Spatio-temporal dynamics and multiple feature maps in primary visual cortex

本项目的长期目标是建立初级视皮层（V1）神经元如何对视觉刺激的多个（而不是单个）特征产生协调反应的动力学理论，以及这些反应如何在大脑皮层中进行空间整合以产生更多的视觉场景全局信息。 这项工作的一个主要重点是扩展当前的网络模型的方向调整，以纳入这样一个事实，即V1细胞也选择空间频率。 这是由相当多的生理和心理证据表明，皮层电路进行局部二维傅立叶分解的刺激，而不是简单地执行局部边缘检测的动机。 大脑皮层表面的光学成像揭示了大脑皮层的空间频率偏好和方向性分布之间的复杂关系。 这两个featurepreference地图之间的相关性是如何表现出的本地和远程circuitry的V1，和后果的大规模的circuitics的V1也进行了研究。 初级视觉皮层（V1）位于大脑后部，是处理从眼睛接收到的视觉信息的第一个皮层区域。 研究V1区神经元（脑细胞）功能的经典结果之一是它们能分析视觉图像的每一个局部特征，也就是说，它们能进行图像的超分辨率分解。(For例如，V1细胞对代表图像亮区和暗区之间边界的边缘的方向敏感。 这一发现由Hubel和Wieselled获得诺贝尔医学奖）。 由此产生的一个非常重要的问题是，我们对世界的连贯感知是如何重建的。 直到最近，人们还认为来自V1细胞的局部信息是通过大脑中发生认知的高级处理阶段传递的。然而，越来越清楚的是，V1中的长程回路本身也可能有助于重建过程。 该提案的基本目的是通过开发一个大规模的初级视觉皮层数学模型来研究这一过程，该模型结合了有关其内部电路的最新解剖数据。 了解视觉大脑的早期阶段如何编码图像对信息技术（如人工视觉系统的开发）和生物技术（如为视力受损者开发人工假体）具有重要的应用。 在后一种情况下，也许有一天可以人工刺激初级视觉皮层来诱导视觉感觉，就像受控的视觉幻觉一样。

The long term goal of this project is to develop a dynamicaltheory of how neurons in primary visual cortex (V1) generate atuned response to multiple (rather than single) features of avisual stimulus, and how these responses are spatially integratedacross the cortex to generate more global information about avisual scene. A primary focus of the work is to extend currentnetwork models of orientation tuning to incorporate the fact thatV1 cells are also selective for spatial frequency. This ismotivated by the considerable physiological and psychophysicalevidence suggesting that cortical circuits carry out a localizedtwo-dimensional Fourier decomposition of a stimulus rather thansimply performing local edge detection. Optical imaging of thesurface of cortex has revealed an intricate relationship betweenthe distribution of orientation and spatial frequency preferencesacross cortex. How correlations between these two featurepreference maps is manifested by the local and long-rangecircuitry of V1, and the consequences for the large-scaledynamics of V1 is also investigated. The primary visual cortex (V1) located at the back of thebrain is the first cortical area to process visual informationreceived from the eyes. One of the classical results regardingthe function of neurons (brain cells) in V1 is that they analyzevery local features of a visual image, that is, they carry outimage decomposition. (For example, V1 cells are sensitive to theorientation of an edge representing the boundary between a lightand dark region of the image. This discovery by Hubel and Wieselled to the Nobel prize in medicine). A very important questionthat follows from this is how our coherent perception of theworld is reconstructed. Until recently, it was thought that thelocal information from cells in V1 was passed through higherorder processing stages in the brain where cognition occurs.However, it is becoming clear that long-range circuitry within V1could itself contribute to the process of reconstruction. Thebasic aim of the proposal is to investigate this process bydeveloping a large-scale mathematical model of primary visualcortex that incorporates the latest anatomical data regarding itsinternal circuitry. Understanding how early stages in the visualbrain encode images has important applications to informationtechnology (such as the development of artificial vision systems)and biotechnology (such as the development of an artificialprosthesis for the visually impaired). In the latter case itmight be possible one day to artificially stimulate primaryvisual cortex to induce a visual sensation, rather like acontrolled visual hallucination.