Core-matrix protocol · False activation × detection

Idle & command on ds005342

Name: BCI Report: Idle & command on ds005342 — protocol and results
Creator: BCI Report
License: https://creativecommons.org/licenses/by/4.0/

Everything that produced the scores below — cohort, split, electrodes, window, what each method was allowed to learn, and the idle false-activation rate that command detection must be read with — as the released protocol file states it. Compare scores within this protocol only.

The protocol at a glance

Task: Seated motor imagery · cue-gated replay
Evaluation: False activation × detection
Dataset: ds005342
People: 4
Data: 60 idle / 60 command test trials
Input: 180 seconds of test idle
Chance level: Not applicable. Command detection is read together with the idle false-activation rate: always abstaining scores zero false activations.
Metrics: Command detection ≤3s (primary) · Idle false activation (secondary)

Results

Every method run under this protocol, with the score the released results file holds. Compare down this table only: other protocols differ in cohort, electrodes, window or chance level.

Method	Training mode	Command detection ≤3s	Idle false activation	Channels	People	Scoring time
CSP+LDAClassical method	Supervised fit	23.3%14 / 60 command trials	0.0%0 / 60 idle trials1 of 4 people always abstained	17	4	0.1 s
LaBraMFoundation model	Frozen encoder + linear head	18.3%11 / 60 command trials	3.3%2 / 60 idle trials0 of 4 people always abstained	17	4	2.8 s
EEGNetCompact model	Scratch · 20 epochs	1.7%1 / 60 command trials	0.0%0 / 60 idle trials2 of 4 people always abstained	17	4	10.1 s
ShallowFBCSPNetCompact model	Scratch · 20 epochs	43.3%26 / 60 command trials	1.7%1 / 60 idle trials1 of 4 people always abstained	17	4	28.6 s
CBraModFoundation model	Frozen encoder + linear head	18.3%11 / 60 command trials	1.7%1 / 60 idle trials1 of 4 people always abstained	17	4	2.3 s
Deep4NetCompact model	Scratch · 20 epochs	3.3%2 / 60 command trials	1.7%1 / 60 idle trials1 of 4 people always abstained	17	4	13.9 s

Scoring time includes fitting and prediction, may include accelerator waiting, and excludes data preparation. It is configuration-specific, not a hardware benchmark.

Not run under this protocol: Spectral ridge, Standard CCA, Temporal ridge. A method missing here was not run on this protocol — that is not a failure.

Read with care

Detection resets at each cue. Only three minutes of test idle are observed; these results cannot estimate natural, always-on false activations per hour.

The protocol, step by step

For each subject, the first two blocks train the model, the third selects the threshold, and the final block is held out for testing.
Class events 1/2 define task onset. Two-second history windows produce decisions at 2.0, 2.5 and 3.0 seconds.
Two consecutive threshold crossings trigger one command. Thresholds use calibration data only and may reject every command.
17 channels at 250 Hz; one-way 4–40 Hz filtering. Normalization uses training data only; no future samples enter a decision window.
Visual cues, original feedback and short calibration exposure can influence results. This is not a natural continuous-idle test.
Additional models use protocol ds005342-sitting-cue-gated-expanded-mvp-v1; independent audit SHA256: 14445d3423b5268654a1f73f7e1aca8bb03a2f793b076f450883fea89c7bcc83.

Stability

Single fixed configuration; no test-set hyperparameter selection.

Pretraining exposure

Unknown unless explicitly documented; no unseen-pretraining claim.

Notes on the methods

Fixed calibration rule; 60 training trials and 30 calibration trials per participant. Four-person case study; cohort aggregates only, no subgroup or population claim.

Model terms

CSP+LDA: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.
LaBraM: Code/repository: MIT · Checkpoint: committed in that repository; no separate weight terms
EEGNet: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.
ShallowFBCSPNet: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.
CBraMod: Code: MIT · Weights: Apache-2.0 (official model card)
Deep4Net: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.

Source and licence

ds005342

Credit OpenNeuro ds005342 contributors · version 1.0.3, doi:10.18112/openneuro.ds005342.v1.0.3; associated study doi:10.3389/fninf.2022.961089. Original author credits are retained at the linked source.

Licence CC0-1.0 ↗

Dataset record ↗ · Every result on this dataset →

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

Permitted scope Personal noncommercial research; aggregate results only

Privacy Only cohort aggregates are published here: no recording, no participant identifier, no per-person score. The full review note is in the protocol JSON ↓

Public-data register note Eligible only as an aggregate-only case study: remove all participant IDs/results and condition breakdowns, label n=4 prominently, avoid subgroup claims, and make no claim that the cohort is anonymous.

Rights reviewed 2026-09-20 · against doi.org ↗ · eegdash.org ↗ · doi.org ↗

Reproducibility record

Protocol id: ds005342-sitting-cue-gated-pilot-v1
Dataset release: OpenNeuro snapshot 1.0.3 · 30bb3b67d76ce007b822fed801e496fafe5598a0
Hardware: Apple M5 / MPS and CPU
Scoring stage sum: 58.0 s · may include accelerator waiting
Audit record SHA-256: ce2474c547f5f11c256752b0a07466beb5b6928da34bb39783aaa4647973d2e4

Downloads

Results · CSV ↓Protocol · JSON ↓Core matrix · JSON ↓

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