Dissecting beta-state changes during timed movement preparation in Parkinson's disease

Simone G. Heideman; Andrew J. Quinn; Mark W. Woolrich; Freek van Ede; Anna C. Nobre

doi:10.1016/j.pneurobio.2019.101731

Dissecting beta-state changes during timed movement preparation in Parkinson's disease

Simone G. Heideman, Andrew J. Quinn, Mark W. Woolrich, Freek van Ede, Anna C. Nobre^*

^*Corresponding author for this work

Psychology

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

An emerging perspective describes beta-band (15−28 Hz) activity as consisting of short-lived high-amplitude events that only appear sustained in conventional measures of trial-average power. This has important implications for characterising abnormalities observed in beta-band activity in disorders like Parkinson's disease. Measuring parameters associated with beta-event dynamics may yield more sensitive measures, provide more selective diagnostic neural markers, and provide greater mechanistic insight into the breakdown of brain dynamics in this disease. Here, we used magnetoencephalography in eighteen Parkinson's disease participants off dopaminergic medication and eighteen healthy control participants to investigate beta-event dynamics during timed movement preparation. We used the Hidden Markov Model to classify event dynamics in a data-driven manner and derived three parameters of beta events: (1) beta-state amplitude, (2) beta-state lifetime, and (3) beta-state interval time. Of these, changes in beta-state interval time explained the overall decreases in beta power during timed movement preparation and uniquely captured the impairment in such preparation in patients with Parkinson's disease. Thus, the increased granularity of the Hidden Markov Model analysis (compared with conventional analysis of power) provides increased sensitivity and suggests a possible reason for impairments of timed movement preparation in Parkinson's disease.

Original language	English
Article number	101731
Journal	Progress in neurobiology
Volume	184
DOIs	https://doi.org/10.1016/j.pneurobio.2019.101731
Publication status	Published - Jan 2020

Bibliographical note

Funding Information:
This work was supported by the Medical Research Council (MRC) and Engineering and Physical Sciences Research Council (EPSRC) UK MEG Partnership award (grant number MR/K005464/1 ) and an MRC Doctoral Training Grant ( MR/K501086/1 ), a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award ( 220020448 ), the NIHR Oxford Health Biomedical Research Centre , a Wellcome Trust Senior Investigator Award ( 104571/Z/14/Z ) to ACN, a Wellcome Investigator Award ( 106183/Z/14/Z ) to MWW, and a Marie Skłodowska-Curie Individual Fellowship ( ACCESS2WM ) from the European Commission to FvE. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust ( 203139/Z/16/Z ). Appendix A

Funding Information:
We thank Joshua Chauvin for his assistance with participant recruitment and testing. We are grateful to Sven Braeutigam for his assistance with the MEG data collection. We thank Malcolm Proudfoot, Nahid Zokaei, and Alex Thompson for their help with the clinical evaluation of our participants. We acknowledge the support of the National Institute for Health Research Clinical Research Network (NIHR CRN).

Funding Information:
This work was supported by the Medical Research Council (MRC) and Engineering and Physical Sciences Research Council (EPSRC) UK MEG Partnership award (grant number MR/K005464/1) and an MRC Doctoral Training Grant (MR/K501086/1), a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award (220020448), the NIHR Oxford Health Biomedical Research Centre, a Wellcome Trust Senior Investigator Award (104571/Z/14/Z) to ACN, a Wellcome Investigator Award (106183/Z/14/Z) to MWW, and a Marie Sk?odowska-Curie Individual Fellowship (ACCESS2WM) from the European Commission to FvE. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z).

Publisher Copyright:
© 2019 The Authors

Keywords

Beta oscillations
Burst-events
Movement
Parkinson's disease
Timing

ASJC Scopus subject areas

General Neuroscience

Access to Document

10.1016/j.pneurobio.2019.101731

Cite this

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title = "Dissecting beta-state changes during timed movement preparation in Parkinson's disease",

abstract = "An emerging perspective describes beta-band (15−28 Hz) activity as consisting of short-lived high-amplitude events that only appear sustained in conventional measures of trial-average power. This has important implications for characterising abnormalities observed in beta-band activity in disorders like Parkinson's disease. Measuring parameters associated with beta-event dynamics may yield more sensitive measures, provide more selective diagnostic neural markers, and provide greater mechanistic insight into the breakdown of brain dynamics in this disease. Here, we used magnetoencephalography in eighteen Parkinson's disease participants off dopaminergic medication and eighteen healthy control participants to investigate beta-event dynamics during timed movement preparation. We used the Hidden Markov Model to classify event dynamics in a data-driven manner and derived three parameters of beta events: (1) beta-state amplitude, (2) beta-state lifetime, and (3) beta-state interval time. Of these, changes in beta-state interval time explained the overall decreases in beta power during timed movement preparation and uniquely captured the impairment in such preparation in patients with Parkinson's disease. Thus, the increased granularity of the Hidden Markov Model analysis (compared with conventional analysis of power) provides increased sensitivity and suggests a possible reason for impairments of timed movement preparation in Parkinson's disease.",

keywords = "Beta oscillations, Burst-events, Movement, Parkinson's disease, Timing",

author = "Heideman, {Simone G.} and Quinn, {Andrew J.} and Woolrich, {Mark W.} and {van Ede}, Freek and Nobre, {Anna C.}",

note = "Funding Information: This work was supported by the Medical Research Council (MRC) and Engineering and Physical Sciences Research Council (EPSRC) UK MEG Partnership award (grant number MR/K005464/1 ) and an MRC Doctoral Training Grant ( MR/K501086/1 ), a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award ( 220020448 ), the NIHR Oxford Health Biomedical Research Centre , a Wellcome Trust Senior Investigator Award ( 104571/Z/14/Z ) to ACN, a Wellcome Investigator Award ( 106183/Z/14/Z ) to MWW, and a Marie Sk{\l}odowska-Curie Individual Fellowship ( ACCESS2WM ) from the European Commission to FvE. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust ( 203139/Z/16/Z ). Appendix A Funding Information: We thank Joshua Chauvin for his assistance with participant recruitment and testing. We are grateful to Sven Braeutigam for his assistance with the MEG data collection. We thank Malcolm Proudfoot, Nahid Zokaei, and Alex Thompson for their help with the clinical evaluation of our participants. We acknowledge the support of the National Institute for Health Research Clinical Research Network (NIHR CRN). Funding Information: This work was supported by the Medical Research Council (MRC) and Engineering and Physical Sciences Research Council (EPSRC) UK MEG Partnership award (grant number MR/K005464/1) and an MRC Doctoral Training Grant (MR/K501086/1), a James S. McDonnell Foundation Understanding Human Cognition Collaborative Award (220020448), the NIHR Oxford Health Biomedical Research Centre, a Wellcome Trust Senior Investigator Award (104571/Z/14/Z) to ACN, a Wellcome Investigator Award (106183/Z/14/Z) to MWW, and a Marie Sk?odowska-Curie Individual Fellowship (ACCESS2WM) from the European Commission to FvE. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z). Publisher Copyright: {\textcopyright} 2019 The Authors",

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Dissecting beta-state changes during timed movement preparation in Parkinson's disease

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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