Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

12The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P ≤ 5 x 10 -8 ); 199 survived multiple testing correction (P ≤ 8.3 x 10 -10 ; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression and ADHD.One Sentence Summary: Common genetic variation is associated with inter-individual variation in the structure of the human cortex, both globally and within specific regions, and is shared with genetic risk factors for some neuropsychiatric disorders.The human cerebral cortex is the outer grey matter layer of the brain, which is implicated in multiple aspects of higher cognitive function. Its distinct folding pattern is characterised by convex (gyral) and concave (sulcal) regions. Computational brain mapping approaches use the consistent folding patterns across individual cortices to label brain regions(1). During fetal development excitatory neurons, the predominant neuronal cell-type in the cortex, are generated from neural progenitor cells in the developing germinal zone(2). The radial unit hypothesis(3) posits that the expansion of cortical surface area (SA) is driven by the proliferation of these neural progenitor cells, whereas thickness (TH) is determined by the number of neurogenic divisions. Variation in global and regional measures of cortical SA and TH are associated with neuropsychiatric disorders and psychological traits(4) ( Table S1). Twin and family-based brain imaging studies show that SA and TH measurements are highly heritable and are largely influenced by independent genetic factors(5). Despite extensive studies of genes impacting cortical structure in model organisms (6), our current understanding of genetic variation impacting human cortical size and patterning is limited to rare, highly penetrant variants (7,8). These variants often disrupt cortical development, leading to altered post-natal structure. However, little is known about how common genetic variants impact human cortical SA and TH.To address this, we conducted genome-wide association meta-analyses of cortical SA and TH measures in 51,662 individuals from 60 cohorts from around the world (Tables S2-S4). Cortical measures were extracted from structural brain MRI scan...

Background Though rehabilitation therapy is commonly provided after stroke, many patients do not derive maximal benefit due to access, cost, and compliance. A telerehabilitation-based program may overcome these barriers. We designed then evaluated a home-based telerehabilitation system in patients with chronic hemiparetic stroke. Methods Patients were 3–24 months post-stroke with stable arm motor deficits. Each received 28 days of telerehabilitation using a system delivered to their home. Each day consisted of one structured hour focused on individualized exercises and games, stroke education, and an hour of free-play. Results Enrollees (n=12) had baseline Fugl-Meyer (FM) score of 39±12 (mean±SD). Compliance was excellent: participants engaged in therapy on 329/336 (97.9%) assigned days. Arm repetitions across the 28 days averaged 24,607±9,934 per subject. Arm motor status showed significant gains (FM change 4.8±3.8 points, p=0.0015), with half of subjects exceeding the minimal clinically important difference. Although scores on tests of computer literacy declined with age (r=−0.92, p<0.0001), neither the motor gains nor the amount of system use varied with computer literacy. Daily stroke education via the telerehabilitation system was associated with a 39% increase in stroke prevention knowledge (p=0.0007). Depression scores obtained in person correlated with scores obtained via the telerehabilitation system 16 days later (r=0.88, p=0.0001). In-person blood pressure values closely matched those obtained via this system (r=0.99, p<0.0001). Conclusions This home-based system was effective in providing telerehabilitation, education, and secondary stroke prevention to participants. Use of a computer-based interface offers many opportunities to monitor and improve the health of patients after stroke.

Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use.

EEG has been used to study acute stroke for decades; however, because of several limitations EEG-based measures rarely inform clinical decision-making in this setting. Recent advances in EEG hardware, recording electrodes, and EEG software could overcome these limitations. The present study examined how well dense-array (256 electrodes) EEG, acquired with a saline-lead net and analyzed with whole brain partial least squares (PLS) modeling, captured extent of acute stroke behavioral deficits and varied in relation to acute brain injury. In 24 patients admitted for acute ischemic stroke, 3 min of resting-state EEG was acquired at bedside, including in the ER and ICU. Traditional quantitative EEG measures (power in a specific lead, in any frequency band) showed a modest association with behavioral deficits [NIH Stroke Scale (NIHSS) score] in bivariate models. However, PLS models of delta or beta power across whole brain correlated strongly with NIHSS score (R(2) = 0.85-0.90) and remained robust when further analyzed with cross-validation models (R(2) = 0.72-0.73). Larger infarct volume was associated with higher delta power, bilaterally; the contralesional findings were not attributable to mass effect, indicating that EEG captures significant information about acute stroke effects not available from MRI. We conclude that 1) dense-array EEG data are feasible as a bedside measure of brain function in patients with acute stroke; 2) high-dimension EEG data are strongly correlated with acute stroke behavioral deficits and are superior to traditional single-lead metrics in this regard; and 3) EEG captures significant information about acute stroke injury not available from structural brain imaging.