Hong Yue, Alvarado Rachel L, Jog Amod, Greve Douglas N, Salat David H
Home Base, A Red Sox Foundation and Massachusetts General Hospital Program, Boston, MA, USA.
Department of Radiology, Brain Aging and Dementia (BAnD) Laboratory; MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
J Alzheimers Dis. 2020;74(2):491-500. doi: 10.3233/JAD-191323.
Studies have found that individuals with mild cognitive impairment (MCI) exhibit a range of deficits outside the realm of primary explicit memory, yet the role of response speed and implicit learning in older adults with MCI have not been established.
The current study aims to explore and document response speed and implicit learning in older adults with neuropsychologically defined MCI using a simple serial reaction (SRT) task. In addition, the study aims to explore the feasibility of a novel utilization of the simple cognitive task using machine learning procedures as a proof of concept.
Participants were 22 cognitively healthy older adults and 20 older adults with MCI confirmed through comprehensive neuropsychological evaluation. Two-sample t-test, multivariate regression, and mixed-effect models were used to investigate group difference in response speed and implicit learning on the SRT task. We also explored the potential utility of SRT feature analysis through random forest classification.
With demographic variables controlled, the MCI group showed overall slower reaction time and higher error rate compared to the cognitively healthy volunteers. Both groups showed significant simple motor learning and implicit learning. The learning patterns were not statistically different between the two groups. Random forest classification achieved overall accuracy of 80.9%.
Individuals with MCI demonstrated slower reaction time and higher error rate compared to cognitively healthy volunteers but demonstrated largely preserved motor learning and implicit sequence learning. Preliminary results from random forest classification using features from SRT performance supported further research in this area.
研究发现，轻度认知障碍（MCI）个体在主要的外显记忆领域之外还表现出一系列缺陷，但反应速度和内隐学习在患有MCI的老年人中的作用尚未明确。
本研究旨在使用简单序列反应（SRT）任务，探索并记录经神经心理学定义为MCI的老年人的反应速度和内隐学习情况。此外，本研究旨在探索将简单认知任务与机器学习程序进行创新性结合作为概念验证的可行性。
参与者包括22名认知健康的老年人和20名经全面神经心理学评估确诊为MCI的老年人。使用两样本t检验、多元回归和混合效应模型来研究两组在SRT任务中反应速度和内隐学习的差异。我们还通过随机森林分类探索了SRT特征分析的潜在效用。
在控制人口统计学变量后，与认知健康的志愿者相比，MCI组的总体反应时间较慢，错误率较高。两组均表现出显著的简单运动学习和内隐学习。两组之间的学习模式在统计学上没有差异。随机森林分类的总体准确率达到80.9%。
与认知健康的志愿者相比，患有MCI的个体反应时间较慢，错误率较高，但在很大程度上保留了运动学习和内隐序列学习能力。使用SRT表现特征进行随机森林分类的初步结果支持了该领域的进一步研究。
