39 By BP
…screen, and scores were recorded, potentially including decimal values, to accommodate for…
- Participants
- 39
- Channels
- 64 (10-10)
- Size
- 22.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "Event-related potential" · page 7 of 10 · ranked by relevance
…screen, and scores were recorded, potentially including decimal values, to accommodate for…
…unsupervised learning, brain-computer interface, event-related potentials, P300 speller, expectation-maximization…
…Visual P300 is an event-related potential (ERP) elicited by an expected…
This dataset comprises simultaneous EEG and fNIRS recordings from 12 participants performing semantic imagery tasks involving silent naming and sensory-based imagination of animals and tools. Participants engaged in visual, auditory, and tactile perception tasks while neural activity was captured using a 64-channel BioSemi EEG system and a NIRx fNIRS imaging system with integrated optodes. The multimodal neuroimaging data supports research in semantic decoding and brain-computer interface applications.
…Study neural signals, including event-related potentials and oscillations, alongside peripheral physiology…
…model with a traditional event-related potential (ERP) technique. We calibrate the…
This dataset contains BIDS-formatted EEG and behavioral data from a study investigating the neural mechanisms underlying subjective experiences of time passage. Participants completed experimental tasks designed to probe temporal perception across different conditions. The raw electrophysiological recordings and associated behavioral measures provide empirical evidence for a common neural substrate supporting temporal perception. Data were collected using standard EEG acquisition protocols and preprocessed according to BIDS conventions. The study includes multiple participants across several experimental sessions examining how the brain processes and perceives the passage of time.
…is limited, potentially reducing the salience of pain-related signals. This athlete…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003522-blue…