We use light-weight head mounted fluorescence microscopes and electrode arrays to study the structure of neural activity patterns and the rules governing the choreography of complex behavior and its underlying neural states.
Video: Activity in annotated ROIs aligned to song reveals a sequence-sensitive code depending on long-range order correlations.
We develop and leverage machine learning algorithms for annotating large datasets of canary songs to study the maintenance and changes of their rich repertoires across different time scales and social contexts. We combine realtime behavior manipulation by targeted perturbations with detailed video tagging and motion analysis to characterize the rules governing song syntax adaptation and perception by its target audience
Video: Canaries in the aviary
We combine tracking neural activity over time scales in which experience shapes behavior with theory and simulation of neural plasticity to ask which network architectures and which plasticity mechanisms underlie the acquisition of new long-range syntax rules and the reshaping of existing ones.
