Decision Making on Continuous Scales in Aging and Alzheimers Disease

衰老和阿尔茨海默病的连续规模决策

• 批准号: 9563046
• 负责人: GAIL A MCKOON
• 金额: $ 57.58万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9563046
• 关键词: Adopted; Adult; Affect; Age; Aging; Alzheimer' s Disease; Applications Grants; Attention deficit hyperactivity disorder; Child; Clinical; Color; Data; Decision Making; Decision Modeling; Depressed mood; Development; Diffusion; Dimensions; Discrimination; Dyslexia; Elderly; Eye Movements; Fingers; Goals; Gold; Grant; Impaired cognition; Impairment; Individual; Investigation; Judgment; Knowledge; Memory; Mental Depression; Modality; Modeling; Motion; Movement; Mus; Neurosciences; Patients; Perception; Performance; Population; Process; Property; Psychology; Publishing; Reaction Time; Recovery; Research; Research Personnel; Sampling; Schizophrenia; Short-Term Memory; Speed; Stimulus; Tablets; Testing; Time; Variant; base; clinically relevant; cognitive ability; cognitive process; cognitive task; comparative; discrete data; discrete time; experimental study; long term memory; mild cognitive impairment; normal aging; psychologic; response; simulation; skills; theories; tool; touchscreen; two-dimensional; young adult

Project Summary/Abstract The goal of the project is to develop a model that explains the processes by which decisions are made about information that is continuously distributed across one-dimensional and two-dimensional spaces, with responses made on continuous scales. Large comprehensive bodies of data will be collected in the domains of decision- making in perception, long-term memory, working memory, and numerosity and these will allow tight constraints on the theoretical assumptions of the modeling. The model will provide a unified explanation of the full range of data for continuous tasks, including accuracy, the distributions of response times for correct and incorrect responses, how they change with manipulations of independent variables, and how they differ among individuals and groups of individuals. Statistical properties of the model will be examined and the numbers of observations needed in experiments with clinical and other populations will be examined. The model and the data collected to test it will be completely new to decision-making research. Four populations of adults will be studied, young adults, unimpaired older adults, adults with Mild Cognitive Impairment (MCI), and adults with early Alzheimer's Disease (AD). The aim will be to understand how normal aging affects individual components of processing in continuous decision-making and how MCI and early AD affect the components. Almost no research has been conducted with AD and MCI patients modeling the time course of decision-making. It is not known if the components of decision-making are the same as those for adults who are not cognitively impaired or how independent variables affect their accuracy and RTs or whether a modeling approach can uncover preserved skills not discernible from accuracy and RT data alone. 1

项目总结/摘要 该项目的目标是开发一个模型，解释决策的过程， 信息连续分布在一维和二维空间中，并有响应 在连续的尺度上。将在决策领域收集大量综合数据， 在感知、长期记忆、工作记忆和数字方面，这些都将允许严格的限制。 在建模的理论假设上。该模型将提供一个统一的解释， 连续任务的数据，包括准确性，正确和不正确的响应时间分布 反应，它们如何随着独立变量的操纵而变化，以及它们在个体之间的差异 和个人群体。将检查模型的统计特性， 在临床和其他人群的实验中需要进行检查。模型和收集的数据 对决策研究来说是全新的。 将研究四个成人人群，年轻人、未受损的老年人、轻度认知障碍的成人 损害（MCI）和患有早期阿尔茨海默病（AD）的成年人。我们的目标是了解正常的 衰老影响连续决策过程中的个体成分，以及MCI和早期AD 影响组件。几乎没有对AD和MCI患者进行建模时间的研究 决策过程。目前尚不清楚决策的组成部分是否与成人相同 没有认知障碍的人，自变量如何影响他们的准确性和RT， 建模方法可以发现保存的技能，而不是单独从准确性和RT数据中辨别出来。 1