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Modeling Hierarchical Functional Brain Networks via L2 -Normalized Fully Convolutional Recurrent Attention Autoencoder for Multi-task fMRI Data

2024-10-21

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<title>Abstract</title> <p>Modeling functional brain networks is essential for revealing the functional mechanisms of the human brain. Deep Neural Network (DNN) models have widely been employed for extracting multi-scale spatiotemporal features from functional Magnetic Resonance Imaging (fMRI) data. Nonetheless, existing DNN approaches often struggle with capturing generic temporal features across diverse tasks d...

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Literature Corpus work: 74ae388a-d027-5ed4-82cf-cfb1223affcb
DOI: 10.21203/rs.3.rs-5275268/v1

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