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

这个项目的长期目标是发展一个动态理论，研究初级视觉皮质(V1)的神经元如何对多个(而不是单一)特征的动态刺激产生反应，以及这些反应如何在整个大脑皮层空间整合，以产生更多关于无视觉场景的全局信息。这项工作的一个主要焦点是扩展定向调谐的当前网络模型，以纳入V1细胞对空间频率也具有选择性的事实。这是因为大量的生理和心理生理证据表明，大脑皮层回路对刺激进行局部二维傅立叶分解，而不是简单地进行局部边缘检测。对大脑皮质表面的光学成像揭示了大脑皮质的方位分布和空间频率偏好之间的复杂关系。这两个特征偏好图之间的相关性如何通过V1的局部和长期循环表现出来，以及V1的大尺度动力学后果也被研究。位于大脑后方的初级视觉皮质(V1)是处理从眼睛接收到的视觉信息的第一个皮质区域。关于V1中神经元(脑细胞)功能的经典结果之一是，它们分析视觉图像的每个局部特征，即它们进行图像分解。(例如，V1单元格对代表图像明暗区域之间边界的边缘的方向很敏感。胡贝尔和威瑟斯的这一发现使他获得了诺贝尔医学奖。随之而来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，人们一直认为，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，越来越明显的是，V1内的远程回路本身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型初级视觉皮质的数学模型来研究这一过程，该模型包含了关于其内部回路的最新解剖学数据。了解视觉大脑的早期阶段是如何编码图像的，对信息技术(如人工视觉系统的开发)和生物技术(如为视障人士开发人工假肢)具有重要的应用。在后一种情况下，有一天可能会人为地刺激初级视觉皮质来产生视觉感觉，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.