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Margolis, A.

Publications and source records attributed to Margolis, A..

2 recordsLinked to original sources

A convergent structure-function substrate of cognitive imbalances in autism

Autism is a common neurodevelopmental condition characterized by substantial phenotypic heterogeneity, which hinders diagnosis, research, and intervention. A leading example can be found in marked imbalances in language and perceptual skills, where deficits in one domain often co-exist with normal or even superior performance in the other domain. The current work capitalized on multiple data analytics including data-driven subtyping and dimensional approaches to quantify cognitive imbalances in multi-site datasets of individuals diagnosed with autism spectrum disorder (ASD) and neurotypical controls, and assessed structural and functional brain network substrates. Studying cognitive dimensions as well as multimodal neuroimaging signatures in 155 ASD and 151 neurotypical individuals, we observed robust evidence for a structure-function substrate of cognitive imbalances in ASD. Specifically, ASD presented with marked imbalances in cognitive profiles relative to neurotypical controls, characterized by verbal to non-verbal intelligence discrepancy. Different analytical approaches including subtyping and dimensional regression methods converged in showing that these imbalances were reflected in atypical cortical thickening and functional integration of language networks, alongside with sensory and higher cognitive networks. Phenotypic findings could be replicated in an independent sample of 325 ASD and 569 neurotypical controls. Although verbal and non-verbal intelligence are currently considered as specifiers unrelated to the categorical diagnosis of autism, our results show that intelligence disparities are accentuated in ASD and relate to a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity of autism and potentially inform intervention-oriented subtyping.

neuroscience↗

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