Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

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.

Progress in pharmacological treatment development for neurodevelopmental disorders is hindered by a misalignment between targeted mechanisms, outcome measures, and trial designs. This study was initiated as a post-trial access pathway for bumetanide and later expanded with treatment-naive participants. Within this framework, we implemented a parent-cocreated sensory outcome measure set (PROMset) in an unmasked, multiple-baseline single-case experimental design with randomized baseline periods of 2-12 weeks, followed by 6 months of bumetanide treatment (up to 1.5 mg twice daily). Participants (7-19 years) had atypical sensory reactivity and a diagnosis of ASD, ADHD, epilepsy, or TSC. The primary outcome was a PROMset comprising seven PROMIS item banks assessing anxiety, depressive symptoms, sleep disturbance, fatigue, sleep-related impairment, cognitive function, and peer relationships. Secondary outcomes included SSP, SRS-2, RBS-R, and ABC. Of 113 enrolled participants (mean age 13.2 [SD 2.7], 64% male), 102 completed the trial and 95 had analyzable PROMsets. At baseline, PROMset scores showed substantial impairment across domains (mean deviation =9.0 T-score points, p<.001) and correlated with sensory reactivity (SSP; r=-0.40, p<.001). Individual-level analyses showed improvement in 24-41% of participants per PROM domain, most frequently in anxiety and depressive symptoms (41% and 38%; mean across-case Cohen's d=-1). Overall, 83% improved on at least one domain. Group-level analyses showed improvement across all secondary outcomes (p<.001), with superiority over historic placebo for RBS-R and SSP. Integrating PROMsets with individualized trial designs can reveal clinically meaningful changes, supporting a more sensitive and patient-centered framework for treatment evaluation in heterogeneous populations.

Regular cannabis use has been associated with alterations in reward-related neural processes, yet findings remain inconsistent and the relationship between neural activity and behavioural performance is not fully understood. The present study aimed to characterise neural and behavioural correlates of reward processing in regular cannabis users (CU) compared with matched non-users (NU) using the Monetary Incentive Delay Task (MIDT). Firstly, we assessed behavioural performance through reaction times, accuracy and monetary earnings to determine whether potential neural alterations were reflected in task performance. Secondly, focusing on reward-related brain regions, we examined group differences in BOLD functional MRI activity during anticipation and outcome phases separately for monetary win and loss conditions. Finally, we explored the association between behavioural performance and neural activation. Our findings indicate that regular cannabis use is associated with altered engagement of key nodes within the mesocorticolimbic circuit during both anticipatory and outcome phases of reward processing, accompanied by impaired behavioural performance. Particularly, compared with NU, CU showed (I) lower striatal activity during anticipation of monetary win and higher ventral striatum and frontal pole activity during anticipation of monetary loss; (II) greater VTA activation during outcome of successful monetary win and loss avoidance and lower frontal pole activity during outcome of unsuccessful loss avoidance; (III) impaired behavioural performance, reflected in lower monetary rewards and a trend towards slower reaction times and reduced accuracy; (IV) disrupted brain-behaviour coupling. Results from this study may help inform future research on the neurobiological mechanisms underlying changes in reward function and the resultant behavioural consequences of cannabis use.

