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).

项目概要 视觉感知决策（PDM）是一个无处不在的过程，它将我们嘈杂的视觉体验转化为 将环境纳入相关的感知决策非常重要，因为它直接影响我们的方式。 从之前的研究中，我们知道许多认知因素与我们的周围环境相互作用并形成我们的行为。 随着年龄的增长，这些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，功能不断增强，随后在衰老过程中功能下降。 关于 PDM 整个生命周期轨迹的直接证据 我们发现了我们对 PDM 理解中的三个差距： 1) 儿童 PDM 尚未得到充分研究，可能是因为方法论问题，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，并且 3）我们没有 清楚地了解噪音如何与儿童和老年人的 PDM 能力相互作用；这一点值得注意； PDM 常常成为高刺激噪声条件下行为的关键限制因素。 该提案的目的是通过仔细审查 PDM 与年龄相关的影响以及 在目标 1 中，我们建议使用不同的方法来绘制 PDM 整个生命周期的典型发展。 使用两个任务（即随机点运动任务和分类任务）检查整个生命周期的 PDM。 我们将使用经典的反应时间 (RT) 方法进行建模（即 DDM：漂移扩散模型），允许 我们将 RT 分解为其组成部分（即证据积累、非决策时间和决策时间） 时间）来阐明 PDM 不同组成部分与年龄相关的影响，这是实现目标 1 的第一步。 了解 PDM 与年龄相关的影响以及绘制典型发展的重要一步 在目标 2 中，我们将探索使用一种补充方法，即持续时间阈值，其特征是 通过足以让个人感知刺激的最短时间，作为一种新颖的方法 使用与目标 1 相同的任务来估计 PDM 的时间限制。这种方法具有明显的优点： 需要复杂的建模，并且更适合儿童和老年人，因为它消除了非 在目标 3 中，我们将使用经典（RT/DDM）和新颖（持续时间）。 阈值）方法，通过将不同级别的噪声包含到刺激噪声中来检查刺激噪声如何影响 PDM 目标 1 中提到的任务。我们的感官体验本质上是嘈杂的，有证据表明儿童和 老年人更容易受到噪音刺激。我们的假设是噪音的存在会影响老年人的健康。 PDM 中与年龄相关的缺陷日益恶化，这将是我们对 PDM 理解的重大进步。 生命周期轨迹作为有效的 PDM 在嘈杂的感官条件下尤其重要（例如，骑车） 总之，拟议的研究将提供有关低能见度条件下的自行车的新颖见解。 PDM 的典型发展和衰退，并由此建立研究非典型的基线 PDM 中的发育和衰老（例如自闭症谱系障碍、阿尔茨海默病）。