Perceptual decision making over the lifespan

项目摘要 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 将环境转化为相关的感知决策。PDM很重要，因为它直接影响我们如何 与周围环境相互作用并形成我们的行为。从先前的研究中，我们知道许多认知 随着年龄的增长，这些过程会发生发展变化，通常以倒U形模式为特征： 从儿童期到成年早期功能增加，随后衰老下降。但没有 PDM整个生命周期轨迹的直接证据。我们在对PDM的理解中发现了三个差距： 1)儿童PDM没有得到很好的研究，可能是因为方法问题，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;这是值得注意的， 在高刺激噪声条件下，PDM往往成为行为的关键限制因素。总目标 这项建议的目的是通过仔细研究PDM的年龄相关影响以及 采用不同的方法绘制出PDM在整个生命周期中的典型发展图。在目标1中，我们建议 要使用两个任务在整个生命周期内检查PDM（即，随机点运动任务和分类任务）。 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分解为它的组件（即，证据积累、非决策时间和决策 时间），以阐明PDM的不同组成部分的年龄相关的影响。目标1是第一步， 了解PDM的年龄相关影响，是绘制典型发展的重要一步， PDM。在目标2中，我们将探索使用一种补充方法，持续时间阈值，其特征在于 通过最短的时间，这是足够的个人感知刺激，作为一种新的方法， 使用与目标1相同的任务估计PDM的时间限制。这是一种明显的好处， 需要复杂的建模，它更适合儿童和老年人，因为它消除了非 决策组件（即，运动反应）。在目标3中，我们将使用经典（RT/DDM）和新（持续时间 阈值）的方法来检查刺激噪声如何影响PDM，包括不同水平的噪声， 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 老年人更容易受到刺激噪音的影响。我们的假设是噪音的存在 加剧PDM中与年龄相关的缺陷。这将是我们对PDM理解的一个重大进步 作为有效PDM的寿命轨迹在嘈杂的感觉条件下可能特别重要（例如，骑 低能见度条件下的自行车）。总之，拟议的研究将提供有关 PDM的典型发展和衰落，并通过扩展建立研究非典型的基线 PDM中的开发和老化（例如，自闭症谱系障碍，阿尔茨海默病）。

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).