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Invariant visual object and face recognition : neural and computational bases, and a model, VisNet
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Rolls, Edmund T. (2012) Invariant visual object and face recognition : neural and computational bases, and a model, VisNet. Frontiers in Computational Neuroscience, Volume 6 . Article number 35. doi:10.3389/fncom.2012.00035 ISSN 1662-5188.
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WRAP_Rolls_fncom-06-00035.pdf - Published Version Available under License Creative Commons Attribution Non-commercial. Download (8Mb) | Preview |
Official URL: http://dx.doi.org/10.3389/fncom.2012.00035
Abstract
Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Library of Congress Subject Headings (LCSH): | Neurosciences -- Mathematical models, Computational neuroscience, Vision, Face perception, Short-term memory, Cerebral cortex -- Research | ||||
Journal or Publication Title: | Frontiers in Computational Neuroscience | ||||
Publisher: | Frontiers Research Foundation | ||||
ISSN: | 1662-5188 | ||||
Official Date: | 19 June 2012 | ||||
Dates: |
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Volume: | Volume 6 | ||||
Page Range: | Article number 35 | ||||
DOI: | 10.3389/fncom.2012.00035 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 1 August 2016 | ||||
Date of first compliant Open Access: | 1 August 2016 | ||||
Funder: | Medical Research Council (Great Britain) (MRC), Wellcome Trust (London, England), Oxford McDonnell Network for Cognitive Neuroscience, Oxford Centre for Computational Neuroscience |
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