Laminar Neural Field Models for the Visual Cortex of the Brain

这个项目的重点是发展对大脑初级视觉皮层功能的改进见解。这是大脑皮层（灵长类动物大脑中负责高级认知功能的卷曲部分）接收和处理来自眼睛的视觉信息的第一个区域。它可以被看作是由数百万脑细胞（神经元）通过电信号相互交流的二维薄片。这些神经元的电活动模式对视觉图像的信息进行编码，然后由大脑的其他区域进行处理，从而产生对动态变化的三维世界的视觉感知。视觉信息通常由空间结构或连贯的活动模式表示。了解这些动态模式的起源和维持机制不仅对理解视觉脑的正常功能很重要，而且对癫痫发作和偏头痛期间病理状态的发生也很重要。神经科学的主要挑战之一是确定视觉大脑的线路如何促进皮层活动模式的产生。研究者建立了初级视觉皮层的数学模型，该模型描述了电活动在二维皮质薄片上的产生和传播。然而，最近的实验研究表明，初级视觉皮层的层状或分层结构在这些活动模式的产生中起着至关重要的作用。这个研究项目是犹他大学莫兰眼科中心一个更大的合作项目的一部分，旨在扩展以前的数学模型，以考虑层流结构，并确定它是如何影响一系列自发视觉现象的。此次合作的主要重点是结合神经生理学、解剖学和计算建模来了解初级视觉皮层的功能结构及其在视觉处理中的作用。莫兰小组目前正在开发利用光来控制转基因细胞和病毒标记技术，以了解视觉皮层的精细结构，这将用于完善数学模型。连接这两个项目的基本思想是，用于理解自发活动的数学模型中的神经回路与用于解释观察到的皮层对视觉刺激的正常反应的神经回路是相同的。该项目促进了数学神经科学与视觉交叉领域的科学进步，有助于跨学科培养研究生和博士后。初级视觉皮层的建模涉及连续神经场模型的构建和分析，在连续神经场模型中，神经元空间结构网络的大规模动态用非线性积分微分方程来描述。研究神经领域的一个主要优势是，非线性偏微分方程数学理论中的强大方法可以用于分析这些模型。以往关于神经领域的研究几乎都忽略了大脑皮层具有层流结构，不同层的神经元往往具有不同的刺激反应特性，参与不同的回路。通过所谓的垂直连接，层与层之间也存在广泛的耦合。在本项目中，层流神经场模型将用于研究自发视觉现象的两个重要例子，即双目竞争波和视幻觉。后者的一种可能机制是基于这样一种观点，即某些化学或物理干扰会破坏大脑视觉部分的稳定，从而诱发一种自发的皮层活动模式。由此产生的幻觉的几何形状反映了视觉皮层的内在结构和对称性。分析这些模式可以进一步了解大脑如何处理正常视觉中的图像。双眼竞争是一种现象，在呈现给两只眼睛的不同图像之间，感知来回切换。由此产生的感知优势和抑制的波动为人类视觉系统的非侵入性研究和识别潜在的有意识视觉意识的可能神经机制提供了基础。

This project is focused on developing improved insights into the functioning of the primary visual cortex of the brain. This is the first region of the cerebral cortex (the convoluted part of the brain responsible for higher cognitive function in primates) to receive and process visual information from the eyes. It can be viewed as a two-dimensional sheet of millions of brain cells (neurons) communicating with each other via electrical signals. The electrical activity patterns of these neurons encode information about a visual image, which is then processed by other regions of the brain, resulting in the visual perception of a dynamically changing three-dimensional world. Visual information is often represented by spatially structured or coherent activity patterns. Understanding the mechanisms that underpin the origin and maintenance of these dynamical patterns is not only important for understanding the normal functioning of the visual brain, but also the occurrence of pathological states during epileptic seizures and migraines. One of the major challenges in neuroscience is determining how the wiring of the visual brain contributes to the generation of cortical activity patterns. The investigator has developed mathematical models of the primary visual cortex based on models that describe the generation and spread of electrical activity across the two-dimensional cortical sheet. Recent experimental studies indicate, however, that the laminar or layered structure of the primary visual cortex plays a crucial role in the production of these activity patterns. This research project, which is part of a larger collaborative program with the Moran Eye Center at the University of Utah, aims to extend previous mathematical models in order to take into account the laminar structure and determine how it affects a range of spontaneous visual phenomena. The main focus of the collaboration is to use a combination of neurophysiology, anatomy, and computational modeling to understand the functional architecture of the primary visual cortex and its role in visual processing. The Moran group is currently developing the use of light to control genetically modified cells and virus labeling techniques in order to understand the fine-structure of the visual cortex, which will be used to refine the mathematical models. The underlying idea linking the two projects is that the neural circuits used in the mathematical models to understand spontaneous activity are the same as those used to explain observations of the normal response of the cortex to visual stimulations. This project promotes scientific progress in the interdisciplinary field of mathematical neuroscience and vision and contributes to the interdisciplinary training of graduate students and postdocs.The modeling of the primary visual cortex involves the construction and analysis of continuum neural field models, in which the large-scale dynamics of spatially structured networks of neurons is described in terms of nonlinear, integro-differential equations. A major advantage of working with neural fields is that powerful methods from the mathematical theory of nonlinear partial differential equations can be adapted to analyze such models. Almost all previous studies of neural fields have ignored the fact that the cerebral cortex has a laminar structure, with neurons in distinct layers often having distinct stimulus response properties and participating in distinct circuits. There is also extensive coupling between layers via so-called vertical connections. In this project the laminar neural field models will be used study two important examples of spontaneous visual phenomena, namely, binocular rivalry waves and visual hallucinations. One possible mechanism for the latter is based on the idea that some chemical or physical disturbance can destabilize the visual part of the brain, inducing a spontaneous pattern of cortical activity. The geometry of the resulting hallucination thus reflects the intrinsic architecture and symmetry of the visual cortex. Analyzing such patterns can provide further insight in how the brain processes images in normal vision. Binocular rivalry is the phenomenon where perception switches back and forth between different images presented to the two eyes. The resulting fluctuations in perceptual dominance and suppression provide a basis for non-invasive studies of the human visual system and the identification of possible neural mechanisms underlying conscious visual awareness.