Tianjin Research Centre of Basic Medical Science, Tianjin Medical University, Tianjin 300070, China

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Abstract—Functional connectivity networks on prefrontal cortex of rat during working memory task in vivo are analyzed. Neural ensemble entropy coding is applied to find the time interval of working memory event occurrence. The analysis of functional connectivity networks is carried out though the method of cross-covariance. And functional networks of the occurrence working memory event and resting state are obtained. The complex network topology parameters are calculated, the two networks satisfy the small-world network property as the clustering coefficients of them are larger than their corresponding random networks and their characteristic path lengths are approximately equal to their corresponding random networks. Finally, the simulations of spiking neuronal networks of working memory event occurrence and resting state are presented. Hindmarsh-Rose neuron model is chosen as single neuron of prefrontal cortex that connected by functional network of working memory event occurrence and resting state, receptivity. The simulation results are agreed with experiment data in rat prefrontal cortex during a working memory task.

Index Terms—functional connectivity, neuronal entropy coding, spike trains, working memory, small-world network, neuronal network simulation

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Cite: Dexuan Qi, Xin Tian, " Functional Networks Analysis from Multi Neuronal Spike Trains on Prefrontal Cortex of Rat during Working Memory Task and Neuronal Network Simulation," Journal of Computers vol. 8, no. 6, pp. 1377-1384, 2013.