Evaluation of a shape-based model of human face discrimination using fMRI and behavioral techniques
Evaluation of a shape-based model of human face discrimination using fMRI and behavioral techniques
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DOI：
10.1016/j.neuron.2006.03.012
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发表时间：
2006-04-06
期刊：
影响因子：
16.2
通讯作者：
Riesenhuber, M
中科院分区：
文献类型：
--
作者：
Jiang, X;Rosen, E;Riesenhuber, M
了解物体识别背后的神经机制是视觉神经科学的基本挑战之一。虽然神经生理学实验为基于日益复杂的图像特征层次结构的“从简单到复杂”的处理模型提供了证据，但面部处理的行为和功能磁共振成像研究被解释为与这种解释不相容。我们提出了一种神经生理学上合理的、基于特征的模型，该模型定量地解释了面部辨别特征，包括面部反转和“配置”效应。该模型预测面部识别基于针对面部形状选择性的单元的稀疏表示，而不需要假设额外的“面部特定”机制。我们推导并测试了将模型 FFA 面部神经元调整、在 fMRI 快速适应范式中测量的神经适应以及面部辨别性能定量联系起来的预测。实验数据与模型预测非常一致，即当面孔变得足够不同以激活不同的神经元群体时，辨别能力应该渐近。
Understanding the neural mechanisms underlying object recognition is one of the fundamental challenges of visual neuroscience. While neurophysiology experiments have provided evidence for a "simple-to-complex" processing model based on a hierarchy of increasingly complex image features, behavioral and fMRI studies of face processing have been interpreted as incompatible with this account. We present a neurophysiologically plausible, feature-based model that quantitatively accounts for face discrimination characteristics, including face inversion and "configural" effects. The model predicts that face discrimination is based on a sparse representation of units selective for face shapes, without the need to postulate additional, "face-specific" mechanisms. We derive and test predictions that quantitatively link model FFA face neuron tuning, neural adaptation measured in an fMRI rapid adaptation paradigm, and face discrimination performance. The experimental data are in excellent agreement with the model prediction that discrimination performance should asymptote as faces become dissimilar enough to activate different neuronal populations.