Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset.

ABSTRACT: Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks.

SUBMITTER: Guo H 

PROVIDER: S-EPMC5717514 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature