…copy-spell 'PATTERN RECOGNITION MACHINE LEARNING' (36 characters). Each character received 5…
FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants. In one session, EEG was recorded during a food categorisation task in which participants judged images as healthy, tasty, or something they were willing to eat. In a second session, participants completed a food go/no-go task, a paired choice task, and questionnaires on dietary style and motivation. The dataset also includes raw and cleaned EEG data and normative ratings of the food stimuli from online samples.
…Moody PhysioNet Challenge 2023, for which these data were the training set…
This dataset contains EEG recordings from phoneme discrimination tasks combined with transcranial magnetic stimulation (TMS) of the motor cortex. It merges two studies: a 2019 study of consonant-vowel and vowel-consonant pairs in 8 participants, and a 2021 study in 16 participants that added single phonemes, real words and pseudowords. It is intended to support research on speech decoding and the role of articulation and coarticulation in speech perception.
…electroencephalography, EEG analysis, machine learning, end-to-end learning, brain-machine interface…
…For each participant, the two machine learning models obtained in the offline…
An EEG-BIDS dataset from a three-person hyperscanning experiment in which participants played a prisoner's dilemma game. It includes 11 triads (3 participants each), with recordings across decision, feedback, and rest tasks. Behavioral labels are provided in the events files, and EEG data are stored in EEGLAB .set format.
…Machine Learning Group, Berlin Institute of Technology, Bernstein Focus Neurotechnology, Berlin, Neurophysics…
EEG, galvanic skin response (GSR) and electrocardiogram (ECG) recordings from 16 healthy participants who listened to 40 s synthetically generated music clips targeting two affective states defined by valence and arousal. Data were collected over three sessions on separate days, each with four runs of 18 trials. The recordings were made to train an affective brain-computer music interface (BCMI-MIdAS) to induce target emotional states in individual users. Self-reported valence and arousal values and auxiliary variables are included.
The Automatic Evoked Response Detection (ER-Detect) dataset contains intracranial EEG recordings collected during single-pulse electrical stimulation at the Mayo Clinic (Rochester, MN, USA) and the University Medical Center Utrecht (The Netherlands). It supports the development and evaluation of automated detection of stimulation-evoked cortico-cortical responses in epilepsy patients. The data are organized in BIDS format.