ArticleFrontiers in computational neuroscience2021
Photorealistic Reconstruction of Visual Texture From EEG Signals.
Article in Frontiers in computational neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Symbiotic brain-machine drawing via visual brain-computer interfaces.npj biomedical innovations · 2026Article
- Quantifying network behavior in the rat prefrontal cortex.Frontiers in computational neuroscience · 2024Article
- Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding.Frontiers in neuroscience · 2023Article
- Visualizing the mind's eye: a future perspective on applications of image reconstruction from brain signals to psychiatry.Psychoradiology · 2023Article
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Authors and funding
3 authors.
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Abstract
Recent advances in brain decoding have made it possible to classify image categories based on neural activity. Increasing numbers of studies have further attempted to reconstruct the image itself. However, because images of objects and scenes inherently involve spatial layout information, the reconstruction usually requires retinotopically organized neural data with high spatial resolution, such as fMRI signals. In contrast, spatial layout does not matter in the perception of "texture," which is known to be represented as spatially global image statistics in the visual cortex. This property of "texture" enables us to reconstruct the perceived image from EEG signals, which have a low spatial resolution. Here, we propose an MVAE-based approach for reconstructing texture images from visual evoked potentials measured from observers viewing natural textures such as the textures of various surfaces and object ensembles. This approach allowed us to reconstruct images that perceptually resemble the original textures with a photographic appearance. The present approach can be used as a method for decoding the highly detailed "impression" of sensory stimuli from brain activity.
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