Neural Models of Behavior

行为的神经模型

• 批准号: 7810574
• 负责人: DANA H. BALLARD
• 金额: $ 32.79万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7810574
• 关键词: Acceleration; Alzheimer' s Disease; Animals; Architecture; Arts; Attention deficit hyperactivity disorder; Automobile Driving; Behavior; Behavioral; Brain; Cell Nucleus; Clinical; Coffee; Cognition; Cognitive; Complex; Controlled Environment; Data; Development; Diagnosis; Diagnostic; Disease; Distal; Drug Formulations; Environment; Eye; FarGo; Fire - disasters; Gilles de la Tourette syndrome; Goals; Hand; Head; Human; Huntington Disease; Image; Interruption; Learning; Link; Location; Measures; Mediating; Methods; Modeling; Movement; Neurons; Performance; Peripheral; Play; Primates; Principal Investigator; Process; Property; Psychological reinforcement; Research; Rewards; Role; Services; Signal Transduction; Specific qualifier value; Stimulus; Structure; Tail; Tea; Techniques; Testing; Thinking; Time; Training; Vision; Visual; Walking; area striata; arm; base; experience; fovea centralis; gaze; human data; human subject; instrumentation; multitask; neural model; neuromechanism; programs; public health relevance; research facility; research study; response; sample fixation; skills; theories; tool; virtual; virtual reality; visual information; visual process; visual processing

DESCRIPTION (provided by applicant): Extensive research has provided a comprehensive understanding of the neural mechanisms of gaze deployment, but there is still a fundamental lack of understanding of the cognitive mechanisms that choose one possible fixation over another. Attempts to characterize these choices in terms of image properties have been a beginning, but at this point we can only go further by introducing cognitive factors. The proposed research uses driving in virtual reality as a controlled environment within which we can ask when and where fixations are made and what influences these choices. Driving is a complex but circumscribed skill that most subjects have extensive experience with. Our studies and those of others have demonstrated that other complex behaviors such as tea making and sandwich making can be readily seen as consisting as compositions of more elemental behaviors. Our modularized theory of behavior allows us to propose very specific testable hypotheses as to the deployment of gaze that are aimed at elucidating its essential link with cognition. Unique capabilities of our facility allow us to measure the eye, head and hand movements, as well as acceleration, braking and steering movements within the confines of a very realistic driving simulator that uses a state of the art Sensics wide field of view head-mounted binocular display (HMD). The simulator is mounted on a hydraulic platform that delivers realistic acceleration stimuli and the driver is immersed in a very complex cityscape driving venue rendered in real time on the HMD. Our theory is that the rules for the deployment of gaze are learned by reinforcement and based on reward-based optimality criteria. This theory is to be tested using human driving experiments as well as a human avatar driver that has realistic gaze movements with fixations. The avatar performs complicated tasks by decomposing them into essential modules. Each of the modules can achieve its goal by repeatedly recognizing crucial visual features in the scene and carrying out the relevant action. Our preliminary studies have successfully modeled human data from walking and making a sandwich and have suggested several hypotheses as to the conduct of human visually guided behaviors that we propose to develop and test using the more demanding virtual automobile driving environment. The proposed research will have three interrelated foci directed at three central questions in task-directed visual processing. 1. When is gaze deployed? Our theory suggests that gaze is deployed in the aid of the behavior that needs it the most. 2. Is the disposition of gaze reward-based? Since gaze is not easily shared among concurrent behaviors, there has to be some way of allocating it. This project will test a new analytical formulation that describes gaze competition in a multi-task situation. 3. How is visual alerting handled? How do humans recognize important interruptions from the visual environment? We will test a hypothesis is that a behavior for recognizing a new situation tries to successfully compete with the current behaviors by promising greater rewards. PUBLIC HEALTH RELEVANCE: When we perform common everyday tasks, such as driving, making coffee or making a sandwich, we depend heavily on the ability to use our eyes. These eyes direct our actions by looking at the items we use in the task and also helping coordinate our arm and other body movements. We have a good idea how nerve cells make the eyes move from place to place, but we do not understand how our brain chooses one particular place over another. People have initially reasoned that image objects, such as a stop sign or a fire hydrant, are the main thing that commands our gaze, but we think its likely to depend on what people are thinking about from moment to moment. Our proposed research uses driving in virtual reality as a controlled environment where we can see where eye fixations are made and what influences these choices. Driving is a common skill with which most subjects have extensive experience and make similar eye fixations, so it's a good venue for our studies. Unique capabilities of our research facility allow us to measure the eye, head and hand movements, as well as acceleration, braking and steering movements within the confines of a very realistic driving simulator that uses a head-mounted binocular display (HMD). The simulator is mounted on a hydraulic platform that provides a sense of acceleration and the driver is immersed in a very complex cityscape that looks very much like reality. The combination of new instrumentation and analytical techniques proposed here should produce a detailed model of cognition that will help us understand disease-related cognitive problems in people and will spur the use of eye gaze in clinical diagnostic tools. Diseases like Schizophernia, Huntington's, Tourette's, Alzheimer's and ADHD all can be diagnosed through characteristically abnormal eye fixations. The even larger hope is that, by knowing how the eyes are used in these instances, we can get a general idea on how the brains function.

