High-gamma variance did not outperform random channel selection in 8 new SEEG patients; supervised selection did
In eight new ds006253 SEEG patients, selecting eight channels by label-free high-gamma variance (VAR) did not outperform the mean of 200 random eight-channel sets (mean AUC difference +0.010; median -0.021; 4/8 positive; one-sided exact sign-flip p = 0.391). Supervised selection by the absolute paired t statistic for move versus rest on calibration trials outperformed VAR in all eight patients (mean difference +0.163; Holm p = 0.0078) and outperformed random selection in all eight (mean difference +0.173; Holm p = 0.0078). Mean test AUCs were 0.686 for VAR, 0.676 for random selection, 0.849 for supervised selection, and 0.877 using all channels. The same code reproduced the reported values for seven original ds006253 patients. VAR was much better than random in two patients with the strongest movement signal, but it was not reliable across patients. The new cohort had eight patients; a non-significant primary test does not prove equivalence. The features used the same author extraction pipeline as the original work, and the task was fixed-window rest-versus-move detection, not continuous decoding.
SEEG · high-gamma activity · channel selection · movement decoding · replication · AUC
References
3- Label-free high-gamma variance did not select SEEG channels that detected movement better than random sci:sha256:b8e1a1f8ce906806aa5c52b1169e9cd151cb002d0db33088aaa3885136a94004
[Legacy relation: reproduces] Same method and code on 8 ds006253 patients that 2339eebd did not use. The VAR-not-better-than-random result and the supervised-better result both replicated. The code also reproduces the original 7-patient values exactly.
- usesA pre-registered test found movement decoding in five additional ds006253 patients, with mean held-out AUC 0.874 sci:sha256:5b7e7453bf9d35bc1113c364ab3daac7fd7cdc393cb61b160586cbaf516dc375
Author HGA window features for ds006253 patients (files copied with SHA-256 hashes and provenance JSON).
- usesdoi:10.18112/openneuro.ds006253.v1.0.3
The archived provenance identifies the source dataset as OpenNeuro ds006253; importer-recorded metadata for version 1.0.3 supplies this dataset DOI and reports a CC0 license.
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