Synergistic delay and strength tuning for logical operations in a chaotic neuron

doi:10.1088/1674-1056/ae5786

Abstract An improved FitzHugh-Nagumo neuron model is proposed, incorporating electromagnetic induction via a flux-controlled memristor and dual autaptic feedback with tunable strengths and delays. This brain-inspired unit can reliably perform AND and OR logic operations under chaotic driving, serving as a tunable nonlinear computing element. Systematic numerical analysis reveals that the synergistic interplay between autaptic delays and strengths plays a key role in achieving optimal logical stochastic resonance. Specifically, the system achieves near-perfect success rates within specific parameter regions, where a compensatory effect enables delay asymmetry to balance synaptic strength mismatch. Furthermore, at lower coupling strengths, a multiple logical resonance phenomenon is observed, in which the success probability exhibits multiple peaks as a function of synaptic delay. This work not only elucidates the dynamical mechanism underlying reliable neuronal logic operation but also provides a co-design principle for tuning neuromorphic circuits, with potential implications for low-power, high-flexibility computing hardware.

Keywords: FitzHugh-Nagumo neuron model memristor multi-scale autapse logical resonance time delay

Received: 04 February 2026
Revised: 19 March 2026
Accepted manuscript online: 26 March 2026

PACS:	02.30.Hq	(Ordinary differential equations)
	02.30.Oz	(Bifurcation theory)
	05.45.-a	(Nonlinear dynamics and chaos)
	05.40.Ca	(Noise)

Fund: Project supported by the Key R&D Program of Shandong Province, China (Grant No. 2025CXPT087) and the National Natural Science Foundation of China (Grant No. 12402061).

Corresponding Authors: Ying Xu
E-mail: uryysunshine@163.com

Cite this article:

Ying Xu(徐莹) Synergistic delay and strength tuning for logical operations in a chaotic neuron 2026 Chin. Phys. B 35 060201

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Synergistic delay and strength tuning for logical operations in a chaotic neuron

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