Individuals diagnosed with schizophrenia spectrum disorder (SSD) face an elevated risk of premature mortality, with life expectancy reduced by 10 to 20 years compared with the general population. This excess mortality is largely due to the early onset of medical conditions typically associated with older age, a process known as accelerated aging. While unhealthy lifestyle behaviors, such as smoking and poor diet, contribute to this risk, they do not fully account for the excess of physical comorbidities. Social isolation, which is associated with numerous health conditions in the general population and is a common, persistent characteristic among people with SSD, has not been comprehensively investigated as a contributing factor. The Social Isolation and Aging in Schizophrenia spectrum disorders (SIAS) study establishes a longitudinal database of 650 participants initially recruited to studies in the Netherlands, UK, Spain, and US, including 500 individuals with SSD and 150 unaffected first-degree relatives. An accelerated longitudinal design is employed, combining prior research data collected when participants were aged 20–55 with new follow-up assessments now that they are aged 40–70, allowing to study exposures and outcomes through the entire age-range of the sample (20–70). Clinical and digital phenotype data are being collected. The primary objective is to determine the association between social isolation and adverse health outcomes in SSD. Additionally, the study examines the directionality of this relationship, moderating factors, and the impact of the COVID-19 pandemic. This is the first large-scale follow-up study examining the long-term health impact of social isolation in individuals with SSD. Key strengths include the integration of data across a five-decade age span, the cross-national design, the inclusion of unaffected first-degree relatives to assess familial factors, and the integration of digital phenotypic and clinical assessments. Findings from SIAS will provide critical insights into prevention targets for reducing premature mortality and improving overall health in SSD. This study was registered at ClinicalTrials.gov with ID number NCT07419321.

Reproducibility of neuroimaging analyses and aggregation of heterogenous datasets are significant challenges in human subjects imaging research. This stems in part from a lack of an easy to use and universal data format that encompasses all steps of neuroimaging. The BIDS format has become widely adopted, however it is increasingly complex to implement as features are added, with the documentation now exceeding 500 pages. As such, there is a need for standards that can handle the complexity of the data while minimizing the complexity of the format. Here we present a simple but generalizable data sharing specification, called the squirrel format (not related to the squirrel programming language), to share imaging data in a simple, but flexible, specification. It is so named because squirrels are effective at storing significant quantities of food and knowing exactly where and when to find it. The design objectives of the format specification are to 1) store subject information, experimental parameters, raw data, analyzed data, and analysis methods 2) organize data in a human-readable hierarchy 3) enable easy sharing and dissemination of data packages. We developed a relational hierarchy with a structured representation of all steps of neuroimaging data collection and analysis, and a generalizable specification to store any modality of neuroimaging data, which satisfies the design objectives. Additionally, redundancy is minimized by using relational database principles. The specification allows all research data to be classified into one of ten object types, thus simplifying the sharing of neuroimaging data. Like how squirrels employ 'chunking', the squirrel format chunks data into a manageable number of object types. The squirrel format was developed to share neuroimaging data but can be generalized to share any imaging research.

AIMS:In the context of increasing cannabis use, understanding how cannabis affects specific driving behaviors is crucial in mitigating risks and ensuring road safety. DESIGN AND SETTING:The current study included 38 adults aged 18-40 years, administered a single 0.5 g acute dose of vaporized cannabis (5.9% Tetrahydrocannabinol (THC), 13% THC or placebo) in a randomized, within-subject, double-blind, counterbalanced design. Throughout each of the three, 8-h assessment days, at 4 time points, participants underwent simulated driving tests, including lane-keeping, car following, and overtaking tasks, capturing 19 behavioral metrics. An SPSS linear mixed model assessed the main effects of dose, time, and dose × time. FINDINGS:During lane-keeping, participants exhibited reduced steering reversal rates up to 5.5 h following 13% THC and 3.5 h for 5.9%. For car following, participants showed reduced pedal peak-to-peak deviation and reversal rates, persisting for 1-3 h post-dose (only at 13% THC). During overtaking, following 13% THC, subjects demonstrated a shorter median gap to passed cars, lower time-to-potential collision, and more time in the oncoming lane. Drug effects on driving metrics improved gradually, to varying degrees over time. Approximately 66% of participants reported willingness to drive, despite subjective awareness of being impaired and objectively worse driving performance. CONCLUSIONS:Our study reveals for the first time long-lasting cannabis-induced impairments across multiple driving behaviors, that extend beyond the typical 3-h window explored in most previous research. The observed discrepancy between participants' willingness to drive and their actual impairment highlights an important public safety concern. In addition, the lack of correlation between cannabinoid metabolite concentrations and driving performance challenges the reliability of blood THC levels as impairment indicators, emphasizing the need for a multifaceted approach to assessing cannabis-impaired driving risk.

