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Research Article | Open Access

Delayed feedback and sensitivity analysis for oscillations in Parkinson's disease

Quanbao Ji1,2Hongjian Meng1( )
School of Mathematical Sciences, Guangxi Minzu University, Nanning 530006, China
Guangxi Key Laboratory of Universities Optimization Control and Engineering Calculation, Nanning 530006, China
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Abstract

Pathological oscillations within the basal ganglia (BG) are a hallmark of Parkinson's disease (PD), a prevalent neurodegenerative disorder. This study aims to evaluate the effects of delayed feedback on oscillatory activity in a PD model and to analyze the roles of synaptic weights and transmission delays within the feedback circuit. Results indicate that the model induced by delayed feedback increase leads to the transition in firing activity, progressing from regular gamma activity to pathological beta oscillation states, and may even transition into complex states. This transition is further modulated by synaptic weights, which could not only change the model from a steady state to an oscillating state, but also cause a high-saturation steady state when sufficiently large. Furthermore, sensitivity analysis based on polynomial chaos expansions enables the quantification of the contributions of transmission delays and synaptic weights to the oscillation frequency variance of the model. The analysis shows that with increasing delayed feedback, the transmission delay parameter that contributes the most to model oscillation shifts from transmission delay within the BG circuit to that of the cerebral cortex circuit. Synaptic weights between the external globus pallidus and the subthalamic nucleus have a significant impact on oscillatory activity when delayed feedback is large. Our findings provide new directions for further clinical treatment of PD.

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Electronic Research Archive
Pages 1079-1094

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Cite this article:
Ji Q, Meng H. Delayed feedback and sensitivity analysis for oscillations in Parkinson's disease. Electronic Research Archive, 2026, 34(2): 1079-1094. https://doi.org/10.3934/era.2026050

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Received: 09 December 2025
Revised: 24 January 2026
Accepted: 28 January 2026
Published: 30 January 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)