Visual Perception and Attention Laboratory, School of Kinesiology and Health Science, York University Toronto, ON, Canada ; Centre for Vision Research, York University Toronto, ON, Canada.
Visual Perception and Attention Laboratory, School of Kinesiology and Health Science, York University Toronto, ON, Canada ; Centre for Vision Research, York University Toronto, ON, Canada ; Departments of Biology and Psychology, York University Toronto, ON, Canada ; Canadian Action and Perception Network, York University Toronto, ON, Canada.
Front Comput Neurosci. 2014 Aug 5;8:84. doi: 10.3389/fncom.2014.00084. eCollection 2014.
a ventral stream that receives color and form information and a dorsal stream that receives motion information. Each stream processes that information hierarchically, with each stage building upon the previous. In the ventral stream this leads to the formation of object representations that ultimately allow for object recognition regardless of changes in the surrounding environment. In the dorsal stream, this hierarchical processing has classically been thought to lead to the computation of complex motion in three dimensions. However, there is evidence to suggest that there is integration of both dorsal and ventral stream information into motion computation processes, giving rise to intermediate object representations, which facilitate object selection and decision making mechanisms in the dorsal stream. First we review the hierarchical processing of motion along the dorsal stream and the building up of object representations along the ventral stream. Then we discuss recent work on the integration of ventral and dorsal stream features that lead to intermediate object representations in the dorsal stream. Finally we propose a framework describing how and at what stage different features are integrated into dorsal visual stream object representations. Determining the integration of features along the dorsal stream is necessary to understand not only how the dorsal stream builds up an object representation but also which computations are performed on object representations instead of local features.
一个腹侧流接收颜色和形状信息,一个背侧流接收运动信息。每条流都按照层次结构处理信息,每个阶段都在前一个阶段的基础上进行。在腹侧流中,这导致形成物体表示,最终允许物体识别,而不管周围环境的变化。在背侧流中,这种分层处理经典上被认为导致三维复杂运动的计算。然而,有证据表明,背侧流和腹侧流信息被整合到运动计算过程中,产生中间物体表示,从而促进背侧流中的物体选择和决策机制。首先,我们回顾沿着背侧流的运动的分层处理和沿着腹侧流的物体表示的建立。然后,我们讨论了最近关于整合腹侧流和背侧流特征的工作,这些工作导致了背侧流中的中间物体表示。最后,我们提出了一个框架,描述了不同特征是如何以及在哪个阶段被整合到背侧视觉流物体表示中的。确定沿着背侧流的特征整合对于理解不仅背侧流如何建立物体表示,而且还对物体表示而不是局部特征执行哪些计算是必要的。