Modeling shape representation in visual cortex area V4
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2006
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| Online Access: | http://hdl.handle.net/1721.1/30367 |
| _version_ | 1811081603230728192 |
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| author | Cadieu, Charles Fredrick |
| author2 | Tomaso Poggio. |
| author_facet | Tomaso Poggio. Cadieu, Charles Fredrick |
| author_sort | Cadieu, Charles Fredrick |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005. |
| first_indexed | 2024-09-23T11:49:24Z |
| format | Thesis |
| id | mit-1721.1/30367 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:49:24Z |
| publishDate | 2006 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/303672019-04-11T01:41:53Z Modeling shape representation in visual cortex area V4 Cadieu, Charles Fredrick Tomaso Poggio. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Includes bibliographical references (p. 85-89). Visual processing in biological systems is classically described as a hierarchy of increasingly sophisticated representations, originating in primary visual cortex (V1), progressing through intermediate area V4, and ascending to inferotemporal cortex. The computational mechanisms that produce representations in intermediate area V4 have remained a mystery. In this thesis I show that the standard model, a quantitative model which extends the classical description of visual processing, provides a computational mechanism capable of reproducing and predicting the responses of neurons in area V4 with a translation invariant combination of V1 responses. Using techniques I have developed, model neurons accurately predict the responses of 8 V4 neurons to within-class stimuli, such as closed contours and gratings, and achieve an average correlation coefficient of 0.77 between predicted responses and measured V4 responses. Furthermore, model neurons fit to a V4 neuron's grating stimulus response, can qualitatively predict the V4 neuron's 2-spot reverse correlation map. These results successfully demonstrate the first attempt to bridge V1 and V4 experimental data, by describing how representation in V4 could emerge from the nonlinear combination of V1 neural responses. by Charles Fredrick Cadieu. M.Eng. 2006-03-21T21:08:58Z 2006-03-21T21:08:58Z 2005 2005 Thesis http://hdl.handle.net/1721.1/30367 62232884 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 89 p. 6101326 bytes 6330172 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Cadieu, Charles Fredrick Modeling shape representation in visual cortex area V4 |
| title | Modeling shape representation in visual cortex area V4 |
| title_full | Modeling shape representation in visual cortex area V4 |
| title_fullStr | Modeling shape representation in visual cortex area V4 |
| title_full_unstemmed | Modeling shape representation in visual cortex area V4 |
| title_short | Modeling shape representation in visual cortex area V4 |
| title_sort | modeling shape representation in visual cortex area v4 |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/30367 |
| work_keys_str_mv | AT cadieucharlesfredrick modelingshaperepresentationinvisualcortexareav4 |