scanners. MRI data underwent standardized processing, quality control procedures and statistical site-adjustment using ComBat. Participants: A total of N = 438 individuals with 22q11DS (5-54 years, 48% females) and 380 typically developing controls (6-58 years, 48% females). Main Outcomes and Measures: Primary outcomes were global and regional cortical thickness and surface area . Mean and dispersion estimates were calculated using double generalized linear models, correcting for age, age2, sex (and intracranial volume for surface area). Quantile shift functions characterized fine-scale distributional differences. Sensitivity analyses adjustedt for co-occurring neuropsychiatric disorders, antipsychotic use and deletion subtype. Secondary outcomes included spatial correspondence between regional structural alterations and normative maps of neurotransmitter receptor density and cortical expansion. Results: Compared with controls, individuals with 22q11DS showed widespread mean differences in cortical thickness and surface area. Notably, 22q11DS was associated with greater regional heterogeneity in both measures, except for reduced dispersion in the anterior cingulate. Effects were attenuated after covariate adjustment. Cortical thickness differences spatially overlapped with regions enriched for glutamatergic and GABAergic receptors. There was partial evidence linking surface area dispersion patterns to normative cortical growth trajectories. Conclusions and Relevance: 22q11DS exerts broad effects on cortical structure consistent with a global developmental mechanism, reflected in widespread mean shifts. Beyond these, region-specific variability, particularly in cortical thickness, suggests individualized neurobiological processes. The anterior cingulate emerges as a region of consistent structural deviation. Overall, structural variability in 22q11DS aligns with normative patterns of excitatory-inhibitory signaling and cortical development, implicating these pathways as potential targets for intervention.

BackgroundAttention-deficit/hyperactivity disorder (ADHD) has traditionally been conceptualized categorically, with efforts to identify disorder-specific neurobiological endophenotypes. However, dimensional models suggest that brain-behavior organization may follow developmental axes that cut across diagnostic boundaries. We tested whether neural dynamics and cortical excitability differentiate those with ADHD diagnoses from typically developing (TD) peers, and whether brain-behavior covariance aligns with diagnostic or developmental dimensions. MethodsWe studied 84 participants aged 8-17 years (51 ADHD, 33 TD). High-density electrophysiological (hdEEG) measures included task-free source-resolved data used to derive mean global brain fluidity (variance of dynamic functional connectivity) and region-specific cortical excitability. Behavioural measures included self- and parent-report questionnaires, cognitive control (CC) tasks, and neuropsychological tests. Partial least squares (PLS) assessed multivariate brain-behavior associations including age, followed by clustering based on latent component scores. ResultsGroup differences emerged in parent-report questionnaires and CC tasks, but not in neuropsychological measures. ADHD individuals showed higher mean global brain fluidity and increased cortical excitability. The excitability-fluidity relationship was network-dependent: higher excitability predicted higher fluidity in task-positive networks and lower fluidity in default-mode and salience networks, with no group effects. PLS identified a latent dimension linking neural metrics with age, verbal fluency, inhibitory control, and positive affect, but it did not distinguish ADHD from TD. Clustering revealed two neurodevelopmental profiles spanning both groups. ConclusionsWhile ADHD is associated with mean-level differences in neural dynamics, brain-behaviour organization follows a developmental neurocognitive-affective axis that transcends the diagnostic boundary. These findings support a dimensional framework for understanding neurobiological variation in neurodevelopmental conditions.

Background: While counterfactual thinking ('what could have been') guides adaptive decision-making, it remains unclear how this process is altered by the negative biases and motivational deficits characteristic of Major Depressive Disorder (MDD). Methods: We used a sequential economic decision-making task designed to emulate a volatile stock market to assess choice behavior in adults with or without MDD (Total N=178); a subset of these participants completed the task during functional MRI (N=53). The task allowed participants to make either positive ('invest') or negative ('short') bets, under either positive or negative contextual valence, defined by whether the immediately preceding stock price change was positive or negative. Fictive errors were defined as the difference between realized and best-possible outcomes. Results: Across the full cohort, group differences in behavioral adjustments to fictive error signals emerged exclusively under negative contextual valence, when stock prices decreased. Compared with controls, participants with MDD showed heightened sensitivity to invest-and-loss fictive errors, reflected in a greater reduction in subsequent bets (interaction beta = -0.63, p < .001), but blunted adjustment to short-and-gain fictive errors (beta = -0.86, p < .001). In the imaging cohort, blunted short-and-gain adjustment was accompanied by heightened anterior cingulate (ACC) activity and attenuated ventromedial prefrontal (vmPFC)-to-ACC coupling in MDD. vmPFC activity following negative market returns also tracked depression symptom severity. Conclusions: Depression selectively disrupts the use of counterfactual outcomes to guide adaptive choice under negative contextual valence, implicating altered frontocingulate function in maladaptive decision-making.