ObjectiveSocial difficulties are transdiagnostic in childhood, but their heterogeneity is poorly characterised and rarely treated as a primary neurodevelopmental phenotype. This matters because childhood and adolescence are sensitive periods for peer relationships and brain development. We used data-driven modelling and non-linear mapping to derive social profiles and test their clinical, cognitive, and neural correlates. MethodsParticipants were 992 children aged 5-18 years from CALM (Mage = 9.6). Social items from the SDQ, CCC-2, and Conners-3 were modelled using a regularised partial correlation network to derive core social dimensions. A self-organising map captured graded social profiles. Simulated archetypes, SVM-based island identification, and permutation testing defined profile regions and centroid-distance scores. Profiles were related to referral, diagnosis, cognition, BRIEF indices, and T1-derived MIND network structure in an MRI subsample (n = 431). ResultsWe identified four profiles: social engagement, friendship difficulties, social withdrawal, and peer victimisation. Profile expression tracked variation in referral and diagnostic pathways. Social withdrawal showed the clearest disadvantage across cognitive domains, whereas social engagement was associated with fewer executive function difficulties across BRIEF indices. MIND strength components covaried with profile expression (a significant PLS latent variable, p = 0.02), with covariance strongest for social withdrawal and peer victimisation. ConclusionsChildhood social functioning organises graded signatures that relate to clinically relevant pathways, cognitive and executive outcomes, and brain structure. Profiling social signatures provides a scalable framework for identifying social need beyond diagnostic categories, motivating studies to test directionality and improve developmental outcomes.

BackgroundThe severity of positive psychotic symptoms largely defines emerging psychosis syndromes. However, depressive and negative symptoms are strongly psychologically and biologically interlinked. A transdiagnostic exploration of symptom severity across early illness syndromes could enhance the understanding of shared common factors and future trajectories of mental illness. We aimed to identify subgroups based on the severity of positive, negative, and depressive symptoms and assess relationships with: 1) premorbid functioning, 2) longitudinal illness course, 3) genetic risk, and 4) brain volume differences. MethodsWe analysed 749 participants from a multisite, naturalistic, longitudinal (18 months) cohort study of: clinical high risk for psychosis (n=147), recent onset psychosis (n=161), and healthy controls (n=286), and recent onset depression (n=155). Participants were stratified into subgroups based on severity of baseline positive, negative, and depression symptoms. Baseline and longitudinal differences between groups for clinical, functioning, and polygenic risk scores (schizophrenia, depression, cross-disorder) were assessed with ANOVAs and linear mixed models. Voxel-based morphometry was used to examine whole-brain grey matter volume differences. Discovery findings were replicated in a held-out sample (n=610). ResultsParticipants were stratified into no (n=241), mild (n=50), moderate (n=182), and severe symptom (n=254) subgroups. The mean (SD) age was 25.3 (6.0) and 344 (47.3%) were male. Symptom severity was associated with poorer premorbid functioning and illness trajectory, greater genetic risk, and lower brain volume. Findings were not confounded by the original study groups or symptoms and were largely replicated. Conclusions and relevanceTransdiagnostic symptom severity is linked to shared aetiologies, prognoses, and biological markers across diagnoses and illness stages. Such commonalities could guide therapeutic selection and future research aiming to detect unique contributions to specific psychopathologies.

Subcallosal cingulate cortex (SCC) deep brain stimulation (DBS) can provide relief for individuals with Treatment Resistant Depression (TRD), but ongoing clinical management remains challenging due to nonspecific symptom fluctuations that can obscure core depression recovery on standard rating scales. Objective, stable biomarkers that selectively track the therapeutic effects of SCC DBS are therefore essential for developing principled decision support systems to guide stimulation adjustments. Recent bidirectional DBS systems enable chronic recording of local field potentials (LFPs) and prior work using the Activa PC+S device identified an electrophysiological signature of stable clinical recovery. However, translation to practical clinical deployment requires demonstrating that this biomarker is robustly generalizable, specific to the impact of the DBS therapy, and deployable in real-world recording contexts. To address this need, we developed an at-home SCC LFP data collection platform (built on the Medtronic Summit RC+S system) enabling at home data collection for a new cohort of ten SCC DBS participants with TRD (ClinicalTrials.gov identifier NCT04106466). Using longitudinal LFP recordings collected from this system, we report findings demonstrating that the previously reported biomarker of stable recovery generalizes across subject cohorts and devices, is robust to common potential confounds (including time of day and stimulation status), and shows symptom specificity, sensitivity and stability necessary to support clinical decision making. Across both cohorts, biomarker changes show relationships to pre-DBS white matter structure and network function measured using diffusion MRI and resting-state functional MRI (rsFMRI). These findings replicating and extending previous findings support the biomarkers utility as a foundation for scalable, electrophysiology-informed decision support in SCC DBS.

