Effective Connectivity-based Unsupervised Channel Selection Method for Electroencephalography
Neda Abdollahpour, Nabi Sertac Artan, Ian Daly, Mohammadreza Yazdchi, Zahra Baharlouei · 2026
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Description
A brain-wave cap with many sensors gives more data than most tasks need, and the extra channels cost time and add noise. Neda Abdollahpour and four co-authors pick the channels that count in 2026, by how much each one drives the rest. Their score rates each channel by its causal pull on its peers.
The pick needs no labels: it reads the web of pull among channels and keeps the hubs. The team tests it on three known brain-wave sets across four kinds of task, scoring the pick with five gauges of causal pull. A leaner cap set that keeps the signal's spine could make brain-wave tools faster and cheaper to run. It could also sharpen what the reads say about how the brain talks to itself.
Catalog record
| CREATOR | Neda Abdollahpour, Nabi Sertac Artan, Ian Daly, Mohammadreza Yazdchi, Zahra Baharlouei |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 56 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |