EEG dataset for natural image recognition through visual stimuliMendeley Data
Electroencephalography (EEG) is a technique for measuring the brain's electrical activity in the form of action potentials with electrodes placed on the scalp. Because of its non-invasive nature and ease of use, the approach is becoming increasingly popular for investigations. EEG reveals a wid...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925003701 |
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| Summary: | Electroencephalography (EEG) is a technique for measuring the brain's electrical activity in the form of action potentials with electrodes placed on the scalp. Because of its non-invasive nature and ease of use, the approach is becoming increasingly popular for investigations. EEG reveals a wide spectrum of human brain potentials, such as event-related, sensory, and visually evoked potentials (VEPs), which aids in the development of intricate applications. Developing Apps or Brain-Computer Interface (BCI) devices demands data on these potentials. The present dataset comprises EEG recordings generated by thirty-two individuals in reaction to visual stimuli (VEPs). The rationale behind gathering this data is its ability to support EEG-based image classification and reconstruction while also advancing visual decoding. The primary purpose is to examine the cognitive processes behind both familiar and unfamiliar observations. A standardized experimental setup comprising many experimental phases was employed to capture the essence of the investigation and gather the dataset. |
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| ISSN: | 2352-3409 |