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Intensity Coding in Two-Dimensional Excitable Neural Networks | | Mauro Copelli
; Osame Kinouchi
; | | Date: |
28 Sep 2004 | | Subject: | Neurons and Cognition; Tissues and Organs; Cellular Automata and Lattice Gases; Pattern Formation and Solitons; Biological Physics; Disordered Systems and Neural Networks; Statistical Mechanics | q-bio.NC cond-mat.dis-nn cond-mat.stat-mech nlin.CG nlin.PS physics.bio-ph q-bio.TO | | Abstract: | In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed. | | Source: | arXiv, q-bio.NC/0409032 | | Services: | Forum | Review | PDF | Favorites | |
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