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Computational Neuroscience explores brain function through mathematical modeling across scales, from molecules and cells to entire systems. Scientists in this field create simulations to decipher how neural networks process information. Breakthroughs in computational neuroscience have significantly advanced our knowledge of neurological mechanisms, notably exemplified by Hodgkin and Huxley's Nobel Prize-winning research on action potentials. Our graduate program excels in this discipline. At the University of Minnesota, labs specializing in computational analysis of neural systems typically maintain robust experimental programs to support their modeling work. These research groups frequently concentrate on behavioral and cognitive neuroscience topics. The university offers annual Computational Neuroscience courses covering both cellular-level models and broader systems-level information processing.