演講公告

演講主題：A population density approach to capturing interneuronal correlation in large-scale feedforward neuronal networks
主講人：Mr. Chin-Yueh Liu (University of Minnesota)
演講日期：98年3月17日(星期二)<br>下午3:10-4:15
演講地點：(光復校區)科學一館223室
摘要內容：
We present an approach for using kinetic theory to capture first and second order statistics of neuronal activity. We coarse grain neuronal networks into populations of neurons and calculate the population average firing rate and output cross-correlation in response to time varying correlated input. We derive coupling equations for the populations based on first and second order statistics of the network cnnectivity. This coupling scheme is based on the hypothesis that second order statistics of the network connectivity are sufficient to determine second order statistics of neuronal activity. We implement a kinetic theory representation of a simple feed-forward network and demonstrate that the kinetic theory model captures key aspects of the emergence and propagation of correlations in the network, as long as the correlations do not become too strong. By analyzing the correlated activity of feed-forward networks with a variety of connectivity patterns, we provide evidence supporting our hypothesis of the sufficiency of second order connectivity statistics.

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