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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=658248
• 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绩效上(相对于B组，A组完成一项任务的速度要快或好多少)。不幸的是，这种以均值为中心的关注掩盖了对绩效中个体内变异性(IIV)的研究，例如在一系列反应潜伏期试验中，给定个体反应的快或慢的波动，或者执行任务时皮质血流动力学反应功能的变化(即神经复杂性)。包括认知神经科学、神经心理学和数学建模在内的各个科学学科越来越多的共识表明，从理论上讲，认知功能的有趣方面并不是仅仅通过平均数来捕捉的。为了加深我们对IIV的特征模式、潜在机制和相关因素的理解，本研究计划将：(1)使用和改进新的方法和先进的量化方法来测量变异性，包括使用测量突发研究设计来促进IIV在认知功能中的短期(试验到试验)波动和长期(年复一年)变化的索引，推导和对比认知变异性的竞争性操作，并探索同时模拟平均值和变异性的方法；(2)研究神经和生理功能变异性的新定义(例如，NIRS索引的神经活动信号的多尺度熵及其优越的时间采样特性；跨时间和空间步态指标的变异性)，并检验这些变异性指数与认知功能的关系；和(3)通过计算变异性的跨域估计之间的关联来表征潜在的机制和过程，通过利用测量突发设计的优势来检查不同变异性信号的动态时变协变及其对认知表现的相应影响(例如，神经IIV是否系统地与认知相关？)，并通过评估或操纵包括双重任务的影响(增加认知负荷)的关键调节因素来探索IIV的延展性。*该计划的主要优点包括采用密集的测量突发设计，以及我的研究实验室中已经安装的新型仪器的使用，包括GAITRite计算机化走道以及功能性近红外光谱(NIRS)系统。这一研究计划对认知科学领域的预期意义在于更好地理解了测量和计算变异性的最佳方法，确定了变异性和认知的系统性变化是否相关，并进一步了解了潜在的变异性机制。