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

摘要 加工速度训练（SOPT），练习提高信息处理效率， 执行各种知觉和认知任务，是最广泛的检查类型的计算机化认知训练 在老龄化人群中，包括轻度认知障碍（MCI）人群。然而，现有的 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 初步研究表明，自主神经系统的灵活性与学习有关 认知和神经增益在现有的SOPT与MCI的老年人。我们的前提是适应能力， 这主要反映在ANS的灵活性，是一个关键的贡献者，神经可塑性的基础广泛， 认知干预的持续效果。在这项拟议的研究中，我们将联合收割机这一ANS反应概况 与传统的学习索引开发一个“个性化引擎”，称为pSOPT，更好地 反映个人适应能力，并测试pSOPT的可行性（R21阶段）和初步 MCI中R33相的影响。在R21阶段（干预细化，阶段Ia），我们将建立一个 通过利用来自ANS的独特信息，为SOPT提供“个性化引擎” 与学习相关的评估，并测试MCI的可行性。高级时间序列数据分析 方法（例如，shapelet分析）将用于基于先前确定的 ANS shapelet。将通过访谈、问卷调查和 使用单组设计在患有MCI的老年人中记录性能数据（n = 10）。具体目标包括 (1)使用所识别的ANS shapelet来开发一个“个性化引擎”，该引擎可以根据 ANS的实时测量;（2）检查施用pSOPT的可行性。在R33阶段（中试， 阶段Ib），我们将测试pSOPT在MCI中的初步效果。一项试验性双盲随机 对照试验（RCT）。MCI组（N = 50）将被随机分配至6周pSOPT（n = 25）或关注组 对照组（n = 25）。将在整个训练过程中记录各组基于心脏监测器的ANS信号。 学习是通过在训练任务中的一组连续试验中准确地执行来索引的。认知功能成套测试 （测量认知增益）和基于BOLD fMRI的脑功能（测量神经增益）将在 基线、训练后（7周）和短期随访（3个月）;神经退行性病变（T1 MRI和血液- 基于阿尔茨海默病的病理学）。具体目的包括：（1）比较认知功能的变化， （2）探索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增益。这项研究是有效开展有效性试验的先决条件， pSOPT减缓痴呆症进展。

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.