描述（由申请人提供）：广泛的研究已经提供了对凝视部署的神经机制的全面理解，但是对于选择一种可能的注视而不是另一种可能的注视的认知机制仍然缺乏基本的理解。尝试根据图像属性来描述这些选择只是一个开始，但此时我们只能通过引入认知因素来进一步推进。拟议的研究使用虚拟现实中的驾驶作为受控环境，在其中我们可以询问何时何地进行注视以及什么影响这些选择。驾驶是一项复杂但受限的技能，大多数受试者都拥有丰富的经验。我们和其他人的研究表明，其他复杂的行为，例如泡茶和制作三明治，很容易被视为由更基本的行为组成。我们的模块化行为理论使我们能够针对凝视的部署提出非常具体的可测试假设，旨在阐明其与认知的本质联系。我们设施的独特功能使我们能够在非常逼真的驾驶模拟器的范围内测量眼睛、头部和手部的运动，以及加速度、制动和转向运动，该模拟器使用最先进的 Sensics 宽视野头戴式驾驶模拟器双目显示器（HMD）。该模拟器安装在液压平台上，可提供逼真的加速刺激，驾驶员沉浸在 HMD 上实时渲染的非常复杂的城市景观驾驶场地中。我们的理论是，凝视部署的规则是通过强化学习的，并且基于基于奖励的最优标准。该理论将使用人类驾驶实验以及具有逼真注视运动的人类化身驾驶员进行测试。化身通过将复杂的任务分解为基本模块来执行这些任务。每个模块都可以通过重复识别场景中的关键视觉特征并执行相关动作来实现其目标。我们的初步研究成功地模拟了步行和制作三明治的人类数据，并提出了关于人类视觉引导行为的几种假设，我们建议使用更苛刻的虚拟汽车驾驶环境来开发和测试这些假设。拟议的研究将有三个相互关联的焦点，针对任务导向的视觉处理中的三个核心问题。 1.什么时候展开凝视？我们的理论表明，凝视被用来帮助最需要它的行为。 2. 凝视的倾向是基于奖励的吗？由于凝视不容易在并发行为之间共享，因此必须有某种方法来分配它。该项目将测试一种新的分析公式，该公式描述多任务情况下的注视竞争。 3. 如何处理视觉警报？人类如何识别视觉环境中的重要干扰？我们将测试一个假设，即识别新情况的行为试图通过承诺更大的奖励来成功地与当前行为竞争。 公共卫生相关性：当我们执行常见的日常任务时，例如开车、煮咖啡或做三明治，我们在很大程度上依赖于使用眼睛的能力。这些眼睛通过观察我们在任务中使用的物品来指导我们的行动，并帮助协调我们的手臂和其他身体运动。我们很清楚神经细胞如何使眼睛从一个地方移动到另一个地方，但我们不明白我们的大脑如何选择一个特定的位置而不是另一个位置。人们最初认为图像对象（例如停车标志或消防栓）是控制我们视线的主要物体，但我们认为这可能取决于人们时时刻刻在想什么。我们提出的研究使用虚拟现实中的驾驶作为受控环境，我们可以在其中看到眼睛注视的位置以及影响这些选择的因素。驾驶是一项常见技能，大多数受试者都拥有丰富的经验并进行类似的注视，因此这是我们学习的一个很好的场所。我们研究设施的独特功能使我们能够在使用头戴式双目显示器 (HMD) 的非常逼真的驾驶模拟器的范围内测量眼睛、头部和手部的运动，以及加速、制动和转向运动。模拟器安装在一个液压平台上，提供加速感，驾驶员沉浸在非常复杂的城市景观中，看起来非常像现实。这里提出的新仪器和分析技术的结合应该会产生一个详细的认知模型，这将帮助我们了解人们与疾病相关的认知问题，并促进眼睛凝视在临床诊断工具中的使用。精神分裂症、亨廷顿舞蹈症、抽动秽语症、阿尔茨海默氏症和多动症等疾病都可以通过特征性的异常注视来诊断。更大的希望是，通过了解在这些情况下如何使用眼睛，我们可以大致了解大脑的功能。