Object recognition relies on a series of transformations among which only the first cortical stage is relatively well understood. Already at the second stage, the visual area V2, the complexity of the transformation precludes a clear understanding of what specifically this area computes. Previous work has found multiple types of V2 neurons, with neurons of each type selective for multi-edge features. Here we analyse responses of V2 neurons to natural stimuli and find three organizing principles. First, the relevant edges for V2 neurons can be grouped into quadrature pairs, indicating invariance to local translation. Second, the excitatory edges have nearby suppressive edges with orthogonal orientations. Third, the resulting multi-edge patterns are repeated in space to form textures or texture boundaries. The cross-orientation suppression increases the sparseness of responses to natural images based on these complex forms of feature selectivity while allowing for multiple scales of position invariance.

译文

:对象识别依赖于一系列转换,其中只有第一个皮质阶段才被相对较好地理解。在第二阶段,即可视区域V2中,转换的复杂性使得无法清楚地了解此区域的具体计算方式。先前的工作发现了多种类型的V2神经元,每种类型的神经元对多边缘特征具有选择性。在这里,我们分析了V2神经元对自然刺激的反应,并发现了三个组织原则。首先,可以将V2神经元的相关边缘分组为正交对,表明本地翻译的不变性。其次,兴奋性边缘具有附近的正交方向的抑制性边缘。第三,所得的多边缘图案在空间中重复以形成纹理或纹理边界。交叉定向抑制基于这些复杂的特征选择性形式,增加了对自然图像响应的稀疏性,同时允许多个尺度的位置不变性。

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