OpenNeuro ds005342 contains 17-channel EEG (250 Hz) from 32 healthy participants who, following on-screen cues, imagined sit-to-stand or stand-to-sit movements or stayed in an idle state, first in offline calibration runs and then in online BCI runs. Released on OpenNeuro by Triana-Guzman et al. (2024); the study appeared in Frontiers in Neuroinformatics (2022).
Also known asds005342 · EEG data offline and online during motor imagery for standing and sitting · Triana-Guzman et al. (2022)
35.0%Summed test trials. Fixed calibration rule; 60 training trials and 30 calibration trials per participant. Four-person case study; cohort aggregates only, no subgroup or population claim.
6.7%Summed test trials. Fixed calibration rule; 60 training trials and 30 calibration trials per participant. Four-person case study; cohort aggregates only, no subgroup or population claim.
35.0%Summed test trials. Fixed calibration rule; 60 training trials and 30 calibration trials per participant. Four-person case study; cohort aggregates only, no subgroup or population claim.
1.7%Summed test trials. Fixed calibration rule; 60 training trials and 30 calibration trials per participant. Four-person case study; cohort aggregates only, no subgroup or population claim.
4
Further foundation encoders, frozen · idle & command
11 / 600 of 4 people always abstained. Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.
Weights terms: REVE under the REVE Responsible Use License v1.0 (model versions: REVE Base @ dc2a075c · REVE Large @ 317531c7); LUNA under CC BY-ND 4.0, with no modified weights shared; BrainOmni, EEGMamba, ST-EEGFormer and SingLEM under MIT; CodeBrain and ZUNA under Apache-2.0; eeg-fm-masking under CC-BY-4.0; ERP-FM under CC BY-NC-SA 4.0, non-commercial. No model’s authors endorse these results. Every weights licence and its terms →
Same run as the published LaBraM idle row; the published CBraMod idle row comes from another run, so a comparison with it is across runs. The window balanced accuracy and AUROC were computed from this run’s saved probabilities with the definitions of the further foundation-encoder rows; the run itself recorded the counts.
Every core window is shorter than EEGPT’s 4-second pretraining window: 1 or 2 seconds, and sleep as fifteen 2-second segments. The encoder computes each 0.25-second patch the same way at any length; a shorter window gives fewer patches to average.
The readout is the site’s fixed probe on the frozen summary tokens, as for the published LaBraM and CBraMod rows: ridge (alpha 100) on 2,048 pooled values, and on idle a per-person logistic head. It is not the authors’ downstream probe, a learnable spatial filter with a linear head, and the windows are fed without the average reference EEGPT was pretrained with.
EEGPT: the checkpoint’s licence is unresolved, and no original or converted weights are distributed; Apache-2.0 covers the repository’s code only. Its licence and terms →
Source and licence
ds005342
CreditOpenNeuro 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.
BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data remain their creators’.