…learning (analogous to automatic speech recognition) - High-bandwidth neuromotor interfaces ## Dataset Details…
…on Computer Vision and Pattern Recognition (CVPR), 1–9. https://doi.org…
EEG dataset from the PURSUE project of a face perception task designed to elicit the N170 event-related potential. Data were collected from participants at three primarily undergraduate institutions in Southern California, Massachusetts, and Virginia during 2017 and 2018. The task follows the ERP CORE paradigm, and the dataset includes participant race information.
This dataset contains magnetoencephalography (MEG) recordings from participants performing a cued recall task involving personally familiar people and places. It was collected to examine sustained neural representations of familiar people and places during recall. The data are organized in BIDS format.
A multi-session, multi-task EEG dataset for passive brain-computer interface research, collected from 15 healthy participants across two sessions. Recordings include resting state and three difficulty levels (easy, medium, difficult) of the MATB-II multitasking environment, recorded with 62 active electrodes at 500 Hz. The dataset supports cross-session and cross-subject mental workload estimation and neuroergonomics applications.
EEG recordings from ten participants who viewed six marketing videos from three companies (Red Bull, GoPro, Columbia Sportswear). The videos were either traditional product-focused advertisements or 'extreme' authentic documentary-style content. The dataset supports research on neural correlates of consumer responses to different marketing video styles.
Preprocessed 64-channel EEG recordings from six healthy participants performing imagined speech of a short word ('in') versus a long word ('cooperate'). The data were band-pass and notch filtered and cleaned of EOG artifacts. They were used to classify imagined speech with Riemannian manifold covariance features and relevance vector machines for brain-computer interface applications. The dataset is re-hosted in BIDS format through the MOABB benchmark collection.