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Reconstructing visual illusory experiences from human brain activity
Fan L Cheng1,2, Tomoyasu Horikawa2, Kei Majima1
1Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan.
Science Advances
|November 15, 2023
Summary
Researchers reconstructed visual illusions from brain activity using deep neural networks (DNNs). This technique visualizes subjective experiences, offering insights into the brain
Area of Science:
- Neuroscience
- Cognitive Science
- Computer Vision
Background:
- Visual illusions offer insights into sensory processing.
- The neural basis of subjective visual experiences is not fully understood.
Purpose of the Study:
- To reconstruct illusory percepts from brain activity using deep neural network (DNN) models.
- To investigate how brain activity relates to subjective visual experiences.
Main Methods:
- Utilized a brain decoding technique combined with DNN representations.
- Trained a reconstruction model on natural images to link brain activity with perceptual features.
- Tested the model on illusory line and neon color spreading phenomena.
Main Results:
- Successfully reconstructed images of illusory lines and neon color spreading from brain activity.
- Reconstructed percepts aligned with subjective illusory experiences.
- Observed variations in reconstructions across different visual cortical areas.
Conclusions:
- The developed framework can materialize subjective visual experiences.
- This approach sheds light on the brain's internal representations during visual processing.
- Brain decoding combined with DNNs is a promising method for studying visual perception.
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