Disambiguating Visual Motion Through Contextual Feedback Modulation.
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| Title: | Disambiguating Visual Motion Through Contextual Feedback Modulation. |
|---|---|
| Authors: | Bayerl, Pierre, Neumann, Heiko, Simoncelli, Communicated by Eero |
| Source: | Neural Computation. Oct2004, Vol. 16 Issue 10, p2041-2066. 26p. |
| Subjects: | Brain -- Mathematical models, Neuroinformatics, Computational mathematics, Mathematical analysis, Mathematical models, Neurons |
| Abstract: | Motion of an extended boundary can be measured locally by neurons only orthogonal to its orientation (aperture problem) while this ambiguity is resolved for localized image features, such as corners or nonocclusion junctions. The integration of local motion signals sampled along the outline of a moving form reveals the object velocity. We propose a new model of V1-MT feedforward and feedback processing in which localized V1 motion signals are integrated along the feedforward path by model MT cells. Top-down feedback from MT cells in turn emphasizes model V1 motion activities of matching velocity by excitatory modulation and thus realizes an attentional gating mechanism. The model dynamics implement a guided filling-in process to disambiguate motion signals through biased on-center, off-surround competition. Our model makes predictions concerning the time course of cells in area MT and V1 and the disambiguation process of activity patterns in these areas and serves as a means to link physiological mechanisms with perceptual behavior. We further demonstrate that our model also successfully processes natural image sequences. [ABSTRACT FROM AUTHOR] |
| Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 14222824 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Disambiguating Visual Motion Through Contextual Feedback Modulation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bayerl%2C+Pierre%22">Bayerl, Pierre</searchLink><br /><searchLink fieldCode="AR" term="%22Neumann%2C+Heiko%22">Neumann, Heiko</searchLink><br /><searchLink fieldCode="AR" term="%22Simoncelli%2C+Communicated+by+Eero%22">Simoncelli, Communicated by Eero</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Neural+Computation%22">Neural Computation</searchLink>. Oct2004, Vol. 16 Issue 10, p2041-2066. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Brain+--+Mathematical+models%22">Brain -- Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Neuroinformatics%22">Neuroinformatics</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+mathematics%22">Computational mathematics</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Neurons%22">Neurons</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Motion of an extended boundary can be measured locally by neurons only orthogonal to its orientation (aperture problem) while this ambiguity is resolved for localized image features, such as corners or nonocclusion junctions. The integration of local motion signals sampled along the outline of a moving form reveals the object velocity. We propose a new model of V1-MT feedforward and feedback processing in which localized V1 motion signals are integrated along the feedforward path by model MT cells. Top-down feedback from MT cells in turn emphasizes model V1 motion activities of matching velocity by excitatory modulation and thus realizes an attentional gating mechanism. The model dynamics implement a guided filling-in process to disambiguate motion signals through biased on-center, off-surround competition. Our model makes predictions concerning the time course of cells in area MT and V1 and the disambiguation process of activity patterns in these areas and serves as a means to link physiological mechanisms with perceptual behavior. We further demonstrate that our model also successfully processes natural image sequences. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=14222824 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1162/0899766041732404 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 2041 Subjects: – SubjectFull: Brain -- Mathematical models Type: general – SubjectFull: Neuroinformatics Type: general – SubjectFull: Computational mathematics Type: general – SubjectFull: Mathematical analysis Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Neurons Type: general Titles: – TitleFull: Disambiguating Visual Motion Through Contextual Feedback Modulation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bayerl, Pierre – PersonEntity: Name: NameFull: Neumann, Heiko – PersonEntity: Name: NameFull: Simoncelli, Communicated by Eero IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2004 Type: published Y: 2004 Identifiers: – Type: issn-print Value: 08997667 Numbering: – Type: volume Value: 16 – Type: issue Value: 10 Titles: – TitleFull: Neural Computation Type: main |
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