Visual information flow in Wilson–Cowan networks

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• dc.contributor.author Gómez Villa, Alexander
• dc.contributor.author Bertalmío, Marcelo
• dc.contributor.author Malo, Jesús
• dc.date.accessioned 2020-07-03T09:17:22Z
• dc.date.issued 2020
• dc.description.abstract In this paper, we study the communication efficiency of a psychophysically tuned cascade of Wilson–Cowan and divisive normalization layers that simulate the retina-V1 pathway. This is the first analysis of Wilson–Cowan networks in terms of multivariate total correlation. The parameters of the cortical model have been derived through the relation between the steady state of the Wilson–Cowan model and the divisive normalization model. The communication efficiency has been analyzed in two ways: First, we provide an analytical expression for the reduction of the total correlation among the responses of a V1-like population after the application of the Wilson–Cowan interaction. Second, we empirically study the efficiency with visual stimuli and statistical tools that were not available before 1) we use a recent, radiometrically calibrated, set of natural scenes, and 2) we use a recent technique to estimate the multivariate total correlation in bits from sets of visual responses, which only involves univariate operations, thus giving better estimates of the redundancy. The theoretical and the empirical results show that, although this cascade of layers was not optimized for statistical independence in any way, the redundancy between the responses gets substantially reduced along the neural pathway. Specifically, we show that 1) the efficiency of a Wilson–Cowan network is similar to its equivalent divisive normalization model; 2) while initial layers (Von Kries adaptation and Weber-like brightness) contribute to univariate equalization, and the bigger contributions to the reduction in total correlation come from the computation of nonlinear local contrast and the application of local oriented filters; and 3) psychophysically tuned models are more efficient (reduce more total correlation) in the more populated regions of the luminance-contrast plane. These results are an alternative confirmation of the efficient coding hypothesis for the Wilson–Cowan systems, and, from an applied perspective, they suggest that neural field models could be an option in image coding to perform image compression.en
• dc.description.sponsorship This work was partially funded by the Spanish Government and EU FEDER fund through the MINECO grants TIN2015-71537-P and DPI2017-89867-C2-2-R; and by the European Union’s Horizon 2020 research and innovation programme under grant agreement number 761544 (project HDR4EU) and under grant agreement number 780470 (project SAUCE).
• dc.format.mimetype application/pdf
• dc.identifier.citation Gomez-Villa A, Bertalmío M, Malo J. Visual information flow in Wilson–Cowan networks. Journal of Neurophysiology. 2020 Jun 12;123(6):2249-68. DOI: 10.1152/jn.00487.2019
• dc.identifier.doi http://dx.doi.org/10.1152/jn.00487.2019
• dc.identifier.issn 0022-3077
• dc.identifier.uri http://hdl.handle.net/10230/45071
• dc.language.iso eng
• dc.publisher American Physiological Society
• dc.relation.ispartof Journal of Neurophysiology. 2020 Jun 12;123(6):2249-68
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-71537-P
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/DPI2017-89867-C2-2-R
• dc.rights © 2020 the American Physiological Society. http://dx.doi.org/10.1152/jn.00487.2019
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Divisive normalizationen
• dc.subject.keyword Efficient representation principleen
• dc.subject.keyword Multi-informationtotal correlationen
• dc.subject.keyword Wilson–Cowan equationsen
• dc.title Visual information flow in Wilson–Cowan networks
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion