Linking neural representations to behavior using generalization

Abstract

Sensory-guided decisions are the result of sensorimotor transformations across many brain areas. Recent studies have localized the motor- and decision-related components of these transformations using brain-wide neural recordings. It has been more difficult to localize sensory computations in the same way. Here we developed a new approach for linking sensory computations to behavior by training mice to discriminate between two stimuli and testing their responses with new stimuli. In separate animals, we calculated the similarity of neural representations between train and test stimuli, using recordings of up to 73,000 simultaneously-recorded neurons from 9 primary and higher-order visual areas (HVAs) across layers 2 and 3. We found that neural discrimination on test but not train images correlated with behavioral discrimination, and this relation required prior visual experience as it was not present in dark-reared mice. The link between neural and behavioral performance was highest in the medial HVAs, suggesting this region is a critical component of sensory transformations and generalization.