MSM: Collaborative Research: Cortical Processing across Multiple Time and Space Scales

该项目的目标是创建理论和计算工具来解释发生在哺乳动物初级视觉皮层中的“大脑计算”，初级视觉皮层是视觉通路沿着的第一个位置，在视觉通路中，单个神经细胞（神经元）“识别”视觉场景的基本特征，例如模式方向。 将开发一个大规模的、生物学上真实的数值神经元网络模型，用于模拟初级视觉皮层如何作为“计算机”来使这种特征识别成为可能，并用于模拟一片大约5毫米乘5毫米大小的初级视觉皮层，其中包含近100万个神经元。 初级视皮层的粗粒度表示也将被开发出来，它将视皮层视为一个连续体，而不是一组单独的神经元，并在描述中纳入大量实验运行的统计数据，而不仅仅是一个，从而消除了对大量模拟的需要。最后，将开发混合表示，其中选择神经元组由大规模神经元模型描述，而其他神经元组由批量粗粒度表示描述。 这种表示似乎特别有前途的模拟现实的神经元处理刺激的大脑的更大的portions.The模型和软件将验证和展示在初级视觉皮层中观察到的处理的两个引人注目的例子：自发皮层活动和运动错觉的模式。 前者被认为包括数千个毫米级神经元的集体行为，并且似乎在神经元偏好相同方向的区域被激活。 在一个流行的运动错觉中，显示一个小正方形紧跟着一个长条，使正方形看起来好像正在“成长”成为长条。 实验观察到这种错觉的生理机制是与感知到的正方形“生长”到条形中相对应的实际皮层活动，类似于真实的运动引起的活动。 这些软件和模型的一个预期任务是解释初级视觉皮层的动力学行为以及这些和其他皮层现象背后的机制。视觉皮层如何处理信息是神经科学中最具挑战性的问题之一。 提出的大尺度时空活动的研究，使用一个非常大的计算模型的初级视觉皮层以及粗粒度的理论方法，解决了迫切需要在现代神经科学，这是理论上的补充，最近发展的多模式，大规模的实验方法。 在这个项目中开发的模型和软件的目的是获得定性和定量的生物学机制，神经元计算在初级视觉皮层，并可能在其他皮层区域的现实解释。该软件将提供给神经科学领域的大量研究人员使用，其目的是帮助科学界对感官知觉机制和其他大脑功能的理论理解取得重大进展。

The project's goal is to create theoretical and computational tools to explain "brain computations" taking place in the mammalian primary visual cortex, the first location along the visual pathway in which individual nerve cells (neurons) "recognize" elementary features of the visual scene, such as pattern orientation. A large-scale, biologically realistic numerical neuronal network model will be developed for simulating how the primary visual cortex acts as a "computer" to make this feature recognition possible, and used to simulate a patch of the primary visual cortex of about 5 millimeters by 5 millimeters in size and containing close to a million neurons. Coarse-grained representations of the primary visual cortex will also be developed, which treat it as a continuum rather than a set of individual neurons and incorporate the statistics of a multitude of experimental runs in the description instead of just one, thus eliminating the need for large numbers of simulations. Finally, hybrid representations will be developed, in which select groups of neurons are described by a large-scale neuronal model, while others are described by a bulk coarse-grained representation. Such representations appear particularly promising for simulating realistic neuronal processing of stimuli in yet larger portions of the brain.The models and software will be validated and showcased on two striking examples of observed processing in the primary visual cortex: patterns of spontaneous cortical activity and motion illusions. The former were seen to encompass collective behavior of thousands of neurons on millimeter scales, and appear to get activated in areas in which neurons prefer the same orientation. In a popular motion illusion, showing a small square immediately followed by a long bar makes the square appear as if it is "growing" to become the bar. A physiological mechanism for this illusion was observed experimentally to be actual cortical activity corresponding to the perceived "growth" of the square into the bar, similar to that caused by real motion. One intended task for the software and models is to explain such mechanisms governing the dynamical behavior of the primary visual cortex and underlying these and other cortical phenomena.How information is processed in the visual cortex is one of the most challenging questions in neuroscience. The proposed study of spatiotemporal activity over large scales, using a very large computational model of the primary visual cortex as well as coarse-grained theoretical methods, addresses an urgent need for scale-up in modern neuroscience, which is the theoretical complement to the recent development of multi-mode, large-scale experimental methods. The models and software developed in this project are aimed at obtaining qualitatively and quantitatively realistic explanations of the biological mechanisms that underlie neuronal computations in the primary visual cortex, and possibly other cortical areas. The software will be made readily accessible to a large group of researchers across the neurosciences, with the aim that its results will help science make significant inroads into theoretical understanding of the mechanisms of sensory perception and possibly other brain functions.