Higher-Order Visual Decision Making Networks and Mechanisms

描述（由申请人提供）：定义规范决策回路的结构，从它的输入到输出，是认知神经科学的主要目标之一。为此，视觉感知决策是一种基本的认知功能，其中视觉信息为选择适当的反应提供了基础。在最简单的情况下，感官证据和行为选择之间的联系是二元的：一辆迎面而来的汽车突然转向你的车道，你必须迅速做出决定——左转还是右转。然而，当视力受损时，无论是由于疾病还是创伤，这些决策机制必须适应输入减少，联想视觉处理受损，或两者兼而有之。因此，视觉上的误解更频繁地发生，并且将感觉转化为行动的过程越来越容易受到必须识别的识别和分类错误的影响。因此，了解视觉感知与高阶分类和错误检测相互作用的神经机制对于理解患者的异常至关重要。在这一建议中，我们建立在先前研究灵长类动物和人类感知决策的工作基础上，以评估人类做出高阶视觉决策的过程。一种假设是，低阶（即感知）和高阶（如分类）决策的输入来源可能不同，但由相同的决策网络调节。另一种假设认为，分类不确定性，无论是与对象类别的分离还是与正确与错误反应的分离有关，都代表了一种更抽象的特征，与涉及不同决策过程的信心和背景有关。在这一假设下，知觉不确定性和范畴不确定性应该激活不同的回路。通过结合使用行为心理物理学、数学模型、功能性核磁共振成像和脑电图，在一个经过充分验证的视觉范式中，我们将试图定义允许人类做出视觉分类决策和检测错误的大脑网络和机制。

DESCRIPTION (provided by applicant): Defining the structure of a canonical decision making circuit, from its inputs to its outputs, is one of the principal goals of cognitive neuroscience. T this end, visual perceptual decision making is a fundamental cognitive function in which visual information provides the basis for choosing an appropriate response. In the simplest case, the link between sensory evidence and a behavioral choice is binary: an oncoming car suddenly veers into one's lane and a quick decision must be made - to swerve left or right. However, when vision is compromised, whether through disease or trauma, these decision mechanisms must adapt to degraded input, impaired associative visual processing, or both. As a consequence, visual misperceptions occur more frequently, and the process of translating sensation to action becomes increasingly susceptible to errors of identification and categorization that must be recognized. Understanding the neural mechanisms by which visual perception interacts with higher-order categorization and error detection is thus essential to understanding abnormalities in patients. In this proposal, we build upon previous work studying perceptual decision making in primates and humans to evaluate the process by which humans make higher-order visual decisions. One hypothesis is that both lower-order (i.e. perceptual) and higher-order (e.g. categorization) decisions may differ in the source of their inputs but are mediated by the same decision making network. An alternative hypothesis argues that categorical uncertainty, whether related to the separation of object classes or to the separation of correct from erroneous responses, represents a more abstract feature related to confidence and context that engages different decision processes. Under this hypothesis, perceptual and categorical uncertainty should activate different circuits. By using a combination of behavioral psychophysics, mathematical models, functional MRI, and EEG in a well-validated visual paradigm, here we will attempt to define the brain networks and mechanisms that allow humans to make visual categorization decisions and to detect errors.