dc.contributorFGV
dc.creatorBrogliato, Marcelo Salhab
dc.creatorChada, Daniel de Magalhães
dc.creatorLinhares, Alexandre
dc.date.accessioned2018-05-10T13:36:32Z
dc.date.accessioned2019-05-22T14:04:20Z
dc.date.available2018-05-10T13:36:32Z
dc.date.available2019-05-22T14:04:20Z
dc.date.created2018-05-10T13:36:32Z
dc.date.issued2014-04-28
dc.identifier0013-0133 / 1468-0297
dc.identifierhttp://hdl.handle.net/10438/23386
dc.identifier10.3389/fnhum.2014.00222
dc.identifier000334999000001
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2689787
dc.description.abstractHow can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will interested concerns models of theoritical neuroscience that could explain the speed and robustness of an expert's recollection. the approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the ''tip-of-tongue'' memory event-which is found at a non-linearily in the model. We expand the theoritical framework, deriving an optimization formula to solve this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory.
dc.languageeng
dc.publisherFrontiers Research Foundation
dc.relationFrontiers in human neuroscience
dc.rightsopenAccess
dc.sourceWeb of Science
dc.subjectSparse distributed memory
dc.subjectNon-linearity
dc.subjectCritical distance
dc.subjectTheoretical neuroscience
dc.subjectExpert memory
dc.subjectFusiform face area
dc.subjectPattern-recognition
dc.subjectCell assemblies
dc.subjectChess experts
dc.subjectNeural basis
dc.subjectCérebro
dc.titleSparse distributed memory: understanding the speed and robustness of expert memory
dc.typeArticle (Journal/Review)


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