Gabriela Rosenblau aims to describe how children with ASD learn about others, how learning strategies are implemented in the brain and how learning strategies predict children’s individual treatment outcomes. By providing precise, computational model-based analyses, this project will help guide more targeted behavioral treatments across the autism spectrum.

Gloria Choi will use immunological and behavioral and systems neuroscience tools to gain a mechanistic understanding of how fever-associated immune activation could ameliorate behavioral phenotypes relevant to autism in a mouse model.

Kevin Bender and Nadav Ahituv aim to determine whether upregulation of the remaining functional allele with CRISPR activation-based techniques can rescue cellular and behavioral deficits observed in Scn2a heterozygous mice. If successful, this approach may be applicable to other haploinsufficient genes associated with autism spectrum disorders.

Autism spectrum disorder (ASD) is characterized by changes in sensory perception, integration of information across different senses and simple forms of sensory learning. To better understand the changes in the brain that cause these symptoms, Ethan Scott plans to look at activity in thousands of brain cells simultaneously in transparent zebrafish as they respond to sensory inputs. The huge datasets from these experiments will reveal how sensory information normally flows through the brain and how this flow changes in zebrafish with mutations in ASD risk genes.

Corticostriatal dysfunction has emerged in the past few years as a potential converging pathophysiological mechanism underlying autism. Rui Peixoto will address how the maturation of corticostriatal circuits is affected by early imbalances in network activity using the Shank3 knockout mouse as a model of autism.