Literature DB >> 19397950

Energy efficiency of information transmission by electrically coupled neurons.

Francisco J Torrealdea1, Cecilia Sarasola, Alicia d'Anjou, Abdelmalik Moujahid, N Vélez de Mendizábal.   

Abstract

The generation of spikes by neurons is energetically a costly process. This paper studies the consumption of energy and the information entropy in the signalling activity of a model neuron both when it is supposed isolated and when it is coupled to another neuron by an electrical synapse. The neuron has been modelled by a four-dimensional Hindmarsh-Rose type kinetic model for which an energy function has been deduced. For the isolated neuron values of energy consumption and information entropy at different signalling regimes have been computed. For two neurons coupled by a gap junction we have analyzed the roles of the membrane and synapse in the contribution of the energy that is required for their organized signalling. Computational results are provided for cases of identical and nonidentical neurons coupled by unidirectional and bidirectional gap junctions. One relevant result is that there are values of the coupling strength at which the organized signalling of two neurons induced by the gap junction takes place at relatively low values of energy consumption and the ratio of mutual information to energy consumption is relatively high. Therefore, communicating at these coupling values could be energetically the most efficient option.

Mesh:

Year:  2009        PMID: 19397950     DOI: 10.1016/j.biosystems.2009.04.004

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  6 in total

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Journal:  J Comput Neurosci       Date:  2011-11-01       Impact factor: 1.621

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Authors:  Zahra Rostami; Sajad Jafari
Journal:  Cogn Neurodyn       Date:  2018-01-09       Impact factor: 5.082

3.  Electric activities of time-delay memristive neuron disturbed by Gaussian white noise.

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Journal:  Cogn Neurodyn       Date:  2019-08-01       Impact factor: 5.082

4.  Metabolic efficiency with fast spiking in the squid axon.

Authors:  Abdelmalik Moujahid; Alicia d'Anjou
Journal:  Front Comput Neurosci       Date:  2012-11-15       Impact factor: 2.380

5.  Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model.

Authors:  Yihong Wang; Rubin Wang; Xuying Xu
Journal:  Neural Plast       Date:  2017-02-16       Impact factor: 3.599

6.  Energy expenditure computation of a single bursting neuron.

Authors:  Fengyun Zhu; Rubin Wang; Xiaochuan Pan; Zhenyu Zhu
Journal:  Cogn Neurodyn       Date:  2018-09-03       Impact factor: 5.082

  6 in total

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