Why Do We See Colors in a Black-and-White Top?
— Predictive AI Offers New Clues to a 200-Year-Old Mystery —
When a pattern drawn only in black and white is rotated, people sometimes perceive colors that are not actually present. This phenomenon is known as “subjective color” and has been studied for approximately 200 years as one of the remarkable mysteries of vision. Among such phenomena, Benham’s top is a well-known example in which colors are perceived simply by spinning a black-and-white disk.
A research group led by Kyohei Ueda, a graduate student at the Laboratory of Neurophysiology, National Institute for Basic Biology, and SOKENDAI; Dr. Lana Sinapayen, a researcher at Sony Computer Science Laboratories Kyoto and concurrently a Specially Appointed Associate Professor at the AI Facility, Center for Trans-Scale Biology, National Institute for Basic Biology; and Associate Professor Eiji Watanabe of the Laboratory of Neurophysiology, National Institute for Basic Biology, who also serves as Head of the AI Facility, Center for Trans-Scale Biology, and Associate Professor at SOKENDAI, used an artificial neural network trained through predictive learning to investigate the mechanism underlying this subjective color phenomenon.
The research group presented a black-and-white Benham’s top to an AI model that had been trained to predict “what kind of image will come next” after viewing naturalistic videos. Although the input images contained no color information at all, faint colors appeared in the images predicted by the AI. Furthermore, the artificially generated colors were found to change depending on the colors of moving objects contained in the videos used to train the AI. Analyses using natural videos, 3D computer graphics, and simple two-dimensional videos of moving red, green, and blue squares suggested that learning the association between motion and color may be one factor that enables colors to emerge from black-and-white stimuli.
This study suggests that subjective color may not be a phenomenon completed solely within the retina, but may also be related to the brain’s function of predicting future visual input based on past experience. By using AI, the study provides a new clue to the classical mystery of why colors are perceived from a black-and-white spinning top.
These findings were published in Scientific Reports on June 16, 2026.
Predictive networks generate motion-induced color illusions
Abstract
Subjective color (SC) refers to chromatic perception induced by achromatic stimuli, as classically demonstrated using Benham’s top. Despite nearly two centuries of investigation, the underlying neural mechanisms remain unclear. We developed artificial neural network models trained on natural videos using predictive learning to investigate SC generation. These models successfully reproduced artificial subjective color (ASC) from achromatic testing stimuli that contained no explicit chromatic information. Critically, ASC characteristics were systematically influenced by the colors of moving objects in the training videos. Using progressively simplified stimuli, ranging from natural scenes to 3D computer graphics and 2D animations, we demonstrated that the colors of moving objects primarily determine ASC properties. We propose that predictive learning establishes color associations with motion patterns, causing the arcs on Benham’s top to be perceived as moving objects with corresponding colors. These findings suggest that cortical predictive mechanisms may complement retinal processes in generating subjective color phenomena.
Scientific Reports
Predictive networks generate motion-induced color illusions
Kyohei Ueda, Lana Sinapayen, Eiji WatanabeDOI：https://doi.org/10.1038/s41598-026-57953-w
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