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Explores the integration of brain structure and function using Graph Signal Processing techniques, including functional MRI and structural connectome analysis.
Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
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.
Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.
