O'Toole Alice J, Jiang Fang, Abdi Hervé, Haxby James V
School of Behavioral and Brain Sciences, The University of Texas, Richardson, TX 75083-0688, USA.
J Cogn Neurosci. 2005 Apr;17(4):580-90. doi: 10.1162/0898929053467550.
Object and face representations in ventral temporal (VT) cortex were investigated by combining object confusability data from a computational model of object classification with neural response confusability data from a functional neuroimaging experiment. A pattern-based classification algorithm learned to categorize individual brain maps according to the object category being viewed by the subject. An identical algorithm learned to classify an image-based, view-dependent representation of the stimuli. High correlations were found between the confusability of object categories and the confusability of brain activity maps. This occurred even with the inclusion of multiple views of objects, and when the object classification model was tested with high spatial frequency "line drawings" of the stimuli. Consistent with a distributed representation of objects in VT cortex, the data indicate that object categories with shared image-based attributes have shared neural structure.
通过将来自物体分类计算模型的物体混淆性数据与来自功能性神经成像实验的神经反应混淆性数据相结合，对腹侧颞叶（VT）皮层中的物体和面孔表征进行了研究。一种基于模式的分类算法学会了根据受试者正在观看的物体类别对个体脑图谱进行分类。一种相同的算法学会了对基于图像的、依赖视图的刺激表征进行分类。在物体类别的混淆性与脑活动图谱的混淆性之间发现了高度相关性。即使纳入了物体的多个视图，以及当用刺激的高空间频率“线条图”测试物体分类模型时，这种情况依然出现。与VT皮层中物体的分布式表征一致，数据表明具有共享的基于图像属性的物体类别具有共享的神经结构。
