Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities
The question of how shape is represented is of central interest to understanding visual processing in cortex. While tuning properties of the cells in early part of the ventral visual stream, thought to be responsible for object recognition in the primate, are comparatively well understood, several d...
| Main Authors: | , |
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| Language: | en_US |
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2005
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| Online Access: | http://hdl.handle.net/1721.1/30424 |
| _version_ | 1826195888260775936 |
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| author | Kouh, Minjoon Riesenhuber, Maximilian |
| author_facet | Kouh, Minjoon Riesenhuber, Maximilian |
| author_sort | Kouh, Minjoon |
| collection | MIT |
| description | The question of how shape is represented is of central interest to understanding visual processing in cortex. While tuning properties of the cells in early part of the ventral visual stream, thought to be responsible for object recognition in the primate, are comparatively well understood, several different theories have been proposed regarding tuning in higher visual areas, such as V4. We used the model of object recognition in cortex presented by Riesenhuber and Poggio (1999), where more complex shape tuning in higher layers is the result of combining afferent inputs tuned to simpler features, and compared the tuning properties of model units in intermediate layers to those of V4 neurons from the literature. In particular, we investigated the issue of shape representation in visual area V1 and V4 using oriented bars and various types of gratings (polar, hyperbolic, and Cartesian), as used in several physiology experiments. Our computational model was able to reproduce several physiological findings, such as the broadening distribution of the orientation bandwidths and the emergence of a bias toward non-Cartesian stimuli. Interestingly, the simulation results suggest that some V4 neurons receive input from afferents with spatially separated receptive fields, leading to experimentally testable predictions. However, the simulations also show that the stimulus set of Cartesian and non-Cartesian gratings is not sufficiently complex to probe shape tuning in higher areas, necessitating the use of more complex stimulus sets. |
| first_indexed | 2024-09-23T10:16:59Z |
| id | mit-1721.1/30424 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:16:59Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | mit-1721.1/304242019-04-12T08:26:05Z Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities Kouh, Minjoon Riesenhuber, Maximilian AI Shape Tuning Shape Representation Features HMAX Visual Cortex Gratings V4 The question of how shape is represented is of central interest to understanding visual processing in cortex. While tuning properties of the cells in early part of the ventral visual stream, thought to be responsible for object recognition in the primate, are comparatively well understood, several different theories have been proposed regarding tuning in higher visual areas, such as V4. We used the model of object recognition in cortex presented by Riesenhuber and Poggio (1999), where more complex shape tuning in higher layers is the result of combining afferent inputs tuned to simpler features, and compared the tuning properties of model units in intermediate layers to those of V4 neurons from the literature. In particular, we investigated the issue of shape representation in visual area V1 and V4 using oriented bars and various types of gratings (polar, hyperbolic, and Cartesian), as used in several physiology experiments. Our computational model was able to reproduce several physiological findings, such as the broadening distribution of the orientation bandwidths and the emergence of a bias toward non-Cartesian stimuli. Interestingly, the simulation results suggest that some V4 neurons receive input from afferents with spatially separated receptive fields, leading to experimentally testable predictions. However, the simulations also show that the stimulus set of Cartesian and non-Cartesian gratings is not sufficiently complex to probe shape tuning in higher areas, necessitating the use of more complex stimulus sets. 2005-12-20T22:01:32Z 2005-12-20T22:01:32Z 2003-09-08 MIT-CSAIL-TR-2003-019 AIM-2003-021 CBCL-231 http://hdl.handle.net/1721.1/30424 en_US Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory 14 p. 20150764 bytes 1258167 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | AI Shape Tuning Shape Representation Features HMAX Visual Cortex Gratings V4 Kouh, Minjoon Riesenhuber, Maximilian Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title | Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title_full | Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title_fullStr | Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title_full_unstemmed | Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title_short | Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities |
| title_sort | investigating shape representation in area v4 with hmax orientation and grating selectivities |
| topic | AI Shape Tuning Shape Representation Features HMAX Visual Cortex Gratings V4 |
| url | http://hdl.handle.net/1721.1/30424 |
| work_keys_str_mv | AT kouhminjoon investigatingshaperepresentationinareav4withhmaxorientationandgratingselectivities AT riesenhubermaximilian investigatingshaperepresentationinareav4withhmaxorientationandgratingselectivities |