Neumann H, Sepp W
Universität Ulm, Abt. Neuroinformatik, D-89069 Ulm, Germany.
Biol Cybern. 1999 Nov;81(5-6):425-44. doi: 10.1007/s004220050573.
A majority of cortical areas are connected via feedforward and feedback fiber projections. In feedforward pathways we mainly observe stages of feature detection and integration. The computational role of the descending pathways at different stages of processing remains mainly unknown. Based on empirical findings we suggest that the top-down feedback pathways subserve a context-dependent gain control mechanism. We propose a new computational model for recurrent contour processing in which normalized activities of orientation selective contrast cells are fed forward to the next processing stage. There, the arrangement of input activation is matched against local patterns of contour shape. The resulting activities are subsequently fed back to the previous stage to locally enhance those initial measurements that are consistent with the top-down generated responses. In all, we suggest a computational theory for recurrent processing in the visual cortex in which the significance of local measurements is evaluated on the basis of a broader visual context that is represented in terms of contour code patterns. The model serves as a framework to link physiological with perceptual data gathered in psychophysical experiments. It handles a variety of perceptual phenomena, such as the local grouping of fragmented shape outline, texture surround and density effects, and the interpolation of illusory contours.
大多数皮质区域通过前馈和反馈纤维投射相互连接。在前馈通路中，我们主要观察到特征检测和整合阶段。下行通路在不同处理阶段的计算作用仍然主要未知。基于实证研究结果，我们认为自上而下的反馈通路有助于一种依赖于上下文的增益控制机制。我们提出了一种用于循环轮廓处理的新计算模型，其中方向选择性对比细胞的归一化活动被前馈到下一个处理阶段。在那里，输入激活的排列与轮廓形状的局部模式进行匹配。由此产生的活动随后被反馈到前一阶段，以局部增强那些与自上而下生成的响应一致的初始测量值。总之，我们提出了一种视觉皮质循环处理的计算理论，其中局部测量的重要性是基于以轮廓编码模式表示的更广泛视觉上下文来评估的。该模型作为一个框架，将生理数据与在心理物理学实验中收集的感知数据联系起来。它处理各种感知现象，例如碎片化形状轮廓的局部分组、纹理环绕和密度效应，以及虚幻轮廓的插值。
