By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores brain network modules and community structure, including the natural modular functional connectome, network modularity, and community detection algorithms.
Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.
Explores brain development, from neurulation to adult neurogenesis, emphasizing the influence of environmental factors and the potential impact on memory and brain recovery.
Explores the control of movement, motor cortex characteristics, mirror neurons, brain-machine interfaces, and the role of basal ganglia in movement initiation and suppression.
Explores the development of a mathematical model of the brain, focusing on brain organization and dynamics, including neuronal activity patterns and emergent phenomena.
Covers the basics of brain connectomics, including brain networks, terminology, data schemes, preprocessing, node connectivity, and functional connectome structure.