Individuals at clinical high risk for psychosis (CHR) have variable clinical outcomes and low conversion rates, limiting development of novel and personalized treatments. Moreover, given risks of antipsychotic drugs, safer effective medications for CHR individuals are needed. The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) Program was launched to address this need. Based on past CHR and schizophrenia studies, AMP SCZ assessed electroencephalography (EEG)-based event-related potential (ERP), event-related oscillation (ERO), and resting EEG power spectral density (PSD) measures, including mismatch negativity (MMN), auditory and visual P300 to target (P3b) and novel (P3a) stimuli, 40-Hz auditory steady state response, and resting EEG PSD for traditional frequency bands (eyes open/closed). Here, in an interim analysis of AMP SCZ EEG measures, we assess test-retest reliability and stability over sessions (baseline, month-2 follow-up) in CHR (n = 654) and community control (CON; n = 87) participants. Reliability was calculated as Generalizability (G)-coefficients, and changes over session were assessed with paired t-tests. G-coefficients were generally good to excellent in both groups (CHR: mean = 0.72, range = 0.49–0.85; CON: mean = 0.71, range = 0.44–0.89). Measure magnitudes significantly (p < 0.001) decreased over session (MMN, auditory and visual target P3b, visual novel P3a, 40-Hz ASSR) and/or over runs within sessions (MMN, auditory/visual novel P3a and target P3b), consistent with habituation effects. Despite these small systematic habituation effects, test-retest reliabilities of the AMP SCZ EEG-based measures are sufficiently strong to support their use in CHR studies as potential predictors of clinical outcomes, markers of illness progression, and/or target engagement or secondary outcome measures in controlled clinical trials. Watch Dr Daniel H. Mathalon discuss their work and this article: https://vimeo.com/1066564687 .

Purpose Evidence characterizing brain function in developmental language disorder (DLD) is limited because measured brain function may reflect individual variability in task performance and error processing. This methodological study began characterizing language-specific brain function by administering the adaptive semantic matching paradigm during functional magnetic resonance imaging (fMRI) to individuals with DLD and by using a Bayesian analytical approach appropriate for small clinical samples. Methods and results The adaptive semantic matching paradigm involved word-similarity judgements (e.g., age-night) and perceptual-similarity judgements of symbol strings (e.g., τουχφ-τουχε; i.e., control condition) during fMRI scanning. The adaptive component involved increases or decreases in task difficulty depending on in-the-moment individual participant accuracy (2-up-1-down adaptive weighted staircase, converges >80 % accuracy); controlling for individual variability in task performance. Bayesian analyses involved model comparison and second-level generalized linear models. Participants were adolescents with DLD (n = 5) and neurotypical controls (n = 12). Analyses indicated group differences in activation for right hemisphere frontal, temporal, and semantic language homologue networks, and no reliable differences in left hemisphere language networks or in lateralization. Conclusions and contributions The methodological contributions of the current study were the adaptive paradigm that elicits language-specific function and an analytical approach that is reliable for small, heterogeneous samples. These methods may differentiate whether variability in left hemisphere and lateralization patterns reflect between-study differences on in-scanner task performance versus the heterogeneous DLD profile. Future research guided by these methods and findings may reveal new insights that inform theoretical and clinical models of this highly prevalent neurodevelopmental condition.

