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Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease.
Neural Netw 2019; 122:308-319NN

Abstract

High-frequency deep brain stimulation (HF-DBS) of the subthalamic nucleus (STN), globus pallidus interna (GPi) and globus pallidus externa (GPe) are often considered as effective methods for the treatment of Parkinson's disease (PD). However, the stimulation of a single nucleus by HF-DBS can cause specific physical damage, produce side effects and usually consume more electrical energy. Therefore, we use a biophysically-based model of basal ganglia-thalamic circuits to explore more effective stimulation patterns to reduce adverse effects and save energy. In this paper, we computationally investigate the combined DBS of two nuclei with the phase deviation between two stimulation waveforms (CDBS). Three different stimulation combination strategies are proposed, i.e., STN and GPe CDBS (SED), STN and GPi CDBS (SID), as well as GPi and GPe CDBS (GGD). Resultantly, it is found that anti-phase CDBS is more effective in improving parkinsonian dynamical properties, including desynchronization of neurons and the recovery of the thalamus relay ability. Detailed simulation investigation shows that anti-phase SED and GGD are superior to SID. Besides, the energy consumption can be largely reduced by SED and GGD (72.5% and 65.5%), compared to HF-DBS. These results provide new insights into the optimal stimulation parameter and target choice of PD, which may be helpful for the clinical practice.

Authors+Show Affiliations

Department of Dynamics and Control, Beihang University, 100191, Beijing, China.Department of Dynamics and Control, Beihang University, 100191, Beijing, China.Department of Dynamics and Control, Beihang University, 100191, Beijing, China. Electronic address: nmqingyun@163.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31739269

Citation

Yu, Ying, et al. "Model-based Optimized Phase-deviation Deep Brain Stimulation for Parkinson 's Disease." Neural Networks : the Official Journal of the International Neural Network Society, vol. 122, 2019, pp. 308-319.
Yu Y, Hao Y, Wang Q. Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease. Neural Netw. 2019;122:308-319.
Yu, Y., Hao, Y., & Wang, Q. (2019). Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease. Neural Networks : the Official Journal of the International Neural Network Society, 122, pp. 308-319. doi:10.1016/j.neunet.2019.11.001.
Yu Y, Hao Y, Wang Q. Model-based Optimized Phase-deviation Deep Brain Stimulation for Parkinson 's Disease. Neural Netw. 2019 Nov 9;122:308-319. PubMed PMID: 31739269.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease. AU - Yu,Ying, AU - Hao,Yuqing, AU - Wang,Qingyun, Y1 - 2019/11/09/ PY - 2019/04/03/received PY - 2019/10/21/revised PY - 2019/11/01/accepted PY - 2019/11/19/pubmed PY - 2019/11/19/medline PY - 2019/11/19/entrez KW - Deep brain stimulation KW - Parkinson’s disease KW - Phase deviation KW - Synchronization level SP - 308 EP - 319 JF - Neural networks : the official journal of the International Neural Network Society JO - Neural Netw VL - 122 N2 - High-frequency deep brain stimulation (HF-DBS) of the subthalamic nucleus (STN), globus pallidus interna (GPi) and globus pallidus externa (GPe) are often considered as effective methods for the treatment of Parkinson's disease (PD). However, the stimulation of a single nucleus by HF-DBS can cause specific physical damage, produce side effects and usually consume more electrical energy. Therefore, we use a biophysically-based model of basal ganglia-thalamic circuits to explore more effective stimulation patterns to reduce adverse effects and save energy. In this paper, we computationally investigate the combined DBS of two nuclei with the phase deviation between two stimulation waveforms (CDBS). Three different stimulation combination strategies are proposed, i.e., STN and GPe CDBS (SED), STN and GPi CDBS (SID), as well as GPi and GPe CDBS (GGD). Resultantly, it is found that anti-phase CDBS is more effective in improving parkinsonian dynamical properties, including desynchronization of neurons and the recovery of the thalamus relay ability. Detailed simulation investigation shows that anti-phase SED and GGD are superior to SID. Besides, the energy consumption can be largely reduced by SED and GGD (72.5% and 65.5%), compared to HF-DBS. These results provide new insights into the optimal stimulation parameter and target choice of PD, which may be helpful for the clinical practice. SN - 1879-2782 UR - https://www.unboundmedicine.com/medline/citation/31739269/Model-based_optimized_phase-deviation_deep_brain_stimulation_for_Parkinson_'s_disease L2 - https://linkinghub.elsevier.com/retrieve/pii/S0893-6080(19)30340-5 DB - PRIME DP - Unbound Medicine ER -