Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.
Explores Graph Signal Processing applied to brain networks, emphasizing the relationship between brain function and structure using methods like Graph Fourier Transform and Structural-Decoupling Index.
Covers the basics of brain connectomics, including brain networks, terminology, data schemes, preprocessing, node connectivity, and functional connectome structure.
Explores brain network modules and community structure, including the natural modular functional connectome, network modularity, and community detection algorithms.
Discusses the definitions and assessment of consciousness levels through neuroimaging and brain networks, focusing on connICA for mapping functional connectome traits.
Delves into centrality and hubs in network neuroscience, exploring node importance, small-world networks, brain structural connectome, and percolation theory.
Explores the importance of the hippocampus in memory and spatial navigation, discussing its unique structure and implications for broader brain research.
