An Adaptive Testing Platform for Optimizing RDoC Experimental Cognitive Measures

用于优化 RDoC 实验认知测量的自适应测试平台

• 批准号: 10631079
• 负责人: Michael L Thomas
• 金额: $ 50.8万
• 依托单位: COLORADO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-14 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10631079
• 关键词: Address; Back; Biological Markers; Brain; Brain imaging; Brain region; Clinical; Clinical Research; Cognitive; Communities; Companions; Control Groups; Data; Development; Floor; Individual; Intervention Studies; Learning; Measurement; Measures; Mediator; Memory; Mental Health; Mentored Patient-Oriented Research Career Development Award; Methodology; Methods; Modernization; National Institute of Mental Health; Neurocognitive; Neurons; Neurosciences Research; Outcome; Outcome Measure; Participant; Patients; Performance; Population; Process; Property; Psychometrics; Psychoses; Pythons; Research; Research Domain Criteria; Rewards; Sampling; Schizophrenia; Short-Term Memory; Standardization; Stimulus; System; Task Performances; Technology; Testing; Time; Translational Research; Variant; Work; brain dysfunction; cognitive ability; cognitive control; cognitive function; cognitive neuroscience; cognitive process; cognitive task; cognitive testing; computerized; design; experimental study; improved; neural; neuroimaging; neuronal patterning; neurophysiology; novel; open source; performance tests; psychologic; response; theories; tool; translational study

Project Summary As part of the Research Domain Criteria (RDoC) initiative, the NIMH seeks to improve measures of neuronal and psychological targets for use in intervention research. RDoC tools must precisely measure cognitive and neuronal systems to produce reliable findings. Unfortunately, many RDoC tasks have not been psychometrically evaluated, nor refined, and are liable to confounds that can lead to inaccurate claims of differential deficit, weakened effect size, and contradictory brain imaging findings. As highlighted by FOA PAR- 18-930, there is a critical need for modern psychometric methods and tools designed to support cognitive and clinical neuroscience research. This project responds to this FOA by evaluating and refining a methodology designed to administer statistically robust variants of RDoC tasks, especially in the context of brain imaging. We have created a quantitative methodology designed to administer computerized adaptive tests (CATs) in the context of cognitive and clinical neuroscience research. CATs manipulate stimulus properties in real time in order to improve measurement precision, avoid ceiling and floor effects, and maximize effect size, even for individuals and groups with highly discrepant levels of cognitive functioning. CATs also perform psychometric adjustments to cognitive tasks so that brain functioning abnormalities can be interpreted independent of performance deficits. In pilot work, we have used this approach with an RDoC working memory task, the N- back, to show that the methodology improves the reliability of both cognitive and brain imaging data. We will evaluate the generalizability and impact of adaptive testing, beyond the N-back task, for use in translational and experimental testing. Patients with schizophrenia and controls will be administered both adaptive and non- adaptive versions of four RDoC paradigms used to assess working memory: delayed match-to-sample, Sternberg, self-ordered pointing, and N-back. Additionally, participants will be administered the 5-Choice Continuous Performance Task and Probabilistic Learning Task, translational measures of control and learning respectively. Both groups will undergo functional neuroimaging and respond to adaptive versions of these tasks. The specific aims are to: (1) Determine whether adaptive testing improves the precision and effect size estimates of performance differences produced by RDoC tasks; and (2) Determine whether adaptive testing improves the reliability and effect size estimates of brain activation differences produced by RDoC tasks. While these aims are designed to evaluate a methodology, and to address critical concerns related to the use of RDoC working memory tasks as neural probes, mediators, and outcomes in psychosis research, results also have broad implications across populations, brain regions and networks, and cognitive domains. By addressing concerns of poor reliability, weak effect size, and brain activation confounds, this project will show that adaptive testing broadly improves cognitive neuroscience tasks. To facilitate rapid deployment of adaptive RDoC tasks, we will develop freely available versions of the paradigms used and a companion R package ‘catCog’.

项目摘要 作为研究领域标准（RDoC）倡议的一部分，NIMH寻求改善神经元的测量， 和心理学目标用于干预研究。RDoC工具必须精确地测量认知和 神经系统产生可靠的结果。不幸的是，许多RDoC任务尚未 心理测量评估，也不完善，并容易混淆，可能导致不准确的索赔， 差异性缺陷、效应量减弱和脑成像结果矛盾。如图所示， 18-930，迫切需要现代心理测量方法和工具，旨在支持认知和 临床神经科学研究。本项目通过评估和改进一种方法来响应FOA 设计用于管理RDoC任务的统计学上稳健的变体，特别是在脑成像的背景下。 我们已经创建了一种定量方法，旨在管理计算机化的适应性测试（CAT）， 认知和临床神经科学研究的背景。CAT在真实的时间内操纵刺激特性， 为了提高测量精度，避免天花板和地板的影响，并最大限度地发挥作用的大小，即使是 认知功能高度不一致的个体和群体。CAT还进行心理测量 调整认知任务，使大脑功能异常可以解释独立于 性能缺陷。在试点工作中，我们使用了这种方法与RDoC工作记忆任务，N- 这表明该方法提高了认知和大脑成像数据的可靠性。我们将 评估自适应测试在N-back任务之外用于翻译的普遍性和影响 和实验测试。精神分裂症患者和对照组将接受适应性和非适应性治疗。 用于评估工作记忆的四种RDoC范例的自适应版本：延迟匹配样本， 斯滕贝格，自序指向，和N-回。此外，参与者还将接受5项选择 持续绩效任务和概率学习任务，控制和学习的转化措施 分别两组都将接受功能性神经成像，并对这些适应性版本做出反应。 任务具体目的是：（1）确定自适应测试是否提高了精度和效应量 估计RDoC任务产生的性能差异;（2）确定自适应测试是否 提高了RDoC任务产生的大脑激活差异的可靠性和效应量估计。而 这些目标旨在评估一种方法，并解决与使用 RDoC工作记忆任务作为精神病研究中的神经探针、介质和结果， 对人群、大脑区域和网络以及认知领域都有广泛的影响。通过解决 担心可靠性差，效果大小弱，大脑激活混淆，这个项目将表明，自适应 测试广泛地改善了认知神经科学任务。为了促进自适应RDoC任务的快速部署， 我们将开发所用范式的免费版本和配套的R包'catCog'。