Identifying latent states in decision-making from cortical inactivation data
Zeinab Mohammadi,Zoe C. Ashwood,Lucas Pinto,David W. Tank,Carlos D. Brody,Jonathan Pillow · COSYNE 2022
Recent work has shown that rodent decision-making relies on distinct latent or hidden states that switch on a timescale of tens to hundreds of trials [Ashwood 2021; Bolkan, Stone 2021; Weilnhammer 2021]. However, the neural basis for these states, and the contributions of different brain regions to state-dependent decision-making strategies, remains an important open problem. Here we address this challenge by performing a model-based analysis of decision-making data acquired during multi-region laser-scanning inactivation of dorsal cortex. We analyzed optogenetic inactivation data from mice pe
Thu, Mar 17, 2022