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        The Cat Is On the Mat. Or Is It a Dog? Dynamic Competition in Perceptual Decision Making

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        Quinton_et_al_IEEE_aam.pdf (PDF, 1Mb)
        Author
        Quinton, Jean Charles
        Catenacci Volpi, Nicola
        Barca, Laura
        Pezzulo, Giovanni
        Attention
        2299/20530
        Abstract
        Recent neurobiological findings suggest that the brain solves simple perceptual decision-making tasks by means of a dynamic competition in which evidence is accumulated in favor of the alternatives. However, it is unclear if and how the same process applies in more complex, real-world tasks, such as the categorization of ambiguous visual scenes and what elements are considered as evidence in this case. Furthermore, dynamic decision models typically consider evidence accumulation as a passive process disregarding the role of active perception strategies. In this paper, we adopt the principles of dynamic competition and active vision for the realization of a biologically- motivated computational model, which we test in a visual catego- rization task. Moreover, our system uses predictive power of the features as the main dimension for both evidence accumulation and the guidance of active vision. Comparison of human and synthetic data in a common experimental setup suggests that the proposed model captures essential aspects of how the brain solves perceptual ambiguities in time. Our results point to the importance of the proposed principles of dynamic competi- tion, parallel specification, and selection of multiple alternatives through prediction, as well as active guidance of perceptual strategies for perceptual decision-making and the resolution of perceptual ambiguities. These principles could apply to both the simple perceptual decision problems studied in neuroscience and the more complex ones addressed by vision research.
        Publication date
        2013-09-06
        Published in
        IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans
        Published version
        https://doi.org/10.1109/TSMC.2013.2279664
        Other links
        http://hdl.handle.net/2299/20530
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