| Autor: |
Alexandre Boutet, Radhika Madhavan, Gavin J. B. Elias, Suresh E. Joel, Robert Gramer, Manish Ranjan, Vijayashankar Paramanandam, David Xu, Jurgen Germann, Aaron Loh, Suneil K. Kalia, Mojgan Hodaie, Bryan Li, Sreeram Prasad, Ailish Coblentz, Renato P. Munhoz, Jeffrey Ashe, Walter Kucharczyk, Alfonso Fasano, Andres M. Lozano |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2041-1723 |
| DOI: |
10.1038/s41467-021-23311-9 |
| Popis: |
Deep brain stimulation programming for Parkinson’s disease entails the assessment of a large number of possible simulation settings, requiring numerous clinic visits after surgery. Here, the authors show that patterns of functional MRI can predict the optimal stimulation settings. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full text from SpringerLink