Wulfram Gerstner

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Computational Neuroscience Laboratory

Web site:  Web site:  https://sin.epfl.ch

Web site:  Web site:  https://ssc.epfl.ch

Administrative data

Fields of expertise

 Computational Neuroscience, Theoretical Neuroscience


Selected publications

Teaching & PhD


Computer Science

Life Sciences Engineering
Communication Systems


Learning in neural networks

Artificial Neural Networks are inspired by Biological Neural Networks. One big difference is that optimization in Deep Learning is done with the BackProp Algorithm, whereas in biological neural networks it is not. We show what biologically plausible learning algorithms can do (and what not).

Computational neurosciences: neuronal dynamics

In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by deterministic or stochastic differential equations.