Covers the definition of flow in a network and flow calculation.
Explores graph theory concepts, centrality measures, and real-world network properties, providing insights into handling diverse types of networks.
Explores brain node connectivity, node degree, strength, random networks, power law distributions, and the complexity of real networks.
Explores centrality, hubs, eigenvectors, clustering coefficients, small-world networks, network failures, and percolation theory in brain networks.
Explores neuronal connectivity patterns, connection probabilities, and experimental techniques used to study synaptic connectivity.
