The dynamics of invariant object recognition in the human visual system
The human visual system can rapidly recognize objects despite transformations that alter their appearance. The precise timing of when the brain computes neural representations that are invariant to particular transformations, however, has not been mapped in humans. Here we employ magnetoencephalogra...
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| 格式: | 文件 |
| 语言: | en_US |
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American Physiological Society
2015
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| 在线阅读: | http://hdl.handle.net/1721.1/93890 https://orcid.org/0000-0002-3153-916X https://orcid.org/0000-0002-9255-0151 https://orcid.org/0000-0002-3944-0455 |
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| author | Isik, Leyla Meyers, Ethan M. Leibo, Joel Z. Poggio, Tomaso A. |
| author2 | Massachusetts Institute of Technology. Center for Biological & Computational Learning |
| author_facet | Massachusetts Institute of Technology. Center for Biological & Computational Learning Isik, Leyla Meyers, Ethan M. Leibo, Joel Z. Poggio, Tomaso A. |
| author_sort | Isik, Leyla |
| collection | MIT |
| description | The human visual system can rapidly recognize objects despite transformations that alter their appearance. The precise timing of when the brain computes neural representations that are invariant to particular transformations, however, has not been mapped in humans. Here we employ magnetoencephalography decoding analysis to measure the dynamics of size- and position-invariant visual information development in the ventral visual stream. With this method we can read out the identity of objects beginning as early as 60 ms. Size- and position-invariant visual information appear around 125 ms and 150 ms, respectively, and both develop in stages, with invariance to smaller transformations arising before invariance to larger transformations. Additionally, the magnetoencephalography sensor activity localizes to neural sources that are in the most posterior occipital regions at the early decoding times and then move temporally as invariant information develops. These results provide previously unknown latencies for key stages of human-invariant object recognition, as well as new and compelling evidence for a feed-forward hierarchical model of invariant object recognition where invariance increases at each successive visual area along the ventral stream. |
| first_indexed | 2024-09-23T08:37:07Z |
| format | Article |
| id | mit-1721.1/93890 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:37:07Z |
| publishDate | 2015 |
| publisher | American Physiological Society |
| record_format | dspace |
| spelling | mit-1721.1/938902022-09-23T13:18:27Z The dynamics of invariant object recognition in the human visual system Isik, Leyla Meyers, Ethan M. Leibo, Joel Z. Poggio, Tomaso A. Massachusetts Institute of Technology. Center for Biological & Computational Learning Massachusetts Institute of Technology. Computational and Systems Biology Program Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences McGovern Institute for Brain Research at MIT Poggio, Tomaso A. Isik, Leyla Meyers, Ethan M. Leibo, Joel Z. Poggio, Tomaso A. The human visual system can rapidly recognize objects despite transformations that alter their appearance. The precise timing of when the brain computes neural representations that are invariant to particular transformations, however, has not been mapped in humans. Here we employ magnetoencephalography decoding analysis to measure the dynamics of size- and position-invariant visual information development in the ventral visual stream. With this method we can read out the identity of objects beginning as early as 60 ms. Size- and position-invariant visual information appear around 125 ms and 150 ms, respectively, and both develop in stages, with invariance to smaller transformations arising before invariance to larger transformations. Additionally, the magnetoencephalography sensor activity localizes to neural sources that are in the most posterior occipital regions at the early decoding times and then move temporally as invariant information develops. These results provide previously unknown latencies for key stages of human-invariant object recognition, as well as new and compelling evidence for a feed-forward hierarchical model of invariant object recognition where invariance increases at each successive visual area along the ventral stream. United States. Defense Advanced Research Projects Agency. Information Processing Techniques Office United States. Defense Advanced Research Projects Agency. Defense Sciences Office National Science Foundation (U.S.) (Grant NSF-0640097) National Science Foundation (U.S.) (Grant NSF-0827427) United States. Air Force Office of Scientific Research (Grant FA8650-05-C-7262) Adobe Systems Honda Research Institute USA, Inc. King Abdullah University of Science and Technology NEC Corporation Sony Corporation Eugene McDermott Foundation National Science Foundation (U.S.). Graduate Research Fellowship (Grant 0645960) 2015-02-06T15:38:42Z 2015-02-06T15:38:42Z 2013-10 2013-09 Article http://purl.org/eprint/type/JournalArticle 0022-3077 1522-1598 http://hdl.handle.net/1721.1/93890 Isik, L., E. M. Meyers, J. Z. Leibo, and T. Poggio. “The Dynamics of Invariant Object Recognition in the Human Visual System.” Journal of Neurophysiology 111, no. 1 (October 2, 2013): 91–102. https://orcid.org/0000-0002-3153-916X https://orcid.org/0000-0002-9255-0151 https://orcid.org/0000-0002-3944-0455 en_US http://dx.doi.org/10.1152/jn.00394.2013 Journal of Neurophysiology Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf American Physiological Society Poggio via Courtney Crummett |
| spellingShingle | Isik, Leyla Meyers, Ethan M. Leibo, Joel Z. Poggio, Tomaso A. The dynamics of invariant object recognition in the human visual system |
| title | The dynamics of invariant object recognition in the human visual system |
| title_full | The dynamics of invariant object recognition in the human visual system |
| title_fullStr | The dynamics of invariant object recognition in the human visual system |
| title_full_unstemmed | The dynamics of invariant object recognition in the human visual system |
| title_short | The dynamics of invariant object recognition in the human visual system |
| title_sort | dynamics of invariant object recognition in the human visual system |
| url | http://hdl.handle.net/1721.1/93890 https://orcid.org/0000-0002-3153-916X https://orcid.org/0000-0002-9255-0151 https://orcid.org/0000-0002-3944-0455 |
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