Qinglin Dong

Neuroscience · Life Sciences

19h-index968citations38works7.62yr avg
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Research Topics

Functional Brain Connectivity Studies(32), Neural dynamics and brain function(22), EEG and Brain-Computer Interfaces(20), Advanced Neuroimaging Techniques and Applications(13), Advanced MRI Techniques and Applications(6)

Publications37 total

Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network
UNC Libraries·2026Open Access
Normobaric hyperoxia combined with endovascular treatment for acute ischaemic stroke in China (OPENS-2 trial): a multicentre, randomised, single-blind, sham-controlled trial
The Lancet·2025· 19 cited
Deep learning in functional brain mapping and associated applications
Elsevier eBooks·2024
Contributors
Elsevier eBooks·2024
Functional brain network identification and fMRI augmentation using a VAE-GAN framework
Computers in Biology and Medicine·2023· 24 cited
A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks
Behavioural Brain Research·2023· 18 cited
Learning brain representation using recurrent Wasserstein generative adversarial net
Computer Methods and Programs in Biomedicine·2022· 16 cited
A novel ADHD classification method based on resting state temporal templates (RSTT) using spatiotemporal attention auto-encoder
Neural Computing and Applications·2022· 30 cited
Modeling and augmenting of fMRI data using deep recurrent variational auto-encoder
Journal of Neural Engineering·2021· 35 cited
Simultaneous spatial-temporal decomposition for connectome-scale brain networks by deep sparse recurrent auto-encoder
Brain Imaging and Behavior·2021· 16 cited
Deep Variational Autoencoder for Mapping Functional Brain Networks
IEEE Transactions on Cognitive and Developmental Systems·2020· 35 cited
Modeling task-based fMRI data via deep belief network with neural architecture search
Computerized Medical Imaging and Graphics·2020· 41 citedOpen Access
Deep Variational Autoencoder for Modeling Functional Brain Networks and ADHD Identification
2020· 16 cited
Task fMRI Guided Fiber Clustering via a Deep Clustering Method
2020· 4 cited
Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning
Brain Connectivity·2020· 24 citedOpen Access
Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification
Lecture notes in computer science·2020· 22 cited
A Novel fMRI Representation Learning Framework with GAN
Lecture notes in computer science·2020· 5 cited
Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)
Lecture notes in computer science·2020· 6 cited
Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data
Lecture notes in computer science·2019· 10 cited
Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network
IEEE Transactions on Biomedical Engineering·2019· 45 cited
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Frequent Co-authors

Tianming Liu(34), Ning Qiang(18), Shu Zhang(13), Bao Ge(12), Shijie Zhao(11), Yu Zhao(10), Heng Huang(9), Xintao Hu(9), Jinglei Lv(9), Fangfei Ge(8), Yifei Sun(8), Lei Guo(7), Xi Jiang(7), Hongtao Liang(7), Jie Gao(7), Xiang Li(5), Junwei Han(4), Qing Li(4), Milad Makkie(3), Hanbo Chen(3)