Chaotic resonance in Hodgkin–Huxley neuron

Chaotic Resonance (CR), whereby the response of a nonlinear system to a weak signal can be enhanced by the assistance of chaotic activities that can be intrinsic or extrinsic, has recently been studied widely. In this paper, the effects of extrinsic chaotic signal on the weak signal detection perfor...

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Bibliographic Details
Published in:Nonlinear dynamics 2019-07, Vol.97 (2), p.1275-1285
Main Authors: Baysal, Veli, Saraç, Zehra, Yilmaz, Ergin
Format: Article
Language:English
Subjects:
Automotive Engineering
Chaos theory
Classical Mechanics
Computer simulation
Control
Dynamical Systems
Engineering
Lorenz system
Mechanical Engineering
Neural networks
Neurons
Nonlinear response
Nonlinear systems
Original Paper
Robustness (mathematics)
Signal detection
Vibration
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Summary:Chaotic Resonance (CR), whereby the response of a nonlinear system to a weak signal can be enhanced by the assistance of chaotic activities that can be intrinsic or extrinsic, has recently been studied widely. In this paper, the effects of extrinsic chaotic signal on the weak signal detection performance of the Hodgkin–Huxley neuron are examined via numerical simulation. The chaotic signal has been derived from Lorenz system and is injected to neuron as a current. Obtained results have revealed that the H–H neuron exhibits CR phenomenon depending on the chaotic current intensity. Also, we have found an optimal chaotic current intensity ensuring the best detection of the weak signal in H–H neuron via CR. In addition, we have calculated the maximal Lyapunov exponent to determine whether the H–H neuron is in chaotic regime. After determining the state of the neuron, we have shown that the H–H neuron can be able to detect the weak signal even if it is in the chaotic regime. Finally, we have investigated the effects of chaotic activity on the collective behavior of H–H neurons in small-world networks and have concluded that CR effect is a robust phenomenon which can be observed both in single neurons and neuronal networks.
ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-019-05047-w