The influence of synaptic strength and noise on the robustness of central pattern generator

Feibiao Zhan; Jian Song; Shenquan Liu; Feibiao Zhan; Jian Song; Shenquan Liu

doi:10.3934/era.2024033

Electronic Research Archive

2024, Volume 32, Issue 1: 686-706. doi: 10.3934/era.2024033

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The influence of synaptic strength and noise on the robustness of central pattern generator

1.
School of Mathematics, Nanjing Audit University, Nanjing 211815, China
2.
School of Mathematics, South China University of Technology, Guangzhou 510640, China
3.
School of Mathematical and Computational Sciences, Massey University, Auckland 4442, New Zealand

Received: 25 September 2023 Revised: 23 December 2023 Accepted: 27 December 2023 Published: 09 January 2024

In this paper, we explore the mechanisms of central pattern generators (CPGs), circuits that can generate rhythmic patterns of motor activity without external input. We study the half-center oscillator, a simple form of CPG circuit consisting of neurons connected by reciprocally inhibitory synapses. We examine the role of asymmetric coupling factors in shaping rhythm activity and how different network topologies contribute to network efficiency. We have discovered that neurons with lower synaptic strength are more susceptible to noise that affects rhythm changes. Our research highlights the importance of asymmetric coupling factors, noise, and other synaptic parameters in shaping the broad regimes of CPG rhythm. Finally, we compare three topology types' regular regimes and provide insights on how to locate the rhythm activity.
- rhythm activity,
- topology,
- noise,
- robustness,
- central pattern generator
Citation: Feibiao Zhan, Jian Song, Shenquan Liu. The influence of synaptic strength and noise on the robustness of central pattern generator[J]. Electronic Research Archive, 2024, 32(1): 686-706. doi: 10.3934/era.2024033

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Abstract

In this paper, we explore the mechanisms of central pattern generators (CPGs), circuits that can generate rhythmic patterns of motor activity without external input. We study the half-center oscillator, a simple form of CPG circuit consisting of neurons connected by reciprocally inhibitory synapses. We examine the role of asymmetric coupling factors in shaping rhythm activity and how different network topologies contribute to network efficiency. We have discovered that neurons with lower synaptic strength are more susceptible to noise that affects rhythm changes. Our research highlights the importance of asymmetric coupling factors, noise, and other synaptic parameters in shaping the broad regimes of CPG rhythm. Finally, we compare three topology types' regular regimes and provide insights on how to locate the rhythm activity.

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