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Biologically Plausible Neural Circuits for Realization of Maximum Operations

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dc.creator Yu, Angela J.
dc.creator Giese, Martin A.
dc.creator Poggio, Tomaso A.
dc.date 2004-10-20T21:03:51Z
dc.date 2004-10-20T21:03:51Z
dc.date 2001-09-01
dc.date.accessioned 2013-10-09T02:48:38Z
dc.date.available 2013-10-09T02:48:38Z
dc.date.issued 2013-10-09
dc.identifier AIM-2001-022
dc.identifier CBCL-207
dc.identifier http://hdl.handle.net/1721.1/7240
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brain regions along the ventral pathway extract object features of increasing levels of complexity, accompanied by greater invariance in stimulus size, position, and orientation. Recent theoretical studies postulate a non-linear pooling function, such as the maximum (MAX) operation could be fundamental in achieving such invariance. In this paper, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Four canonical circuits are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we examine the relative performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each circuit and discuss their respective physiological considerations.
dc.format 28 p.
dc.format 2197042 bytes
dc.format 930880 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-2001-022
dc.relation CBCL-207
dc.subject AI
dc.subject maximum operation
dc.subject invariance
dc.subject recurrent inhibition
dc.subject shunting inhibition
dc.title Biologically Plausible Neural Circuits for Realization of Maximum Operations


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