The award winner and his research

Wulfram Gerstner studies spiking neural networks (SNN), in which neurons communicate with each other by means of short pulses (action potentials or 'spikes'), similar to real biological neural networks.

Gerstner is a pioneer. With his theoretical modelling, he proposed hypotheses early on, which could only later be experimentally confirmed. His research on synaptic plasticity ("spike-timing dependent plasticity" (STDP)), the adaptability of the contact points between nerve cells, is outstanding. This property is at the basis of neuronal learning. In one of his first studies, Gerstner contributed decisively to the understanding of the activity-dependent development of a biological nervous system using the auditory system of the barn owl as an example.

Recent work of his research group investigates the interface between learning processes in artificial neural networks and learning in biological neural networks, using an artificial network that learns to compose music as an example.

Wulfram Gerstner was one of the first scientists to introduce benchmarks for neuron models in computational neuroscience by comparing their response to a specific input stimulus to a well-defined set of experimental data. As a result, it was possible to simplify models of neural networks considerably. "Despite their reduced complexity, these neuron models are surprisingly more accurate than some of the more sophisticated biophysical models - important food for thought for future scientific approaches in modelling," says Ad Aertsen, chairman of the jury of the Valentino Braitenberg Award for Computational Neuroscience.

Wulfram Gerstner is the author of the book „Spiking Neuron Models. Single Neurons, Populations, Plasticity” (2002), which has become an indispensable textbook in computational neuroscience.

The award will be conferred at the Bernstein Conference on September 26, 2018 at TU Berlin. Following the award ceremony, Gerstner will give the Valentino Braitenberg Lecture, in which he will present highlights of his research.

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