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Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Explores the mathematical framework and challenges of modeling neurons, discussing passive and active membrane mechanisms and the representation of the membrane as an electrical circuit.
Explores higher-order interactions in brain networks using simplicial complexes and information theory, analyzing data from fMRI, financial time-series, and infectious diseases.