LittlePrince_MEG_French_Listen_Pallier2025
[, learning-oddball (optimized for P3b), and local–global paradigm (for local and global effects). The data were collected in a single EEG session with three consecutive tasks presented as separate sessions, enabling within-individual comparison of event-related potential sensitivity across specialized oddball sequences.
…sequence learning (analogous to automatic speech recognition) - High-bandwidth neuromotor interfaces ## Dataset…
…updating and statistical learning, and speech-in-noise perception and auditory selective…
This dataset comprises intracranial electrophysiological recordings acquired using BCI2000 software and the CorTec BrainInterchange device. The study establishes an integrated ecosystem of technologies and protocols for adaptive neuromodulation research in human subjects, combining invasive neural recordings with brain-computer interface capabilities.
This dataset comprises EEG recordings from 10 healthy participants performing a P300 speller task using a 6×6 character matrix. The study compares two stimulus conditions—famous faces and inverting—to evaluate their effects on online P300 classification performance using language models. Data were collected across 2 sessions per subject with 3 runs per session, sampled at 256 Hz from 32 EEG channels.
This dataset comprises EEG recordings from a modified Sternberg working memory task designed to dissociate neural mechanisms of verbal information retention from those supporting active manipulation. Participants performed two task types—simple retention and alphabetization—across three memory loads (5, 6, or 7 letters), enabling investigation of temporally distinct oscillatory signatures underlying different working memory processes. Please cite: Pavlov, Y. G., & Kotchoubey, B. (2021). Temporally distinct oscillatory codes of retention and manipulation of verbal working memory. Scientific Reports, 11, 11230. https://doi.org/10.1038/s41598-020-72940-5
This dataset comprises multi-session, multi-task EEG recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. The dataset is in raw, unpreprocessed state and has been formatted according to BIDS standards for accessibility and reproducibility.
This event-related potential (ERP) study investigates neural mechanisms underlying the integration of fingerspelling, printed English words, and American Sign Language (ASL) signs in deaf readers. Using a priming paradigm with 300 prime-target pairs, the dataset captures electrophysiological responses to identity and translation primes across three modalities, providing insights into cross-modal language processing in the deaf population.