CRCNS: Attentional Selection and Perceptional Organization

描述（由申请人提供）：提出的研究解决了感知组织如何与视觉系统中的注意选择相连接的问题。虽然这些问题经常被认为是分开的，但我们相信它们是紧密相连的，实际上可能有一个共同的神经基质。我们提出图形-背景组织的神经元机制，即视觉对象边界的神经表征，依赖于神经元回路，该回路也用于表示这些对象是否被关注。我们将研究单细胞的活动与多个电极的外皮层。这些数据将用于约束底层神经元回路的大规模详细模型。将实现三个具体目标。第一个目的是在大脑皮层V2区建立与注意无关的图形-背景组织的机制。在以前的工作中，我们开发了一个图-地分离模型，解释了边界所有权选择性的机制。该模型只能解释平均射击率的变化。新模型将基于包含尖峰的单个神经元模型，因此能够模拟边界所有权信号的振幅和时间过程，以及神经元之间成对尖峰序列的相关性。第二个目的是研究图形-背景结构的短期记忆。我们将在区域V2中同时进行多个单单元记录，以表征边界所有权编码中最近观察到的滞后效应。我们还将记录更高的域外区域（V3和V4），因为边界所有权选择性的快速时间过程使得它很可能是通过白质连接传递的。这些电生理记录将与边界所有权信号的持续和滞后模型的发展相辅相成。我们将通过引入更复杂的单神经元模型来扩展脉冲神经网络模型，这些模型可以解释滞后效应背后的机制。第三个目的是研究选择性注意如何与图底组织和特征绑定机制相互作用。我们认为，在层外皮层中观察到的对前景图形的选择性是由于分组细胞的周期性偏见，并且后者也用于仔细选择图形。我们将记录外皮层区V2的单细胞和成对细胞，研究选择性注意对边界所有权选择性的影响。这些记录将与自上而下的选择性注意与图形地面组织的相互作用模型相结合。我们将扩展在Aim 1中开发的尖峰神经网络模型，以包括选择性注意。该模型将解释结合条件和注意状态变化下的速率效应和成对相关函数。这项研究将有助于我们了解灵长类动物视觉的一些最基本的机制，这对理解人类正常和受损的视觉具有重要意义。从这个项目中获得的见解将有助于理解认知障碍的神经基础，如阅读障碍和半忽视。公共卫生相关性：在我们看来，视力很容易。实际上，这是一个非常复杂的过程，这一点可以从以下事实中看出：计算机在人工视觉方面的表现甚至无法与简单的动物相媲美。本研究的目的是了解如何将视觉场景分解为视觉对象，以及如何仔细选择这些视觉对象进行更详细的处理。注意选择缺陷存在于许多神经系统疾病中，例如半忽视，阐明选择性注意如何与图像理解一起工作对于理解这些疾病的潜在机制将是重要的。

DESCRIPTION (provided by applicant): The proposed research addresses the question of how perceptual organization interfaces with attentional selection in the visual system. While these questions are frequently considered separate, we believe that they are closely connected and may in fact share a common neural substrate. We propose that the neuronal mechanisms of figure-ground organization, that is, the neural representation of the borders of a visual object, relies on neuronal circuitry that is also used to represent whether these objects are attended or not. We will study single cell activity with multiple electrodes in extrastriate cortex. These data will be used to constrain large-scale detailed models of the underlying neuronal circuitry. Three specific aims will be pursued. The first Aim is to model the mechanisms of attention-independent figure-ground organization in cortical area V2. In previous work, we have developed a model of figure-ground segregation that explains mechanisms underlying border ownership selectivity. The model can only explain changes in mean firing rates. The new model will be based on a model of single neurons that includes spiking and will thus be able to model amplitude and time course of the border ownership signals as well as pair wise spike train correlation between neurons. The second Aim is to study short-term memory for figure-ground structure. We will perform multiple simultaneous single-unit recordings in area V2 to characterize the recently observed hysteresis effects in border ownership coding. We will also record in higher extrastriate areas (V3 and V4) since the fast time course of border ownership selectivity makes it likely that it is imparted by connections through the white matter. These electrophysiological recordings will be complemented with the development of a model of persistence and hysteresis of border ownership signals. We will expand the spiking neural network model by introducing more complex single-neuron models that can explain the mechanisms underlying the hysteresis effects. The third Aim is to study how selective attention interacts with mechanisms of figure-ground organization and feature binding. We suggest that the selectivity to side of foreground figure observed in extrastriate cortex arises from a recurrent bias from grouping cells, and that the latter are also used to attentively select the figure. We will record from single cells and pairs of cells in extrastriate area V2 and study the influence of selective attention on border ownership selectivity. These recordings will be combined with a model of the interaction of top-down selective attention with figure ground organization. We will expand the spiking neural network model developed under Aim 1 to include selective attention. The model will explain rate effects and pair wise correlation functions under a variation of binding conditions and attentional states. The proposed research will contribute to our understanding of some of the most fundamental mechanisms of primate vision which is of importance for understanding both normal and impaired vision in humans. The insight gained from this project will contribute to the understanding of the neural basis of cognitive disorders such as dyslexia and hemi-neglect. PUBLIC HEALTH RELEVANCE: It appears to us that seeing is easy. In reality, it is a very complex process, as can be seen by the fact that no computer has a performance in artificial vision comparable to even simple animals. The goal of the proposed research is to understand how a visual scene is dissected into visual objects, and how these visual objects are attentively selected for more detailed processing. Deficiencies in attentional selection are present in many neurological diseases, e.g. hemineglect, and elucidating how selective attention works with image understanding will be important for understanding the mechanisms underlying these diseases.