Electroencephalography‐Based Clustering Reveals Robust Neurophysiological Subtypes in Parkinson's Disease
Daniel Vered, Zoya Katzir, Idan Daniel Grosbard, Avner Thaler, Inbal Maidan · 2026
Read Electroencephalography‐Based Clustering Reveals Robust Neurophysiological Subtypes in Parkinson's Disease by Daniel Vered, Zoya Katzir, Idan Daniel Grosbard, Avner Thaler, Inbal Maidan (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13518290.txt.
Description
Daniel Vered, Zoya Katzir, Idan Daniel Grosbard, Avner Thaler, and Inbal Maidan sort Parkinson's patients into brain-wave subtypes, in a research paper from 2026. The disease varies widely in movement and thinking signs, and clinic scales reveal little about the brain machinery beneath. Scalp recordings offer a direct, scalable window on brain activity.
Recordings from 116 patients and 30 healthy people were taken at rest and while walking. Features covered rhythm power, background signal shape, and signal complexity. Grouping methods settled on three sturdy clusters with distinct brain profiles. The clusters also differed in clinical, gait, and genetic traits. Such subtypes may guide tailored treatment trials.
Catalog record
| CREATOR | Daniel Vered, Zoya Katzir, Idan Daniel Grosbard, Avner Thaler, Inbal Maidan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |