Investigating Co-Activation between Medial Prefrontal and Primary Motor Cortical Spike Trains during Task Learning.

The medial prefrontal cortex (mPFC) and primary motor cortex (M1) are both actively involved in the reward guided learning. However, how the information is conveyed in spike trains between these two regions has not been investigated. Spike prediction models have been developed to predict the spike trains between two cortical areas, for example, CA3 to CA1 in hippocampus, as well as premotor to M1. In this paper, we investigate the co-activation between mPFC and M1 by comparing three spike prediction models with different nonlinear capacity. Our data was collected from the mPFC and M1 of a rat when it was learning a two-lever discrimination task. The mPFC spike trains are served as the input of models and M1 spike trains as the desired output. We compare the spike prediction performances of three models, including generalized linear model (GLM), second order GLM, and staged point-process model. Our results show that all three model outputs have similar discrete-time rescaling Kolmogorov-Smirnov test results and similar correlation coefficient (0.42 on average across neurons). The paired t-tests across neurons also show the lack of significant difference. The preliminary results indicate possible linear co-activation between the M1 and mPFC during the learning stage.