Individuals with autism spectrum disorder (ASD) often exhibit atypical auditory processing, yet it remains unclear whether and how the integration of simple acoustic features and contextual information is impacted in ASD. One real-world example of this integration is the auditory looming bias, the prioritized processing and perception of approaching auditory stimuli. We designed a paradigm that presents intensity-rising (looming) and intensity-falling (receding) auditory stimuli to 3-4-year-old children with ASD (n = 21), children with sensory processing concerns who do not have ASD (SPC; n = 16) and children with typical development (TD; n = 30). We recorded neural responses using electroencephalography (EEG) and found evidence of looming bias in the SPC and TD groups, as indexed by greater P1 peak amplitude during the looming than receding stimuli (TD: t(64) = 6.87, p < .001; SPC: t(64) = 4.07, p < .001). But this finding was not present in the ASD group (p = .194). Additionally, the ASD group showed reduced differentiation between looming and receding stimuli, as indicated by significantly lower Rise-Fall Difference Score (RFDS) in comparison to the TD group (Z = -3.00, padj = .008). These findings suggested altered context-dependent modulation of sensory input in ASD.

Traumatic brain injuries (TBIs) are more than mere lesions and generate a persistent secondary pathology. This, combined with functional reorganization of circuits post-injury, may explain the increased risk for psychiatric disorders in patients with TBI. In the current studies, we demonstrate that frontal TBI changed the Pavlovian behavioral response to reinforcer-predicting cues and reduced the motivational value of cues. TBI also chronically impaired decision-making on a gambling-like task with reinforcer-paired cues. To investigate how these changes occur, we evaluated the nucleus accumbens (NAc) core. At a subacute time point (14 days), we confirmed reduced input to the NAc with optogenetics and evaluated electrophysiological and transcriptional changes. TBI increased neuronal excitability and the single nucleus RNA sequencing profile indicated a substantial stress and inflammatory response, but also high indicators of plasticity, particularly in D1- and D2-positive medium spiny neurons. To evaluate how these subacute changes transitioned to chronic NAc dysfunction, we measured immunohistochemical surrogates of activity post-mortem and recorded calcium activity from the NAc after TBI during Pavlovian conditioning. TBI reduced histological markers of activity and reduced cue-evoked calcium activity. Overall, these data indicate that substantial reorganization of the NAc occurs following frontal brain injury. A primary effect of this is to reduce the salience of environmental cues linked to outcomes. The inability to properly process outcomes could contribute to broader psychiatric symptoms after TBI, including impairments in decision-making, behavioral flexibility, and impulsivity but also presents a potential treatment target.

BackgroundScalable, low-burden behavioral interventions are needed to address rising subclinical mental health symptoms. However, few randomized controlled trials have evaluated ultra-brief, remotely delivered, meditation using multimodal outcome assessment under real-world conditions. MethodsWe conducted a fully remote randomized controlled trial (ClinicalTrials.gov: NCT06014281) evaluating a focused-attention meditation intervention delivered via brief instructor training and independent daily practice. A total of 299 meditation-naive adults were randomized to immediate intervention or waitlist control in a delayed-intervention design. Participants practiced [&ge;]10 minutes daily for 8 weeks within a 16-week study. Outcomes included validated self-report measures, web-based cognitive tasks, and wearable-derived physiological metrics. ResultsAcross randomized and within-participant replication phases, the intervention was associated with significant reductions in anxiety and mind wandering, with effects remaining stable during 8-week follow-up. Improvements were greatest among participants with higher baseline symptom burden. Sleep disturbance improved selectively among individuals with poorer baseline sleep. Secondary outcomes, including rumination, perceived stress, social connectedness, and quality of life, also improved. Cognitive performance showed modest improvements primarily among lower-performing participants. Resting heart rate exhibited nominal reductions. ConclusionsAn ultra-brief, fully remote meditation intervention requiring 10 minutes per day was associated with sustained improvements in psychological functioning and smaller, baseline-dependent effects on cognition in a non-clinical population. These findings support digital delivery of low-dose meditation as a scalable preventive mental health strategy.

