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dc.contributor.authorCowley, Benjamin
dc.contributor.authorThornton, John
dc.date.accessioned2017-07-04T04:57:22Z
dc.date.available2017-07-04T04:57:22Z
dc.date.issued2017
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-319-51691-2_6
dc.identifier.urihttp://hdl.handle.net/10072/341322
dc.description.abstractAttention is both ubiquitous throughout and key to our cognitive experience. It has been shown to filter out mundane stimuli, while simultaneously communicating specific stimuli from the lowest levels of perception through to the highest levels of cognition. In this paper we present a connectionist system with mechanisms that produce both exogenous (bottom-up) and endogenous (top-down) attention. The foundational algorithm of our system is the Temporal Pooler (TP), a neocortically inspired algorithm that learns and predicts temporal sequences. We make a number of modifications to the Temporal Pooler and place it in a framework which is inspired by predictive coding. We use a novel technique in which feedback connections elicit endogenous attention by disrupting the learned representations of attended sequences. Our experiments show that this approach successfully filters attended stimuli and suppresses unattended stimuli.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofpagefrom61
dc.relation.ispartofpageto73
dc.relation.ispartofjournalLecture Notes in Computer Science
dc.relation.ispartofvolume10142
dc.subject.fieldofresearchOther information and computing sciences not elsewhere classified
dc.subject.fieldofresearchcode469999
dc.titleFeedback modulated attention within a predictive framework
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.hasfulltextNo Full Text
gro.griffith.authorThornton, John R.
gro.griffith.authorCowley, Benjamin T.


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