In 13 sessions, evoked SEEG voltage predicted working-memory errors less well than band power, while induced and total band power performed similarly
Question: does the stimulus-locked (evoked) SEEG voltage contain information about later working-memory errors that band power does not contain? We used 13 sessions (12 patients) of OpenNeuro ds006136 (load-3 object working memory, middle frontal and middle temporal contacts). We used the same per-channel shrinkage-LDA ensemble and 5-fold cross-validation for each feature set. Band power gave median AUC 0.651 (13 of 13 sessions above 0.5). Evoked voltage bins gave median AUC 0.519 (8 of 13, p = 0.073) and were lower than band power in 11 of 13 sessions (p = 0.003). Evoked plus band power did not do better than band power alone (median difference -0.011, p = 0.17). Band power after removal of the mean evoked response gave the same AUC (0.648, p = 0.84). A positive control showed clear evoked responses (12% to 67% of channels with |t| > 4). Thus the error information is in induced band power, not in the phase-locked voltage. Limits: offline, within-session decoding, 5-18 cortical contacts, n = 13, one classifier and one evoked feature design. The package has code, per-session results, figures, data hashes and reproduction steps.
SEEG · working memory · error prediction · evoked voltage · band power · induced activity · AUC · within-session decoding
References
3- supportsEncoding and delay SEEG band power predicted later working-memory errors in 12 of 12 subjects (median within-session AUC 0.64) sci:sha256:5034d04e5c0afd95e141b3d67a9e61606e473ac3db09804ec5303871b339ec20
With its unchanged pipeline on all 13 sessions with at least 10 errors (it reported 12), encoding+delay band power predicted errors with median within-session AUC 0.651, 13 of 13 sessions above 0.5. This agrees with its reported median AUC 0.64.
- usesEncoding and delay SEEG band power predicted later working-memory errors in 12 of 12 subjects (median within-session AUC 0.64) sci:sha256:5034d04e5c0afd95e141b3d67a9e61606e473ac3db09804ec5303871b339ec20
We use its ds006136 loader, Welch band-power features, per-channel shrinkage-LDA ensemble and stratified cross-validation without change (code/owm_decode_18254913.py). With this code, band power gave median within-session AUC 0.651 in 13 sessions, which agrees with its reported 0.64. We add evoked-voltage and induced-band-power feature sets to the same pipeline.
- usesdoi:10.18112/openneuro.ds006136.v1.0.1
The analyzed data are identified in the publication as OpenNeuro ds006136 version 1.0.1; this version-specific DOI is recorded in the cached dataset metadata.
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