Early behavioral and temperamental differences are important indicators of later socioemotional development and psychopathology risk, yet their neural bases near birth remain incompletely understood. Using resting-state fMRI data from the Developing Human Connectome Project, we examined whether neonatal functional connectivity predicts 18-month behavioral and temperament outcomes in 397 infants (277 term-born, 120 preterm-born). Outcomes were assessed using the Child Behavior Checklist (CBCL) and the Early Childhood Behavior Questionnaire (ECBQ). We applied a stability-driven, ROI-constrained connectome-based predictive modeling framework to identify robust whole-brain connectivity features associated with later externalizing, internalizing, surgency, negative affect, and effortful control. Significant predictive models were observed for multiple outcomes across the whole cohort as well as within term-born and preterm-born groups, with clear differences in predictive architecture between cohorts. Across analyses, prefrontal and temporoparietal systems were repeatedly implicated, alongside medial temporal, fusiform, parahippocampal, and orbitofrontal-related regions. These findings indicate that large-scale neonatal functional organization is meaningfully related to later socioemotional and behavioral variation, and that preterm birth is associated with partly distinct predictive connectivity patterns.

ImportanceBlood-based biomarkers hold promise for psychiatric diagnosis and prognosis, yet clinical translation is constrained by poor reproducibility. Psychiatric biomarker studies are typically small, and demographic, behavioral, and temporal covariates often go undetected or cannot be adequately modeled. This may lead to residual confounding and unstable associations. ObservationsLeveraging UK Biobank data (N=~500,000), we systematically quantified how technical, demographic, behavioral, and temporal covariates influence 29 blood biomarkers commonly measured in research studies in psychiatry. Variance analyses showed substantial differences across biomarkers. Technical factors explained 1-6% and demographic factors explained 5-15% of the variance, with pronounced age-by-sex interactions for lipids and sex hormones. Behavioral covariates, particularly body mass index (BMI) and smoking, strongly influenced inflammatory markers. Temporal factors introduced systematic confounding. Chronotype was associated with blood collection time, multiple biomarkers exhibited marked diurnal rhythms (including testosterone, triglycerides, and immune markers), and inflammatory markers showed seasonal peaks in winter. In association analysis of biomarkers with major depression, bipolar disorder and schizophrenia, covariate adjustments attenuated or eliminated a substantial proportion of the biomarker-disorder associations, with BMI emerging as the dominant confounder. These findings demonstrate that such confounding structures exist and can be characterized in large cohorts, though specific biomarker-disorder relationships require validation in clinical samples. Conclusions and RelevancePoor reproducibility of biomarkers may not only stem from insufficient biological signal but also from inconsistent handling of confounders. We propose a systematic framework distinguishing technical factors (to be removed), demographic factors (addressed through adjustment or stratification), temporal factors (ideally controlled at design stages), and behavioral factors (requiring explicit causal reasoning). Associations robust to multiple adjustment strategies should be prioritized for clinical biomarker development. Standardized collection protocols, comprehensive covariate measurement, and transparent reporting across models are essential to improve reproducibility and identify biomarkers that reflect genuine illness-related pathophysiology.

