Name
Abstract | ||
|---|---|---|
Symmetry is usually computationally expensive to detect reliably, while it is relatively easy to perceive. In spite of many attempts to understand the neurofunctional properties of symmetry processing, no symmetry-specific activation was found in earlier cortical areas. Psychophysical evidence relating to the processing mechanisms suggests that the basic processes of symmetry perception would not perform a serial, point-by-point comparison of structural features but rather operate in parallel. Here, modeling of neural processes in psychophysical detection of bilateral texture symmetry is considered. A simple fine-grained algorithm that is capable of performing symmetry estimation without explicit comparison of remote elements is introduced. A computational model of symmetry perception is then described to characterize the underlying mechanisms as one-dimensional spatio-temporal neural processes, each of which is mediated by intracellular horizontal connections in primary visual cortex and adopts the proposed algorithm for the neural computation. Simulated experiments have been performed to show the efficiency and the dynamics of the model. Model and human performances are comparable for symmetry perception of intensity images. Interestingly, the responses of V1 neurons to propagation activities reflecting higher-order perceptual computations have been reported in neurophysiologic experiments. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s00422-013-0578-y | Biological Cybernetics |
Keywords | Field | DocType |
Neural processes,Symmetry detection,Processing mechanisms,Computational modeling,Vision | Visual cortex,Models of neural computation,Artificial intelligence,Perception,Mathematics,Machine learning,Computation | Journal |
Volume | Issue | ISSN |
108 | 2 | 1432-0770 |
Citations | PageRank | References |
1 | 0.37 | 6 |
Authors | ||
1 | ||