title: Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses.
abstract: Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2-3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.
authors: Electrical Engineering, School of Electrical, Computer and Energy Engineering, Arizona State University Tempe, AZ, USA.
authors: Hongwei
authors: H
authors: Mao
authors: Electrical Engineering, School of Electrical, Computer and Energy Engineering, Arizona State University Tempe, AZ, USA.
authors: Yuan
authors: Y
authors: Yuan
authors: Electrical Engineering, School of Electrical, Computer and Energy Engineering, Arizona State University Tempe, AZ, USA ; Graduate Faculty of the School of Biological and Health Systems Engineering, Arizona State University Tempe, AZ, USA ; Affiliate Faculty of the Interdisciplinary Graduate Program in Neuroscience, Arizona State University Tempe, AZ, USA.
authors: Jennie
authors: J
authors: Si
keywords: action selection; agranular medial and lateral areas; associative learning; plasticity; support vector machines