Chimera states in neuro-inspired area-efficient asynchronous cellular automata networks

Tsakalos, Karolos-Alexandros; Dragkola, Paraskevi; Karamani, Rafailia-Eleni; Tsompanas, Michail-Antisthenis; Provata, Astero; Dimitrakis, Panagiotis; Adamatzky, Andrew I.; Sirakoulis, Georgios Ch

Abstract

Synchronization transition in neuromorphic networks has attracted much attention recently as a fundamental property of biological neural networks, which relies on network connectivity along with different synaptic features. In this work, an area-optimized FPGA implementation of an Asynchronous Cellular Automata Neuron model that exhibits discrete-state neuron dynamics is introduced. The proposed neuron model is capable of reproducing various neuromorphic oscillations observed in biological neurons using less hardware resources than previous implementations. We investigate synchronization transitions with a focus on the emergence of chimera states in a ring-based network consisting of hardware-based neurons with electrical synaptic coupling. In particular, we study the effects on the network's phase synchronization through changing two control parameters: the coupling range and the coupling strength. We indicate that via proper configuration of the coupling parameters, we influence the synchronization transition and reveal chimera states which have been associated with neurological disorders.

Citation

Tsakalos, K., Dragkola, P., Karamani, R., Tsompanas, M., Provata, A., Dimitrakis, P., …Sirakoulis, G. C. (2022). Chimera states in neuro-inspired area-efficient asynchronous cellular automata networks. IEEE Transactions on Circuits and Systems I: Regular Papers, 69(10), 4128-4140. https://doi.org/10.1109/TCSI.2022.3187376

• Journal Article Type: Article
• Acceptance Date: Jun 13, 2022
• Publication Date: Oct 1, 2022
• Deposit Date: Nov 8, 2022
• Journal: IEEE Transactions on Circuits and Systems I: Regular Papers
• Print ISSN: 1549-8328
• Electronic ISSN: 1558-0806
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 69
• Issue: 10
• Pages: 4128-4140
• DOI: https://doi.org/10.1109/TCSI.2022.3187376
• Keywords: Electrical and Electronic Engineering, Hardware and Architecture, Neurons, Biological system modeling, Synchronization, Couplings, Integrated circuit modeling, Field programmable gate arrays, Neuromorphics, Asynchronous cellular automaton, FPGA, Neuron mo
• Public URL: https://uwe-repository.worktribe.com/output/10005573
• Publisher URL: https://ieeexplore.ieee.org/document/9881389
• Related Public URLs: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8919