Literature DB >> 16486185

Response of electrically coupled spiking neurons: a cellular automaton approach.

Lucas S Furtado1, Mauro Copelli.   

Abstract

Experimental data suggest that some classes of spiking neurons in the first layers of sensory systems are electrically coupled via gap junctions or ephaptic interactions. When the electrical coupling is removed, the response function (firing rate vs. stimulus intensity) of the uncoupled neurons typically shows a decrease in dynamic range and sensitivity. In order to assess the effect of electrical coupling in the sensory periphery, we calculate the response to a Poisson stimulus of a chain of excitable neurons modeled by n-state Greenberg-Hastings cellular automata in two approximation levels. The single-site mean field approximation is shown to give poor results, failing to predict the absorbing state of the lattice, while the results for the pair approximation are in good agreement with computer simulations in the whole stimulus range. In particular, the dynamic range is substantially enlarged due to the propagation of excitable waves, which suggests a functional role for lateral electrical coupling. For probabilistic spike propagation the Hill exponent of the response function is alpha=1, while for deterministic spike propagation we obtain alpha=1/2, which is close to the experimental values of the psychophysical Stevens exponents for odor and light intensities. Our calculations are in qualitative agreement with experimental response functions of ganglion cells in the mammalian retina.

Entities:  

Year:  2006        PMID: 16486185     DOI: 10.1103/PhysRevE.73.011907

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  9 in total

1.  Wave speed in excitable random networks with spatially constrained connections.

Authors:  Nikita Vladimirov; Roger D Traub; Yuhai Tu
Journal:  PLoS One       Date:  2011-06-03       Impact factor: 3.240

2.  Undersampled critical branching processes on small-world and random networks fail to reproduce the statistics of spike avalanches.

Authors:  Tiago L Ribeiro; Sidarta Ribeiro; Hindiael Belchior; Fábio Caixeta; Mauro Copelli
Journal:  PLoS One       Date:  2014-04-21       Impact factor: 3.240

3.  Emergent stochastic oscillations and signal detection in tree networks of excitable elements.

Authors:  Justus Kromer; Ali Khaledi-Nasab; Lutz Schimansky-Geier; Alexander B Neiman
Journal:  Sci Rep       Date:  2017-06-21       Impact factor: 4.379

4.  Single-neuron dynamical effects of dendritic pruning implicated in aging and neurodegeneration: towards a measure of neuronal reserve.

Authors:  Christoph Kirch; Leonardo L Gollo
Journal:  Sci Rep       Date:  2021-01-14       Impact factor: 4.379

5.  A computational study on the role of gap junctions and rod Ih conductance in the enhancement of the dynamic range of the retina.

Authors:  Rodrigo Publio; Rodrigo F Oliveira; Antonio C Roque
Journal:  PLoS One       Date:  2009-09-24       Impact factor: 3.240

6.  Active dendrites enhance neuronal dynamic range.

Authors:  Leonardo L Gollo; Osame Kinouchi; Mauro Copelli
Journal:  PLoS Comput Biol       Date:  2009-06-12       Impact factor: 4.475

7.  Convergence among non-sister dendritic branches: an activity-controlled mean to strengthen network connectivity.

Authors:  Pablo Blinder; Joshua Cove; Maytal Foox; Danny Baranes
Journal:  PLoS One       Date:  2008-11-21       Impact factor: 3.240

8.  Single-neuron criticality optimizes analog dendritic computation.

Authors:  Leonardo L Gollo; Osame Kinouchi; Mauro Copelli
Journal:  Sci Rep       Date:  2013-11-14       Impact factor: 4.379

9.  Toward a theory of coactivation patterns in excitable neural networks.

Authors:  Arnaud Messé; Marc-Thorsten Hütt; Claus C Hilgetag
Journal:  PLoS Comput Biol       Date:  2018-04-09       Impact factor: 4.475

  9 in total

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