Perceptual decision making over the lifespan

一生中的感性决策

• 批准号: 10605083
• 负责人: Ying Lin
• 金额: $ 4.77万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-15 至 2024-06-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10605083
• 关键词: Address; Adolescence; Adult; Affect; Age; Aging; Alzheimer' s Disease; Automobile Driving; Behavior; Brain; Categories; Child; Childhood; Cognitive; Complex; Computer Models; Data; Decision Making; Development; Diffusion; Elderly; Environment; Friends; Goals; Human; Individual; Life; Link; Literature; Longevity; Maps; Measures; Methodology; Methods; Modeling; Motion; Motor; Movement; Noise; Pattern; Performance; Predisposition; Process; Property; Reaction Time; Research; Sampling; Sensory; Shapes; Signal Transduction; Stimulus; Testing; Time; Translating; Visual; Work; age effect; age group; age related; aging population; autism spectrum disorder; behavioral response; cognitive function; cognitive process; design; emerging adult; experience; insight; interest; middle age; model design; novel; novel strategies; recruit; response; senescence; sensory input; sensory integration; sensory stimulus; young adult

Project Summary Visual perceptual decision-making (PDM) is a ubiquitous process that translates our noisy visual experience of the environment into associated perceptual decisions. PDM is important as it directly influences how we interact with our surroundings and form our behavior. From prior studies, we know that many cognitive processes undergo a developmental change as we age, usually characterized by an inverted U-shape pattern: increasing function from childhood to early adulthood and a later decline in senescence. However, there is no direct evidence about the full lifespan trajectory of PDM. We identified three gaps in our understanding of PDM: 1) PDM in children is not well studied, likely because of methodological issues, 2) conclusions about lifespan PDM trajectory are only derived by indirect comparisons between separate studies, and 3) we do not have a clear understanding about how noise interacts with PDM ability in children and older adults; this is notable as PDM often becomes a key limiting factor in behavior under conditions of high stimulus noise. The overall goal of this proposal is to address these gaps in the literature by scrutinizing age-related effects of PDM as well as using different methods to map out the typical development of PDM across the lifespan. In Aim 1, we propose to examine PDM across the lifespan using two tasks (i.e., a random dot motion task and a categorization task). We will use the classical reaction times (RT) method with modeling (i.e., DDM: drift-diffusion model), allowing us to decompose RT into its components (i.e., evidence accumulation, non-decision time, and the decision time) to illuminate age-related effects of the different components of PDM. Aim 1 is the first step to understanding age-related effects of PDM and an important step to mapping out the typical development of PDM. In Aim 2, we will explore the use of a complementary method, duration threshold which is characterized by the shortest amount of time that is sufficient for individuals to perceive a stimulus, as a novel approach for estimating temporal limits of PDM using the same tasks as Aim 1. This is a method with a clear benefit of not necessitating complex modeling and it is more suitable for children and older adults as it eliminates non- decision components (i.e., motor response). In Aim 3 we will use both classical (RT/DDM) and novel (duration threshold) methods to examine how stimulus noise impacts PDM by including different levels of noise to the tasks mentioned in Aim 1. Our sensory experience is inherently noisy and there is evidence that children and older adults are more susceptible to stimulus noise. Our hypothesis is that the presence of noise will exacerbate age-related deficits in PDM. This would be a significant advance in our understanding of PDM lifespan trajectory as effective PDM can be particularly important under noisy sensory conditions (e.g., riding a bike under low visibility conditions). In summary, the proposed research will provide novel insights about the typical development and decline of PDM and, by extension, establish a baseline for studying atypical development and aging in PDM (e.g., Autism Spectrum Disorder, Alzheimer’s Disease).

项目摘要 视觉感知决策（PDM）是一个无处不在的过程，它翻译了我们的噪音视觉体验 环境成为相关的知觉决策。 PDM很重要，因为它直接影响了我们的方式 与周围环境互动并形成我们的行为。从先前的研究中，我们知道许多认知 随着年龄的增长，过程会发生发展变化，通常以倒U形模式为特征： 从童年到成年早期的功能提高，感应后来的下降。但是，没有 有关PDM的完整寿命轨迹的直接证据。我们在对PDM的理解中确定了三个差距： 1）儿童中的PDM不太好研究，可能是由于方法论问题，2）关于寿命的结论 PDM轨迹仅通过单独研究之间的间接比较得出，3）我们没有 清楚了解噪声如何与儿童和老年人中的PDM能力相互作用；这是值得注意的 在高刺激噪声条件下，PDM通常成为行为行为的关键限制因素。总体目标 该建议是通过审查PDM的年龄相关影响以及 使用不同的方法来绘制整个寿命中PDM的典型开发。在AIM 1中，我们建议 使用两个任务（即随机点运动任务和类别任务）检查整个寿命的PDM。 我们将使用建模（即DDM：漂移扩散模型）使用经典反应时间（RT）方法，允许 我们将RT分解为其组成部分（即证据积累，非决定时间和决定 时间）以照亮PDM不同成分的年龄相关效应。目标1是第一步 了解PDM与年龄相关的影响，以及绘制典型发展的重要步骤 PDM。在AIM 2中，我们将探索使用完整的方法，持续时间阈值的使用 以最短的时间足以让个人感知刺激，这是一种新颖的方法 使用与AIM 1相同的任务来估算PDM的临时限制。这是一种具有明显好处的方法 必要的复杂建模，它更适合儿童和老年人，因为它消除了非 - 决策组件（即运动响应）。在AIM 3中，我们将同时使用古典（RT/DDM）和新颖（持续时间） 阈值）方法是检查刺激噪声如何通过将不同级别的噪声与与 AIM 1中提到的任务。我们的感官经历本质上是噪音，有证据表明儿童和 老年人更容易受到刺激噪声的影响。我们的假设是噪音的存在将会 加重与年龄有关的PDM定义。这将是我们对PDM的理解的重大进步 在噪声感觉条件下（例如，骑行A） 在较低的可见性条件下自行车）。总而言之，拟议的研究将提供有关有关的新见解 PDM的典型开发和下降，并扩展为研究非典型的基线 PDM的发展和衰老（例如自闭症谱系障碍，阿尔茨海默氏病）。