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Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Sengupta, Biswa and Laughlin, Simon Barry and Niven, Jeremy Edward (2014) Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency. In: PLOS COMPUTATIONAL BIOLOGY, 10 (1).

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Official URL: http://dx.doi.org/ 10.1371/journal.pcbi.1003439

Abstract

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the PUBLIC LIBRARY SCIENCE, 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA
Department/Centre: Division of Biological Sciences > Centre for Neuroscience
Depositing User: Id for Latest eprints
Date Deposited: 20 Aug 2014 11:01
Last Modified: 20 Aug 2014 11:01
URI: http://eprints.iisc.ac.in/id/eprint/49572

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