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References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896 Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., D

Participants

23

Size

97.7 GB

Bimodal dataset on Inner Speech Code available: https://github.com/LTU-Machine-Learning/Inner\_Speech\_EEG\_FMRI Publication available: https://www.nature.com/articles/s41597-023-02286-w Abstract: The recognition of inner speech, which could give a `voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition.

Participants

4

Size

9.33 GB

Experiment Details Electroencephalography recordings from 16 subjects to fast streams of gabor-like stimuli. Images were presented in rapid serial visual presentation streams at 6.67Hz and 20Hz rates. Participants performed an orthogonal fixation colour change detection task. Experiment length: 1 hour

Participants

16

Size

19.3 GB

This is the preprocessed dataset used for study "Characterization of spatiotemporal dynamics in EEG data during picture naming with optical flow patterns". The Picture Naming Task study included sixteen native French-speaking men, ranging in age from 18 to 70 years old. The participants met the inclusion criteria, which required normal or corrected-to-normal vision and hearing, as well as right-handedness, as determined by a handedness questionnaire [Oldfield1971assessment]. Exclusion criteria

Participants

16

Size

8.78 GB

This dataset was curated for publication as part of the manuscript in Sakakura et al. (in preparation). It contains iEEGs collected from 114 individuals during slow wave sleep. The available Matlab code can be found at https://github.com/kaz1126/MI_HFO. The iEEG coordinate system employed in this dataset is MNI305.

Participants

114

Size

68.9 GB

# Intraoperative EEG dataset during medianus-tibialis stimulation with 8 different rates This dataset was obtained from the publication [1] wherein we varyied the stimulus repetition rate and recorded medianus and tibial nerve SEP. We randomly sampled a number of sweeps corresponding to recording durations up to 20 s and calculated the signal-to-noise ratio (SNR). There are 14 adults subjects and 4 children subjects with continuous EEG data split in sessions (tibial left/right, medianus left/r

Participants

18

Size

7.73 GB

Our dataset contains high-density, dual-layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, T1 structural MR images, and video data from 25 participants playing real-world table tennis. Participants played 60 minutes of table tennis (in total) with a ball machine and a human player, with an additional 10 minutes of standing baseline. For 17 of the participants, we also include video data of all trials. The Adobe Premiere project files (l

Participants

25

Size

34.6 GB

There are three files per participant collected for each of the three stages of the procedure. Stage 1 (before measurement): A two-alternative forced choice discrimination task including letters "b" and "d" Stage 2 (intervention measurement): A simple visual search task including a target letter (either b or d) and three distractor letters chosen at random (p or q). Stage 3 (after measurement): A two-alternative forced choice discrimination task including letters "b" and "d" \_\_\_\_\_\_\_\_\

Participants

21

Size

20.9 GB

Probabilistic Selection Task. Unpublished! Same sample as this published study: 10.1038/ncomms6394. Study 1: 80 healthy participants + 5 placebo session from a pilot of the drug study. Total n=85. But Subj 173 might have bad EEG. Study 2: 30 healthy participants (3 dropout) in a double-blind drug study. Total n=27. Drug was Cabergoline 1.25 mg. If you look in the code folder at the .xls sheet, you'll see that subjects had different initial IDs. Study 1 subjects had subje

Participants

110

Size

21.8 GB

Preprocessed data from Experiment 1 of Ester & Pytel "Changes in behavioral priority influence the accessibility of working memory content". Analytic scripts for this project can be found on OSF: https://osf.io/gtd5f/. Note that to analyze the BIDS data, you'll need to modify the analysis scripts to read in the BIDS .set files rather than the expected .mat files. See the OSF wiki for more information

Participants

34

Size

10.7 GB