Generative network models for neurodevelopment in infants with and without familial risk for autism
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School of Engineering and Applied Science::Department of Bioengineering::Departmental Papers (BE)
Degree type
Discipline
Biomedical Engineering and Bioengineering
Neuroscience and Neurobiology
Neuroscience and Neurobiology
Subject
Generative network models
Structural connectivity
Graph theory
Autism spectrum disorder
Infancy
Brain development
Structural connectivity
Graph theory
Autism spectrum disorder
Infancy
Brain development
Funder
Grant number
Copyright date
2022-06
Distributor
Related resources
Author
Parker, Drew
Tunç, Birkan
Wang, Rongguang
Hernandez, Moises
Estes, Annette
Zwaigenbaum, Lonnie
Styner, Martin
Gerig, Guido
McKinstry, Robert
Contributor
Abstract
Connectivity abnormality has been widely characterized in autistic children and adolescents, but what mechanisms drive network alterations, and when network divergence arises, are unknown. Here we present a longitudinal study of structural networks over the first two years of life in 369 infants at high and low familial risk for autism. We utilize generative network models (GNMs) to explore possible wiring rules in early development and their associations with behavior scores.
Advisor
Date of presentation
2022-06
Conference name
The Organization for Human Brain Mapping (OHBM)
Conference dates
2022-06
Conference location
Glasgow, Scotland, United Kingdom