ObjectiveTo describe the design, feasibility, and baseline characteristics of the Migraine Impact on Neurocognitive Dynamics (MIND) study, a 30-day smartphone-based cohort for high-frequency assessment of cognition and symptoms in adults with migraine. BackgroundCognitive symptoms are an important component of migraine burden, but they are difficult to measure using single-visit testing or retrospective questionnaires. Repeated smartphone-based assessment may better capture real-world variability in cognition and symptoms. MethodsAdults meeting International Classification of Headache Disorders, 3rd edition, criteria for migraine were enrolled remotely and completed 30 days of once-daily ecological momentary assessments and mobile cognitive tasks delivered through the Mobile Monitoring of Cognitive Change platform. Baseline measures assessed demographics, migraine characteristics, disability, mood, stress, and treatment patterns. Feasibility was evaluated using enrollment, completion, and retention metrics. ResultsA total of 177 participants enrolled (mean age 38.8 {+/-} 11.9 years; 79.7% female), including 80/177 (45.2%) with chronic migraine. Across the 30-day protocol, 3688 daily assessments were completed, representing 70.8% of all possible study days, and 70.6% of participants completed at least 20 days of monitoring. Completion remained above 60% across study days. At baseline, chronic migraine was associated with greater burden than low-frequency and high-frequency episodic migraine, including higher MIDAS scores (98.6 vs. 38.7 and 70.3), more days with concentration difficulty (16.0 vs. 7.9 and 11.5), and more days with functional interference (18.5 vs. 7.6 and 13.0). ConclusionsThe MIND study demonstrates the feasibility of high-frequency smartphone-based assessment of cognition and symptoms in migraine and provides a methodological foundation for future analyses of within-person cognitive and symptom dynamics across the migraine cycle.

ObjectivePathological beta-band oscillations (13 to 30 Hz) in the subthalamic nucleus (STN) are a hallmark of Parkinsons disease and a primary target for deep brain stimulation therapy, yet the specific pattern of synaptic reorganization that drives their emergence remains incompletely understood. We developed a GPU-accelerated computational framework to systematically investigate combinations of synaptic changes across basal ganglia pathways that produce Parkinsonian beta oscillations while satisfying literature-based electrophysiology constraints. ApproachWe implemented a biophysically detailed spiking network model of the STN, external globus pallidus (GPe), and internal globus pallidus (GPi) in JAX (a high-performance numerical computing Python library), achieving a 490-fold speedup over conventional CPU-based simulation. Using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) we optimized 10 network parameters across two stages: first establishing a healthy baseline matching primate electrophysiology data, then searching within biologically motivated bounds for synaptic modifications that reproduce Parkinsonian firing rates and beta power. Fixed in-degree connectivity ensured optimized parameters produced scale-invariant dynamics from 450 to 45000 neurons. All simulations ran on a single cloud GPU instance at 84 cents per hour. Main ResultsThe optimizer converged on a coordinated pattern of synaptic reorganization dominated by asymmetric changes within the STN-GPe reciprocal loop: STN to GPe excitation increased 2.21-fold while GPe to STN inhibition collapsed to 0.11-fold of its healthy value. STN to GPi and GPe to GPi pathways changed minimally (1.06-fold and 1.45-fold respectively). This configuration transformed asynchronous firing (beta: 0.4 percent of spectral power) into synchronized bursting with prominent beta oscillations (49.4 percent), with firing rate changes matching experimental observations. Network dynamics were invariant across a 100-fold range of network sizes (firing rate deviation less than 2.4 Hz; all metrics p less than 0.001 across 10 random seeds at 45000 neurons). We implemented a simplified deep brain stimulation model for validation purposes, which achieved complete beta suppression (49.4 percent to 0.0 percent) and restored GPi output to healthy levels. SignificanceThese results suggest that pathological beta oscillations emerge from a specific pattern of synaptic reorganization, namely the reduction of GPe inhibitory feedback to STN. The GPU-accelerated optimization framework, running on commodity cloud infrastructure, demonstrates an accessible platform for parameter exploration in neural circuit models and a foundation for generating synthetic training data for adaptive deep brain stimulation algorithms.

