Abstract:
Emerging evidence demonstrates the feasibility of constructing genetically engineered non-human primates for studying neuropsychiatric disorders. Here we present a comparative fMRI-derived connectomics and behavioral paradigms on both nonhuman primate and human cohorts. Based on resting-state functional connectivity network in transgenic monkeys overexpressing MeCP2 and typically developing monkeys, we aim to identify the discriminant circuit feature triggered by a single genetic event. In parallel, we develop a novel crossspecies machine learning algorithm that leverages features learned from the primate genetic model to improve the classification of human patients with autistic spectrum disorders and obsessive-compulsive disorder. We thrive to probe the mechanistic links between gene expressions, dysfunction of specific neural networks and dimensional phenotypes, thereby providing refreshing insights into the complex etiology of autism-related disorders. These findings with explicable biological grounds are potentially amenable to translation for diagnosis and evaluation of future treatments.
Sponsored by the NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai