Random Segmentation Based Principal Component Analysis to Remove Residual MR Gradient Artifact in the Simultaneous EEG/fMRI: A Preliminary Study. - Hyun-Chul Kim 002; Jong-Hwan Lee (ICONIP (3), 2013)

Desynchronization of the mu oscillatory activity during motor imagery: A preliminary EEG-fMRI study. - Hyun-Chul Kim 002; Jong-Hwan Lee (BCI, 2015)

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data. - Hyun-Chul Kim 002; Seung-Schik Yoo; Jong-Hwan Lee (NeuroImage, 2015)

Evaluation of weight sparsity control during autoencoder training of resting-state fMRI using non-zero ratio and hoyer's sparseness. - Hyun-Chul Kim 002; Jong-Hwan Lee (PRNI, 2016)

Evaluation of weight sparsity regularizion schemes of deep neural networks applied to functional neuroimaging data. - Hyun-Chul Kim 002; Jong-Hwan Lee (ICASSP, 2017)

3D convolutional neural network for feature extraction and classification of fMRI volumes. - Hanh Vu; Hyun-Chul Kim 002; Jong-Hwan Lee (PRNI, 2018)

Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging. - Hyun-Chul Kim 002; Peter A. Bandettini; Jong-Hwan Lee (NeuroImage, 2019)

Mediation analysis of triple networks revealed functional feature of mindfulness from real-time fMRI neurofeedback. - Hyun-Chul Kim 002; Marion Tegethoff; Gunther Meinlschmidt; Esther Stalujanis; Angelo Belardi; Sungman Jo; Juhyeon Lee; Dong-Youl Kim; Seung-Schik Yoo; Jong-Hwan Lee (NeuroImage, 2019)

A naturalistic viewing paradigm using 360° panoramic video clips and real-time field-of-view changes with eye-gaze tracking. - Hyun-Chul Kim 002; Sangsoo Jin; Sungman Jo; Jong-Hwan Lee (NeuroImage, 2020)

fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations. - Hanh Vu; Hyun-Chul Kim 002; Minyoung Jung; Jong-Hwan Lee (NeuroImage, 2020)