Enhanced learning in a cerebellum-specific mouse model of autism

I will present our work on a cerebellum-specific transgenic mouse model of autism spectrum disorder which shows faster learning on a sensory evidence-accumulation task as well as enhanced sensitivity to touch and auditory cues. By combining Neuropixels recordings, optogenetic manipulation, and computational latent-state analysis of behavior, we show the cerebellar perturbations are associated with enhanced neocortical activity and enhanced focus on current rather than past information. Furthermore, in collaboration with other labs, we developed a machine learning classifier to identify cell type in the cerebellum from Neuropixels recordings based on an optotagged ground-truth dataset. Last, I will share some preliminary data from new research lines I am currently developing at the University of Amsterdam about play and social interactions in mice.