Higher-order Correlation in a Feed-forward Network with Inhomogeneous Connectivity

Abstract

[evdate 2013-07-17] StatPhysHK Conference. Talk no. 7 Title from title slide.

IAS Program on Statistical Physics and Computational Neuroscience, held 2-19 July, 2013, at Hong Kong University of Science and Technology. Sponsors, Hong Kong Baptist University, Croucher Foundation, K. C. Wong Education Foundation.

StatPhysHK Conference, a satellite of STATPHYS 25, held 17-19 July, 2013, at Hong Kong University of Science and Technology and Hong Kong Baptist University.

Abstract: We investigated a parsimonious structured network with common inputs and spiking non-linearities. Unlike a homogeneous network, a network with heterogeneous connections can provide not only a tuning curve of firing rates but also a relationship among the statistics gathered from neurophysiological experiments in the primary visual cortex. We found that the heterogeneous structure of the network can dynamically control the structure of 3rd-order correlations and can generate both sparse and synchronized neural activity, and proposed a decisive experiment to test the effect of inhomogeneous connectivity on higher-order correlations. These theoretical results indicate that the 3rd-order correlations resulting from visual stimulation can carry stimulus-specific information.

Duration: 38 min.