One of the big challenges in neuroinformatics is bridging the gap between our biophysical understanding of single cells and of networks of neurons on the one side, and the cognitive functions that are characterized in terms of information processing on the other side. Much effort in training the next generation of neuroscientists has gone into bringing experimentalists and theoreticians together. However, there are also methodological and philosophical differences among theoreticians. Physicists with their dynamical systems toolkit are at one end of the spectrum, and scientists from neuroinformatics and cognitive science have their emphasis on abstract representations and computations at the other end. Our course aims at bringing together these different approaches for understanding the brain. We will showcase some of the best work that has been done in integrating dynamical systems and information processing. We expect that PhD students and post-docs with a background in neuroinformatics, theoretical neuroscience, machine learning, or cognitive science, who want to expand their methodological toolkit, will benefit from this integrative approach.

More concretely, we will offer lectures on dynamical systems, self-organization, probabilistic models of neural coding and learning, mean field methods, large-scale simulations, and cognitive modeling. We will also provide hands-on tutorials on simulations and reservoir computing. The line-up of speakers who have already agreed to help teach this course includes the major experts of these fields (see below) that cover all relevant areas. We are sure that this course perfectly fits into the general scope of INCF, since it will help in training a new generation of scientists who use cutting edge information processing, statistical learning tools, and complex and large dynamical systems to understand and model information processing in the brain.

Target audience

PhD candidates and post-docs with backgrounds in neuroinformatics, theoretical neuroscience, complex systems, machine learning, applied mathematics/statistics or cognitive modeling.

Course duration

6 days INCF short course + 2 days OCCAM workshop (www.occam-os.de)

Dates and location

May 2-10, 2015. Institute of Cognitive Science, University of Osnabrück, Germany.

Organizers and faculty (all confirmed)

  1. Prof. Dr. Nicolas Brunel, Dept. of Statistics and Neurobiology, University of Chicago, USA
  2. Prof. Dr. Dr. Gustavo Deco, Dept. of Information & Communication Technologies, Universitat Pompeu Fabra, Spain
  3. Dr. Marc-Oliver Gewaltig, In-Silico Neuroscience - Cognitive Architectures, Blue Brain Project EPFL, Switzerland
  4. Prof. Dr. Frank Jäkel, Institute of Cognitive Science, Osnabrück, Germany
  5. Prof. Dr. Herbert Jäger, Computational Science, Jacobs University, Bremen, Germany
  6. Prof. Dr. Peter König, Institute of Cognitive Science, Osnabrück, Germany
  7. Prof. Dr. Gordon Pipa, Institute of Cognitive Science, Osnabrück, Germany

The course is hosted by the Institute of Cognitive Science.
We thank the INCF (http://www.incf.org) for their generous financial support.