Graph Neural Networks in Network Neuroscience

Istanbul Technical University · University of Sousse

PubMed
Indexed incrossrefpubmed

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

308
total citations
FWCI
31.12
Percentile
100%
References
136
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Neuroimaging
  • Neuroinformatics
  • Graph
  • Artificial intelligence
  • Systems neuroscience
  • Neuroscience
  • Power graph analysis
No related works found for this paper.