Develop an ANS-based Personalized Cognitive Training for Mild Cognitive Impairment

摘要 处理速度训练(SOPT)，练习在提高信息处理效率的同时 执行各种感知和认知任务，是被检查最广泛的计算机认知训练类型 在老龄化人群中，包括轻度认知障碍(MCI)的人群。然而，现有的药效 SOPT在维持或改善老年人认知健康方面的作用因人而异。我们的 初步研究表明，自主神经系统(Ans)的灵活性与学习有关。 在患有MCI的老年人中，现有SOPT的认知和神经收益。我们的前提是适应能力， 这主要反映在ANS的灵活性上，是广泛和潜在的神经可塑性的关键因素。 认知干预的持续效果。在这项拟议的研究中，我们将结合这一ANS响应配置文件 利用传统的学习索引开发了一个名为pSOPT的个性化引擎，做得更好 反映个人适应能力，并测试pSOPT的可行性(R21阶段)和初步 MCI的疗效(R33期)。在R21阶段(干预改进，阶段Ia)，我们将建立一个 通过利用从ANS派生的独特信息为SOPT提供“个性化引擎” 与学习挂钩的评估，并测试在MCI中的可行性。高级时间序列数据分析 将使用各种方法(例如形状分析)来开发基于先前确定的pSOPT原型 Ans Shapeet。将通过访谈、问卷调查和 在患有MCI的老年人(n=10)中，采用单组设计记录操作数据。具体目标包括 (1)使用识别的ANS形状开发一个可以根据以下条件调整Sopt的“个性化引擎” ANS的实时测量；(2)检查实施pSOPT的可行性。在R33阶段(试运行， 阶段I)，我们将测试pSOPT在MCI中的初步效果。一种随机双盲试验 对照试验(RCT)。MCI组(N=50)将随机进入为期6周的pSOPT(n=25)，或注意 对照组(n=25)。基于心脏监测器的ANS信号将在整个训练过程中跨组记录。 学习是通过在训练任务中的一组连续试验中准确执行来索引的。认知电池 (测量认知收益)和基于BOLD功能磁共振成像的脑功能(测量神经收益)将在 基线、训练后(7周)和短期随访(3个月)；神经变性(T1MRI和血液- 基于阿尔茨海默氏病的病理)在基线上进行评估。具体目标包括(1)比较认知变化 (2)探讨pSOPT是否会增强ANS在支持认知方面的灵活性 相对于基线神经退行性变的收益。这项研究是有效开展药效试验的先决条件。 PSOPT在减缓痴呆症进展方面的作用。

Abstract Speed of processing training (SOPT), practicing to enhance the information processing efficiency while performing various perceptual and cognitive tasks, is the widest examined type computerized cognitive training among aging populations, including those with mild cognitive impairment (MCI). However, the efficacy of existing SOPTs in maintaining or improving older adults' cognitive health greatly varies across individuals. Our preliminary studies identified that the flexibility of autonomic nervous system (ANS) is associated with learning and cognitive and neural gains in existing SOPT in older adults with MCI. Our premise is that adaptation capacity, which is primarily reflected by ANS flexibility, is a key contributor to the neuroplasticity underlying broad and sustained effects of cognitive interventions. In this proposed study, we will combine this ANS response profile with the traditional learning index to develop a “personalization engine”, called pSOPT, for better reflecting individual adaptation capacity, and to test pSOPT's feasibility (R21 phase) and preliminary effect (R33 phase) in MCI. In R21 phase (intervention refinement, Stage Ia), we will establish a “personalization engine” for the SOPT by taking advantage of unique information derived from ANS assessment that links to learning and test the feasibility in MCI. Advanced time-series data analysis methods (e.g., shapelet analysis) will be used to develop a prototype of pSOPT based on the previously identified ANS shapelet. Compliance and usability of the pSOPT will be examined using interviews, questionnaires, and recorded performance data using a single group design in older adults with MCI (n = 10). Specific aims include (1) Use the identified ANS shapelet to develop a “personalization engine” that can modulate SOPT according to real-time measures of ANS; (2) Examine the feasibility of administering the pSOPT. In R33 phase (pilot test, Stage Ib), we will test the preliminary effects of the pSOPT in MCI. A pilot double-blinded randomized controlled trial (RCT). An MCI group (N = 50) will be randomized into a 6-week pSOPT (n = 25), or attention control (n = 25). Cardiac monitor-based ANS signals will be recorded throughout training sessions across groups. Learning is indexed by performing accurately across a consecutive set of trials in training tasks. Cognitive battery (measuring cognitive gains) and BOLD fMRI-based brain function (measuring neural gains) will be assessed at baseline, post training (7-week), and short-term follow-up (3-month); neurodegeneration (T1MRI and blood- based Alzheimer's pathology) assessed at baseline. Specific aims include (1) Compare changes of cognitive and neural gains between groups; (2) Explore whether pSOPT will enhance ANS flexibility in supporting cognitive gains against baseline neurodegeneration. This study is a prerequisite to efficiently launch an efficacy trial of pSOPT in slowing dementia progress.