By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
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.
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.
Covers the basics of brain connectomics, including brain networks, terminology, data schemes, preprocessing, node connectivity, and functional connectome structure.
Explores the importance of the hippocampus in memory and spatial navigation, discussing its unique structure and implications for broader brain research.
Explores brain network modules and community structure, including the natural modular functional connectome, network modularity, and community detection algorithms.
