THINGS-EEG is an electroencephalogram (EEG) dataset for object cognition research, released by the National Institute of Mental Health of the National Institutes of Health (NIH), the Max Planck Institute for Human Cognition and Brain Sciences in Germany, and the University of Giessen Medical School, among other institutions. It records the EEG activity of 50 subjects while viewing images of objects, and is used to analyze the temporal dynamics and cognitive representations of object processing.

This dataset belongs to THINGS-data, and the relevant research papers are as follows:THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behaviorTHINGS-data contains 1,854 object concepts and 26,107 manually selected and labeled images of natural scene objects.

In the experiment, participants viewed a representative subset of stimuli from the THINGS image database, comprising 22,248 images covering 1,854 object concepts. The images were presented in a rapid serial visual presentation (RSVP) manner, requiring participants to maintain central fixation. Some images were presented repeatedly to analyze the stability of neural representations.

The dataset also provides:

• Raw EEG signal
• Preprocessed EEG data
• Derivatives that can be used to construct representation matrices (RDM)

THINGS-EEG provides a rich data foundation for studying the temporal dynamics of visual representations of objects, the structure of human cognition, and cross-modal alignment with fMRI/MEG data.