Arithmetic calculations measured by intracranial EEG in the human brain
…48-52 Hz stop band, Butterworth, 6th order, zero phase). The publication…
- Participants
- 20
- Size
- 7.21 GB
- Version
- v1.0.0
- Updated
- Oct 8, 2026
…48-52 Hz stop band, Butterworth, 6th order, zero phase). The publication…
A mobile EEG dataset of auditory attention from 20 participants performing a two-competing-speaker paradigm. Participants either sat on a chair or walked an indoor route while attending to one of two speakers. Salient environmental events presented from in front of the participant were used to disrupt attention, allowing neural tracking of speech to be studied in realistic, mobile conditions.
…The goal was to reveal whether temporal expectation influences initial sensory processing…
EEG dataset from twenty-one participants performing a continuous feedback learning task in which they predicted the final level of an animated rising bar. Cues (gnomes) differed in how predictable the outcome was (highly predictable, somewhat predictable, unpredictable), enabling study of feedback processing under varying outcome uncertainty. Points were awarded according to the accuracy of each guess.
[ recordings from 80 participants who reported their attitudes on a set of sociopolitical issues and then viewed photographs of protests about those same issues. Each photo was preceded by a pie chart showing low, medium, or high social support for the issue. After each photo, participants rated their support for the protestors. The dataset supports investigation of how moral conviction and metacognitive ability shape multiple stages of information processing.
…under ambulatory conditions, with trials temporally divided into training, validation, and test…
EEG dataset investigating the neural representation of consciously seen and unseen information. The recordings were collected by Rodríguez-San Esteban, Chica, and González-López and are shared in BIDS format. The dataset is mirrored on NEMAR from OpenNeuro (ds005273).
EEG dataset from an alphabetic decision task in which participants viewed letter stimuli rendered in the Arial Light font. It was collected to study sub-letter orthographic processing and to test optimal transport as a model of letter similarity. The dataset includes BIDS-formatted EEG recordings joined with behavioural data, stimulus information, and metadata, plus notes on recording issues and corrections.
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004816-blue…