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Brain against the Machine (♫ and now you do what they told ya! ♫)


Traditionally, researchers from the natural sciences have dominated the study of neural networks in the brain. With methodologies stemming from physics and applied math, these studies usually follow bottom-up approaches, starting from first principles. Recently, the study of biological circuits through the use of artificial neural networks has gained momentum. Here, a network is trained to perform a chosen task or to optimize an outcome. The investigator then probes the learning solutions and asks what are the dynamical and structural properties, and how they relate to biological observations. The two programs of study may complement each other, and at times can be disparate.

The aim of this workshop is to confront traditional theories with the new insights gleaned from machine learning and deep learning. Each of the five sessions in the workshop will focus on one open question of neuroscience and will gather speakers using one of the two different approaches. We will conclude each session with a guided discussion with the speakers. The ultimate goal is to address the different approaches and how they can interact, rather than to extensively cover each problem.