Subthalamic beta targeted neurofeedback speeds up movement initiation but increases tremor in Parkinsonian patients

  1. Shenghong He
  2. Abteen Mostofi
  3. Emilie Syed
  4. Flavie Torrecillos
  5. Gerd Tinkhauser
  6. Petra Fischer
  7. Alek Pogosyan
  8. Harutomo Hasegawa
  9. Yuanqing Li
  10. Keyoumars Ashkan
  11. Erlick Pereira
  12. Peter Brown  Is a corresponding author
  13. Huiling Tan  Is a corresponding author
  1. University of Oxford, United Kingdom
  2. St George's University of London, United Kingdom
  3. Nuffield Dep of Clinical Neurosciences and MRC BNDU, United Kingdom
  4. King's College Hospital NHS Foundation Trust, United Kingdom
  5. South China University of Technology, China
  6. Kings College London, United Kingdom

Abstract

Previous studies have explored neurofeedback training for Parkinsonian patients to suppress beta oscillations in the subthalamic nucleus (STN). However, its impacts on movements and Parkinsonian tremor are unclear. We developed a neurofeedback paradigm targeting STN beta bursts and investigated whether neurofeedback training could improve motor initiation in Parkinson's disease compared to passive observation. Our task additionally allowed us to test which endogenous changes in oscillatory STN activities are associated with trial-to-trial motor performance. Neurofeedback training reduced beta synchrony and increased gamma activity within the STN, and reduced beta band coupling between the STN and motor cortex. These changes were accompanied by reduced reaction times in subsequently cued movements. However, in Parkinsonian patients with pre-existing symptoms of tremor, successful volitional beta suppression was associated with an amplification of tremor which correlated with theta band activity in STN LFPs, suggesting an additional cross-frequency interaction between STN beta and theta activities.

Data availability

Source data and codes for generating Figures 2-7, all supplement figures, and Table II have been provided.

Article and author information

Author details

  1. Shenghong He

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  2. Abteen Mostofi

    Neurosciences Research Centre, St George's University of London, London, United Kingdom
    Competing interests
    No competing interests declared.
  3. Emilie Syed

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  4. Flavie Torrecillos

    Clinical Neurosciences, Nuffield Dep of Clinical Neurosciences and MRC BNDU, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  5. Gerd Tinkhauser

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  6. Petra Fischer

    Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5585-8977
  7. Alek Pogosyan

    Nuffield Department of Clinical Neuroscience; 2. Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  8. Harutomo Hasegawa

    Department of Neurosurgery, King's College Hospital NHS Foundation Trust, London, United Kingdom
    Competing interests
    No competing interests declared.
  9. Yuanqing Li

    School of Automation Science and Engineering, South China University of Technology, Guangzhou, China
    Competing interests
    No competing interests declared.
  10. Keyoumars Ashkan

    Department of Neurosurgery, Kings College Hospital, Kings College London, London, United Kingdom
    Competing interests
    Keyoumars Ashkan, has received educational grants from Medtronic and Abbott.
  11. Erlick Pereira

    Neurosciences Research Centre, St George's University of London, London, United Kingdom
    Competing interests
    No competing interests declared.
  12. Peter Brown

    Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
    For correspondence
    peter.brown@ndcn.ox.ac.uk
    Competing interests
    Peter Brown, is a consultant for Medtronic..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5201-3044
  13. Huiling Tan

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    For correspondence
    huiling.tan@ndcn.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8038-3029

Funding

Medical Research Council (MR/P012272/1)

  • Shenghong He
  • Huiling Tan

Medical Research Council (MC_UU_12024/1)

  • Flavie Torrecillos
  • Gerd Tinkhauser
  • Petra Fischer
  • Alek Pogosyan
  • Peter Brown

National Institute for Health Research (Oxford Biomedical Research Centre)

  • Shenghong He
  • Abteen Mostofi
  • Emilie Syed
  • Flavie Torrecillos
  • Gerd Tinkhauser
  • Petra Fischer
  • Alek Pogosyan
  • Peter Brown
  • Huiling Tan

Rosetrees Trust

  • Shenghong He
  • Huiling Tan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Informed consent and consent to publish was obtained from patients before they took part in the study, which was approved by Oxfordshire Research Ethics Committee, reference number 18/SC/0006.

Copyright

© 2020, He et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,059
    views
  • 306
    downloads
  • 29
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Shenghong He
  2. Abteen Mostofi
  3. Emilie Syed
  4. Flavie Torrecillos
  5. Gerd Tinkhauser
  6. Petra Fischer
  7. Alek Pogosyan
  8. Harutomo Hasegawa
  9. Yuanqing Li
  10. Keyoumars Ashkan
  11. Erlick Pereira
  12. Peter Brown
  13. Huiling Tan
(2020)
Subthalamic beta targeted neurofeedback speeds up movement initiation but increases tremor in Parkinsonian patients
eLife 9:e60979.
https://doi.org/10.7554/eLife.60979

Share this article

https://doi.org/10.7554/eLife.60979

Further reading

    1. Neuroscience
    Jacob A Miller
    Insight

    When navigating environments with changing rules, human brain circuits flexibly adapt how and where we retain information to help us achieve our immediate goals.

    1. Neuroscience
    Zhujun Shao, Mengya Zhang, Qing Yu
    Research Article

    When holding visual information temporarily in working memory (WM), the neural representation of the memorandum is distributed across various cortical regions, including visual and frontal cortices. However, the role of stimulus representation in visual and frontal cortices during WM has been controversial. Here, we tested the hypothesis that stimulus representation persists in the frontal cortex to facilitate flexible control demands in WM. During functional MRI, participants flexibly switched between simple WM maintenance of visual stimulus or more complex rule-based categorization of maintained stimulus on a trial-by-trial basis. Our results demonstrated enhanced stimulus representation in the frontal cortex that tracked demands for active WM control and enhanced stimulus representation in the visual cortex that tracked demands for precise WM maintenance. This differential frontal stimulus representation traded off with the newly-generated category representation with varying control demands. Simulation using multi-module recurrent neural networks replicated human neural patterns when stimulus information was preserved for network readout. Altogether, these findings help reconcile the long-standing debate in WM research, and provide empirical and computational evidence that flexible stimulus representation in the frontal cortex during WM serves as a potential neural coding scheme to accommodate the ever-changing environment.