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Anomalous neuronal responses to fluctuated inputs.

Ryosuke Hosaka1, Yutaka Sakai2

  • 1Department of Applied Mathematics, Fukuoka University, Fukuoka Prefecture 814-0180, Japan.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 14, 2015
PubMed
Summary
This summary is machine-generated.

Neural irregular firing, crucial for brain processing, can arise from fluctuating inputs due to bistability. This study reveals bistability as the origin of anomalous input-output relationships in neuron models, enhancing neural information processing.

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Area of Science:

  • Computational Neuroscience
  • Neural Dynamics
  • Information Processing

Background:

  • Cortical neuron firing irregularity is linked to fluctuating synaptic inputs.
  • Previous work noted anomalous neuron responses where firing irregularity decreased with input irregularity.

Purpose of the Study:

  • Investigate the origin of anomalous neuron responses to fluctuating inputs.
  • Clarify the role of bistability in neural firing patterns.

Main Methods:

  • Utilized the Hindmarsh-Rose neuron model.
  • Employed map-based models and mixture models of interspike interval distributions.
  • Analyzed parameter regions for bifurcations (saddle-node, subcritical Hopf).

Main Results:

  • Hindmarsh-Rose model reproduced anomalous responses, linked to bistability (resting and repetitive firing states).
  • Map-based models with bistability showed anomalous responses; those without did not.
  • Mixture models mimicking bistable firing also reproduced the anomalous responses.

Conclusions:

  • Bistability in neuron models is the origin of the anomalous input-output relationship.
  • Irregular firing, essential for neural information processing, can emerge from fluctuating drives under bistable conditions.
  • These findings suggest a mechanism for efficient neural information processing in the brain.