BACKGROUND:Externalizing and internalizing disorders are common in youth but are often studied separately, preventing researchers from identifying shared (i.e., transdiagnostic) alterations in brain structure. Using data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium, we conducted a mega-analysis to identify shared and distinct cortical and subcortical brain alterations across internalizing (anxiety disorders and depression) and externalizing (attention-deficit/hyperactivity disorder [ADHD] and conduct disorder [CD]) disorders in youth. METHODS:3D T1-weighted magnetic resonance imaging data from youths (age range 4-21 years) with anxiety disorders (n = 1044), depression (n = 504), ADHD (n = 1317), and CD (n = 1172) along with healthy control participants (n = 4743) were analyzed. We assessed group differences in regional cortical thickness, surface area (SA), and subcortical volume using linear models, adjusted for site, age, and sex, as well as total intracranial volume in the SA and subcortical volume models. RESULTS:We observed transdiagnostic associations, with both internalizing and externalizing disorders characterized by lower SA in the insula, entorhinal cortex, and middle temporal gyrus and lower amygdala volume (Cohen's ds = -0.07 to -0.24) as well as total SA and intracranial volume (ds = -0.11 to -0.25). Externalizing-specific reductions in SA were observed in frontoparietal regions (ds = -0.08 to -0.13), but no internalizing-specific associations were identified. Disorder-specific alterations were identified for ADHD, CD, and anxiety disorders but not depression. CONCLUSIONS:Both common and disorder-specific alterations were identified, with regions involved in salience attribution and emotion processing implicated across internalizing and externalizing disorders. These novel findings can guide future research targeting common biological processes across youth psychiatric disorders as well as features unique to individual disorders.

There is a large and growing population of individuals aged over 65 in the United States, many of whom drive automobiles. Elements of aging may adversely impact driving ability; in some individuals, mild cognitive impairment and early dementia are responsible for further deterioration. Older drivers have more crashes per mile driven and are more likely to be injured or die in crashes of similar magnitude. At the same time, an increasing number of older people are using cannabis for medical and recreational purposes. Cannabis (mostly due to its delta-9 tetrahydrocannabinol [THC] content) compromises sensory and neurocognitive abilities necessary for safe driving, and acute use is associated with an increased rate of motor vehicle crashes, including fatal ones. Evidence suggests that older individuals are more likely to be impaired by cannabis, possibly reflecting altered THC metabolism (due to changes in bodily composition and pharmacokinetics), as well as age-related changes in neurocognitive function and in the brain's endocannabinoid system. Consequently, older drivers who use cannabis may be at substantially increased risk of involvement in motor vehicle crashes. Despite this confluence of age-related factors, the amount of research on cannabis' effects on the driving ability of older adults is negligible, and public health messaging related to this situation is lacking. We suggest that more attention be paid to this topic.

Younger versus older adolescents' brains likely are optimized to regulate emotional reactions differently. Here, we test whether age-related differences in trait-like use of diverse cognitive reappraisal styles predicts different emotion regulation (ER)-elicited brain activity.

Because outcomes from cognitive-behavioral therapy (CBT) are modest for hoarding disorder (HD), the objectives of this study were a) to characterize if CBT-related improvements were predicted by anterior cingulate cortex (ACC) or other cingulo-opercular network changes shown to be dysfunctional in our prior HD neuroimaging research, and b) to learn if CBT outcomes could be predicted by pre-CBT brain activity.

OBJECTIVE:Working memory training for Attention-Deficit/Hyperactivity Disorder (ADHD) has focused on increasing working memory capacity, with inconclusive evidence for its effectiveness. Alternative training targets are executive working memory (EWM) processes that promote flexibility or bolster stability of working memory contents to guide behavior via selective attention. This randomized, placebo-controlled study was designed to assess feasibility, tolerability, and behavioral target engagement of a novel EWM training for ADHD. METHOD:62 ADHD-diagnosed adolescents (12-18 years) were randomized to EWM training or placebo arms for 20 remotely coached sessions conducted over 4-5 weeks. Primary outcome measures were behavioral changes on EWM tasks. Secondary outcomes were intervention tolerability, trial retention, and responsiveness to adaptive training difficulty manipulations. RESULTS:Linear regression analyses found intervention participants showed medium effect size improvements, many of which were statistically significant, on Shifting and Filtering EWM task accuracy and Shifting and Updating reaction time measures. Intervention participants maintained strong self-rated motivation, mood, and engagement and progressed through the adaptive difficulty measures, which was further reflected in high trial retention. CONCLUSIONS:The results suggest that these EWM processes show promise as training targets for ADHD. The subsequent NIMH R33-funded extension clinical trial will seek to replicate and extend these findings.