Characterizing Cortical Computation in the Context of Natural Vision

对大脑如何处理视觉刺激的理解，由于自然视觉世界的复杂性，以及发生在多个皮质区域内和跨区域的复杂神经元处理，而变得混乱。在过去的几十年里，通过使用简单的实验室刺激，如移动的条形或点，来发展神经元对这些元素的调节的简单描述，已经取得了实质性的进展。这种方法提供了下皮层区域的合理功能描述，但它不太可能足以表征外皮层区域，其反应被认为代表自然视觉世界的特定元素。通过加拿大和美国的联合合作，该项目结合了基于一组复杂刺激的新实验方法，以适当复杂的模型接近自然视觉，以了解神经元在皮层处理的连续阶段如何调整到更自然的视觉特征。以前大多数关于自然刺激的工作都集中在皮层的腹侧通路上，这与计算物体的形状和身份有关。这是一个极具挑战性的问题，因为形状空间的维数是未知的。这个项目的重点是灵长类视觉皮层的背侧流，它主要与运动处理有关。这种方法的优点是，运动，特别是在自然视觉中看到的运动，可以局部分解为低维光流空间，可以使用为本提案设计的自然刺激进行采样。这种刺激的发展将扩展探针的空间和时间复杂性到背流区域，同时为将开发的新型非线性建模框架提供必要的约束。然后，这些模型将应用于通过模拟自然三维虚拟环境而获得的运动刺激，从而将复杂的处理过程与自然视觉特征联系起来。此外，通过对包括背侧层次（V1、MT和MST）的连续区域进行这项研究，该项目旨在揭示皮层处理的一般原理，即如何从低级视觉特征衍生出高级抽象。该项目由计算神经科学合作研究和OISE美洲计划共同资助。加拿大卫生研究所正在资助一个伙伴项目。

An understanding of how the brain processes visual stimuli is confounded by the complexity of the natural visual world, combined with the intricate neuronal processing that occurs within and across multiple cortical areas. Over the last few decades, substantial progress has been made by using simple laboratory stimuli, such as moving bars or dots, to develop simple descriptions of neuronal tuning to these elements. This approach has provided a reasonable functional description of lower cortical areas, but it is unlikely to be sufficient to characterize the regions of the extrastriate cortex whose responses are thought to represent elements particular to the natural visual world. Though a joint Canadian-US collaboration, this project couples new experimental approaches based on a set of complex stimuli approaching natural vision with appropriately complex models, in order to understand how neurons in successive stages of cortical processing are tuned to more natural visual features.Most previous work with natural stimuli has focused on the ventral pathway in the cortex, which is concerned with computing object shape and identity. This is an extremely challenging problem, as the dimensionality of shape space is unknown. This project focuses instead on the dorsal stream of the primate visual cortex, which is primarily identified with motion processing. The advantage of this approach is that motion, particularly that seen in natural vision, can be locally decomposed into a low-dimensional optic flow space that can be sampled using naturalistic stimuli designed for this proposal. The development of such stimuli will extend both the spatial and temporal complexity of probes to areas in the dorsal stream, while providing the necessary constraints for a novel nonlinear modeling framework that will be developed. These models will then be applied to motion stimuli derived through simulation of natural three-dimensional virtual environments, allowing the complex processing uncovered to be linked to natural visual features. Furthermore, by performing this study across successive areas comprising the dorsal hierarchy (V1, MT, and MST), this project aims to expose general principles of cortical processing, namely how higher level abstractions are derived from lower-level visual features.This project is jointly funded by Collaborative Research in Computational Neuroscience and the OISE Americas program. A companion project is being funded by the Canadian Institutes of Health Research.