Chronic pain and nicotine use frequently co-occur, and individuals with chronic pain often experience greater difficulty quitting. Therefore, we examined nicotine withdrawal behaviors and analgesic-like effects in pain-naive and chronic pain conditions. Adult male and female rats underwent chronic constriction injury or sham surgery. After pain establishment, rats received twice-daily subcutaneous nicotine (0.3 or 0.7 mg/kg) or saline for 14 days. 24 h after the final injection, withdrawal was assessed, including physical signs and anxiety-like behavior. Depressive-like responses were evaluated at 72 h. Pain sensitivity and nicotines analgesic-like effects were assessed throughout. Chronic pain increased physical signs of withdrawal in both sexes, with greater effects in females. It also induced anxiety-like behavior in controls of both sexes. In rats with comorbid chronic pain and withdrawal, anxiety-like behavior was further enhanced in males, whereas females showed variable responses across assays, with increases or decreases depending on the test. Chronic pain induced depressive-like behavior in males but not in females. During withdrawal, depressive-like responses in males with chronic pain were not greater than those in the chronic pain alone group, while chronic nicotine exposure reduced depressive-like behavior in females. Nicotine produced acute analgesic-like effects that diminished over time in both pain-naive and chronic pain conditions, indicating tolerance. In pain-naive rats, repeated nicotine exposure induced mechanical hypersensitivity. Chronic pain intensified nicotine withdrawal severity in a nicotine concentration- and sex-dependent manner. These findings highlight the importance of considering pain status and sex when developing effective cessation strategies, particularly for individuals with comorbid chronic pain. SummaryChronic pain exacerbates nicotine withdrawal severity. Chronic nicotine exposure induces pain hypersensitivity and tolerance to analgesic effects. These effects vary by nicotine concentration and sex.

BackgroundPsilocybin is a classic psychedelic that acutely alters brain functional connectivity. These changes are linked to therapeutic doses and subjective effects, with some evidence that changes persist beyond acute drug administration. However, the effects of lower doses on sustained connectivity changes remain unclear. MethodsTen healthy volunteers received three psilocybin doses (between 5 and 20 mg) in a randomized and blinded order, with at least one week between doses. Resting-state functional magnetic resonance imaging was completed at baseline and one week after a single dose. Functional connectivity changes were analyzed in relation to dose and altered conscious states at both the level of individual brain region connections (edges) and resting-state networks. ResultsDose-dependent changes in 77 edges (76 increases, 1 decrease, of 1275 possible) were observed, but none survived multiple-comparison correction. At the network level, we observed one dose-dependent between-network increase (of 21 possible), and one dose-dependent within-network increase (of seven possible); the latter surviving correction. Alterations in conscious state were positively associated with widespread connectivity changes (dose-adjusted), with many network-level associations surviving correction. These directional patterns showed that lower doses and smaller conscious state alterations were linked to decreased connectivity, whereas higher doses and greater conscious state alterations were linked to increased connectivity. ConclusionsDose level and acute subjective effects were positively associated with multiple functional connectivity changes one week after a low-to-moderate psilocybin dose. Further research is warranted to characterize these sustained effects and their therapeutic relevance to inform studies adopting similar dosing regimens in clinical cohorts. Trial RegistrationAustralian New Zealand Clinical Trials Registry: ACTRN12621000560897 Date registered: 12 May 2021 URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381526&isReview=true

