MSM: Collaborative Research: Cortical Processing Across Multiple 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上单个神经细胞（神经元）“识别”视觉场景的基本特征（如模式方向）的第一个位置。一个大规模的、生物学上逼真的数值神经网络模型将被开发出来，用于模拟初级视觉皮层如何作为一个“计算机”，使这种特征识别成为可能，并用于模拟一个大约5毫米乘5毫米大小的初级视觉皮层补丁，包含近一百万个神经元。初级视觉皮层的粗粒度表征也将被开发出来，它将其视为一个连续体，而不是一组单独的神经元，并在描述中包含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，其中选择的神经元组由大规模神经元模型描述，而其他神经元组由大量粗粒度表示描述。这种表征在模拟大脑更大区域对刺激的真实神经元处理方面显得特别有希望。这些模型和软件将通过观察到的初级视觉皮层处理的两个显著例子进行验证和展示：自发皮层活动模式和运动幻觉。前者被认为包含了数千个毫米尺度的神经元的集体行为，并且似乎在神经元倾向于相同方向的区域被激活。在一种流行的运动错觉中，展示一个小方块紧跟着一个长条，使这个方块看起来好像在“成长”成条。实验观察到，这种错觉的生理机制是大脑皮层的实际活动，与感知到的正方形“成长”到条形的过程相对应，类似于由真实运动引起的活动。软件和模型的一个预期任务是解释控制初级视觉皮层动态行为的机制，以及这些和其他皮层现象的基础。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。本文提出的大尺度时空活动研究，利用初级视觉皮层的大计算模型和粗粒度的理论方法，解决了现代神经科学对放大的迫切需要，这是对最近发展的多模式、大规模实验方法的理论补充。本项目开发的模型和软件旨在定性和定量地解释初级视觉皮层和其他皮层区域神经元计算的生物学机制。整个神经科学领域的大量研究人员都可以很容易地使用该软件，其目的是其结果将有助于科学在对感觉知觉机制和可能的其他大脑功能的理论理解方面取得重大进展。

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.