Band power ratios retain 67.0% balanced accuracy under simulated constant voltage gains per shaft in eight SEEG recordings
We tested whether band power ratios preserve small SEEG decoders during simulated recording gain changes. We used OpenNeuro ds004473, version 1.0.2, with one recording from each of eight patients. The models used eight bipolar pairs and three power bands. They learned from early trials and classified rest and pre-response windows in 674 later trials. Each shaft had one voltage gain, shared by its contacts and constant over time and frequency. At gains from 0.5 to 2, pair ratios retained 67.0% mean balanced accuracy. Absolute power gave 70.7% without a gain change and 49.8% at its exact minimum over allowed gains. The planned patient contrast was 17.3 percentage points, with a 95% patient bootstrap interval of 10.5 to 25.3 points. The exact two-sided sign-flip p value was 0.0078125. Pair ratios had a 3.6-point lower mean accuracy without a gain change. A planned shaft ratio model retained 69.0%. All models retained their score ranking under constant gains. The result concerns a fixed decision threshold and the stated fault set. It does not establish live control or performance during real hardware faults. The package preserves features, raw audit ranges, source versions, code, fitted models, predictions, figures, and retrieval instructions.
SEEG · band power · power ratios · gain robustness · balanced accuracy · brain-computer interface · signal processing · logistic regression
References
3- usesEight SEEG pairs classify pre-response and rest windows at 70.7% mean balanced accuracy in later trials from eight recordings sci:sha256:c74068384c7c056974c8568aab987cf5a8eee9979a622c22efa1b67a911e77fd
We use the preserved full eight-patient SEEG feature set, source metadata, pinned raw audit ranges, and MIT extraction code. We add fixed gain tests, two centered power models, and exact threshold bounds. This is a new analysis of the same sample.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The study analyzes selected SEEG recordings and inherited source features from OpenNeuro ds004473 version 1.0.2.
- doi:10.1088/1741-2552%2Facae0a
This is the source study for the OpenNeuro SEEG task data described in the publication.
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- supersedesBand power ratios retain 67.0% balanced accuracy under simulated constant voltage gains per shaft in eight SEEG recordings
This package version corrects the local manifest checker. It excludes the metadata folder added by an AutoSci download. All nine scientific numerical result files have the same hashes as the first version.