PMID: 11308875Apr 20, 2001Paper

Mutual information in a dilute, asymmetric neural network model

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
E Greenfield, H Lecar

Abstract

Neural networks with asymmetric synaptic connections (w(ij) not equal to w(ji)) display a broad range of dynamical behavior including fixed point, periodic, and "chaotic" trajectories. Previous work has shown that such networks undergo an order-chaos phase transition as various network parameters, such as the connectivity or the degree of asymmetry, are changed. Here, using an information theoretic approach, we present results which suggest that neurons are able to communicate information to each other most effectively in networks that are near the order-chaos transition. We then extend the model to incorporate some biologically relevant features.

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Citations

May 11, 2011·Proceedings of the National Academy of Sciences of the United States of America·Amy Wells QuinkertDonald W Pfaff
Feb 5, 2009·Neural Computation·Barak A Pearlmutter, Conor J Houghton
Jan 7, 2011·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Woodrow L ShewDietmar Plenz
Jan 16, 2009·Nature Reviews. Neuroscience·Dean V Buonomano, Wolfgang Maass
May 26, 2012·The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry·Woodrow L Shew, Dietmar Plenz
Feb 1, 2008·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Takahiro Omi, Shigeru Shinomoto

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