Uncovering the neural code using a rat model during a learning control task

Authors:
Chenhui Yang;Hongwei Mao;Yuan Yuan;Bing Cheng;Jennie Si
Affiliations:
Arizona State University, Tempe, AZ;Arizona State University, Tempe, AZ;Arizona State University, Tempe, AZ;Arizona State University, Tempe, AZ;Arizona State University, Tempe, AZ
Venue:
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
Year:
2012

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Abstract

How neuronal firing activities encode meaningful behavior is an ultimate challenge to neuroscientists. To make the problem tractable, we use a rat model to elucidate how an ensemble of single neuron firing events leads to conscious, goal-directed movement and control. This study discusses findings based on single unit, multi-channel simultaneous recordings from rats frontal areas while they learned to perform a decision and control task. To study neural firing activities, first and foremost we needed to identify single unit firing action potentials, or perform spike sorting prior to any analysis on the ensemble of neural activities. After that, we studied cortical neural firing rates to characterize their changes as rats learned a directional paddle control task. Single units from the rat's frontal areas were inspected for their possible encoding mechanism of directional and sequential movement parameters. Our results entail both high level statistical snapshots of the neural data and more detailed neuronal roles in relation to rat's learning control behavior.