# Marc-Oliver Gewaltig

#### Scientist

marc-oliver.gewaltig@epfl.ch +41 21 693 18 66 http://bluebrain.epfl.ch/page-77938-en.html

Birth date : 31.07.1967

**EPFL ENT-R BBP-CORE **

Campus Biotech

Bâtiment B1

Ch. des Mines 9

CH-1202 Genève

+41 21 693 18 66

Office: B1 5 264.040

EPFL > ENT-R > BBP > BBP-CORE

Web site: Web site: https://www.epfl.ch/research/domains/bluebrain/

### Fields of expertise

Activity dynamics in networks of spiking neurons

Closed-loop neuronal control

Computational Neuroscience

Large-scale network simulations

Neural Simulation Tool NEST

### Current work

### HBP Neurorobotics Platform

https://youtu.be/b_RjzdlN0y4### Biography

Marc-Oliver Gewaltig is the Section Manager of Neurorobotics within the Simulation Neuroscience Division.In our team we investigate the simulation-aided reconstruction of sensory-motor loops in rodents, using data-driven whole brain models and musculoskeletal body models. Of particular interest is closed-action perception loops in which an animal influences or actively controls its sensory input.

Marc-Oliver is the co-author of the Neural Simulation Tool NEST (www.nest-simulator.org), a popular tool for large-scale simulations of spiking neural networks.

Before joining Blue Brain in 2011, Marc-Oliver was Principal Scientist (1998-2011) at the Honda Research Institute Europe in Offenbach, Germany. He completed his Ph.D. in Physics in 1999.

In his spare time, Marc-Oliver enjoys skateboarding, fencing, and filming.

### Professional course

**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

### Education

**PhD**

Physics

Ruhr-University Bochum, Germany

**Diploma**

Physics

Ruhr-Univerisity Bochum, Germany

1993

## Publications

### Selected publications

Alois Knoll and Marc-Oliver Gewaltigin Brain- inspired intelligent robotics: The intersection of robotics and neuroscience (Science/AAAS, Washington, DC, 2016), p. [25-34] |
Neurorobotics: A strategic pillar of the Human Brain Project |

Egidio Falotico, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck, Georg Hinkel, Jacques Kaiser, Igor Peric, Oliver Denninger, Nino Cauli, Murat Kirtay, Arne Roennau, Gudrun Klinker, Axel Von Arnim, Luc Guyot, Daniel Peppicelli, Pablo Martínez-Cañada, Eduardo Ros, Patrick Maier, Sandro Weber, Manuel Huber, David Plecher, Florian Röhrbein, Stefan Deser, Alina Roitberg, Patrick van der Smagt, Rüdiger Dillman, Paul Levi, Cecilia Laschi, Alois C Knoll, Marc-Oliver GewaltigFrontiers in Neurorobotics, 2017; 11: 2.doi: 10.3389/fnbot.2017.00002 |
Connecting artificial brains to robots in a comprehensive simulation framework: The Neurorobotics Platform |

Schrader, S., Gewaltig, M., K�rner, U., & K�rner, E.Neural Networks 22(8), 1055-70. doi:10.1016/j.neunet.2009.07.021 |
Cortext: a columnar model of bottom-up and top-down processing in the neocortex. |

Nordlie, E., Gewaltig, M., & Plesser, H.PLoS Computational Biology, 5(8). doi:10.1371/journal.pcbi.1000456 |
Towards reproducible descriptions of neuronal network models. |

Eppler, J., Helias, M., Muller, E., Diesmann, M., & Gewaltig, M.Frontiers in Neuroinformatics, 2(January), 1-12. Frontiers Research Foundation. doi:10.3389/neuro.11.012.2008. |
PyNEST: a convenient interface to the NEST simulator. |

Helias, M., Rotter, S., Gewaltig, M., & Diesmann, M.Frontiers in computational neuroscience, 2(December), 7 (2008) |
Structural plasticity controlled by calcium based correlation detection. |

