Analysis of differences in EEG Signal features between Visual Imagery and Perception

Abstract

Recent research works have increasingly focused on gaining a better understanding of visual perception from brain activity. This work was partially motivated by functional Magnetic Resonance Imaging (fMRI) based studies on the neurobiology of” mental images” and Brain-Computer Interface (BCI) devices. The ultimate objective is to recreate thoughts from brain activity using generative AI models. It is crucial to extract and enumerate the differences between visual perception (when a stimulus is present) and visual imagery (the recall of the stimulus after that) by the brain. In this work, we determine that it is possible to detect changes in brain activity due to differences in Visual Perception and Imagery even while using EEG signal features recorded with limited channels. The first step in this process was doing a spatiotemporal-based feature estimation on the EEG data for seven people across all channels and trials. Results indicate that Alpha Band power, an essential characteristic in the posterior electrodes and indicating a parieto-occipital origin, significantly differed across the different channels.