A Neural Network Model of Dynamically Fluctuating Perception of Necker Cube as well as Dot Patterns

Hiroaki Kudo, Nagoya University; Tsuyoshi Yamamura, Aichi Prefectural University; Noboru Ohnishi, Nagoya University; Shin Kobayashi and Noboru Sugie, Meijo University

The mechanism underlying perceptual grouping of visual stimuli is not static, but dynamic. In this paper, the dynamical grouping process is implemented with a neural network model consisting of an array of (hyper)columns suggested by Hubel & Wiesel, where intracolumnar inhibition and intercolumnar facilitation are incorporated. The model was applied successfully to figures consisting of a set of dots yielding either of two ways of groupings from time to time due to neural fluctuations and fatigue. Then the model was extended to introduce dependency on fixation points as well as neural fluctuations and fatigue. Then, it was applied to the Necker Cube. The model output from time to time either of two ways of 3D interpretations depending on the fixation points.

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