Synchronization in STDP-driven memristive neural networks with time-varying topology

Yamakou M, Desroches M, Rodrigues S (2023)

Publication Type: Journal article

Publication year: 2023

Journal

Journal of Biological Physics Springer Verlag (Germany)

DOI: 10.1007/s10867-023-09642-2

Abstract

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by spike-timing-dependent plasticity (STDP) and temporal networks subject to homeostatic structural plasticity (HSP) rules remain unclear. Here, we bridge this gap by determining the configurations required to achieve high and stable degrees of complete synchronization (CS) and phase synchronization (PS) in time-varying small-world and random neural networks driven by STDP and HSP. In particular, we found that decreasing P (which enhances the strengthening effect of STDP on the average synaptic weight) and increasing F (which speeds up the swapping rate of synapses between neurons) always lead to higher and more stable degrees of CS and PS in small-world and random networks, provided that the network parameters such as the synaptic time delay τc , the average degree ⟨ k⟩ , and the rewiring probability β have some appropriate values. When τc , ⟨ k⟩ , and β are not fixed at these appropriate values, the degree and stability of CS and PS may increase or decrease when F increases, depending on the network topology. It is also found that the time delay τc can induce intermittent CS and PS whose occurrence is independent F. Our results could have applications in designing neuromorphic circuits for optimal information processing and transmission via synchronization phenomena.

Authors with CRIS profile

Marius Yamakou Department of Data Science

Involved external institutions

Inria FR France (FR) Basque Center of Applied Mathematics (BCAM) ES Spain (ES)

How to cite

APA:

Yamakou, M., Desroches, M., & Rodrigues, S. (2023). Synchronization in STDP-driven memristive neural networks with time-varying topology. Journal of Biological Physics. https://doi.org/10.1007/s10867-023-09642-2

MLA:

Yamakou, Marius, Mathieu Desroches, and Serafim Rodrigues. "Synchronization in STDP-driven memristive neural networks with time-varying topology." Journal of Biological Physics (2023).

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