Computational and Applied Math Seminar 3:00 PM MSCS 514
Mathematics in Neuroscience: From numerical methods to machine learning in brain health Pedro D. Maia, University Texas at Arlington Host: Lucas Stolerman
Abstract: The emerging field of computational neurology provides an important window of opportunity for modeling of complex biophysical phenomena, for scientific computing, for understanding functionality disruption in neural networks, and for applying machine-learning methods for diagnosis and personalized medicine. In this talk, I will illustrate some of our latest results across different spatial scales spanning a broad array of mathematical techniques such as: (i) numerical methods for nonlinear PDEs for solving inhomogeneous active cable equations, (ii) spike-train metrics for quantifying information loss on compromised neural signals, (iii) applied dynamical systems for modeling biological neural networks, (iv) decision-making models, (v) applied inverse-problem techniques for finding the origins of neurodegeneration, and (vi) data methods in medical imaging.
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