Marc-Oliver Gewaltig

Campus Biotech
Bâtiment B1
Ch. des Mines 9
CH-1202 Genève

Données administratives


Activity dynamics in networks of spiking neurons
Closed-loop neuronal control
Computational Neuroscience
Large-scale network simulations
Neural Simulation Tool NEST

Parcours professionnel

Principal Scientist, Project Leader Computational Neuroscience, Cortex Research Honda Research Institute Europe GmbH, Offenbach, Germany 2003-2011
Senior Scientist Future Technology Research Honda R&D Europe (Deutschland) GmbH, Offenbach, Germany 1998-2003
Scientific Collaborator Institute for Biology III Albert-Ludwigs University Freiburg, Germany 1996-1998
Scientific Collaborator Institute for Neuroinformatics Ruhr-University Bochum, Germany 1993-1996


PhD Physics Ruhr-University Bochum, Germany
Diploma Physics Ruhr-Univerisity Bochum, Germany 1993


Enseignement & Phd


  • Life Sciences Engineering,

Programmes doctoraux

  • Doctoral Program in Neuroscience


Master and semester Projects

We offer projects for Master's and Bachelor students in the areas of Computational Neuroscience and Neurorbotics.

Master projects

Interplay between topology and activity in biological neural networks

Keywords:Neural networks, dynamical systems, computational topology Neural networks generally face what is known as the plasticity-stability dilemma: Neural activity changes the topology of the network, which then in turn changes the activity dynamics which of the network. The aim of this project is to investigate the interplay between the topology of a neural network and the activity dynamics which is supported by this topology. Your aim will be to work on the edge between two disciplines - computational topology and neuroscience. You will use methods from computational topology to generate various topologically different networks and then measure the properties of the network activity which can be supported by the specific topology. You will be supervised by the team from the Blue Brain Project, mathematicians from EPFL and from partnering institutions. If successful, this line of research can be continue and eventually turned into a Phd program. Skills: linear algebra, algorithms, Python, C++ Contact: Marc-Oliver Gewaltig, Pawel Dlotko,

Evolutionary optimization of neural morphology synthesis in high-dimensional parameter spaces

Keywords: evolutionary optimization, neurons, neuron morphologies, classification The Blue Brain Project has developed algorithms to synthesize neuron morphologies (the synthesizer). Depending on a set of parameters, the synthesizer generates different classes of neuron morphologies where each class is determined by a number of empirical distributions that capture particular features of a morphology. To generate morphologies for a particular neuron class, one needs to find an appropriate set of parameters through a non-convex and high-dimensional optimization procedure. The objective of this project is to test and compare different optimization algorithms in their ability to determine morphology class specific parameter sets for the synthesizer. The fitness function for the optimization is constructed from the distances between the feature distributions of biological and synthesized neurons. Contact: Marc-Oliver Gewaltig

From detailed to simplified models of neuronal microcircuits

Keywords: neuronal microcircuits, simulation, model selection, model validation The Blue Brain Project is developing morphologically and electrically detailed models of cortical microcircuits. The objective of this project is to investigate how detailed microcircuit models can be mapped to less complex network models while preserving the response properties of the circuit to a range of biologically meaningful stimuli. Complexity levels to be studied in the project are point neuron networks as well as population-level networks. Contact: Marc-Oliver Gewaltig



In Neurorobotics we investigate models of nervous system in the context of a body that is embedded in a realistic (sensory rich) environment.

The neural models ranges from simple artificial networks to detailed reconstructions of mammalian brains. These models are then investigated in closed-action perceptions loops.

Since the real-time simulations of realistic neural systems is still for most cases out of reach, we work with simulated bodies, robots, and environments.