In this work we show how to construct connectivity kernels induced by the receptive profiles of simple cells of the primary visual cortex (V1). These kernels are directly defined by the shape of such profiles: this provides a metric model for the functional architecture of V1, whose global geometry is determined by the reciprocal interactions between local elements. Our construction adapts to any bank of filters chosen to represent a set of receptive profiles, since it does not require any structure on the parameterization of the family. The connectivity kernel that we define carries a geometrical structure consistent with the well-known properties of long-range horizontal connections in V1, and it is compatible with the perceptual rules synthesized by the concept of association field. These characteristics are still present when the kernel is constructed from a bank of filters arising from an unsupervised learning algorithm.

中文翻译：

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从接受档案到V1的度量模型。

在这项工作中，我们展示了如何构建由主要视觉皮层（V1）的简单细胞的接受型态诱导的连通性内核。这些内核由此类轮廓的形状直接定义：这为V1的功能体系结构提供了度量模型，其整体几何结构由局部元素之间的交互作用确定。我们的构造适用于选择来代表一组接收轮廓的任何一组滤波器，因为它不需要该族的参数化任何结构。我们定义的连通性内核具有与V1中远程水平连接的众所周知的属性一致的几何结构，并且与关联字段的概念合成的感知规则兼容。