Article

Representation Learning of Resting State fMRI with Variational Autoencoder

2020-06-18

Abstract excerpt

Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rsfMRI activity. After being trained with large data from the Human Connectome Project, the...

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Literature Corpus work: 0c128323-30af-5692-8b01-71af7084f786
DOI: 10.1101/2020.06.16.155937

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