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A Human EEG Dataset for Multisensory Perception and Mental Imagery
Yan-Han Chang1,2, Hsi-An Chen1, Min-Jiun Tsai3
1Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Scientific Data
|October 1, 2025
Summary
The YOTO dataset offers high-resolution human electroencephalography (EEG) data for studying multisensory perception and mental imagery. This resource aids research into how the brain integrates different sensory inputs and forms internal representations.
Area of Science:
- Neuroscience
- Cognitive Science
- Data Science
Background:
- Multisensory perception and mental imagery are complex cognitive functions.
- Understanding neural mechanisms requires high-temporal-resolution data.
- Existing datasets may not fully capture multimodal integration.
Purpose of the Study:
- Introduce the YOTO (You Only Think Once) dataset, a novel human electroencephalography (EEG) resource.
- Facilitate research into multisensory perception and mental imagery.
- Provide a publicly accessible dataset for advancing cognitive modeling and neural decoding.
Main Methods:
- Collected high-resolution EEG data (1000 Hz sampling rate) from 26 participants.
- Utilized unimodal (visual, auditory) and multimodal stimuli.
- Incorporated self-reported vividness ratings to quantify subjective experience.
- Validated data using event-related potentials (ERPs) and power spectral density (PSD) analyses.
Main Results:
- EEG data captured high-temporal-resolution neural activity.
- Distinct neural responses were observed across different sensory stimuli.
- Technical validation confirmed the dataset's reliability and data quality.
Conclusions:
- The YOTO dataset is a valuable resource for studying the neural basis of multisensory integration and mental imagery.
- Public accessibility promotes further research in neural decoding, perception, and cognitive modeling.
- This dataset can accelerate advancements in understanding and applying multimodal cognitive processes.
