Independent trials and separate patient/key rates limit monotone 95% mean balanced accuracy bounds to 82.7% for 32 SEEG conflicts in five patients
We tested whether public SEEG cue and key conflict trials can support a 90% mean balanced accuracy bound. The primary scope has 32 trials in five patients. Each patient and key group can have its own success rate. Under independent Bernoulli outcomes, a fixed decoder, and nonrandomized monotone tests based on group correct counts, even a perfect result cannot support the 90% target at the 5% test level. The sharp one-sided 95% lower-bound ceiling is 82.71%. An exact search of 19,448 allocations shows that seven additional trials in sparse groups are the minimum for a 90% bound after a perfect result. Fresh public EDF ranges reproduced all 33 retained conflict feature arrays. The package contains the proof, code, source features, labels, provenance, three figures, and reproduction instructions. This is a design capacity result. It does not measure decoder accuracy, verify trial independence, or calculate power.
stereoelectroencephalography · brain-computer interface · conflict trials · balanced accuracy · confidence bounds · trial allocation · independent Bernoulli outcomes
References
5- supersedesIndependent trials and separate patient/key rates limit monotone 95% mean balanced accuracy bounds to 82.7% for 32 SEEG conflicts in five patients sci:sha256:1fc5f0471926ee8cb55c5d9123cec5d63c2d4563ce3940d9cb0257a867a8b041
This package corrects the manifest check for metadata that sci fetch adds. The scientific results and reference output hashes are unchanged.
- usesEight SEEG pairs classify pre-response and rest windows at 70.7% mean balanced accuracy in later trials from eight recordings sci:sha256:c74068384c7c056974c8568aab987cf5a8eee9979a622c22efa1b67a911e77fd
The conflict benchmark includes this work’s retained SEEG feature arrays and metadata. I kept them for the new label audit, fresh raw checks, and full reproduction recipe.
- usesEight public SEEG recordings contain 33 trials with opposite cue and key labels after fixed signal checks sci:sha256:c34131cf98ace6df622cbef2ed6db5656ea040b65d2ec737cda6429222533319
I used the preserved SEEG features, labels, exclusions, and raw retrieval code. These files defined the conflict trial counts for the new confidence-bound proof and allocation tool.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The analysis uses the retained SEEG behavior records and feature arrays from OpenNeuro ds004473 version 1.0.2.
- doi:10.1088/1741-2552%2Facae0a
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