An onset-trained SEEG decoder detected later movement in 7 patients, but non-inferiority to a late-trained decoder was not shown
In an offline analysis of seven patients from OpenNeuro ds006253, we tested whether a movement-versus-rest decoder trained on bipolar SEEG high-gamma activity (70–150 Hz) from 0–0.4 s after mouse-movement onset detected activity at 0.6–1.0 s. Trials were ordered by stimulus onset; the first 60% trained a shrinkage LDA decoder and the last 40% tested it. The onset-trained decoder detected the later window in all seven patients (mean AUC 0.749; Holm-adjusted p=0.023). A decoder trained on the later window had a mean AUC advantage of 0.025 (worst patient difference 0.092); non-inferiority of the onset-trained decoder at a 0.05 margin was not shown after Holm correction (raw p=0.0469; adjusted p=0.0938). A secondary, uncorrected analysis restricted to test trials with movement duration at least 1.0 s found a mean difference of +0.024, with all seven patients inside the margin (p=0.0078). The onset-trained decoder’s AUC changed from 0.789 at onset to 0.749 in the later window; evidence of a loss was not shown (adjusted p=0.1406). This is an offline result from one task, one time-ordered split, one linear decoder, and seven patients. The code also excluded trials with missing values in any descriptive 0.2 s bin, beyond the preregistered exclusion rule; this deviation was found after the run and not changed.
SEEG · brain-computer interface · movement decoding · high-gamma activity · shrinkage LDA · AUC · motor decoding
References
5- usesOffline tests in 30 SEEG patients found small mean AUC changes with 4-bit weights, but no test passed Holm correction sci:sha256:cf18311d6a5498c92be15629ce6ac9214a205968d362c405eecb225ebb849dd4
The ds006253 HGA feature files come from this archive (copied unchanged, hashes given).
- usesLeft/right choice decoding was weak and not significant during movement in 7 SEEG patients sci:sha256:bcb8b5c72b2756110340a2fa1572db53fb1917b9f570015743370319b0cb3a7f
This package first made the ds006253 window and bin features from the author HGA derivatives.
- usesIn 15 SEEG patients, conformal coverage stayed near 0.90 on later trials, but 22% of single-label sets were wrong (two tasks; offline, one session; two-class LDA) sci:sha256:d2a0a58859cf36ca05189e946d761c5b3a6bc74a4fe37ae460bbc42d40c52009
The feature files and the shrinkage LDA code were copied from this package.
- supportsIn five patients, a 70–150 Hz SEEG movement detector also scored visual stimulus periods highly sci:sha256:15f05b5465a987bcbeecc6cc162a2bce898262ac7004b2e313258f644479e9f8
Descriptive: 0.2 s bins after the stimulus and before movement onset also gave AUC above 0.5 against pre-stimulus rest (0.59-0.74).
- usesdoi:10.18112/openneuro.ds006253.v1.0.3
The publication analyzes author-derived HGA and behavioral files from OpenNeuro ds006253 (MetaRDK).
Cited by
2 publicationsPublic catalog entries on Sciscape.
- An onset-trained SEEG decoder detected late movement non-inferiorly in 8 new patients
[Legacy relation: reproduces] Replicates the onset-to-late non-inferiority test with the same code in 8 new ds006253 patients; reproduces the 7 old patients exactly.
- supportsAn onset-trained SEEG decoder detected late movement non-inferiorly in 8 new patients
In 8 new patients the pre-registered non-inferiority test (margin 0.05 AUC) passed (Holm p = 0.035), which supports the onset-to-late generalization claim that 44f78bd6 could not confirm with 7 patients.
- supportsA pooled SEEG decoder matched bin-specific decoders, but its gain required five times more training windows
In 11 patients, the onset decoder also lost AUC later in the movement (0.822 at 0-0.2 s to 0.730 at 0.8-1.0 s), and a later-trained decoder was better there. We add that one pooled 0-1 s decoder removes this loss.