Predicting brain structural network using functional connectivity
Uncovering the non-trivial brain structure–function relationship is fundamentally important
for revealing organizational principles of human brain. However, it is challenging to infer a …
for revealing organizational principles of human brain. However, it is challenging to infer a …
Recovering brain structural connectivity from functional connectivity via multi-gcn based generative adversarial network
Understanding brain structure-function relationship, eg, the relations between brain
structural connectivity (SC) and functional connectivity (FC), is critical for revealing …
structural connectivity (SC) and functional connectivity (FC), is critical for revealing …
Brain functional connectivity analysis via graphical deep learning
Objective: Graphical deep learning models provide a desirable way for brain functional
connectivity analysis. However, the application of current graph deep learning models to …
connectivity analysis. However, the application of current graph deep learning models to …
Attention-diffusion-bilinear neural network for brain network analysis
Brain network provides essential insights in diagnosing many brain disorders. Integrative
analysis of multiple types of connectivity, eg, functional connectivity (FC) and structural …
analysis of multiple types of connectivity, eg, functional connectivity (FC) and structural …
Brain multigraph prediction using topology-aware adversarial graph neural network
Brain graphs (ie, connectomes) constructed from medical scans such as magnetic
resonance imaging (MRI) have become increasingly important tools to characterize the …
resonance imaging (MRI) have become increasingly important tools to characterize the …
Deep fusion of brain structure-function in mild cognitive impairment
abstract Multimodal fusion of different types of neural image data provides an irreplaceable
opportunity to take advantages of complementary cross-modal information that may only …
opportunity to take advantages of complementary cross-modal information that may only …
Modeling spatio-temporal patterns of holistic functional brain networks via multi-head guided attention graph neural networks (Multi-Head GAGNNs)
Mounting evidence has demonstrated that complex brain function processes are realized by
the interaction of holistic functional brain networks which are spatially distributed across …
the interaction of holistic functional brain networks which are spatially distributed across …
Constructing brain functional network by adversarial temporal-spatial aligned transformer for early AD analysis
Q Zuo, L Lu, L Wang, J Zuo, T Ouyang - Frontiers in neuroscience, 2022 - frontiersin.org
Introduction The brain functional network can describe the spontaneous activity of nerve
cells and reveal the subtle abnormal changes associated with brain disease. It has been …
cells and reveal the subtle abnormal changes associated with brain disease. It has been …
Predicting cognitive scores with graph neural networks through sample selection learning
Analyzing the relation between intelligence and neural activity is of the utmost importance in
understanding the working principles of the human brain in health and disease. In existing …
understanding the working principles of the human brain in health and disease. In existing …
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 …