Representation learning of resting state fMRI with variational autoencoder

Representation learning of resting state fMRI with variational autoencoder

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 disentang...

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Bibliographic Details
Main Authors: Jung-Hoon Kim, Yizhen Zhang, Kuan Han, Zheyu Wen, Minkyu Choi, Zhongming Liu
Format: Article
Language:English
Published: Elsevier 2021-11-01
Series:NeuroImage
Subjects:
Variational autoencoder
Deep generative model
Unsupervised learning
Latent gradients
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811921006984

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http://www.sciencedirect.com/science/article/pii/S1053811921006984

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