Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson’s Disease During Deep Brain Stimulation

Title: Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson’s Disease During Deep Brain Stimulation
Authors: Davidson, ClareDe Paor, AnnraoiCagnan, HayriyeLowery, Madeleine M.
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Date: Jan-2016
Online since: 2019-07-09T11:38:54Z
Abstract: Parkinson’s disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson’s disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to t clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed (R2 =0 .690.99). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behaviour with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.
Funding Details: Science Foundation Ireland
metadata.dc.description.othersponsorship: Insight Research Centre
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Biomedical Engineering
Volume: 63
Issue: 1
Start page: 86
End page: 96
Copyright (published version): 2015 IEEE
Keywords: Basal gangliaControl theoryMean field modelParkinson’s diseasePathological oscillations
DOI: 10.1109/TBME.2015.2475166
Language: en
Status of Item: Peer reviewed
Appears in Collections:Insight Research Collection

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