Li Z
Gatsby Computational Neuroscience Unit, University College London, UK.
Network. 1999 May;10(2):187-212.
Stimuli outside classical receptive fields have been shown to exert a significant influence over the activities of neurons in the primary visual cortex. We propose that contextual influences are used for pre-attentive visual segmentation. The difference between contextual influences near and far from region boundaries makes neural activities near region boundaries higher than elsewhere, making boundaries more salient for perceptual pop-out. The cortex thus computes global region boundaries by detecting the breakdown of homogeneity or translation invariance in the input, using local intra-cortical interactions mediated by the horizontal connections. This proposal is implemented in a biologically based model of V1, and demonstrated using examples of texture segmentation and figure-ground segregation. The model is also the first that performs texture or region segmentation in exactly the same neural circuit that solves the dual problem of the enhancement of contours, as is suggested by experimental observations. The computational framework in this model is simpler than previous approaches, making it implementable by V1 mechanisms, though higher-level visual mechanisms are needed to refine its output. However, it easily handles a class of segmentation problems that are known to be tricky. Its behaviour is compared with psycho-physical and physiological data on segmentation, contour enhancement, contextual influences and other phenomena such as asymmetry in visual search.
经典感受野之外的刺激已被证明对初级视觉皮层中神经元的活动有显著影响。我们提出，上下文影响被用于前注意视觉分割。靠近和远离区域边界的上下文影响之间的差异使得区域边界附近的神经活动高于其他地方，从而使边界在感知突显方面更加显著。因此，皮层通过检测输入中同质性或平移不变性的破坏，并利用由水平连接介导的局部皮层内相互作用来计算全局区域边界。这一观点在基于生物学的V1模型中得以实现，并通过纹理分割和图形-背景分离的例子进行了演示。该模型也是第一个在解决轮廓增强这一双重问题的同一神经回路中执行纹理或区域分割的模型，正如实验观察所表明的那样。该模型中的计算框架比以前的方法更简单，虽然需要更高层次的视觉机制来完善其输出，但它可以通过V1机制来实现。然而，它能够轻松处理一类已知棘手的分割问题。其行为与关于分割、轮廓增强、上下文影响以及其他现象（如视觉搜索中的不对称性）的心理物理学和生理学数据进行了比较。
