Dependence of correlated firing on strength of inhibitory feedback

Authors:
Jinli Xie;Zhijie Wang;Haibo Shi
Affiliations:
College of Information Science and Technology, Donghua University, Shanghai, China;College of Information Science and Technology, Donghua University, Shanghai, China;College of Information Science and Technology, Donghua University, Shanghai, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Year:
2011

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Abstract

Correlation coefficient is a way to capture the structure of correlation, which is widely used for analysis and interpretation of multiple simultaneously recorded spike trains. We study the correlation coefficient of a global delayed feedback network with a population of excitatory neurons and a population of inhibitory neurons and show the contribution of the inhibitory feedback to the oscillations and correlation. We find that, with the increase of the strength of the inhibitory feedback, the mean firing rate of the excitatory neurons decreases monotonically, while the correlation coefficient first goes down, and then goes up when the excitatory neurons oscillate and the spectrum shows significant resonance. The non-monotonic relationship between the correlation coefficient and the strength of inhibitory feedback is thus due to the combined effect of the mean firing rate and the power of oscillations.