View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation.
View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation.
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DOI：
10.1016/j.cub.2016.10.015
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发表时间：
2017-01-09
期刊：
影响因子：
--
通讯作者：
Poggio T
中科院分区：
文献类型：
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作者：
Leibo JZ;Liao Q;Anselmi F;Freiwald WA;Poggio T
灵长类动物的大脑包含一个视觉区域的层次结构，被称为腹侧流，它可以快速计算对象表征，这些表征既针对对象身份，又对深度旋转等身份保持变换具有鲁棒性。当前的对象识别计算模型，包括最近的深度学习网络，通过交替增加选择性的过滤和增加容忍度的池化操作的层次结构来生成这些属性，类似于简单-复杂的细胞操作。在这里，我们证明了一类层次结构和一组广泛的生物学上合理的学习规则产生近似不变性，以保持身份的处理层次结构的顶层转换。然而，所有过去的模型测试未能再现最显着的属性的中间表示的三个层次的脸处理层次的大脑：镜像对称调谐到头部方向。在这里，我们证明了一个特定的生物合理的赫布型学习规则产生镜像对称的调整，双边对称的刺激，如面对中间层次的架构，并显示为什么它这样做。因此，视觉流中单个细胞的调谐特性似乎是它们编码的刺激的群体特性的结果，并反映了塑造它们所在的信息处理系统的学习规则。
The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside.