Structural connectivity enriched functional brain network using simplex regression with graphnet
The connectivity analysis is a powerful technique for investigating a hard-wired brain
architecture as well as flexible, functional dynamics tied to human cognition. Recent multi …
architecture as well as flexible, functional dynamics tied to human cognition. Recent multi …
Graph learning for brain imaging
Unprecedented collections of large-scale brain imaging data, such as MRI, PET, fMRI,
M/EEG, DTI, etc. provide a unique opportunity to deepen our understanding of the brain …
M/EEG, DTI, etc. provide a unique opportunity to deepen our understanding of the brain …
Deep graph normalizer: a geometric deep learning approach for estimating connectional brain templates
A connectional brain template (CBT) is a normalized graph-based representation of a
population of brain networks—also regarded as an 'average'connectome. CBTs are …
population of brain networks—also regarded as an 'average'connectome. CBTs are …
The Semi-constrained Network-Based Statistic (scNBS): Integrating Local and Global Information for Brain Network Inference
Functional connectomics has become a popular topic over the last two decades.
Researchers often conduct inference at the level of groups of edges, or “components", with …
Researchers often conduct inference at the level of groups of edges, or “components", with …
Comparative survey of multigraph integration methods for holistic brain connectivity mapping
One of the greatest scientific challenges in network neuroscience is to create a
representative map of a population of heterogeneous brain networks, which acts as a …
representative map of a population of heterogeneous brain networks, which acts as a …
Graph neural networks in network neuroscience
A Bessadok, MA Mahjoub… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Noninvasive medical neuroimaging has yielded many discoveries about the brain
connectivity. Several substantial techniques mapping morphological, structural and …
connectivity. Several substantial techniques mapping morphological, structural and …
Learning dynamic graph representation of brain connectome with spatio-temporal attention
Functional connectivity (FC) between regions of the brain can be assessed by the degree of
temporal correlation measured with functional neuroimaging modalities. Based on the fact …
temporal correlation measured with functional neuroimaging modalities. Based on the fact …
Adaptive Brain Network Augmentation Based on Group-aware Graph Learning
Brain network analysis significantly improves artificial intelligence techniques in the realm of
digital health. Most existing methods uniformly construct brain networks for different groups …
digital health. Most existing methods uniformly construct brain networks for different groups …
Brain dynamics via Cumulative Auto-Regressive Self-Attention
Multivariate dynamical processes can often be intuitively described by a weighted
connectivity graph between components representing each individual time-series. Even a …
connectivity graph between components representing each individual time-series. Even a …
Joint graph convolution for analyzing brain structural and functional connectome
Abstract The white-matter (micro-) structural architecture of the brain promotes synchrony
among neuronal populations, giving rise to richly patterned functional connections. A …
among neuronal populations, giving rise to richly patterned functional connections. A …