Neuromorphic Implementation of Orientation Hypercolumns

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dc.contributor.authorChoi, Thomas Yu Wing
dc.contributor.authorMerolla, Paul A.
dc.contributor.authorArthur, John V.
dc.contributor.authorBoahen, Kwabena A
dc.contributor.authorShi, Bertram E.
dc.date2023-05-16T22:57:22.000
dc.date.accessioned2023-05-22T12:17:30Z
dc.date.available2023-05-22T12:17:30Z
dc.date.issued2005-06-01
dc.date.submitted2005-11-21T07:27:28-08:00
dc.description.abstractNeurons in the mammalian primary visual cortex are selective along multiple stimulus dimensions, including retinal position, spatial frequency, and orientation. Neurons tuned to different stimulus features but the same retinal position are grouped into retinotopic arrays of hypercolumns. This paper describes a neuromorphic implementation of orientation hypercolumns, which consists of a single silicon retina feeding multiple chips, each of which contains an array of neurons tuned to the same orientation and spatial frequency, but different retinal locations. All chips operate in continuous time, and communicate with each other using spikes transmitted by the address-event representation protocol. This system is modular in the sense that orientation coverage can be increased simply by adding more chips, and expandable in the sense that its output can be used to construct neurons tuned to other stimulus dimensions. We present measured results from the system, demonstrating neuronal selectivity along position, spatial frequency and orientation. We also demonstrate that the system supports recurrent feedback between neurons within one hypercolumn, even though they reside on different chips. The measured results from the system are in excellent concordance with theoretical predictions.
dc.description.commentsCopyright 2005 IEEE. Reprinted from IEEE Transactions on Circuits and Systems--I: Regular Papers, Volume 52, Issue 6, June 2005, pages 1049-1060. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/2941
dc.legacy.articleid1074
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1074&context=be_papers&unstamped=1
dc.source.issue62
dc.source.journalDepartmental Papers (BE)
dc.source.peerreviewedtrue
dc.source.statuspublished
dc.subject.otherAddress-event representation (AER)
dc.subject.otherGabor filter
dc.subject.otherimage processing
dc.subject.othermixed analog-digital integrated circuits
dc.subject.otherneural chips
dc.subject.otherneuromorphic engineering
dc.subject.othervisual cortex
dc.titleNeuromorphic Implementation of Orientation Hypercolumns
dc.typeArticle
digcom.contributor.authorChoi, Thomas Yu Wing
digcom.contributor.authorMerolla, Paul A.
digcom.contributor.authorArthur, John V.
digcom.contributor.authorisAuthorOfPublication|email:boahen@seas.upenn.edu|institution:University of Pennsylvania|Boahen, Kwabena A
digcom.contributor.authorShi, Bertram E.
digcom.identifierbe_papers/62
digcom.identifier.contextkey118769
digcom.identifier.submissionpathbe_papers/62
digcom.typearticle
dspace.entity.typePublication
relation.isAuthorOfPublication93e1cefd-0e80-4a17-92e2-4fc25cb0e18a
relation.isAuthorOfPublication93e1cefd-0e80-4a17-92e2-4fc25cb0e18a
relation.isAuthorOfPublication.latestForDiscovery93e1cefd-0e80-4a17-92e2-4fc25cb0e18a
upenn.schoolDepartmentCenterDepartmental Papers (BE)
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