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The effect of cell size and channel density on neuronal information encoding and energy efficiency

Sengupta, Biswa and Faisal, Aldo A and Laughlin, Simon B and Niven, Jeremy E (2013) The effect of cell size and channel density on neuronal information encoding and energy efficiency. In: Journal of Cerebral Blood Flow & Metabolism, 33 (9). pp. 1465-1473.

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Official URL: http://dx.doi.org/10.1038/jcbfm.2013.103


Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Item Type: Journal Article
Publication: Journal of Cerebral Blood Flow & Metabolism
Publisher: Nature Publishing Group
Additional Information: Copyright of this article belongs to Nature Publishing Group.
Keywords: Action Potentials; Energy Metabolism; Na+ Channels; K+ Channels; Mathematical Modeling
Department/Centre: Division of Biological Sciences > Centre for Neuroscience
Date Deposited: 25 Oct 2013 05:32
Last Modified: 25 Oct 2013 05:32
URI: http://eprints.iisc.ac.in/id/eprint/47539

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