| RRC ID |
88424
|
| Author |
Li C, Hasegawa I, Tanigawa H.
|
| Title |
Protocol for assisting frequency band definition and decoding neural dynamics using hierarchical clustering and multivariate pattern analysis.
|
| Journal |
STAR Protoc
|
| Abstract |
Traditional fixed frequency band divisions often limit neural data analysis accuracy. Here, we present a protocol for assisting frequency band definition for multichannel neural data using macaque electrocorticography (ECoG) data. We describe steps for performing time-frequency analysis on preprocessed signals and applying hierarchical clustering to frequency power profiles to identify data-informed groupings. We then detail procedures for defining frequency bands guided by these clusters and using multivariate pattern analysis (MVPA) on the derived bands for functional validation via time-series decoding. For complete details on the use and execution of this protocol, please refer to Tanigawa et al.1.
|
| Volume |
6(2)
|
| Pages |
103870
|
| Published |
2025-6-20
|
| DOI |
10.1016/j.xpro.2025.103870
|
| PII |
S2666-1667(25)00276-X
|
| PMID |
40465456
|
| PMC |
PMC12171811
|
| MeSH |
Animals
Brain / physiology
Cluster Analysis
Electrocorticography* / methods
Macaca
Multivariate Analysis
Signal Processing, Computer-Assisted*
|
| Resource |
| Japanese macaques |
|
