Cognitive Performance and Learning Parameters Predict Response to Working Memory Training in Parkinson's Disease.

ABSTRACT:

Background

Working memory (WM) training (WMT) is a popular intervention approach against cognitive decline in patients with Parkinson's disease (PD). However, heterogeneity in WM responsiveness suggests that WMT may not be equally efficient for all patients.

Objective

The present study aims to evaluate a multivariate model to predict post-intervention verbal WM in patients with PD using a supervised machine learning approach. We test the predictive potential of novel learning parameters derived from the WMT and compare their predictiveness to other more commonly used domains including demographic, clinical, and cognitive data.

Methods

37 patients with PD (age: 64.09±8.56, 48.6% female, 94.7% Hoehn & Yahr stage 2) participated in a 5-week WMT. Four random forest regres

SUBMITTER: Ophey A 

PROVIDER: S-EPMC9661332 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature