To Explore the Predictive Power of Visuomotor Network Dysfunctions in Mild Cognitive Impairment and Alzheimer's Disease.

ABSTRACT:

Background

Research into Alzheimer's disease has shifted toward the identification of minimally invasive and less time-consuming modalities to define preclinical stages of Alzheimer's disease.

Method

Here, we propose visuomotor network dysfunctions as a potential biomarker in AD and its prodromal stage, mild cognitive impairment with underlying the Alzheimer's disease pathology. The functionality of this network was tested in terms of timing, accuracy, and speed with goal-directed eye-hand tasks. The predictive power was determined by comparing the classification performance of a zero-rule algorithm (baseline), a decision tree, a support vector machine, and a neural network using functional parameters to classify controls without cognitive disorders, mild cognitive impaired

SUBMITTER: Staal J 

PROVIDER: S-EPMC8273577 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature