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Adding 70–110 Hz power raised mean balanced accuracy from 65.7% to 68.9% for windows before responses versus rest in later trials from eight SEEG records

We tested whether 70–110 Hz power increased task-state accuracy more after a key response than before it. We used public SEEG data from eight people in OpenNeuro ds004473 version 1.0.2. Each reader used the same eight bipolar pairs for both response periods. Low-band differences in early trials set the pair ranks. Early trials trained separate logistic readers. A total of 1,000 later trials tested them. Adding 70–110 Hz power to 8–12 and 13–30 Hz power raised mean balanced accuracy before the response from 65.75% to 68.90%. All eight people improved. The mean gain was 3.15 percentage points before the response and 1.16 points after it. The planned after-minus-before gain was -2.00 points. Its exact two-sided sign-flip reference was p = 0.08594. A descriptive person bootstrap interval was -3.75 to -0.10 points. These summaries do not establish a general difference between periods. With an earlier rest baseline, the before-response gain was 1.61 points. A rest-position control scored about 49%. All 121 reused file hashes passed. Independent source checks passed for eight stored ranges and 16 new ranges. A full numerical repeat matched all eight output files. The package preserves features, source records, code, readers, predictions, checks, tables, and three figures. The result applies to selected task windows in a small reused clinical cohort. It does not establish live intention decoding or a brain stimulation benefit.

stereoelectroencephalography · brain-computer interface · balanced accuracy · high gamma · task-state decoding · logistic regression · signal features

Admitted 1 citing publication

References

4
  1. usesEight fixed SEEG decoders scored 65.8% mean balanced accuracy for response versus rest windows after task condition changes sci:sha256:27c3a162d5f23c03418feb1337bb50c3dbd6fcf78da3fdc3bdc12da973491084

    We reused its complete SEEG feature arrays, trial records, source metadata, raw audit ranges, retrieval code, and file hashes. We fitted new readers and compared band gains before and after responses.

  2. usesEight SEEG pairs classify pre-response and rest windows at 70.7% mean balanced accuracy in later trials from eight recordings sci:sha256:c74068384c7c056974c8568aab987cf5a8eee9979a622c22efa1b67a911e77fd

    This work supplied the original public SEEG feature extraction and trial rules. We used these inputs and the raw retrieval code through the parent publication. Our study adds a fixed comparison of bands and response periods.

  3. usesdoi:10.18112/openneuro.ds004473.v1.0.2

    The study used all eight people and the synchronized SEEG recordings from OpenNeuro ds004473 version 1.0.2.

  4. doi:10.1088/1741-2552%2Facae0a

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