Graph Neural Networks in Network Neuroscience
Istanbul Technical University · University of Sousse
Abstract
Noninvasive medical neuroimaging has yielded many discoveries about the brain connectivity. Several substantial techniques mapping morphological, structural and functional brain connectivities were developed to create a comprehensive road map of neuronal activities in the human brain -namely brain graph. Relying on its non-euclidean data type, graph neural network (GNN) provides a clever way of learning the deep graph structure and it is rapidly becoming the state-of-the-art leading to enhanced performance in various network neuroscience tasks. Here we review current GNN-based methods, highlighting the ways that they have been used in several applications related to brain graphs such as missing brain graph…
Citation impact
- FWCI
- 31.12
- Percentile
- 100%
- References
- 136
Authors
3Topics & keywords
- Computer science
- Neuroimaging
- Neuroinformatics
- Graph
- Artificial intelligence
- Systems neuroscience
- Neuroscience
- Power graph analysis