Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.
Covers the basics of brain connectomics, including brain networks, terminology, data schemes, preprocessing, node connectivity, and functional connectome structure.
Discusses the definitions and assessment of consciousness levels through neuroimaging and brain networks, focusing on connICA for mapping functional connectome traits.
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.
Explores higher-order interactions in brain networks using simplicial complexes and information theory, analyzing data from fMRI, financial time-series, and infectious diseases.
Explores brain network modules and community structure, including the natural modular functional connectome, network modularity, and community detection algorithms.
Explores dynamic functional connectivity methods in fMRI, emphasizing the identification of multiple brain states and their applications in understanding brain disorders.
Covers the basics of networks, focusing on brain networks, historical breakthroughs, small-world and scale-free network discoveries, and the importance of the human connectome.
