EEG Semantic Imagination and Perception Dataset
…stimuli from three modalities; visual pictorial, visual orthographic (writing) or auditory. Each…
- Participants
- 12
- Channels
- 124 (10-05)
- Citations
- 1
- Size
- 79.1 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
100 results for "visual processing" · page 2 of 10 · ranked by relevance
…stimuli from three modalities; visual pictorial, visual orthographic (writing) or auditory. Each…
…to another person’s fingers (visual trials). There were 12 runs in…
…An EEG Dataset for Visual Imagery-Based Brain-Computer Interface. Scientific Data…
…False ## Signal Processing - **Classifiers**: LLP (Learning from Label Proportions), shrinkage-LDA, EM…
…a multimodal resource for studying information processing in the developing brain (EEG…
Imported from OpenNeuro ds002718
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.
This dataset comprises human electroencephalography recordings from 20 participants performing a visual attention task involving rapid sequences of overlaid oriented gratings. Participants detected target gratings while manipulating both attention (cued by color) and temporal expectation (predictable vs. unpredictable stimulus onset timing). The study dissociates feature-based attention effects from temporal expectation and target-related decision processes, providing insights into the temporal dynamics of selective attention.
This dataset comprises intracranial EEG (ECoG) recordings from 14 epilepsy patients implanted with subdural grid and depth electrodes, collected while they viewed grayscale and color visual stimuli varying in spatial and temporal properties. The recordings were designed to characterize temporal and spatial dynamics of neural responses in human visual cortex, including population receptive field mapping and category-selective responses. Pre-implantation T1-weighted MRI scans are also included for electrode localization. The dataset supports multiple published studies on visual cortical dynamics and adaptation.
A high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.