Genetic risk for autism spectrum disorders (ASD) is associated with hundreds of genes spanning a wide range of biological functions 1-6 . The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals 6,7 . Here, we leveraged organoid models of the human cerebral cortex to identify cell type-specific developmental abnormalities resulting from haploinsufficiency in three ASD risk genes, SUV420H1 (KMT5B), ARID1B, and CHD8, in multiple cell lines from different donors, using single-cell RNA-seq (scRNA-seq) of over 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations demonstrates asynchronous development of two main cortical neuronal lineages, GABAergic neurons and deep-layer excitatory projection neurons, but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This work uncovers cell typespecific neurodevelopmental abnormalities shared across ASD risk genes that are finely modulated Paulsen et al.

Motor skills improve with practice, requiring outcomes to be evaluated against ever-changing performance benchmarks, yet it remains unclear how performance error signals are computed. Here, we show that the songbird ventral pallidum (VP) is required for song learning and sends diverse song timing and performance error signals to the ventral tegmental area (VTA). Viral tracing revealed inputs to VP from auditory and vocal motor thalamus, auditory and vocal motor cortex, and VTA. Our findings show that VP circuits, commonly associated with hedonic functions, signal performance error during motor sequence learning.

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms.Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences.Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks.Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.