NeuroMathComp Laboratory, INRIA, Sophia Antipolis, CNRS, ENS Paris, Paris, France.
J Math Neurosci. 2011 Jun 6;1(1):4. doi: 10.1186/2190-8567-1-4.
We study the neural field equations introduced by Chossat and Faugeras to model the representation and the processing of image edges and textures in the hypercolumns of the cortical area V1. The key entity, the structure tensor, intrinsically lives in a non-Euclidean, in effect hyperbolic, space. Its spatio-temporal behaviour is governed by nonlinear integro-differential equations defined on the Poincaré disc model of the two-dimensional hyperbolic space. Using methods from the theory of functional analysis we show the existence and uniqueness of a solution of these equations. In the case of stationary, that is, time independent, solutions we perform a stability analysis which yields important results on their behavior. We also present an original study, based on non-Euclidean, hyperbolic, analysis, of a spatially localised bump solution in a limiting case. We illustrate our theoretical results with numerical simulations.Mathematics Subject Classification: 30F45, 33C05, 34A12, 34D20, 34D23, 34G20, 37M05, 43A85, 44A35, 45G10, 51M10, 92B20, 92C20.
我们研究了 Chossat 和 Faugeras 引入的神经场方程,这些方程用于模拟皮质 V1 超柱中图像边缘和纹理的表示和处理。关键实体,结构张量,本质上存在于非欧几里得,实际上是双曲,空间。它的时空行为由定义在二维双曲空间的庞加莱圆盘模型上的非线性积分微分方程控制。我们使用泛函分析理论中的方法证明了这些方程的解的存在性和唯一性。对于固定的,即时间独立的,解,我们进行了稳定性分析,得出了关于它们行为的重要结果。我们还基于非欧几里得的双曲分析,对一个极限情况下的空间局部隆起解进行了原创性研究。我们用数值模拟来说明我们的理论结果。数学主题分类:30F45、33C05、34A12、34D20、34D23、34G20、37M05、43A85、44A35、45G10、51M10、92B20、92C20。