Core-matrix protocol · Transfer to a new person

SSVEP · 4 channels on BETA

Name: BCI Report: SSVEP · 4 channels on BETA — 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 what guessing would score — as the released protocol file states it. Compare scores within this protocol only.

The protocol at a glance

Task: 40 visual targets · 4 posterior electrodes
Evaluation: Transfer to a new person
Dataset: BETA
People: 70
Data: 11,200 trials · 7 participant-disjoint folds
Input: 4 channels selected from a 64-channel recording · 2-second windows
Chance level: 2.5%
Metrics: Balanced accuracy (primary) · Macro F1 (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.

Standard CCA

57.6% (51.8%–63.5%)

Spectral ridge

48.2% (43.1%–53.3%)

LaBraM

12.9% (11.2%–14.6%)

CBraMod

27.6% (24.1%–31.3%)

EEGNet

44.1% (38.6%–49.6%)

Balanced accuracy, every method under this protocol. Dot: the estimate; line: descriptive 95% interval; dashed line: chance level.

Method	Training mode	Balanced accuracy	Macro F1	Channels	People	Scoring time
Standard CCAClassical method	Known-frequency reference · no fitting	57.6%51.8%–63.5%	0.567Mean across held-out participants	4	70	1.1 s
Spectral ridgeClassical method	Supervised fit	48.2%43.1%–53.3%	0.467Mean across held-out participants	4	70	0.7 s
LaBraMFoundation model	Frozen encoder + ridge head	12.9%11.2%–14.6%	0.110Mean across held-out participants	4	70	2.5 s
CBraModFoundation model	Frozen encoder + ridge head	27.6%24.1%–31.3%	0.257Mean across held-out participants	4	70	3.0 s
EEGNetCompact model	Scratch · 20 epochs	44.1%38.6%–49.6%	0.421Mean across held-out participants	4	70	146.7 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: CSP+LDA, ShallowFBCSPNet, Deep4Net, Temporal ridge. A method missing here was not run on this protocol — that is not a failure.

Read with care

Near-floor scores are not ordered reliably between the 8- and 4-electrode subsets. Electrode subsets from laboratory recordings do not validate a physical low-channel cap. Prompted SSVEP does not measure idle false activations. Single-seed results; pretraining overlap unknown.

The protocol, step by step

Seven participant-disjoint folds: train on 60 people, test on ten. All four blocks stay with their participant.
Two seconds from stimulus onset; no visual-latency shift. Source data were already zero-phase filtered. Additional 6–80 Hz filtering applies to each selected window separately.
Microvolt units are inferred from an independently documented loader, not explicitly stated in the author MAT description. Inconsistent phase metadata are unused by all methods.
Standard CCA uses known frequencies and three harmonics without training labels. Frozen encoders use training-only standardized ridge heads (alpha 100). EEGNet trains from scratch for 20 epochs with one seed (20260912).
Electrodes: POZ, O1, OZ, O2.
Uniform-guessing reference: 2.5%. Descriptive 95% intervals resample participants; training sets overlap across folds.
No cross-task overall ranking, model fine-tuning optimum or hardware benchmark is claimed.

Stability

One fixed seed and training budget; multi-seed sensitivity pending.

Pretraining exposure

Unknown unless explicitly documented; no unseen-pretraining claim.

Notes on the methods

One fixed configuration. Foundation encoders remain frozen; small networks train from scratch. These scores do not establish optimal fine-tuned performance. No individual predictions or participant-level results are distributed.

Model terms

Standard CCA: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.
Spectral ridge: 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
CBraMod: Code: MIT · Weights: Apache-2.0 (official model card)
EEGNet: Trained from scratch / deterministic reference; no third-party pretrained weights. Braindecode BSD-3-Clause; MNE/scikit-learn BSD where used.

Source and licence

BETA

Credit Bingchuan Liu et al. · BETA: A Large Benchmark Database Toward SSVEP-BCI Application (2020), doi:10.3389/fnins.2020.00627. Figshare 12264401 v3; mirror Bingchuan/BETA.

Licence CC BY 4.0 ↗

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 under the stated personal, research-led, noncommercial operation. Any ads, sponsorship, fees, or use directed toward commercial advantage requires fresh review or permission.

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

Reproducibility record

Protocol id: beta-ssvep-2s-posterior4and8-subject7fold-v1/posterior4
Dataset release: Hugging Face mirror of BETA database, Figshare record 12264401 v3 · mirror d4290c0200db8a104e0f557349dc49f90ba79506 · upstream Figshare version 3, 2022-06-15
Hardware: Apple M5 / MPS and CPU
Scoring stage sum: 153.9 s · may include accelerator waiting
Audit record SHA-256: ccddf911864b8471f488e46cae45a3651369dae1134afcdeaede68bdfcc31950
Summary SHA-256: 547a35763f7bca10a65c7b44c2f8c46af290159c692d237e92cd682fc21127a6
Protocol SHA-256: dcd1d2bf4dbb46b7db8c4562623448633cde4641fa372c90f25ba9d84012c2f0

Downloads

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

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