Hierarchical dynamic graph convolutional network with interpretability for EEG-based emotion recognition
Graph convolutional networks (GCNs) have shown great prowess in learning topological
relationships among electroencephalogram (EEG) channels for EEG-based emotion …
relationships among electroencephalogram (EEG) channels for EEG-based emotion …
Deep spatial-temporal feature fusion from adaptive dynamic functional connectivity for MCI identification
Dynamic functional connectivity (dFC) analysis using resting-state functional Magnetic
Resonance Imaging (rs-fMRI) is currently an advanced technique for capturing the dynamic …
Resonance Imaging (rs-fMRI) is currently an advanced technique for capturing the dynamic …
[HTML][HTML] Brain encoding and decoding in fMRI with bidirectional deep generative models
Brain encoding and decoding via functional magnetic resonance imaging (fMRI) are two
important aspects of visual perception neuroscience. Although previous researchers have …
important aspects of visual perception neuroscience. Although previous researchers have …
fmri brain decoding and its applications in brain–computer interface: A survey
Brain neural activity decoding is an important branch of neuroscience research and a key
technology for the brain–computer interface (BCI). Researchers initially developed simple …
technology for the brain–computer interface (BCI). Researchers initially developed simple …
A survey on brain effective connectivity network learning
Human brain effective connectivity characterizes the causal effects of neural activities
among different brain regions. Studies of brain effective connectivity networks (ECNs) for …
among different brain regions. Studies of brain effective connectivity networks (ECNs) for …
Foreground-attention in neural decoding: Guiding Loop-Enc-Dec to reconstruct visual stimulus images from fMRI
K Chen, Y Ma, M Sheng… - 2022 International Joint …, 2022 - ieeexplore.ieee.org
The reconstruction of visual stimulus images from functional Magnetic Resonance Imaging
(fMRI) has received extensive attention in recent years, which provides a possibility to …
(fMRI) has received extensive attention in recent years, which provides a possibility to …
AECA: An ambiguous-entropy clustering algorithm for the analysis of resting-state fMRISs of human brain and their functional connections
The ambiguous set theory has recently been introduced to characterize ambiguities inherent
in information. Based on ambiguous set and ambiguous entropy (AE), this study presents a …
in information. Based on ambiguous set and ambiguous entropy (AE), this study presents a …
Images structure reconstruction from fmri by unsupervised learning based on vae
How to reconstruct the stimulus images from fMRI signals is an important problem in the field
of neuroscience. Limited by the complexity and the acquisition accuracy of brain signals, it is …
of neuroscience. Limited by the complexity and the acquisition accuracy of brain signals, it is …
Investigation of local white matter properties in professional chess player: a diffusion magnetic resonance imaging study based on automatic annotation fiber …
Y Feng, J Song, W Yan, J Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article investigates whether the white matter (WM) anatomical changes exist in the brain
of professional chess players. Diffusion magnetic resonance imaging (dMRI) and fiber …
of professional chess players. Diffusion magnetic resonance imaging (dMRI) and fiber …
Dynamic Pathway Selection Mechanisms of Brain Networks
Y Chen, Y Hu, J Liu, Y Wang, A Li - Applied Sciences, 2022 - mdpi.com
Based on the dynamic reorganization mechanism of brain science and the fact that synaptic
adaptability is affected by synaptic type, synaptic number and ion concentration, a bionic …
adaptability is affected by synaptic type, synaptic number and ion concentration, a bionic …