Serial Reaction Time Task Performance in Older Adults with Neuropsychologically Defined Mild Cognitive Impairment

被引:9
作者
Hong, Yue [1 ,2 ,3 ]
Alvarado, Rachel L. [2 ,3 ,4 ]
Jog, Amod [5 ]
Greve, Douglas N. [6 ,7 ,8 ]
Salat, David H. [2 ,3 ,8 ,9 ]
机构
[1] Home Base, Boston, MA USA
[2] Massachusetts Gen Hosp, Brain Aging & Dementia BAnD Lab, Dept Radiol, Charlestown, MA USA
[3] Massachusetts Gen Hosp, MGH MIT HMS Athinoula A Martinos Ctr Biomed Imagi, Charlestown, MA USA
[4] Emory Univ, Rollins Sch Publ Hlth, Atlanta, GA 30322 USA
[5] IBM Watson Hlth, Cambridge, MA USA
[6] Massachusetts Gen Hosp, Lab Computat Neuroimaging, Charlestown, MA USA
[7] Massachusetts Gen Hosp, MGH MIT HMS Athinoula Martinos Ctr Biomed Imaging, Dept Radiol, Charlestown, MA USA
[8] Harvard Med Sch, Boston, MA 02115 USA
[9] VA Boston Healthcare Syst, Neuroimaging Res Vet NeRVe Ctr, Boston, MA USA
基金
美国国家卫生研究院;
关键词
Aging; implicit learning; mild cognitive impairment; response speed; supervised machine learning; ALZHEIMERS ASSOCIATION WORKGROUPS; DIAGNOSTIC GUIDELINES; NATIONAL INSTITUTE; DISEASE; MCI; RECOMMENDATIONS; MEMORY;
D O I
10.3233/JAD-191323
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: 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. Objective: 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. Method: Participants were 22 cognitively healthy older adults and 20 older adults withMCIconfirmed 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. Results: 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%. Conclusions: 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.
引用
收藏
页码:491 / 500
页数:10
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