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首页> 外文期刊>NeuroImage >Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a 'face' area?
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Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a 'face' area?

机译:腹颞叶的组合码用于物体识别:Haxby(2001)重新研究:是否存在“面部”区域?

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摘要

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.
机译:Haxby等。 [Science 293(2001)2425]最近指出,视觉对象识别过程中腹颞叶(VT)的类别相关响应是重叠的,并且分布在地形图中。该观察结果与普遍的观点形成了鲜明的对比,后者认为目标代码集中于并定位于梭形和海马旁回旋肌等特定区域。我们使用神经网络(NN)分类器提供了Haxby假设的关键检验,该分类器可以检测更一般的地形表示形式,并在样本外测试中对体素响应模式实现83%的正确泛化性能。使用体素敏感度分析,我们显示出基本上相同的VT瓣体素对所有对象类别的分类都起作用,这表明代码是组合的。此外,我们没有发现本地单一类别表示形式的证据。体素代码的神经网络表示对类别和上级功能都很敏感,这些功能仅在对象类别中隐式可用。

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