Chronotype reflects individual circadian preference for timing of sleep, wakefulness, and peak performance and has been linked to variability in prefrontal cognitive function across the day. Whether chronotype independently relates to dual-task gait cost (DTC) and whether this relationship differs by cognitive task domain is unclear. Sixty-nine healthy young adults (37 female; mean age 21.3 years) completed the Morningness-Eveningness Questionnaire (MEQ). Spatiotemporal gait parameters were recorded with three-dimensional motion capture during single-task walking and three dual-task conditions: backward word spelling (5LWB; phonological), serial subtraction by seven (SS7; arithmetic), and reverse month recitation (RMR; sequential). DTC was calculated for eight gait parameters. Condition differences were assessed with nonparametric tests and post-hoc comparisons. Multiple linear regression, adjusting for age, sex, BMI, and baseline gait velocity, tested the independent association between MEQ score and mean velocity DTC; exploratory Spearman correlations examined other parameters. SS7 produced the largest mean velocity DTC (-12.76%), significantly greater than 5LWB (-7.95%; p = 0.002) and RMR (-9.57%; p = 0.021). MEQ score independently predicted mean velocity DTC in 5LWB ({beta} = -0.51, p < 0.001, R{superscript 2} = 0.269) and RMR ({beta} = -0.55, p = 0.004, R{superscript 2} = 0.222), indicating greater morningness associated with better gait-speed preservation under cognitive load; the SS7 association was not significant ({beta} = -0.33, p = 0.071). Exploratory correlations showed MEQ-DTC associations across 7/8 parameters in 5LWB, 4/8 in RMR, and 3/8 in SS7. Chronotype is independently associated with dual-task gait cost in a task-domain-specific manner, with stronger effects for phonological and sequential tasks than for arithmetic processing. The SS7 condition yielded the largest interference but weakest chronotype modulation, suggesting arithmetic dual-task disruption may be less sensitive to circadian arousal. Fixed testing time and cross-sectional design warrant within-subject, multi-timepoint studies to confirm chronotype effects separate from time-of-day confounds.

Background: Early adolescence is a common period of onset for depressive symptoms. In part, this may reflect a developmental manifestation of individual's genetic propensities as they undergo physiological and hormonal changes and interact with new environments. Many commonly proposed mechanisms assume direct effects of an individual's own genes on emerging variation in their depressive symptomatology. However, estimates of genetic influence based on analyses in unrelated individuals capture not only direct genetic effects but also genetic effects from parents and other biologically related family members. Aim: In data from the Norwegian Mother, Father and Child Cohort (MoBa), we used linear mixed models to distinguish developmentally-stable and adolescence-specific direct and parental indirect genetic effects. We examined effects of polygenic scores for major depressive disorder (MDD), ADHD, anxiety disorders, and educational attainment (EA) on depressive symptoms, which were assessed by maternal reports at ages 8 and 14. Results: Children's own MDD polygenic scores showed adolescence-specific effects on depressive symptoms ( b_PGS*wave=0.041, [95% CI: 0.017, 0.065]). Developmentally-stable direct effects from children's polygenic scores for MDD (b=0.016, [0.006, 0.039]), ADHD (b=0.024, [0.008, 0.041]) and EA (b=-0.02, [ -0.038, -0.002]) were also evident. The only evidence of indirect genetic effects was a stable effect of maternal EA polygenic scores (b=0.04, [0.024, 0.054]). Conclusion: Direct genetic effects linked to genetic liability to MDD accounted for emerging variation in depressive symptoms in adolescence. These results imply that specific etiological mechanisms related to MDD may become particularly relevant for depressive symptoms during early adolescence compared to at earlier ages.

Metabotropic glutamate 2/3 receptors (mGluR2/3) have been implicated in depression, anxiety, learning, and memory. However, their causal role in reward-related behaviors remains unclear. Here, we examined the effects of intraperitoneal administration of LY341495, a selective mGluR2/3 antagonist, on reward-related behaviors in mice. In a head-fixed temporal conditioning task, mice received a 10% sucrose solution every 10 seconds. After training, mice exhibited anticipatory licking and pupil dilation aligned with expected reward delivery, indicating successful reward prediction. LY341495 dose-dependently reduced licking behavior without disrupting temporal prediction, as normalization analyses revealed reduced gain but preserved timing. LY341495 also induced overall pupil dilation and attenuated reward-proximity pupillary responses. To determine whether reduced licking reflected general motor impairment, we assessed spontaneous locomotion in a freely moving open-field task. LY341495 did not affect locomotor activity or excretion, suggesting intact general motor and autonomic function. To further evaluate orofacial motor function, we measured ultrasonic vocalizations (USVs) during a social interaction task. LY341495 did not significantly alter USVs, indicating preserved mouth-related motor function independent of licking. In contrast, LY341495 dose-dependently reduced food intake in a freely moving feeding task. Moreover, social preference testing revealed that LY341495 reduced social interaction, suggesting impaired processing of non-food rewards. Together, these findings demonstrate that mGluR2/3 signaling regulates reward-seeking behaviors independently of general locomotor or orofacial motor function. These results provide new insights into glutamatergic mechanisms underlying reward processing and may have clinical implications for obesity, eating disorders, and psychiatric conditions involving motivational dysfunction.

