Topics in Theoretical Biophysics


What can Deep Learning teach us about the Brain? What can Artificial Intelligence in Neural Networks teach us about the functioning of Natural Intelligence in Brains? What can Computational Neuroscience teach us about the functioning of Artificial Intelligence in Neural Networks? Do the mechanisms of Artificial Intelligence in deep networks serve as a framework for the investigation of Natural Intelligence in evolved brains? Deep Neural Networks (DNNs) have revolutionized Machine Learning and Artificial Intelligence. These networks have recently found their way back into computational neuroscience. DNNs reach human-level performance in certain tasks. Importantly, DNNs can display certain characteristics of brain function that cannot be captured with shallow handcrafted models. With this, DNNs offer an intriguing novel framework that may enable computational neuroscientists to address fundamental questions concerning complexity and neural computation in brains. In this course we will evaluate the tantalizing hypothesis that DNNs can serve as a tool to understand aspects of brain function, thus moving closer towards an understanding of both, natural and artificial intelligence. The course will be organized around 15 key papers illustrating major ideas of DNNs and computational neuroscience. Background material will be provided.
Course Attributes: BU SCI; AS NSM

Section 01

Topics in Theoretical Biophysics
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Ralf Wessel

Ralf Wessel

Professor of Physics