This study is a step towards using non-trivial navigation tasks in rodents as a tool to study cognitive processes. Mice can learn to perform a spatial task where they have to form, retain & use hypotheses to identify otherwise ambiguous landmarks that can only be seen one at a time. Neurons in RSC encode the ensuing hypothesis states (states that are informed by prior sensory information & self-motion, and can disambiguate future sensory data) conjunctively with many other variables, and were constrained by stable recurrent dynamics. In collaboration with Ingmar Kanitscheider in Fiete lab we found that this type of recurrent dynamics can in principle solve the task, showing that local circuits in of associative cortex can form, retain, and apply hypotheses. This suggests that general sequential reasoning can be performed via low dimensional recurrent neural dynamics, where hypotheses, motor and sensory data, and their interpretation are co-represented and influence each other.
Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex
J Voigts, I Kanitscheider, NJ Miller, EHS Toloza, JP Newman, IR Fiete, MT Harnett, bioRxiv