Jehee Janneke F M, Roelfsema Pieter R, Deco Gustavo, Murre Jaap M J, Lamme Victor A F
University of Amsterdam, Department of Psychology, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands.
Brain Res. 2007 Jul 9;1157:167-76. doi: 10.1016/j.brainres.2007.03.090. Epub 2007 Apr 12.
Recent theories of visual perception propose that feedforward cortical processing enables rapid and automatic object categorizations, yet incorporates a limited amount of detail. Subsequent feedback processing highlights high-resolution representations in early visual areas and provides spatial detail. To verify this hypothesis, we separate the contributions of feedforward and feedback signals to the selectivity of cortical neurons in a neural network simulation that is modeled after the hierarchical feedforward-feedback organization of cortical areas. We find that in such a network the responses of high-level neurons can initially distinguish between low-resolution aspects of objects but are 'blind' to differences in detail. After several feedback-feedforward cycles of processing, however, they can also distinguish between objects that differ in detail. Moreover, we find that our model captures recent paradoxical results of crowding phenomena, showing that spatial detail that is lost in visual crowding is nevertheless able to evoke specific adaptation effects. Our results thus provide an existence proof of the feasibility of novel theoretical models and provide a mechanism to explain various psychophysical and physiological results.
近期的视觉感知理论提出，前馈皮层处理能够实现快速且自动的物体分类，但包含的细节有限。随后的反馈处理突出了早期视觉区域中的高分辨率表征，并提供空间细节。为了验证这一假设，我们在一个基于皮层区域分层前馈-反馈组织建模的神经网络模拟中，分离了前馈和反馈信号对皮层神经元选择性的贡献。我们发现，在这样的网络中，高级神经元的反应最初能够区分物体的低分辨率特征，但对细节差异“视而不见”。然而，经过几个反馈-前馈处理循环后，它们也能够区分在细节上不同的物体。此外，我们发现我们的模型捕捉到了近期拥挤现象的矛盾结果，表明在视觉拥挤中丢失的空间细节仍然能够引发特定的适应效应。因此，我们的结果为新型理论模型的可行性提供了存在性证明，并提供了一种机制来解释各种心理物理学和生理学结果。
