The brain is both a structural and functional network
3
Exploring the brain using networks analysis: pipeline
4
Usual graph statistics
5
Comparisons of healthy volunteers and patients
6
Graph comparisons: other methods
7
Graph comparisons: new methods needed
8
Nodal statistics-based structural pattern on single graph
9
Nodal structural roles
10
Structural patterns for graph collections characterization
11
Results: PC for different sparsity graph models
12
Results of orthogonality on simulated WS and BA models
13
Illustrations of classification on orthogonality curves
14
Conclusion and future work
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Explore statistical comparisons of spatio-temporal networks in this 49-minute conference talk by Sophie Achard at the Centre International de Rencontres Mathématiques in Marseille, France. Delve into brain network analysis, comparing healthy volunteers and patients using graph statistics. Learn about new methods for graph comparisons, including nodal statistics-based structural patterns and structural roles. Examine results from PC models with varying sparsity and orthogonality in simulated Watts-Strogatz and Barabási–Albert models. Discover applications in classification using orthogonality curves. Gain insights into the future of network analysis in neuroscience through this comprehensive presentation on machine learning and signal processing on graphs.
Statistical Comparisons of Spatio-Temporal Networks - Sophie Achard