BCItempo
- Participants
- 18
- Size
- 2.39 GB
- Updated
- Jun 6, 2026
Showing 10 of 613 datasets · page 61 of 62
This experiment has 20 subjects. Subjects asked to mentally concentrate on a target (see published article for more information) for periods of about 15 seconds. There are 4 verbal instructions given to subject by an automated computer program connected to a speakerphone: - The instruction is to wait until the experiment starts - The instruction is to relax - The instruction is to get ready as the trial is about to start - The instruction is to mentally concentrate on the target All the exp
Participants seated in a dimly lit room at 110 cm from a computer screen piloted from a PC computer. Two tasks alternated: a categorization task and a recognition task. In both tasks, target images and non-target images were equally likely presented. Participants were tested in two recording phases. The first day was composed of 13 series, the second day of 12 series, with 100 images per series (see details of the series below). To start a series, subjects had to press a touch-sensitive button.
———————————————————————————————— ORIGINAL PAPERS ———————————————————————————————— Lioi, G., Cury, C., Perronnet, L., Mano, M., Bannier, E., Lécuyer, A., & Barillot, C. (2019). Simultaneous MRI-EEG during a motor imagery neurofeedback task: an open access brain imaging dataset for multi-modal data integration Authors. Accepted for publication in Scientific Data. https://doi.org/https://doi.org/10.1101/862375 Mano, Marsel, Anatole Lécuyer, Elise Bannier, Lorraine Perronnet, Saman Noorzadeh, and Ch
———————————————————————————————— ORIGINAL PAPERS ———————————————————————————————— Lioi, G., Cury, C., Perronnet, L., Mano, M., Bannier, E., Lécuyer, A., & Barillot, C. (2019). Simultaneous MRI-EEG during a motor imagery neurofeedback task: an open access brain imaging dataset for multi-modal data integration Authors. BioRxiv. https://doi.org/https://doi.org/10.1101/862375 Mano, Marsel, Anatole Lécuyer, Elise Bannier, Lorraine Perronnet, Saman Noorzadeh, and Christian Barillot. 2017. “How to Bu
This EEG dataset was recorded as part of a study of the predictive mechanisms of rhythm perception by using an omission paradigm to separate out predictive neural activity from sensory evoked neural activity. The study had 18 participants listen to auditory rhythms and watch visual flashing rhythms separately. The stimulus trains of both kinds of rhythms contained occasional omissions. Code for preprocessing, time/freq computation, frequency band extraction and statistics is provided. Cluster fo
This dataset contains the data in Pereira, M., Faivre, N., Iturrate, I., Wirthlin, M., Serafini, L., Martin, S., Desvachez, A., Blanke, O., Van De Ville, D., Millan, JdR. (2020). Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging. Proceedings of the National Academy of Science, 117 (15) pp. 8382-8390 https://doi.org/10.1073/pnas.1918335117 Preprint: https://www.biorxiv.org/content/10.1101/496877v1 ABSTRACT The human capacity to compute the lik
This dataset contains the EEG recordings used in the paper: "Real-time EEG Feedback on Alpha Power Lateralization Leads to Behavioral Improvements in a Covert Attention Task" (Schneider, C., Pereira, M., Tonin, L. et al. Brain Topogr (2019). https://doi.org/10.1007/s10548-019-00725-9) Participants: Fourteen healthy subjects (seven female, seven male), age 23±1.52 years, with normal or corrected to normal vision took part in the study. All gave informed written consent and received course credit
This mobile brain body imaging (MoBI) gait adaptation experiment contains 18 subjects. Participants were walking on a treadmill at a constant speed and were required to step in time to an auditory tone sequence and adapt their step length and rate to occasional shifts in tempo of the pacing stimulus (i.e., following shifts to a faster or slower tempo). The scientific article (see Reference) contains all methodological details - Johanna Wagner (June 6, 2019)