Suppression of pathological beta oscillations in Parkinson’s disease by delayed feedback control targeting the thalamic nucleus-cortex direct pathway
Source abstract
Abstract
The motor symptoms of Parkinson’s disease are closely associated with pathological neural oscillations within the cortico-basal ganglia circuit. Although deep brain stimulation (DBS) can alleviate symptoms by suppressing abnormal oscillatory activity, the efficacy of current treatment regimens remains suboptimal. Conventional understanding posited that the basal ganglia influence the cortex primarily via thalamic relay. However, recent studies have identified a direct inhibitory projection from the basal ganglia to the cortex, the subthalamic nucleus (STN)-cortical pathway, offering new possibilities for optimizing DBS strategies. Building upon the classic pedunculopontine nucleus–basal ganglia (PPN-BG) closed-loop model, this study developed a computational neural mass model of the cortex-basal ganglia-thalamus-pedunculopontine nucleus (Cor-BGTh-PPN) that incorporates the direct STN-to-cortex pathway. We systematically evaluated the suppressive effects of four delayed feedback stimulation strategies, two targeting the globus pallidus externa (GPe) and two targeting the STN, on pathological oscillations. Simulation results demonstrate that all delayed feedback strategies effectively suppress pathological oscillations and reduce energy consumption. Notably, GPe-targeted strategies outperform STN-targeted ones in both control efficacy and energy efficiency. These findings provide a theoretical foundation for developing more efficient closed-loop DBS systems and suggest promising directions for refining treatment strategy selection.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Neurological disorders and treatments · Transcranial Magnetic Stimulation Studies · Parkinson's Disease Mechanisms and Treatments
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematics and Physics, Shanghai University of Electric Power , Shanghai 201306,
Funding
National Natural Science Foundation of China
References (47)
Show source-provided references
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