Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face” area?
Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to s...
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| Published in | NeuroImage (Orlando, Fla.) Vol. 23; no. 1; pp. 156 - 166 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
01.09.2004
Elsevier Limited |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-8119 1095-9572 |
| DOI | 10.1016/j.neuroimage.2004.05.020 |
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| Abstract | Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to specific areas such as the fusiform and parahippocampal gyri. We provide a critical test of Haxby's hypothesis using a neural network (NN) classifier that can detect more general topographic representations and achieves 83% correct generalization performance on patterns of voxel responses in out-of-sample tests. Using voxel-wise sensitivity analysis we show that substantially the same VT lobe voxels contribute to the classification of all object categories, suggesting the code is combinatorial. Moreover, we found no evidence for local single category representations. The neural network representations of the voxel codes were sensitive to both category and superordinate level features that were only available implicitly in the object categories. |
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| AbstractList | Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to specific areas such as the fusiform and parahippocampal gyri. We provide a critical test of Haxby's hypothesis using a neural network (NN) classifier that can detect more general topographic representations and achieves 83% correct generalization performance on patterns of voxel responses in out-of-sample tests. Using voxel-wise sensitivity analysis we show that substantially the same VT lobe voxels contribute to the classification of all object categories, suggesting the code is combinatorial. Moreover, we found no evidence for local single category representations. The neural network representations of the voxel codes were sensitive to both category and superordinate level features that were only available implicitly in the object categories. Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to specific areas such as the fusiform and parahippocampal gyri. We provide a critical test of Haxby's hypothesis using a neural network (NN) classifier that can detect more general topographic representations and achieves 83% correct generalization performance on patterns of voxel responses in out-of-sample tests. Using voxel-wise sensitivity analysis we show that substantially the same VT lobe voxels contribute to the classification of all object categories, suggesting the code is combinatorial. Moreover, we found no evidence for local single category representations. The neural network representations of the voxel codes were sensitive to both category and superordinate level features that were only available implicitly in the object categories.Haxby et al. [Science 293 (2001) 2425] recently argued that category-related responses in the ventral temporal (VT) lobe during visual object identification were overlapping and distributed in topography. This observation contrasts with prevailing views that object codes are focal and localized to specific areas such as the fusiform and parahippocampal gyri. We provide a critical test of Haxby's hypothesis using a neural network (NN) classifier that can detect more general topographic representations and achieves 83% correct generalization performance on patterns of voxel responses in out-of-sample tests. Using voxel-wise sensitivity analysis we show that substantially the same VT lobe voxels contribute to the classification of all object categories, suggesting the code is combinatorial. Moreover, we found no evidence for local single category representations. The neural network representations of the voxel codes were sensitive to both category and superordinate level features that were only available implicitly in the object categories. |
| Author | Hanson, Stephen José Matsuka, Toshihiko Haxby, James V. |
| Author_xml | – sequence: 1 givenname: Stephen José surname: Hanson fullname: Hanson, Stephen José email: jose@psychology.rutgers.edu organization: Rutgers University, Newark, NJ 07102, USA – sequence: 2 givenname: Toshihiko surname: Matsuka fullname: Matsuka, Toshihiko organization: Rutgers University, Newark, NJ 07102, USA – sequence: 3 givenname: James V. surname: Haxby fullname: Haxby, James V. organization: Princeton University, Princeton, NJ 08540, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/15325362$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Adult Brain Mapping Codes Combinatorial codes Discriminant analysis Discrimination Learning - physiology Humans Image Processing, Computer-Assisted - statistics & numerical data Logistics Magnetic Resonance Imaging - statistics & numerical data Mathematical Computing Medical imaging Nerve Net - physiology Neural networks Neural Networks (Computer) Object recognition Occipital Lobe - physiology Orientation - physiology Oxygen Consumption - physiology Parahippocampal Gyrus - physiology Pattern Recognition, Visual - physiology Reference Values Response rates Sensitivity analysis Statistical methods Temporal Lobe - physiology Ventral temporal lobe |
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| Title | Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face” area? |
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