Intraindividual Variability as an Indicator of Cognitive Function: Contrasting Operationalizations and Exploring Mechanisms

作为认知功能指标的个体差异：对比操作和探索机制

• 批准号: RGPIN-2017-06468
• 负责人: MacDonald, Stuart
• 金额: $ 2.04万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764074
• 关键词: Intraindividual; Variability; Indicator; Cognitive; Function

Most research focuses on average performance (how much faster or better does group A perform a task relative to Group B). Unfortunately, this mean-centric focus has overshadowed research on intraindividual variability (IIV) in performance, such as the fluctuations in how fast or slow a given individual responds across a series of response latency trials, or the variation in the cortical haemodynamic response function (i.e., neural complexity) when performing a task. Growing consensus from various scientific disciplines, including cognitive neuroscience, neuropsychology, and mathematical modeling, suggests that theoretically interesting aspects of cognitive function are not captured by the mean alone. To further our understanding of the characteristic patterns, underlying mechanisms, and correlates of IIV, this research program will: (1) employ and refine novel methodological and advanced quantitative approaches for measuring variability including the use of measurement burst research designs to facilitate indexing short-term (trial-to-trial) fluctuations and long-term (year-to-year) change for IIV in cognitive function, derive and contrast competing operationalizations of cognitive variability, and explore approaches for simultaneous modeling of mean and variability; (2) investigate novel definitions of variability in neural and physiological function (e.g., multiscale entropy for the neural activity signal indexed by NIRS and its superior temporal sampling properties; variability across temporal and spatial gait indicators), and examine these variability indices in relation to cognitive function; and (3) characterize potential mechanisms and processes underlying individual differences in variability by computing associations among cross-domain estimates of variability, by capitalizing on the strengths of the measurement burst design to examine the dynamic time-varying covariation for distinct variability signals and their corresponding impact on cognitive performance (e.g., is neural IIV systematically associated with cognition?), and to explore the malleability of IIV by assessing or manipulating key moderating factors including the impact of dual tasking (increasing cognitive load).Key advantages of this program include the adoption of an intensive measurement burst design, as well as the use of novel instrumentation already installed in my research laboratory including a GAITRite computerized walkway, as well as a functional near infrared spectroscopy (NIRS) system. The expected significance of this research program to the field of cognitive science lies in the improved understanding of optimal ways to measure and compute estimates of variability, ascertaining whether systematic changes in variability and cognition are associated, and furthering our understanding of the potential mechanisms underlying variability.

大多数研究都集中在平均表现上（A组相对于B组完成任务的速度或效果如何）。不幸的是，这种以平均值为中心的焦点已经掩盖了对表现中的个体内变异性（IIV）的研究，例如给定个体在一系列响应潜伏期试验中响应的快慢的波动，或者皮质血液动力学响应功能的变化（即，神经复杂性）执行任务时。认知神经科学、神经心理学和数学建模等多个科学学科的共识不断增加，这表明认知功能的理论上有趣的方面不仅仅是平均值。为了进一步了解IIV的特征模式，潜在机制和相关因素，本研究计划将：（1）采用和改进新的方法和先进的定量方法来测量变异性，包括使用测量突发研究设计，以促进短期指数化，（试验间）波动和长期（逐年）认知功能IIV的变化，推导并对比认知变异性的竞争性操作化，并探索用于同时建模平均值和变异性的方法;（2）研究神经和生理功能中变异性的新定义（例如，通过NIRS及其上级时间采样特性索引的神经活动信号的多尺度熵;跨时间和空间步态指标的变异性），并检查与认知功能相关的这些变异性指标;以及（3）通过计算变异性的跨域估计之间的关联来表征变异性中个体差异的潜在机制和过程，通过利用测量突发设计的强度来检查不同可变性信号的动态时变协变及其对认知性能的相应影响（例如，神经IIV是否与认知系统相关？），并通过评估或操纵关键调节因素（包括双重任务的影响（增加认知负荷））来探索IIV的可塑性。该计划的主要优势包括采用密集测量突发设计，以及使用我的研究实验室中已经安装的新型仪器，包括GAITRite计算机化走道，以及功能性近红外光谱（NIRS）系统。该研究计划对认知科学领域的预期意义在于提高对测量和计算变异性估计的最佳方法的理解，确定变异性和认知的系统性变化是否相关，并进一步了解变异性的潜在机制。