Braingb: a benchmark for brain network analysis with graph neural networks

H Cui, W Dai, Y Zhu, X Kan, AAC Gu… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Mapping the connectome of the human brain using structural or functional connectivity has
become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph …

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 …

Deep reinforcement learning guided graph neural networks for brain network analysis

X Zhao, J Wu, H Peng, A Beheshti, JJM Monaghan… - Neural Networks, 2022 - Elsevier
Modern neuroimaging techniques enable us to construct human brains as brain networks or
connectomes. Capturing brain networks' structural information and hierarchical patterns is …

Attention-diffusion-bilinear neural network for brain network analysis

J Huang, L Zhou, L Wang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Brain network provides essential insights in diagnosing many brain disorders. Integrative
analysis of multiple types of connectivity, eg, functional connectivity (FC) and structural …

Braingnn: Interpretable brain graph neural network for fmri analysis

X Li, Y Zhou, N Dvornek, M Zhang, S Gao… - Medical Image …, 2021 - Elsevier
Understanding which brain regions are related to a specific neurological disorder or
cognitive stimuli has been an important area of neuroimaging research. We propose …

Interpretable graph neural networks for connectome-based brain disorder analysis

H Cui, W Dai, Y Zhu, X Li, L He, C Yang - International Conference on …, 2022 - Springer
Human brains lie at the core of complex neurobiological systems, where the neurons,
circuits, and subsystems interact in enigmatic ways. Understanding the structural and …

Joint embedding of structural and functional brain networks with graph neural networks for mental illness diagnosis

Y Zhu, H Cui, L He, L Sun… - 2022 44th Annual …, 2022 - ieeexplore.ieee.org
Multimodal brain networks characterize complex connectivities among different brain
regions from both structural and functional aspects and provide a new means for mental …

Pooling regularized graph neural network for fmri biomarker analysis

X Li, Y Zhou, NC Dvornek, M Zhang, J Zhuang… - … Image Computing and …, 2020 - Springer
Understanding how certain brain regions relate to a specific neurological disorder has been
an important area of neuroimaging research. A promising approach to identify the salient …

GraphVar: a user-friendly toolbox for comprehensive graph analyses of functional brain connectivity

JD Kruschwitz, D List, L Waller, M Rubinov… - Journal of neuroscience …, 2015 - Elsevier
Background Graph theory provides a powerful and comprehensive formalism of global and
local topological network properties of complex structural or functional brain connectivity …

Learning dynamic graph representation of brain connectome with spatio-temporal attention

BH Kim, JC Ye, JJ Kim - Advances in Neural Information …, 2021 - proceedings.neurips.cc
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 …