Neural ensemble sparse coding during working memory task in rat prefrontal cortex

Xu Yunhua; Bai Wenwen; Tian Xin

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Neural ensemble sparse coding during working memory task in rat prefrontal cortex

Xu Yunhua 1 #,Bai Wenwen 2,Tian Xin 2 *

1.Laboratory of Neuroengineering, Reaearch Centre of Basic Medicine, Tianjin Medical University

2.Laboratory of Neuroengineering, Reaearch Centre of Basic Medicine, Tianjin Medical University, Tianjin, 300070, China

*Correspondence author

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Funding: Specialized Research Fund for the Doctoral Program of Higher Education （No.SRFDP), Grant No. 20101202110007）

Opened online: 4 January 2011

Accepted by: none

Citation: Xu Yunhua,Bai Wenwen,Tian Xin.Neural ensemble sparse coding during working memory task in rat prefrontal cortex[OL]. [ 4 January 2011] http://en.paper.edu.cn/en_releasepaper/content/4401529

The neural ensemble aims to provide a mechanistic explanation of how groups of neurons acting together during a cognitive processing. It is significant to expressing neural ensemble at a higher precision when neural population activity data are recoded from experiment. In this article, we propose the use of sparse coding as a new methodology to address this issue by recording the activities of neurons in the rat prefrontal cortex during the working memory task in Y-maze. The time information of neural activity is summarized into bin counts using 200 milliseconds windows, and a sparse code for the bin-count matrix is found by means of a linear generative model. The meaningful components are extracted to reconstruct the input by an inverse of the sparsifying transform. None of the feature components are ignored or missed, as the number of the source components is greater than that of neurons. The reconstructed sparse neuronal activities are compared with rate coding. The recording twenty cases dealt show that, using sparse coding, it is possible to identify spatiotemporal patterns of neural activity in the form of reconstructed signal. The results indicate that the spatiotemporal location of neural ensemble could be more precisely detected, using sparse coding.

Keywords:Sparse coding; Neural ensemble; Neuronal firing activity; Working memory

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