cff-version: 1.2.0
message: >-
  If you use these aggregate results, cite BCI Report and the release you used,
  and cite the upstream dataset each figure was computed on: every dataset page
  at https://bci.report/datasets/ gives its credit line. The licence below,
  CC BY 4.0, covers the aggregate measurements this project produced
  (LICENSE-DATA); the underlying recordings keep their own terms. The code in
  the repository is under the MIT License (LICENSE).
type: dataset
title: "BCI Report: public EEG decoding results reported with their protocol"
abstract: >-
  Cohort-level EEG decoding results, each published with the protocol that
  produced it — cohort, electrode count, evaluation split, chance level,
  interval and known limitations — across motor imagery, SSVEP, P300 and
  semantic ERP, cognitive load, sleep staging (including simple baselines on
  healthy and sleep-apnoea cohorts, kept apart, with accuracy beside balanced
  accuracy), idle false activation and non-control rejection, sensor and
  display transfer, image-rate transfer, movement, calibration budget within a
  recording and across sessions, foundation-model adaptation (head only, last
  block, LoRA), pretraining controls and a clinical case/control comparison. No
  raw EEG, no per-participant scores, no overall ranking.
authors:
  - name: "BCI Report"
    website: "https://bci.report"
url: "https://bci.report"
repository-code: "https://github.com/twu3202/bci-report"
repository-artifact: "https://huggingface.co/datasets/Twu31/bci-report"
doi: "10.5281/zenodo.23123296"
identifiers:
  - type: doi
    value: "10.5281/zenodo.23123296"
    description: "Zenodo concept DOI: resolves to the newest archived release"
  - type: url
    value: "https://bci.report/releases/"
    description: "Every release, with the SHA-256 of each file it ships"
license: CC-BY-4.0
version: "large-source-update-20261003"
date-released: "2026-10-03"
keywords:
  - EEG
  - electroencephalography
  - brain-computer interface
  - BCI
  - benchmark
  - SSVEP
  - P300
  - motor imagery
  - sleep staging
  - EEG foundation models
  - LoRA