Showing 10 of 668 datasets · page 2 of 67
A practice dataset containing EEG recordings collected during a student neuroscience workshop. This dataset is intended for educational and training purposes only and is not suitable for scientific analysis or research applications.
This dataset comprises EEG recordings and concurrent audio data collected during speech production and auditory listening tasks. Participants performed overt speech vocalization, passive listening to prerecorded speech, and covert speech imagery tasks while EEG was recorded using three different acquisition systems (g.tec g.Pangolin, g.SCARABEO, and ANT Neuro eego sports). The dataset supports brain decoding research investigating the neural correlates of speech perception and production.
This longitudinal brain-machine interface study presents multimodal neurophysiological and kinematic data from seven healthy adults performing motor imagery tasks to control a lower-limb exoskeleton. The dataset comprises 60-channel EEG with EOG, dual inertial measurement units, and exoskeleton control signals collected across nine sessions per participant. Data include both open-loop calibration phases and closed-loop BMI control trials, providing a comprehensive resource for investigating neural correlates of motor imagery and human-machine interaction in ambulatory tasks.
A fully anonymized long-term intracranial EEG dataset from 40 patients with pharmacoresistant epilepsy recorded at the Sleep-Wake-Epilepsy-Center, University of Bern. The dataset comprises 5376 hours of continuous iEEG with 381 annotated electrographic seizures, sampled at 512 or 1024 Hz and preprocessed with band-pass filtering and median referencing. This resource supports development and validation of seizure detection and neuronal activity modeling algorithms.
A raw EEG neuroimaging dataset containing pre and post intervention measurements organized according to BIDS standards. The dataset includes electroencephalography recordings from multiple groups collected to assess intervention effects through longitudinal pre-post measurements. Data is suitable for comparative group-level analysis of changes across study phases. For detailed information about study design, methods, participant demographics, and data organization, please refer to the README.md file in the dataset root directory.
A BIDS-formatted neuroimaging dataset containing pre and post intervention EEG recordings from multiple subjects. This dataset provides raw EEG data suitable for comparative analysis of neural activity changes across baseline and post-intervention conditions. The dataset includes EEG recordings in .edf format with accompanying BIDS-compliant metadata documenting acquisition parameters, electrode configurations, sampling rates, and participant information. The intervention protocol and specific clinical or research context are documented in the accompanying dataset files.
MorseEEG-ATP is a multitask electroencephalography dataset comprising synchronously recorded EEG and behavioral data from 32 healthy adult participants performing auditory discrimination tasks using Morse code stimuli. The dataset addresses auditory temporal processing and temporal pattern discrimination across two tasks (dot-count and first-last match) and three presentation-rate conditions (15, 30, and 40 characters per minute). Raw 62-channel EEG recordings sampled at 600 Hz are provided alongside minimally preprocessed derivatives, trial-aligned event annotations, behavioral measures, and analysis scripts in BIDS-compatible format. Technical validation is provided through behavioral performance, event-related potential responses, and listening-related measures as described in the accompanying Scientific Data publication. Note: Data quality issues including corrupted channels for sub-13 (channel 56), sub-14 (channel 56), and sub-15 (channel 43) have been addressed through interpolation in the preprocessed derivatives.
The CrossModal Study is an EEG dataset investigating how the brain prepares for and discriminates targets across sensory modalities. Participants received cues to prepare for auditory, visual, or non-specific targets, followed by a 3-second interval with frequency-tagged visual stimulation (36 Hz) and amplitude-modulated auditory stimulation (40 Hz). Targets were either Gabor patches or tones, with cross-modal distractors presented in cued conditions. The dataset comprises 28 experimental blocks per participant and includes EOG recordings to monitor eye activity.
This dataset comprises electroencephalography (EEG) recordings from 40 participants performing a two-door decision-making task with monetary feedback. Participants completed 20 blocks of 20 trials each, alternating between learnable blocks where one door had a 60% win probability and the other a 10% win probability, and unlearnable blocks where outcomes were randomized. Post-block surveys assessed subjective perceptions of door quality, enjoyment, motivation, and performance. The dataset enables investigation of neural correlates of learning, decision-making, and feedback processing under conditions of varying environmental predictability.
ROAMM is a large-scale multimodal neuroimaging dataset combining simultaneous EEG and eye-tracking recordings from 44 participants during naturalistic reading of standardized articles. The dataset includes span-level mind-wandering annotations, reading comprehension assessments, and linguistic stimulus information, providing a benchmark resource for mind-wandering detection and EEG-based language decoding in naturalistic contexts.