On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1.

IF 2.3 4区 医学 Q1 Neuroscience Journal of Mathematical Neuroscience Pub Date : 2015-12-01 Epub Date: 2015-05-30 DOI:10.1186/s13408-015-0023-8
Romain Veltz, Pascal Chossat, Olivier Faugeras
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Abstract

This paper challenges and extends earlier seminal work. We consider the problem of describing mathematically the spontaneous activity of V1 by combining several important experimental observations including (1) the organization of the visual cortex into a spatially periodic network of hypercolumns structured around pinwheels, (2) the difference between short-range and long-range intracortical connections, the first ones being rather isotropic and producing naturally doubly periodic patterns by Turing mechanisms, the second one being patchy, and (3) the fact that the Turing patterns spontaneously produced by the short-range connections and the network of pinwheels have similar periods. By analyzing the PO maps, we are able to classify all possible singular points (the pinwheels) as having symmetries described by a small subset of the wallpaper groups. We then propose a description of the spontaneous activity of V1 using a classical voltage-based neural field model that features isotropic short-range connectivities modulated by non-isotropic long-range connectivities. A key observation is that, with only short-range connections and because the problem has full translational invariance in this case, a spontaneous doubly periodic pattern generates a 2-torus in a suitable functional space which persists as a flow-invariant manifold under small perturbations, for example when turning on the long-range connections. Through a complete analysis of the symmetries of the resulting neural field equation and motivated by a numerical investigation of the bifurcations of their solutions, we conclude that the branches of solutions which are stable over an extended range of parameters are those that correspond to patterns with an hexagonal (or nearly hexagonal) symmetry. The question of which patterns persist when turning on the long-range connections is answered by (1) analyzing the remaining symmetries on the perturbed torus and (2) combining this information with the Poincaré-Hopf theorem. We have developed a numerical implementation of the theory that has allowed us to produce the predicted patterns of activities, the planforms. In particular we generalize the contoured and non-contoured planforms predicted by previous authors.

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视觉 V1 区风车网络的对称性对皮层自发活动的影响
本文挑战并扩展了之前的开创性工作。我们考虑了用数学方法描述 V1 自发活动的问题,结合了几个重要的实验观察结果,包括:(1) 将视觉皮层组织成一个围绕风车结构的超视柱空间周期性网络;(2) 皮层内短程连接和长程连接的区别、(3) 短程连接和风车网络自发产生的图灵模式具有相似的周期。通过分析 PO 映射,我们能够将所有可能的奇异点(风车)归类为具有由一小部分壁纸组描述的对称性。然后,我们提出了一种基于电压的经典神经场模型来描述 V1 的自发活动,该模型的特点是各向同性的短程连接性受到非各向同性的长程连接性的调制。一个关键的观察结果是,在只有短程连接的情况下,由于问题在这种情况下具有完全的平移不变性,自发的双周期模式会在一个合适的功能空间中产生一个 2-torus,该 2-torus在微小的扰动下(例如在打开长程连接时)作为流动不变的流形持续存在。通过对由此产生的神经场方程的对称性进行全面分析,并通过对其解的分岔进行数值研究,我们得出结论:在参数的扩展范围内保持稳定的解的分支是那些与具有六边形(或近似六边形)对称性的模式相对应的分支。至于在打开长程连接时哪些模式会持续存在,我们可以通过以下方法来回答:(1)分析扰动环上的剩余对称性;(2)将这些信息与波恩卡莱-霍普夫定理相结合。我们开发了该理论的数值实现方法,使我们能够生成预测的活动模式--平面图。特别是,我们将前人预测的轮廓平面图和非轮廓平面图进行了概括。
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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
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审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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