Reconstructing visual illusory experiences from human brain activity

Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural...

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Bibliographic Details
Published in:Science advances 2023-11, Vol.9 (46), p.eadj3906-eadj3906
Main Authors: Cheng, Fan L, Horikawa, Tomoyasu, Majima, Kei, Tanaka, Misato, Abdelhack, Mohamed, Aoki, Shuntaro C, Hirano, Jin, Kamitani, Yukiyasu
Format: Article
Language:English
Subjects:
Brain
Form Perception
Humans
Illusions
Neural Networks, Computer
Visual Cortex
Visual Perception
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Summary:Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity. The reconstruction model was trained on natural images to establish a link between brain activity and perceptual features and then tested on two types of illusions: illusory lines and neon color spreading. Reconstructions revealed lines and colors consistent with illusory experiences, which varied across the source visual cortical areas. This framework offers a way to materialize subjective experiences, shedding light on the brain's internal representations of the world.
ISSN:2375-2548
2375-2548
DOI:10.1126/sciadv.adj3906