Non-invasive suppression of essential tremor via phase-locked disruption of its temporal coherence
Name
s41467-020-20581-7.pdf
Description
Published version
Size
2.36 MB
Format
Adobe PDF
Checksum (MD5)
e47a77682ba6a065b7def54b23fed1e8
Author(s)
Schreglmann, Sebastian R
Wang, David
Peach, Robert L
Li, Junheng
Zhang, Xu
Latorre, Anna
Rhodes, Edward
Panella, Emanuele
Cassara, Antonino M
Boyden, Edward S
Date Issued
2021
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
© 2021, The Author(s). Aberrant neural oscillations hallmark numerous brain disorders. Here, we first report a method to track the phase of neural oscillations in real-time via endpoint-corrected Hilbert transform (ecHT) that mitigates the characteristic Gibbs distortion. We then used ecHT to show that the aberrant neural oscillation that hallmarks essential tremor (ET) syndrome, the most common adult movement disorder, can be transiently suppressed via transcranial electrical stimulation of the cerebellum phase-locked to the tremor. The tremor suppression is sustained shortly after the end of the stimulation and can be phenomenologically predicted. Finally, we use feature-based statistical-learning and neurophysiological-modelling to show that the suppression of ET is mechanistically attributed to a disruption of the temporal coherence of the aberrant oscillations in the olivocerebellar loop, thus establishing its causal role. The suppression of aberrant neural oscillation via phase-locked driven disruption of temporal coherence may in the future represent a powerful neuromodulatory strategy to treat brain disorders.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
McGovern Institute for Brain Research at MIT
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Center for Neurobiological Engineering
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41467-020-20581-7
