
This study demonstrates the feasibility of reconstructing visual images from electroencephalography (EEG) data using a latent diffusion modeling approach, despite the inherent limitations of EEG in spatial resolution and visual information encoding.


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decoding-visual-perception-from-electroencephalography-using-latent-diffusion-modeling


Decoding Visual Perception from Electroencephalography Using Latent Diffusion Modeling


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The author proposes a novel method using EEG signals to reconstruct visual stimulus images, emphasizing the advantages of low cost and portability compared to fMRI-based methods.


reconstructing-visual-stimulus-images-from-eeg-signals-using-deep-visual-representation-model


Reconstructing Visual Stimulus Images from EEG Signals Using Deep Visual Representation Model
