Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease

Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS).Objective:...

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Autores principales:	Alireza Kazemi, Maryam S. Mirian, Soojin Lee, Martin J. McKeown
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	EEG biomarker LASSO motor vigor GVS Parkinson's disease Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/75c1ced1ee9c4e0a81e59df7f64981ee
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spelling	oai:doaj.org-article:75c1ced1ee9c4e0a81e59df7f64981ee2021-11-04T06:16:46ZGalvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease1664-229510.3389/fneur.2021.759149https://doaj.org/article/75c1ced1ee9c4e0a81e59df7f64981ee2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fneur.2021.759149/fullhttps://doaj.org/toc/1664-2295Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS).Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS.Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50–100 Hz “GVS1” or 100–150 Hz “GVS2”) stimuli. For each trial, we determined the time to reach maximum force after a “Go” signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance.Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG.Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.Alireza KazemiMaryam S. MirianSoojin LeeSoojin LeeMartin J. McKeownMartin J. McKeownFrontiers Media S.A.articleEEGbiomarkerLASSOmotor vigorGVSParkinson's diseaseNeurology. Diseases of the nervous systemRC346-429ENFrontiers in Neurology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	EEG biomarker LASSO motor vigor GVS Parkinson's disease Neurology. Diseases of the nervous system RC346-429
spellingShingle	EEG biomarker LASSO motor vigor GVS Parkinson's disease Neurology. Diseases of the nervous system RC346-429 Alireza Kazemi Maryam S. Mirian Soojin Lee Soojin Lee Martin J. McKeown Martin J. McKeown Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
description	Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS).Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS.Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50–100 Hz “GVS1” or 100–150 Hz “GVS2”) stimuli. For each trial, we determined the time to reach maximum force after a “Go” signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance.Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG.Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.
format	article
author	Alireza Kazemi Maryam S. Mirian Soojin Lee Soojin Lee Martin J. McKeown Martin J. McKeown
author_facet	Alireza Kazemi Maryam S. Mirian Soojin Lee Soojin Lee Martin J. McKeown Martin J. McKeown
author_sort	Alireza Kazemi
title	Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
title_short	Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
title_full	Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
title_fullStr	Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
title_full_unstemmed	Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease
title_sort	galvanic vestibular stimulation effects on eeg biomarkers of motor vigor in parkinson's disease
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/75c1ced1ee9c4e0a81e59df7f64981ee
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Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease

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