Touryan Jon, Felsen Gidon, Dan Yang
Group in Vision Science, School of Optometry, University of California, Berkeley, CA 94720, USA.
Neuron. 2005 Mar 3;45(5):781-91. doi: 10.1016/j.neuron.2005.01.029.
Neuronal receptive fields (RFs) play crucial roles in visual processing. While the linear RFs of early neurons have been well studied, RFs of cortical complex cells are nonlinear and therefore difficult to characterize, especially in the context of natural stimuli. In this study, we used a nonlinear technique to compute the RFs of complex cells from their responses to natural images. We found that each RF is well described by a small number of subunits, which are oriented, localized, and bandpass. These subunits contribute to neuronal responses in a contrast-dependent, polarity-invariant manner, and they can largely predict the orientation and spatial frequency tuning of the cell. Although the RF structures measured with natural images were similar to those measured with random stimuli, natural images were more effective for driving complex cells, thus facilitating rapid identification of the subunits. The subunit RF model provides a useful basis for understanding cortical processing of natural stimuli.
神经元感受野（RFs）在视觉处理中起着至关重要的作用。虽然早期神经元的线性感受野已得到充分研究，但皮层复杂细胞的感受野是非线性的，因此难以表征，尤其是在自然刺激的背景下。在本研究中，我们使用一种非线性技术，根据复杂细胞对自然图像的反应来计算其感受野。我们发现，每个感受野都可以由少量亚单位很好地描述，这些亚单位具有方向性、局部性且为带通型。这些亚单位以对比度依赖、极性不变的方式对神经元反应做出贡献，并且它们在很大程度上可以预测细胞的方向和空间频率调谐。尽管用自然图像测量的感受野结构与用随机刺激测量的相似，但自然图像对驱动复杂细胞更有效，从而有助于快速识别亚单位。亚单位感受野模型为理解皮层对自然刺激的处理提供了有用的基础。
