Strong effect of weak correlation in excitation-inhibition balanced neural networks

• 作 者: YangDongping[1]ZhouHaijun[2]TangLeihan[3]ZhouChangsong[3]
• 机 构: 1Department of Physics,Institute of Computational and Theoretical Studies,Hong Kong Baptist Universi
• 出 处: 中国物理学会2013年秋季学术会议
• 发表日期: 2013年期

　　Dynamical activity in biological neural networks is characterized by irregular firing of individual neurons and weak,near zero pair-wise correlation.It has been shown that decorrelated,asynchronous state can be supported by a balance of excitation and inhibition,where the positive current from excitatory population and negative current from inhibitory population into a neuron in the recurrent network cancel on average and the neuronal dynamics is governed purely by the residual fluctuations.One may expect that weak correlation is insignificant in the dynamics of balanced neural networks.