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dc.contributor.authorSherbakov, Lenaen_US
dc.contributor.authorYazdanbakhsh, Arashen_US
dc.date.accessioned2019-02-25T16:11:19Z
dc.date.available2019-02-25T16:11:19Z
dc.date.issued2013-01-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000326618300018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationLena Sherbakov, Arash Yazdanbakhsh. 2013. "Multiscale sampling model for motion integration." JOURNAL OF VISION, Volume 13, Issue 11, pp. ? - ? (14). https://doi.org/10.1167/13.11.18
dc.identifier.issn1534-7362
dc.identifier.urihttps://hdl.handle.net/2144/33619
dc.description.abstractBiologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.en_US
dc.description.sponsorshipThis work was supported in part by CELEST, a National Science Foundation Science of Learning Center; NSF SBE-0354378 and OMA-0835976; ONR (N00014-11-1-0535); and AFOSR (FA9550-12-1-0436). (CELEST, a National Science Foundation Science of Learning Center; SBE-0354378 - NSF; OMA-0835976 - NSF; N00014-11-1-0535 - ONR; FA9550-12-1-0436 - AFOSR)en_US
dc.format.extent14 p.en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherAssoc Research Vision Ophthalmology Incen_US
dc.relation.ispartofJOURNAL OF VISION
dc.subjectScience & technologyen_US
dc.subjectLife sciences & biomedicineen_US
dc.subjectOphthalmologyen_US
dc.subjectAperture problemen_US
dc.subjectMotion integrationen_US
dc.subjectReceptive fielden_US
dc.subjectLGNen_US
dc.subjectV1en_US
dc.subjectInterareal connectionsen_US
dc.subjectIntra-areal connectionsen_US
dc.subjectMonkey visual-cortexen_US
dc.subjectArea MTen_US
dc.subjectInterlaminar connectionsen_US
dc.subjectOrientation selectivityen_US
dc.subjectNeural dynamicsen_US
dc.subjectStriate cortexen_US
dc.subjectUnified modelen_US
dc.subjectOptical-flowen_US
dc.subjectMacaqueen_US
dc.subjectComputer simulationen_US
dc.subjectFeedbacken_US
dc.subjectHumansen_US
dc.subjectInterneuronsen_US
dc.subjectNeuronsen_US
dc.subjectPattern recognition, visualen_US
dc.subjectSynapsesen_US
dc.subjectVisual cortexen_US
dc.subjectVisual pathwaysen_US
dc.subjectMedical and health sciencesen_US
dc.subjectPsychology and cognitive sciencesen_US
dc.subjectExperimental psychologyen_US
dc.titleMultiscale sampling model for motion integrationen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1167/13.11.18
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Psychological & Brain Sciencesen_US
pubs.publication-statusPublisheden_US


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