Reproducibility of graph measures at the subject level using resting-state fMRI.

ABSTRACT:

Introduction

Graph metrics have been proposed as potential biomarkers for diagnosis in clinical work. However, before it can be applied in a clinical setting, their reproducibility should be evaluated.

Methods

This study systematically investigated the effect of two denoising pipelines and different whole-brain network constructions on reproducibility of subject-specific graph measures. We used the multi-session fMRI dataset from the Brain Genomics Superstruct Project consisting of 69 healthy young adults.

Results

In binary networks, the test-retest variability for global measures was large at low density irrespective of the denoising strategy or the type of correlation. Weighted networks showed very low test-retest values (and thus a good reproducibility) for global

SUBMITTER: Ran Q 

PROVIDER: S-EPMC7428495 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature