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Irregular Dynamics in Up and Down Cortical States

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  • Jorge F Mejias
  • Hilbert J Kappen
  • Joaquin J Torres

Abstract

Complex coherent dynamics is present in a wide variety of neural systems. A typical example is the voltage transitions between up and down states observed in cortical areas in the brain. In this work, we study this phenomenon via a biologically motivated stochastic model of up and down transitions. The model is constituted by a simple bistable rate dynamics, where the synaptic current is modulated by short-term synaptic processes which introduce stochasticity and temporal correlations. A complete analysis of our model, both with mean-field approaches and numerical simulations, shows the appearance of complex transitions between high (up) and low (down) neural activity states, driven by the synaptic noise, with permanence times in the up state distributed according to a power-law. We show that the experimentally observed large fluctuation in up and down permanence times can be explained as the result of sufficiently noisy dynamical synapses with sufficiently large recovery times. Static synapses cannot account for this behavior, nor can dynamical synapses in the absence of noise.

Suggested Citation

  • Jorge F Mejias & Hilbert J Kappen & Joaquin J Torres, 2010. "Irregular Dynamics in Up and Down Cortical States," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0013651
    DOI: 10.1371/journal.pone.0013651
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    Cited by:

    1. di Volo, Matteo & Livi, Roberto, 2013. "The influence of noise on synchronous dynamics in a diluted neural network," Chaos, Solitons & Fractals, Elsevier, vol. 57(C), pages 54-61.
    2. Guido Gigante & Gustavo Deco & Shimon Marom & Paolo Del Giudice, 2015. "Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-23, November.

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