Cannon, R., Gewaltig, M., Gleeson, P., Bhalla, U., Cornelis, H., Hines, M., De Schutter, E.Neuroinformatics, 5(2), 127�138. Springer. doi:10.1007/s12021-007-0004-5. |
Interoperability of neuroscience modeling software: current status and future directions. |

Kupper, R., Knoblauch, a., Gewaltig, M., Korner, U., & Korner, E.Neurocomputing, 70(10-12), 1711-1716. doi:10.1016/j.neucom.2006.10.085. 2007 |
Simulations of signal flow in a functional model of the cortical column. |

Knoblauch, A., Kupper, R., Gewaltig, M., K�rner, U., & K�rner, E.Neurocomputing, 70(10-12), 1838�1842. Elsevier. doi: 10.1016/j.neucom.2006.10.092., 2007 |
A cell assembly based model for the cortical microcircuitry |

Eppler, J. M., Plesser, H., Morrison, A., Diesmann, M., & Gewaltig, M.In A. Kermarrec, L. Boug�, & T. Priol, Euro-Par 2007: Parallel Processing, Lecture Notes in Computer Science Vol 4641. Berlin: Springer-Verlag. 2007 |
Multithreaded and Distributed Simulation of Large Biological Neuronal Networks. |

Plesser, H., Eppler, J., Morrison, A., Diesmann, M., & Gewaltig, MLecture Notes in Computer Science, 4641, 672. Springer. |
Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers. |

Gewaltig, M., & Diesmann, M.Scholarpedia, 2(4):1430., revision #130182 |
NEST (Neural Simulation Tool). |

Kupper, R., Gewaltig, M., K�rner, U., & K�rner, E.Neurocomputing, 65, 189�194. Elsevier, 2005 |
Spike-latency codes and the effect of saccades. |

Gewaltig, M., K�rner, U., & K�rner, E.Neurocomputing, 52--54, 519-524. Elsevier, 2003 |
A model of surface detection and orientation tuning in primate visual cortex. |

Gewaltig, M. O., Diesmann, M., & Aertsen, A.Neural Networks, 14(6-7), 657-73. Elsevier. (2001) |
Propagation of cortical synfire activity: survival probability in single trials and stability in the mean |

Gewaltig, M., Diesmann, M., & Aertsen, A.Neurocomputing, 38-40(1-4), 621-626. doi:10.1016/S0925-2312(01)00454-4 (2001) |
Cortical synfire-activity: Configuration space and survival probability. |

Diesmann, M., Gewaltig, M., Rotter, S., & Aertsen, A.Neurocomputing, 38, 565�572. (2001) |
State space analysis of synchronous spiking in cortical neural networks. |

Aertsen, A., Diesmann, M., Gewaltig, M. O., Gr�n, S., & Rotter, S.Novartis Found Symp, 239, 193-197,234-240. (2001) |
Neural dynamics in cortical networks--precision of joint-spiking events. |

Diesmann, M., Gewaltig, M. O., & Aertsen, A.Nature, 402(6761), 529-33. doi: 10.1038/990101 (1999) |
Stable propagation of synchronous spiking in cortical neural networks. |

K�rner, E., Gewaltig, M., K�rner, U., Richter, A., & Rodemann, T.Neural Networks, 12(7-8), 989�1005. (1999) |
A model of computation in neocortical architecture. |

Aertsen, A., Diesmann, M., & Gewaltig, M. O.J Physiol Paris, 90, 243-247 (1996) |
Propagation of synchronous spiking activity in feedforward neural networks. |

### Research

#### Neurorobotics

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.

### Teaching & PhD

#### PhD Programs

#### PhD Students

Kuras Ihor, Rodarie Dimitri Bruno Marie,#### Past PhD Students

Denizdurduran Berat , Erö Csaba , Wybo Willem Anna Mark ,## 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, marc-oliver.gewaltig@epfl.ch Pawel Dlotko, pawel.dlotko@inria.fr

#### 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