Rest2vec: Vectorizing the resting-state functional connectome using graph embedding.

ABSTRACT: Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used in connectomics for studying the functional relationships between regions of the human brain. rs-fMRI connectomics, however, has inherent analytical challenges, such as how to properly model negative correlations between BOLD time series. In addition, functional relationships between brain regions do not necessarily correspond to their anatomical distance, making the functional topology of the brain less well understood. Recent machine learning techniques, such as word2vec, have used embedding methods to map high-dimensional data into vector spaces, where words with more similar meanings are mapped closer to one another. Inspired by this approach, we have developed the graph embedding pipeline rest2vec for studyin

SUBMITTER: Morrissey ZD 

PROVIDER: S-EPMC7978175 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature