Characterizing Cortical Computation in the Context of Natural Vision

对大脑如何处理视觉刺激的理解被自然视觉世界的复杂性所混淆，再加上发生在多个皮层区域内和跨多个皮层区域的复杂神经元处理。 在过去的几十年里，通过使用简单的实验室刺激，如移动的条或点，已经取得了实质性的进展，以开发简单的描述神经元调谐到这些元素。 这种方法提供了对下部皮质区域的合理功能描述，但不太可能足以描述纹外皮质区域的特征，这些区域的反应被认为代表了自然视觉世界特有的元素。 通过与美国和美国的合作，该项目将基于一组接近自然视觉的复杂刺激的新实验方法与适当复杂的模型相结合，以了解皮层处理的连续阶段中的神经元如何调整到更自然的视觉特征。大多数以前的自然刺激工作都集中在皮层中的腹侧通路上，该通路与计算物体形状和身份有关。 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动物视觉皮层的背流，这主要是确定与运动处理。 这种方法的优点是，运动，特别是在自然视觉中看到的运动，可以局部分解成一个低维的光流空间，可以使用为这个建议设计的自然刺激采样。 这种刺激的发展将扩展的空间和时间的复杂性探针的背流中的区域，同时提供必要的约束，将开发一种新的非线性建模框架。 然后，这些模型将被应用于通过模拟自然三维虚拟环境而获得的运动刺激，从而使所揭示的复杂处理与自然视觉特征联系起来。 此外，通过在包括背侧层次（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，即如何从较低级别的视觉特征中获得更高级别的抽象。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配套项目。

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.