Variational autoencoder: An unsupervised model for encoding and decoding fMRI activity in visual cortex-Reference-Cited by-同舟云学术

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Variational autoencoder: An unsupervised model for encoding and decoding fMRI activity in visual cortex

Published:2019-09 Issue: Volume:198 Page:125-136
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Han Kuan,Wen Haiguang,Shi Junxing,Lu Kun-Han,Zhang Yizhen,Fu Di,Liu Zhongming

Funder

NIH

College of Engineering at Purdue University

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference82 articles.

1. Increasing the reliability of data analysis of functional magnetic resonance imaging by applying a new blockwise permutation method;Adolf;Front. Neuroinf.,2014

2. Retinotopic organization of human ventral visual cortex;Arcaro;J. Neurosci.,2009

3. Unsupervised learning;Barlow;Neural Comput.,1989

4. Canonical microcircuits for predictive coding;Bastos;Neuron,2012

5. CircStat: a MATLAB toolbox for circular statistics;Berens;J. Stat. Softw.,2009

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