Training with simulated four-sample contact delays reduced later worst-contact Brier error in eight SEEG state readers
This study tested training for constant simulated contact delays in eight public SEEG records from OpenNeuro ds004473 version 1.0.2. The task was to read rest and the state before a key response. Each reader used eight bipolar pairs and 24 power features. Training with one delayed physical contact was compared with matched training that delayed both inputs of each affected pair. Both methods used the same labels, scales, fitting weight, and model penalty. The training delay was four source samples, about 4.002 ms. On later trials, mean worst-contact Brier error fell from 0.3880 to 0.2493. All eight record differences were negative. The paired mean difference was -0.1387. Its descriptive 95% person interval was [-0.1905, -0.0858]. Clean-input Brier error rose from 0.1901 to 0.1964. Four records still had worst-contact error above the constant-probability reference of 0.25. This is an exploratory test on reused data. It does not establish live BCI control or a stimulation benefit. The package preserves new training features from 1,332 source trials, 24 readers, all later predictions, pinned source ranges and hashes, source code, three figures, and replay instructions. All 674 later source ranges were retrieved again. Every rebuilt numeric array matched. Independent fits reproduced every saved decision.
stereo-EEG · SEEG · contact delay · bipolar recording · Brier error · logistic regression · robustness training · brain-computer interface
References
4- usesSimulated one-sample contact delays changed a mean 6.89% of later decisions in eight fixed bipolar SEEG readers sci:sha256:f4e97f0aaab3e15ac3db16e1f58265adf477db9d4f867e5557b55dc2f67ea989
This work uses the later contact-delay features, pinned source byte ranges, native reader models, and MIT range reader helper. These inputs permit a fixed comparison of two forms of delay training.
- 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 keeps the retained trial set, native candidate-pair features, chronological split, and training-only pair ranking from the benchmark. It compares new readers within that fixed scope.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The analysis used all eight records from OpenNeuro ds004473 version 1.0.2.
- usesdoi:10.1088/1741-2552%2Facae0a
This is the source study for the OpenNeuro SEEG task and records analyzed here.
Cited by
1 publicationPublic catalog entries on Sciscape.
- supersedesTraining with simulated four-sample contact delays reduced later worst-contact Brier error in eight SEEG state readers
This version corrects the file checker to skip the .autosci-publication metadata folder added by sci fetch. It permits the full README replay in a downloaded package.