Journal article
Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson’s disease
- Abstract:
- Deep brain stimulation (DBS) for Parkinson's disease is a highly effective treatment in controlling otherwise debilitating symptoms. Yet the underlying brain mechanisms are currently not well understood. Whole-brain computational modeling was used to disclose the effects of DBS during resting-state functional Magnetic Resonance Imaging in ten patients with Parkinson's disease. Specifically, we explored the local and global impact that DBS has in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts global brain dynamics of patients towards a Healthy regime. This effect was more pronounced in very specific brain areas such as the thalamus, globus pallidus and orbitofrontal regions of the right hemisphere (with the left hemisphere not analyzed given artifacts arising from the electrode lead). Global aspects of integration and synchronization were also rebalanced. Empirically, we found higher communicability and coherence brain measures during DBS-ON compared to DBS-OFF. Finally, using our model as a framework, artificial in silico DBS was applied to find potential alternative target areas for stimulation and whole-brain rebalancing. These results offer important insights into the underlying large-scale effects of DBS as well as in finding novel stimulation targets, which may offer a route to more efficacious treatments.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 5.2MB, Terms of use)
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- Publisher copy:
- 10.1038/s41598-017-10003-y
Authors
+ Danish National Research Foundation
More from this funder
- Funding agency for:
- Kringelbach, M
- Grant:
- DNRF117
- Publisher:
- Springer Nature
- Journal:
- Scientific Reports More from this journal
- Volume:
- 7
- Issue:
- 1
- Article number:
- 9882
- Publication date:
- 2017-08-29
- Acceptance date:
- 2017-06-28
- DOI:
- ISSN:
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2045-2322
- Pmid:
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28851996
- Language:
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English
- Pubs id:
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pubs:725053
- UUID:
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uuid:30fd2f4b-e23e-4929-8c7c-4d6f923fdb68
- Local pid:
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pubs:725053
- Source identifiers:
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725053
- Deposit date:
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2018-02-14
Terms of use
- Copyright holder:
- Saenger et al
- Copyright date:
- 2017
- Notes:
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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