[HTML][HTML] A comprehensive survey of complex brain network representation
Recent years have shown great merits in utilizing neuroimaging data to understand brain
structural and functional changes, as well as its relationship to different neurodegenerative …
structural and functional changes, as well as its relationship to different neurodegenerative …
Community graph convolution neural network for alzheimer's disease classification and pathogenetic factors identification
XA Bi, K Chen, S Jiang, S Luo, W Zhou… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
As a complex neural network system, the brain regions and genes collaborate to effectively
store and transmit information. We abstract the collaboration correlations as the brain region …
store and transmit information. We abstract the collaboration correlations as the brain region …
Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns
J Casas-Roma, E Martinez-Heras… - Network …, 2022 - direct.mit.edu
In recent years, research on network analysis applied to MRI data has advanced
significantly. However, the majority of the studies are limited to single networks obtained …
significantly. However, the majority of the studies are limited to single networks obtained …
Topological data analysis for multivariate time series data
Over the last two decades, topological data analysis (TDA) has emerged as a very powerful
data analytic approach that can deal with various data modalities of varying complexities …
data analytic approach that can deal with various data modalities of varying complexities …
Graph autoencoder-based embedded learning in dynamic brain networks for autism spectrum disorder identification
Recent applications of pattern recognition techniques to brain connectome-based
classification focus on static functional connectivity (FC) neglecting the dynamics of FC over …
classification focus on static functional connectivity (FC) neglecting the dynamics of FC over …
Gated graph convolutional network based on spatio-temporal semi-variogram for link prediction in dynamic complex network
Link prediction is one of the most important methods to uncover evolving mechanisms of
dynamic complex networks. Determining these links raises well-known technical challenges …
dynamic complex networks. Determining these links raises well-known technical challenges …
Alertness estimation using connection parameters of the brain network
M Wang, C Ma, Z Li, S Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Alertness mechanism of unmanned monitoring vehicles to environment is important.
Especially, the vigilance modeling of underground security robots has a particularly …
Especially, the vigilance modeling of underground security robots has a particularly …
Dynamic community detection for brain functional networks during music listening with block component analysis
The human brain can be described as a complex network of functional connections between
distinct regions, referred to as the brain functional network. Recent studies show that the …
distinct regions, referred to as the brain functional network. Recent studies show that the …
Approximate bayesian computation for panel data with signature maximum mean discrepancies
Simulation models are becoming a staple tool across application domains from economics
to biology. When such models are stochastic, evaluating their likelihood functions in a …
to biology. When such models are stochastic, evaluating their likelihood functions in a …