Jordan E. Parker, M.A.

Health Psychology Doctoral Candidate


Curriculum vitae



Department of Psychology

University of California, Los Angeles



Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements


Journal article


Raumin S Neuville, M. Petrucci, K. B. Wilkins, Ross W. Anderson, S. L. Hoffman, J. E. Parker, A. Velisar, H. Bronte-Stewart
Frontiers in Neuroscience, 2020

Semantic Scholar DOI PubMedCentral PubMed
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APA   Click to copy
Neuville, R. S., Petrucci, M., Wilkins, K. B., Anderson, R. W., Hoffman, S. L., Parker, J. E., … Bronte-Stewart, H. (2020). Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements. Frontiers in Neuroscience.


Chicago/Turabian   Click to copy
Neuville, Raumin S, M. Petrucci, K. B. Wilkins, Ross W. Anderson, S. L. Hoffman, J. E. Parker, A. Velisar, and H. Bronte-Stewart. “Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements.” Frontiers in Neuroscience (2020).


MLA   Click to copy
Neuville, Raumin S., et al. “Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements.” Frontiers in Neuroscience, 2020.


BibTeX   Click to copy

@article{raumin2020a,
  title = {Differential Effects of Pathological Beta Burst Dynamics Between Parkinson’s Disease Phenotypes Across Different Movements},
  year = {2020},
  journal = {Frontiers in Neuroscience},
  author = {Neuville, Raumin S and Petrucci, M. and Wilkins, K. B. and Anderson, Ross W. and Hoffman, S. L. and Parker, J. E. and Velisar, A. and Bronte-Stewart, H.}
}

Abstract

Background: Resting state beta band (13–30 Hz) oscillations represent pathological neural activity in Parkinson’s disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb, and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states. Methods: Subthalamic (STN) and local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC + S, Medtronic PLC.) in fourteen PD participants (six tremor-dominant and eight akinetic-rigid) off medication/off STN DBS during 30 s of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups. Results: Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group. Conclusion: The conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.


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