Neural Codes Underlying Visual Segmentation

项目摘要 自然场景通常包含多个实体。将视觉场景分隔为不同对象的能力 而表面，被称为分割，是视觉的基本功能。细分市场对于 解释视觉图像并产生对我们环境的感知。然而，神经 图像分割的基本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的活动中产生的 网络。在视觉的子形态中，视觉运动为分割提供了有效的线索。建议数 研究使用视觉运动来研究多个刺激是如何由视觉皮质中的神经元代表的 从而可以实现对多个刺激的分割和感知。隔离视觉效果的步骤 在图像分割上，我们将使用随机点图案来分割来自空间线索的运动线索 同一区域的视觉空间在不同的方向。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倾向于遵循反应的平均值 由单独呈现的成分刺激引起的。然而，这样的方案对细分构成了挑战 两个仅略有不同的刺激，因为平均基本上会带走关于 单个刺激成分的身份。拟议的研究要解决的中心问题是 如何通过视觉实现对略微不同但可感知区分的刺激的分割 系统。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。这个 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如何由 视觉皮质中的神经元群体和这种神经表征的时间动力学，而 视觉系统解决了分割不同方向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是如何调节神经表征的 多个刺激朝不同方向移动。拟议中的研究将提供对基本情况的洞察 大脑皮层网络在处理感觉信息方面的神经操作，将扩大我们对 知觉组织的神经机制。从研究正常视觉功能中获得的见解 承诺提高我们对视力和眼科疾病的病因、治疗和预防的了解 动静。

Project Summary 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 of 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.