Neural Codes Underlying Visual Segmentation

描述(申请人提供)：自然场景通常包含多个实体。将视觉场景分离成不同的对象和表面的能力，称为分割， 是视觉的基本功能。分割对于解释视觉图像和 产生对我们环境的感知。然而，图像分割背后的神经机制还没有被很好地理解。我们的长期目标是了解知觉组织的神经基础，以及最终知觉是如何从神经元网络中的活动中产生的。在视觉的子形态中，视觉运动为分割提供了有效的线索。这项研究使用视觉运动来研究多个刺激是如何被视皮层中的神经元代表的，从而实现对多个刺激的分割和感知。为了分离视觉运动线索和空间线索对图像分割的影响，我们将使用在视觉空间的同一区域以不同方向移动的随机点图案。先前的研究表明，由多个可感知分离的刺激引起的皮质神经元的反应倾向于遵循由单独的成分刺激引起的反应的平均值。然而，这样的方案在分割仅略有不同的两个刺激方面提出了挑战，因为平均基本上带走了关于单个刺激成分的身份的信息。这项拟议的研究要解决的中心问题是，视觉系统如何实现对略有不同但可感知区分的刺激的分割。我们将结合神经生理学、行为学和计算的方法来实现我们的目标。该提案有两个具体目标。在目标1中，我们将确定多个运动刺激是如何由视觉皮质中的神经元群体来表示的，以及这种神经表示的时间动力学，而视觉系统则解决了分割在不同方向上运动的重叠刺激的问题。在目标2中，我们将阐明视觉深度和速度线索以及选择性注意如何调节不同方向移动的多个刺激的神经表征。这项拟议的研究将深入了解皮层网络在处理感觉信息时的基本神经操作，并将扩大我们对知觉组织潜在神经机制的了解。从研究正常视觉功能中获得的见解有望提高我们对视力障碍和眼球运动障碍的原因、治疗和预防的理解。

DESCRIPTION (provided by applicant): Natural scenes often contain multiple entities. The ability to segregate visual scenes into distinct objects and surfaces, referred to as segmentation, is a fundamental function of vision. Segmentation is crucial for interpreting visual images and for generating the perception of our environment. However, the neural mechanisms underlying image segmentation are not well understood. Our long-term goal is to understand the neural basis underlying perceptual organization and ultimately how perception arises from activity in neuronal network. Among sub-modalities of vision, visual motion provides a potent cue for segmentation. The proposed research uses visual motion to investigate how multiple stimuli are represented by neurons in the visual cortex such that the segmentation and perception of multiple stimuli can be achieved. To isolate the effects of visual motion cues from those of spatial cues on image segmentation, we will use random-dot patterns that move in the same region of visual space in different directions. Previous studies have shown that the responses of cortical neurons elicited by multiple, perceptually separable, stimuli tend to follow the average o the responses elicited by the constituent stimuli presented alone. Such a scheme, however, poses a challenge in segmenting two stimuli that differ only slightly, because averaging essentially takes away the information regarding the identities of individual stimulus components. The central problem to be addressed by the proposed research is how the segmentation of slightly different, but perceptually distinguishable, stimuli is achieved by the visual system. We will combine the methods of neurophysiology, behavior and computation to achieve our goals. The proposal has two specific aims. In Aim #1, we will determine how multiple moving stimuli are represented by populations of neurons in the visual cortex and the temporal dynamics of such neural representation, while the visual system solves the problem of segmenting overlapping stimuli moving in different directions. In Aim #2, we will elucidate how visual depth and speed cues, and selective attention modulate the neural representation of multiple stimuli moving in different directions. The proposed research will provide insight into fundamental neural operations of cortical network in processing sensory information and will expand our knowledge of the neural mechanisms underlying perceptual organization. Insights gained from studying normal visual functions promise to improve our understanding of the cause, treatment and prevention of disorders of vision and eye movements.