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Critical behavior at the onset of synchronization in a neuronal model

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  • Safaeesirat, Amin
  • Moghimi-Araghi, Saman

Abstract

It has been observed experimentally that the neural tissues generate highly variable and scale-free distributed outbursts of activity both in vivo and in vitro. Understanding whether these heterogeneous patterns of activity come from operation of the brain at the edge of a phase transition is an interesting possibility. Therefore, constructing a simple model that exhibits such behavior is of great interest. Additionally, the presence of both critical behavior and oscillatory patterns in brain dynamics is a very interesting phenomenon: Oscillatory patterns define a temporal scale, while criticality imposes scale-free characteristics. In this paper, we consider a model for a neuronal population where each neuron is modeled by an over-damped rotator. We find that there are some regions in the space of external parameters where the system shows synchronization. Interestingly, just at the transition point, the avalanche statistics show power-law behavior. Also, in the case of small systems, the (partial) synchronization and power-law behavior can occur simultaneously.

Suggested Citation

  • Safaeesirat, Amin & Moghimi-Araghi, Saman, 2022. "Critical behavior at the onset of synchronization in a neuronal model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    • Handle: RePEc:eee:phsmap:v:587:y:2022:i:c:s0378437121007767
    DOI: 10.1016/j.physa.2021.126503
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    References listed on IDEAS

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    1. K. Christensen & N. Farid & G. Pruessner & M. Stapleton, 2008. "On the scaling of probability density functions with apparent power-law exponents less than unity," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(3), pages 331-336, April.
    2. Shree Hari Gautam & Thanh T Hoang & Kylie McClanahan & Stephen K Grady & Woodrow L Shew, 2015. "Maximizing Sensory Dynamic Range by Tuning the Cortical State to Criticality," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-15, December.
    3. Marc Benayoun & Jack D Cowan & Wim van Drongelen & Edward Wallace, 2010. "Avalanches in a Stochastic Model of Spiking Neurons," PLOS Computational Biology, Public Library of Science, vol. 6(7), pages 1-13, July.
    4. Bruno Del Papa & Viola Priesemann & Jochen Triesch, 2017. "Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-21, May.
    5. Paolo Moretti & Miguel A. Muñoz, 2013. "Griffiths phases and the stretching of criticality in brain networks," Nature Communications, Nature, vol. 4(1), pages 1-10, December.
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