Visual Information Flow in Wilson Cowan Networks. Gómez-Villa et al. Journal of Neurophysiology 2019.
The Wilson-Cowan interaction of wavelet-like visual neurons is analyzed in total correlation terms for the first time. Theoretical and empirical results show that a psychophysically-tuned interaction achieves the biggest efficiency in the most frequent region of the image space. This an original confirmation of the Efficient Coding Hypothesis and suggests that neural field models can be an alternative to Divisive Normalization in image compression.
References
- Visual information Flow in Wilson Cowan Networks
A. Gómez-Villa, M. Bertalmío and J. Malo
J. Neurophysiol. 123 (6): 2249-2268 (2020) https://doi.org/10.1152/jn.00487.2019 - Spatio-Chromatic Information available from different Neural Layers via Gaussianization
J. Malo
J. Mathematical Neuroscience (2020) https://doi.org/10.1186/s13408-020-00095-8 - Information Flow in Color Appearance Neural Networks arXiv: Quantitative Biology, Neurons and Cognition
J. Malo
arXiv: Quantitative Biology, Neurons and Cognition https://arxiv.org/abs/1912.12093 (2019) - Visual information Flow in Psychophysical-Physiological networks
J. Malo and Q. Li
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