Hanson Stephen José, Matsuka Toshihiko, Haxby James V
Rutgers University, Newark, NJ 07102, USA.
Neuroimage. 2004 Sep;23(1):156-66. doi: 10.1016/j.neuroimage.2004.05.020.
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.
哈克斯比等人[《科学》293卷（2001年）第2425页]最近提出，在视觉物体识别过程中，腹侧颞叶（VT）的类别相关反应相互重叠且呈拓扑分布。这一观察结果与普遍观点形成对比，普遍观点认为物体编码是局部的，局限于特定区域，如梭状回和海马旁回。我们使用神经网络（NN）分类器对哈克斯比的假设进行了关键测试，该分类器能够检测更一般的拓扑表示，并在样本外测试中对体素反应模式实现了83%的正确泛化性能。通过体素敏感性分析，我们表明基本上相同的VT叶体素对所有物体类别的分类都有贡献，这表明编码是组合式的。此外，我们没有发现局部单类别表示的证据。体素编码的神经网络表示对类别和上位水平特征都敏感，而这些特征在物体类别中只是隐含存在的。
