Tracking the changes of hippocampal population nonlinear dynamics in rats learning a memory-dependent task

Neurobiological processes associated with learning are known to be highly nonlinear, dynamical, and time-varying. Characterizing the time-varying functional input-output properties of neural systems is a critical step to understand the neurobiological basis of learning. In this paper, we present a study on tracking of the changes of neural dynamics in rat hippocampus during learning of a memory-dependent delayed nonmatch-to-sample (DNMS) task. The rats were first trained to perform the DNMS task without a delay between the sample and response events. After reaching a performance level, they were subjected to the DNMS task with variable delays with a 5s mean duration. Spike trains were recorded from hippocampal CA3 (input) and CA1 (output) regions during all training sessions and constitute the input-output data for modeling. We applied the time-varying Generalized Laguerre-Volterra Model to study the changes of the CA3-CA1 nonlinear dynamics using these data. Result showed significant changes in the Volterra kernels after the introduction of delays. This result suggests that the CA3-CA1 nonlinear dynamics established in the initial training sessions underwent a functional reorganization as animals were learning to perform the task that now requires delays.