Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex
We easily recognize objects and faces across a myriad of retinal images produced by each object. One hypothesis is that this tolerance (a.k.a. “invariance”) is learned by relying on the fact that object identities are temporally stable. While we previously found neuronal evidence supporting this ide...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Elsevier
2015
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| Online Access: | http://hdl.handle.net/1721.1/96054 https://orcid.org/0000-0002-1592-5896 |
| _version_ | 1826203129336561664 |
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| author | Li, Nuo DiCarlo, James |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Li, Nuo DiCarlo, James |
| author_sort | Li, Nuo |
| collection | MIT |
| description | We easily recognize objects and faces across a myriad of retinal images produced by each object. One hypothesis is that this tolerance (a.k.a. “invariance”) is learned by relying on the fact that object identities are temporally stable. While we previously found neuronal evidence supporting this idea at the top of the nonhuman primate ventral visual stream (inferior temporal cortex, or IT), we here test if this is a general tolerance learning mechanism. First, we found that the same type of unsupervised experience that reshaped IT position tolerance also predictably reshaped IT size tolerance, and the magnitude of reshaping was quantitatively similar. Second, this tolerance reshaping can be induced under naturally occurring dynamic visual experience, even without eye movements. Third, unsupervised temporal contiguous experience can build new neuronal tolerance. These results suggest that the ventral visual stream uses a general unsupervised tolerance learning algorithm to build its invariant object representation. |
| first_indexed | 2024-09-23T12:32:06Z |
| format | Article |
| id | mit-1721.1/96054 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:32:06Z |
| publishDate | 2015 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/960542022-10-01T09:35:52Z Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex Li, Nuo DiCarlo, James Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences McGovern Institute for Brain Research at MIT DiCarlo, James Li, Nuo We easily recognize objects and faces across a myriad of retinal images produced by each object. One hypothesis is that this tolerance (a.k.a. “invariance”) is learned by relying on the fact that object identities are temporally stable. While we previously found neuronal evidence supporting this idea at the top of the nonhuman primate ventral visual stream (inferior temporal cortex, or IT), we here test if this is a general tolerance learning mechanism. First, we found that the same type of unsupervised experience that reshaped IT position tolerance also predictably reshaped IT size tolerance, and the magnitude of reshaping was quantitatively similar. Second, this tolerance reshaping can be induced under naturally occurring dynamic visual experience, even without eye movements. Third, unsupervised temporal contiguous experience can build new neuronal tolerance. These results suggest that the ventral visual stream uses a general unsupervised tolerance learning algorithm to build its invariant object representation. National Institutes of Health (U.S.) (Grant R01-EY014970) United States. American Recovery and Reinvestment Act of 2009 (NRSA 1F31EY020057) McKnight Endowment Fund for Neuroscience 2015-03-17T18:51:27Z 2015-03-17T18:51:27Z 2010-09 2010-08 Article http://purl.org/eprint/type/JournalArticle 08966273 1097-4199 http://hdl.handle.net/1721.1/96054 Li, Nuo, and James J. DiCarlo. “Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex.” Neuron 67, no. 6 (September 23, 2010): 1062–1075. © 2010 Elsevier Inc. https://orcid.org/0000-0002-1592-5896 en_US http://dx.doi.org/10.1016/j.neuron.2010.08.029 Neuron Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Elsevier Elsevier |
| spellingShingle | Li, Nuo DiCarlo, James Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title | Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title_full | Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title_fullStr | Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title_full_unstemmed | Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title_short | Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex |
| title_sort | unsupervised natural visual experience rapidly reshapes size invariant object representation in inferior temporal cortex |
| url | http://hdl.handle.net/1721.1/96054 https://orcid.org/0000-0002-1592-5896 |
| work_keys_str_mv | AT linuo unsupervisednaturalvisualexperiencerapidlyreshapessizeinvariantobjectrepresentationininferiortemporalcortex AT dicarlojames unsupervisednaturalvisualexperiencerapidlyreshapessizeinvariantobjectrepresentationininferiortemporalcortex |