Principal component analysis to identify the major contributors to task-activated neurovascular responses.

ABSTRACT:

Background

Consensus on the optimal metrics for neurovascular coupling (NVC) is lacking. The aim of this study was to use principal component analysis (PCA) to determine the most significant contributors to NVC responses in healthy adults (HC), Alzheimer's disease (AD), and mild cognitive impairment (MCI).

New method

PCA was applied to three datasets: 1) 69 HC, 2) 30 older HC, 34 AD, and 22 MCI, 3) 1&2 combined. Data were extracted on peak percentage change in cerebral blood flow velocity (CBFv), variance ratio (VR), cross-correlation function peak (CCF), and blood pressure, for five cognitive tasks. An equamax rotation was applied and factors were significant where the eignevalue was ≥1. Rotated factor loadings ≥0.4 determined significant NVC variables.

Results

PCA i

SUBMITTER: Ball J 

PROVIDER: S-EPMC9616234 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature