By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores neuroimaging basics, brain network scales, connectivity, history, and physics, emphasizing the importance of understanding data at different scales.
Discusses the challenges and future of neuromorphic computing, comparing digital computers and specialized hardware, such as SpiNNaker and NEST, while exploring the Human Brain Project's Neuromorphic Computing Platform.
Explores brain network modules and community structure, including the natural modular functional connectome, network modularity, and community detection algorithms.
Covers the caveats and summary of Simulation Neuroscience, emphasizing the importance of critical data and the three fundamental approaches to understanding the brain.
