Reproducibility of graph measures at the subject level using resting-state fMRI.
Qian RanTarik JamoulleJolien SchaeverbekeKaren MeersmansRik VandenberghePatrick DupontPublished in: Brain and behavior (2020)
Our results demonstrated that normalized global graph measures based on a weighted network using the absolute (partial) correlation as weight were reproducible. The denoising pipeline and the granularity of the whole-brain parcellation used to define the nodes were not critical for the reproducibility of normalized graph measures.
Keyphrases
- resting state
- functional connectivity
- convolutional neural network
- neural network
- body mass index
- magnetic resonance
- physical activity
- squamous cell carcinoma
- network analysis
- magnetic resonance imaging
- weight gain
- sentinel lymph node
- radiation therapy
- lymph node
- body weight
- white matter
- machine learning
- brain injury