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.

Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) exhibit high clinical overlap, but categorical diagnostic boundaries obscure their shared, dynamic physiological vulnerabilities during real-world sensory processing. Methods: We analyzed multimodal eye-tracking synchrony in a large transdiagnostic pediatric cohort (N = 2,026) during naturalistic viewing of four distinct media paradigms. A novel 2D complex correlation framework captured gaze inter-subject correlation (ISC) magnitude and spatiotemporal phase divergence, while 1D pupil ISC measured autonomic arousal synchrony. Linear models evaluated dimensional (RDoC) and categorical (2x2 ANCOVA) diagnostic frameworks alongside rigorous medication and severity controls. Results: Dimensional models revealed a domain-general vulnerability: autistic traits independently predicted widespread reductions across gaze synchrony in all media contexts, and pupillary synchrony in narrative-driven contexts, whereas continuous ADHD traits showed minimal independent effects. In contrast, severe spatiotemporal misalignment (phase divergence) did not scale dimensionally but emerged strictly at clinical boundaries, reflecting highly idiosyncratic spatial locking in isolated ASD. Furthermore, categorical models demonstrated a robust, non-additive interaction: the clinical co-occurrence of ADHD paradoxically buffered against this severe spatiotemporal decoupling. Crucially, this protective phenotype was localized strictly to character-driven social narratives and remained highly significant after rigorously adjusting for daily stimulant medication, outlier instability, and baseline autism trait severity. Conclusions: These findings validate model-free physiological synchrony as a candidate transdiagnostic biomarker. Rather than compounding impairment, comorbid ASD and ADHD reflect competing, non-additive neurocognitive strategies that yield distinct, context-dependent visual phenotypes.

Impulsivity is a core dimension of ADHD and a transdiagnostic vulnerability factor for a wide range of adverse psychiatric and somatic outcomes, that could be mitigated through more effective screening of at-risk individuals. However, laboratory-based measures of impulsivity show weak convergence across paradigms and limited prediction of real-world behavior, constraining their utility. We tested whether combining repeated ecological assessment with computational modeling of response-time (RT) dynamics improves measurement of impulsivity and its cross-paradigm validity. Sixty participants, including adolescents with ADHD, individuals with 22q11.2 deletion syndrome, and healthy controls, completed a total of 1347 smartphone-based Balloon-Analogue-Risk-Task (D-BART) assessments repeatedly in daily life, alongside a single-session Conners CPT-3. RT was modeled using linear mixed-effects models as a function of objective risk and subjective uncertainty, with random effects capturing between- and within-person variability. Dynamic RT parameters were integrated with conventional performance metrics and related to CPT-3 variables using partial least squares analysis. External validity was evaluated against parent-rated behavioral symptoms. RT increased with both risk and uncertainty, consistent with adaptive modulation of speed-accuracy trade-offs. These effects varied substantially across individuals and repeated assessments. Dynamic RT parameters differentiated clinical from control participants, whereas traditional aggregate metrics did not. A PLS latent component linked D-BART and CPT-3 patterns and was associated with real-world hyperactivity/impulsivity, whereas CPT-3-derived scores alone were not. Experimental manipulation of ecological sampling density directly impacted D-BART predictive accuracy. These findings show that ecological repetition combined with parsimonious RT-dynamics modeling enhances construct validity, cross-paradigm convergence, and behavioral relevance of impulsivity measures, providing a scalable framework for capturing dynamic cognitive-control processes.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Stimulation of two rTMS-targets, the ventromedial prefrontal cortex (vmPFC) and the left dorsolateral prefrontal cortex (LDLPFC), limbic and executive control network hubs respectively, may yield differential effects. In this pilot trial, we explored the differential effects of 36-sessions of rTMS applied to either the vmPFC or LDLPFC. Methods: Treatment-seeking participants with moderate or severe CUD (n=20, 10F, age=33.3+9.8SD) were randomized to 36-sessions of open-label rTMS (two sessions-per-visit, two or three visits-per-week) to either the LDLPFC (3000-pulses; 10Hz) or vmPFC (900-pulses; 1Hz) using personalized functional Magnetic Resonance Imaging (fMRI) targets along with three-sessions of Motivational Enhancement Therapy. At baseline and following rTMS, the Time-Line Follow-Back was used to measure Days-per-week of cannabis use and the fMRI Regulation of Craving (ROC) task was used to measure network activation to cues associated with long-term negative ('Later') and short-term positive ('Now') consequences of cannabis use. Results: Eighty percent of participants completed study-rTMS. There was a significant decrease in days-per-week of cannabis use in both groups (vmPFC: d=7.9; DLPFC, d=3.1) between the four-weeks of baseline and seven-weeks of follow-up. LDPFC-rTMS reduced fMRI BOLD signal magnitude and increased LDLPFC functional connectivity in response to cues, while vmPFC-TMS reduced functional connectivity. Conclusions: Treatment-seeking participants with CUD reduced the number of days-per-week they used cannabis when receiving rTMS applied to either the LDPFC or vmPFC, while fMRI effects differed by treatment target. Future larger sham-controlled trials are needed for efficacy and biomarker determination.

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.

BackgroundA central goal in psychiatry is to move from symptom-defined diagnoses toward biologically interpretable and reliable phenotypes. In cocaine use disorder (CUD), many resting-state abnormalities have been reported, but few circuit-level findings have been explicitly screened for reliability. We tested whether prespecified thalamocortical features yield a reproducible phenotype in CUD and whether that phenotype reflects diagnosis, recent cocaine use, or longer-term illness history. MethodsDiscovery analyses used resting-state data from 105 participants (46 healthy controls, 59 CUD). From a 13-region thalamocortical circuit, we derived an HC-trained LEiDA state model, generated 11 prespecified features, and advanced only those meeting split-half reliability criteria (ICC[3,1] [&ge;]0.40). A separate paired TMS sample (n=44) was used for extension analyses. ResultsFive features survived reliability screening. Within CUD, longer duration since beginning cocaine use was associated with greater occupancy of a control-like state (standardized {beta}=0.37, q=0.005) and stronger whole-thalamus connectivity with control frontoparietal cortex (standardized {beta}=0.30, q=0.018). Neither days since last use nor CUD vs. healthy diagnosis were associated with any reliable feature after correction. Joint-history models indicated that the signal was better explained by longer-term use history than by recent use. Localization analyses indicated the connectivity effect was concentrated in dorsal thalamic regions. TMS-interaction and effective-connectivity follow-ups were null. ConclusionsReliability screening identified a thalamocortical control-network phenotype in CUD that tracks longer cocaine-use history rather than diagnosis or recent use. More broadly, this workflow offers a practical framework for screening candidate circuit-level psychiatric phenotypes for reliability.

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.

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.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Targeting incentive-salience circuitry via the ventromedial prefrontal cortex (vmPFC) and central-executive circuitry via the left dorsolateral prefrontal cortex (LDLPFC) are both promising treatment approaches; however, to date structural targets have predominated whereas functional targeting may allow for more precision. In this pilot trial we adapted a functional Magnetic Resonance Imaging (fMRI) Regulation of Craving (ROC) task to generate fMRI-based rTMS targets in the vmPFC and LDLPFC. Methods: We recruited treatment-seeking participants with moderate or severe CUD as a part of an open-label trial and administered an adapted ROC-task during fMRI following 24-hours of cannabis abstinence. We identified sub-portions of maximal activation of the LDLPFC when participants thought of long-term consequences of cannabis use (Later) and of the vmPFC when participants thought of short-term positive aspects of cannabis use (Now). We hypothesized that our task would generate acceptable rTMS targets in >66% of baseline fMRI scans. Results: A total of 20-participants enrolled in the trial (50%F, age=33.3+9.8) and completed the baseline fMRI. The adapted ROC-task elicited group level activation in the LDLPFC and precuneus in the Later>Now and in the bilateral vmPFC, ACC, and striatum in the Now>Later contrast. Acceptable functional targets resolved in both the vmPFC and LDLPFC in 19 of 20 participants (one participant did not tolerate MRI). Conclusions: The adapted ROC-task elicits activation in incentive salience and central executive circuitry and can feasibly generate rTMS targets when using a cluster selection algorithm.

ObjectiveLate adolescence is a critical developmental period that typically precedes psychosis onset, yet the neural correlates of subclinical hallucinatory experiences that may impact psychosis risk are poorly understood. Given evidence from adult psychosis models implicating abnormal "triple network" connectivity among the frontoparietal (FPN), default mode (DMN) and salience/cingulo-opercular (CON) networks, as well as dopaminergic abnormalities, we examined whether hallucinatory experiences in adolescents are associated with altered triple network organization and dopamine-related measures in the midbrain. MethodsWe performed a cross-sectional analysis of 171 community adolescents aged 14-17 who underwent resting-state functional magnetic resonance imaging and neuromelanin-sensitive MRI. Hallucinatory experience severity was measured using the Specific Psychotic Experiences Questionnaire. Resting-state functional connectivity was calculated among a priori DMN, FPN, and CON cortical regions; we examined associations between connectivity, hallucinatory experience severity, within-network connectivity, system segregation, and neuromelanin signal in the ventral tegmental area (VTA). ResultsGreater hallucinatory experience severity was associated with stronger connectivity in a subnetwork composed of CON-DMN and CON-FPN edges. Greater hallucinatory experience severity was also associated with lower global network segregation. VTA neuromelanin signal was not directly associated with hallucinatory experience severity, but greater VTA signal predicted lower connectivity in the hallucination-related subnetwork. Greater VTA neuromelanin signal was also associated with a distinct pattern of stronger connectivity within DMN midline regions. ConclusionsThese findings implicate altered triple network organization in hallucinatory experiences during late adolescence and suggest that dopamine-related midbrain signal may reflect broader developmental variation in cortical network organization rather than symptom severity directly. Plain Language SummaryHallucinatory experiences during adolescence may signal increased risk for later psychotic disorders, but their brain basis is unclear. We studied 171 adolescents aged 14-17 using resting-state fMRI to measure brain network activity and neuromelanin-sensitive MRI to estimate dopamine-related midbrain signal. More severe hallucinatory experiences were linked to abnormal communication among three brain networks often implicated in psychosis. Dopamine-related signal was not directly related to hallucination severity but was associated with developmentally relevant network organization. Overall, this work serves to improve our understanding of the risk factors that may contribute to psychosis conversion in adulthood.

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.

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.

BackgroundDeep brain stimulation (DBS) is effective for approximately two-thirds of patients with treatment-resistant obsessive-compulsive disorder (OCD). While prior work has emphasized the engagement of specific white matter tracts in mediating outcomes, the contribution of region-specific white matter integrity to clinical response remains unclear. MethodsTwelve patients with treatment-resistant OCD underwent preoperative neuroimaging and DBS at our center. We assessed OCD severity preoperatively and at [~]18 months postoperatively. We extracted mean fractional anisotropy (FA) for the anterior limb of the internal capsule (ALIC) and a control tract and used Spearmans rank correlations to evaluate associations between FA and symptom improvement. We additionally evaluated this relationship for 49 white matter bundles. Finally, we used diffusion tractography to determine endpoints connected with ALIC voxels most predictive of symptom improvement. ResultsHigher preoperative ALIC FA was associated with greater clinical improvement following DBS (p=0.002). This effect was specific to the ALIC and not the control tract. Hemispheric asymmetry (right>left) in ALIC FA was moderately correlated with clinical improvement. Among all 49 bundles, the right ALIC demonstrated the strongest association with clinical improvement. Streamlines passing through the ALIC voxels that most strongly correlated with outcome ended in the diencephalon and superior frontal cortex. ConclusionsBaseline structural integrity of the ALIC was associated with the magnitude of clinical improvement following DBS for OCD. These findings suggest that regional variation in white matter integrity may reflect an underlying circuit disruption amenable to DBS, supporting the use of neuroimaging-based metrics as potential biomarkers in DBS treatment.

Background: Major depressive disorder (MDD) is the leading cause of non-fatal disability in youth and disproportionately affects adolescent females. Structural MRI studies of adolescent depression have yielded inconsistent findings, potentially reflecting symptom heterogeneity and rapid developmental changes in brain morphology. Methods: In this longitudinal study, we examined associations between specific depressive symptoms and structural brain MRI measures in 9,722 youth (53% male, age range = 10.0-17.7, 24,378 observations) from the Adolescent Brain Cognitive Development (ABCD) Study. A four-wave panel graphical vector autoregression (GVAR) model was estimated to separate within-person (contemporaneous and temporal networks) from stable between-person effects. Brain measures included cortical thickness in the insula, cingulate, medial orbitofrontal cortex (mOFC) and fusiform gyrus, as well as hippocampal volume. Depressive symptoms included parent-reported depressed mood, anhedonia, lethargy, and worthlessness. Additionally, sex-differences in network structures were tested. Results: Strong within-domain associations were observed among brain measures and among symptoms, with the largest effects in the symptom domain. Cross-domain (brain-symptom) associations emerged only at the within-person level, where elevated depressed mood was associated with contemporaneous and subsequent reductions in cingulate and fusiform gyrus thickness (partial r = [-0.02 - 0.04]). No cross-domain associations were detected in the between-person networks. Sex-differences emerged only in the within-person networks. Conclusions: Associations between brain structure and depressive symptoms were subtle, symptom-specific, and dynamic rather than reflecting stable individual differences. Longitudinal within-person approaches are therefore important for understanding neurodevelopmental contributions to adolescent depression risk.