Background: The etiology and nosological status of seasonal affective disorder (SAD) as a specifier of depressive episodes versus a transdiagnostic disorder are the subject of debate. In this study, we investigated the underlying etiology of SAD and dimensional seasonality by examining their association with latitude and genetic risk for a range of traits, and investigated gene-environment interactions. Methods: This study included 12,460 adults aged 18-90 with a history of depression from the Australian Genetics of Depression Study. Regression models included predictors for latitude (distance from equator) and polygenic scores for eight traits; major depressive disorder, bipolar disorder, anxiety disorders, chronotype, sleep duration, body mass index, vitamin D levels, and educational attainment. Outcomes were SAD status and general seasonality score. Results: SAD was positively associated with latitude (OR[95%CI] = 1.05[1.03-1.06], padjusted<0.001), and there was nominal evidence of additive and multiplicative interactions between chronotype genetic risk and latitude (OR = 0.99[0.99-0.99], padjusted=0.381; OR=0.98[0.97-0.99], padjusted=0.489). General seasonality score was associated with latitude (IRR=1.01[1.01-1.01], padjusted 0.001) and genetic risk for major depressive disorder (IRR =1.02[1.01-1.03], padjusted<0.001), bipolar disorder (IRR=1.02[1.01-1.03], padjusted=0.001), anxiety disorders (IRR=1.03[1.01-1.04], padjusted<0.001), vitamin D levels (OR=0.89[0.80-0.95], padjusted=0.048), and educational attainment (IRR=0.97[0.96-0.99], padjusted<0.001). Conclusions: These findings enhance understanding of SAD etiology, highlighting contributions of psychiatric genetic risk and geographic measures on seasonal behavior, and support examining seasonality as a continuous dimension.

Substance use disorders run in families, yet the mechanisms underlying intergenerational transmission remain unclear. We investigated indirect genetic effects, pathways through which parental genotypes influence offspring phenotypes via the family environment, for alcohol use disorder (AUD), nicotine dependence (ND), and related quantitative outcomes, and aimed to identify family environmental factors through which such effects may operate. Using transmitted and non-transmitted polygenic scores (PGS) constructed for problematic alcohol use, tobacco use disorder, and general addiction liability, we analyzed 5972 European-ancestry adult offspring with at least one genotyped parent from the population-based Lifelines cohort (Netherlands). Offspring outcomes included lifetime DSM-5 AUD diagnosis, AUD symptom count, maximum drinks in 24 hours, Fagerstrom Test for Nicotine Dependence score, and cigarettes per day. AUD findings were meta-analyzed with data from the Brisbane Longitudinal Twin Study (N = 1368; Australia). We also examined parent-of-origin effects and mediation by parental substance use and socioeconomic status using structural equation modeling. Transmitted PGS robustly predicted all AUD and ND outcomes ({beta} = 0.07-0.16; OR = 1.20 for AUD diagnosis). Non-transmitted PGS, indexing indirect genetic effects, were negligible for all clinical syndrome outcomes. The only significant indirect genetic effect was on cigarettes per day ({beta} = 0.03, p = 0.01), mediated by parental smoking behavior but not socioeconomic status. These findings indicate that intergenerational transmission of risk for AUD and ND is driven primarily by direct genetic effects, with modest indirect genetic effects on smoking quantity. Larger samples and cross-trait analyses are needed to further elucidate these mechanisms.