100 results for "brain activity" · page 7 of 10 · ranked by relevance
…These HPI coordinates have been acquired from the neuronavigation system brainsight (https…
This dataset comprises neuroimaging and electrophysiological recordings from 18 participants who engaged in reward-based cognitive tasks during wakefulness followed by sleep monitoring in an MRI scanner. Participants played two games (FACE and MAZE) during 3T fMRI acquisition, with one game designated as rewarded and the other as non-rewarded. Subsequent sleep sessions were recorded with simultaneous 64-channel EEG and fMRI for 1-2 hours, during which participants reached either N2 or N3 sleep stages, followed by a memory test. The dataset enables investigation of how reward biases spontaneous neural reactivation during sleep through multimodal neuroimaging analysis.
This dataset contains 64-channel EEG recordings from 62 participants (31 pairs) who played a competitive, computerised version of the Rock-Paper-Scissors game across 480 games. The study investigates the neural correlates of competitive decision-making during real-time social interaction. This dataset supports research on neural decoding of strategic choices in a dyadic competitive context.
…Dataset combining EEG, eye-tracking, and high-speed video for ocular activity…
…Dataset combining EEG, eye-tracking, and high-speed video for ocular activity…
This dataset comprises resting-state EEG recordings and behavioral executive function assessments from 140 healthy adult participants, collected to investigate the relationship between intrinsic brain spatio-temporal dynamics (via EEG microstates) and executive functions. Participants underwent a 5-minute resting-state EEG recording (eyes open/closed) followed by a battery of nine cognitive tasks assessing executive functions. The study aimed to correlate EEG microstate metrics (occurrence, duration) with executive function performance scores.
[. The study investigates how the brain constructs hierarchical syntactic structure and generates rapid linguistic predictions during continuous speech comprehension. Each word event is annotated with linguistic predictors including lexical frequency, acoustic properties, and surprisal estimates from n-gram, recurrent neural network, and context-free grammar models.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004851-blue…