ArticleFrontiers in psychology2018
Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.
Article in Frontiers in psychology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comprehensive investigation of predictive processing: A cross- and within-cognitive domains fMRI meta-analytic approach.Human brain mapping · 2024Pooled it
- Predictive networks generate motion-induced color illusions.Scientific reports · 2026Article
- Age-Related Differences in Perception of the Rotating Snakes Illusion Among Young and Older Adults with Normal Visual Acuity.Eye and brain · 2026Article
- Perceptual distortions in PredNet and quantification of top-down/bottom-up flow.Frontiers in computational neuroscience · 2026Article
- Contrasting predictive coding and representational accounts of perceptual organization, stimulus predictability, and attentional modulation in the visual cortical hierarchy.Neuroscience of consciousness · 2026Review
- Article
- Adaptation optimizes sensory encoding for future stimuli.PLoS computational biology · 2025Article
- Motion-induced blindness shows spatial anisotropies in conscious perception.Scientific reports · 2024Article
- Evaluating large language models in theory of mind tasks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Optimization in Visual Motion Estimation.Annual review of vision science · 2024Review
- Predictive coding networks for temporal prediction.PLoS computational biology · 2024Article
- Article
- Integration of motion information in illusory motion perceived in stationary patterns.Scientific reports · 2023Article
- Reconstructing visual illusory experiences from human brain activity.Science advances · 2023Article
- Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans.Scientific reports · 2023Article
- Challenging deep learning models with image distortion based on the abutting grating illusion.Patterns (New York, N.Y.) · 2023Article
- Learning on Arbitrary Graph Topologies via Predictive Coding.Advances in neural information processing systems · 2022Article
- On the synthesis of visual illusions using deep generative models.Journal of vision · 2022Article
- Identifying specular highlights: Insights from deep learning.Journal of vision · 2022Article
- Motion illusion-like patterns extracted from photo and art images using predictive deep neural networks.Scientific reports · 2022Article
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.
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