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Analysis of biased competition and cooperation for attention in the cerebral cortex

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Turova, Tatyana and Rolls, Edmund T. (2019) Analysis of biased competition and cooperation for attention in the cerebral cortex. Frontiers in Computational Neuroscience, 13 . 51. doi:10.3389/fncom.2019.00051 ISSN 1662-5188.

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Official URL: http://dx.doi.org/10.3389/fncom.2019.00051

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Abstract

A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition operates. The analytic results are supported by simulations that illustrate the operation of the system with parameters selected from the analysis. The findings provide a detailed mathematical analysis of the operation of these neural systems with nodes connected by feedforward (bottom-up) and feedback (top-down) connections. The analysis provides the critical value of the top-down attentional bias that enables biased competition to operate for a range of input values to the network, and derives this as a function of all the parameters in the model. The critical value of the top-down bias depends linearly on the value of the other inputs, but the coefficients in the function reveal non-linear relations between the remaining parameters. The results provide reasons why the backprojections should not be very much weaker than the forward connections between two cortical areas. The major advantage of the analytical approach is that it discloses relations between all the parameters of the model.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Q Science > QL Zoology
Q Science > QP Physiology
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Cerebral cortex, Mathematical analysis, Neural networks (Neurobiology)
Journal or Publication Title: Frontiers in Computational Neuroscience
Publisher: Frontiers Research Foundation
ISSN: 1662-5188
Official Date: 31 July 2019
Dates:
DateEvent
31 July 2019Published
4 July 2019Accepted
Volume: 13
Article Number: 51
DOI: 10.3389/fncom.2019.00051
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 2 August 2019
Date of first compliant Open Access: 7 August 2019
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDEuropean Cooperation in Science and Technologyhttp://dx.doi.org/10.13039/501100000921
UNSPECIFIEDNuffield College, University of Oxfordhttp://dx.doi.org/10.13039/501100000666
UNSPECIFIEDRoyal Swedish Academy of Scienceshttp://dx.doi.org/10.13039/501100001725

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