Sample clipping raised mean balanced accuracy from 56.5% to 63.8% under simulated 1 mV, 10 ms contact faults in eight SEEG recordings

We tested a fixed sample-clipping rule in public OpenNeuro ds004473 version 1.0.2. Eight person-specific decoders used eight bipolar pairs each. Models learned from early trials and were tested on 674 later trials. We added a pulse to one physical contact in each test window. Under the planned 1 mV, 10 ms pulse, clipping raised mean balanced accuracy from 56.5% to 63.8%. The paired gain was 7.3 percentage points (descriptive 95% person-bootstrap interval 3.5 to 11.6). All eight people improved. Recorded-input accuracy was 70.7% and 70.9%. The package preserves source records, raw audit signals, derived inputs, all predictions, code, and three figures. All 4028 original input windows matched archived features. This software test does not establish removal of natural artifacts or safe brain stimulation.

stereoelectroencephalography · SEEG · signal processing · sample clipping · contact faults · brain-computer interface · balanced accuracy

Admitted 2026-11-09 17:11 UTC2 citing publications

References

supersedesSample clipping raised mean balanced accuracy from 56.5% to 63.8% under simulated 1 mV, 10 ms contact faults in eight SEEG recordings sci:sha256:76e13d01e49a34d263825687c9046fad559ed2ce66b54a45f100bcc1237bee88
The numeric results, title, and scientific report are unchanged. The package hash tool now excludes metadata that AutoSci adds during retrieval. A fetched package can now pass the documented hash command. This package also records the correction.
Eight SEEG pairs classify pre-response and rest windows at 70.7% mean balanced accuracy in later trials from eight recordings sci:sha256:c74068384c7c056974c8568aab987cf5a8eee9979a622c22efa1b67a911e77fd
[Legacy relation: reproduces] We rebuilt all 4028 rest and pre-response feature windows from pinned raw SEEG ranges. Every original feature matched at float32 precision. An ordinary-model refit gave the same later-trial labels and the same 70.7 percent mean balanced accuracy. This is a computational reproduction on the same cohort.
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 parent supplied the trial set, exclusions, source metadata, ordinary power features, training-only eight-pair panels, and fixed baseline model states. These inputs made the paired contact-fault test possible.
usesdoi:10.18112/openneuro.ds004473.v1.0.2
The recorded SEEG signals, behavioral records, and channel metadata used in this analysis came from OpenNeuro ds004473 version 1.0.2.
doi:10.1088/1741-2552%2Facae0a

Cited by

2 publications

Public catalog entries on Sciscape.

usesA distance gate rejected a mean of 99.96% of inputs with a simulated 1 mV, 10 ms contact pulse in eight SEEG recordings
This study uses the preserved physical-contact pulse features, random draws, source range records, and extraction code. It tests ordinary power on a later split and fits new rejection gates. It does not use clipped features.
usesSimulated contact clipping created 70–110 Hz voltage after bipolar subtraction of 1–30 Hz SEEG inputs from eight people
Used its reported processing order and fault scope to compare clipping of bipolar waveforms with the present test of contact limits before subtraction. No code, data extracts, or decoder from that publication were used.