Characterizing Cortical Computation in the Context of Natural Vision

自然视觉背景下的皮质计算特征

• 批准号: 0904430
• 负责人: Daniel Butts
• 金额: $ 45.44万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0904430&HistoricalAwards=false
• 关键词: Characterizing; Cortical; Computation; Context; Natural

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.

自然视觉世界的复杂性，以及多个皮质区域内和跨多个皮质区域发生的复杂神经元处理，使人们对大脑如何处理视觉刺激的理解感到困惑。 在过去的几十年里，通过使用简单的实验室刺激（例如移动条或点）来开发对这些元素的神经元调节的简单描述，已经取得了实质性进展。 这种方法为下层皮质区域提供了合理的功能描述，但它不太可能足以描述纹状外皮质区域的特征，这些区域的反应被认为代表了自然视觉世界特有的元素。 通过加拿大和美国的联合合作，该项目将基于一组接近自然视觉的复杂刺激与适当复杂的模型的新实验方法结合起来，以了解皮层处理的连续阶段中的神经元如何调整为更自然的视觉特征。之前对自然刺激的研究主要集中在皮层的腹侧通路上，该通路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。 该项目的重点是灵长类视觉皮层的背侧流，该背侧流主要通过运动处理来识别。 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，可以使用为此建议设计的自然刺激进行采样。 这种刺激的发展将把探针的空间和时间复杂性扩展到背流区域，同时为将要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得出的运动刺激，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结构（V1、MT 和 MST）的连续区域中进行这项研究，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导出较高级别的抽象。该项目是由计算神经科学合作研究和 OISE 美洲计划联合资助。 加拿大健康研究所资助了一个配套项目。