Göttingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences

Geisel, Theo, Prof. Dr.

Professor of Theoretical Physics; Director, Max Planck Institute for Dynamics and Self-Organization; Coordinator, Bernstein Center for Computational Neuroscience


  • Dr. rer. nat., University of Regensburg (1975)
  • Heisenberg fellow (1983 1987)
  • Professor of Theoretical Physics, Universities of Würzburg (1988 1989), Frankfurt (1989 1996), and Göttingen (since 1996)
  • Director, Max Planck Institute for Dynamics and Self-Organization, Göttingen (since 1996)
  • Founder and Coordinator, Bernstein Center for Computational Neuroscience, Göttingen (2004 2013)




Major Research Interests

How do the myriads of neurons in our cortex cooperate when we perceive an object or perform another task? How do they self-organize in the preceding learning process? Questions like these address the complex dynamics of spatially extended and multicomponent nonlinear systems, which still reserve many surprises. In networks of sufficiently many spiking neurons e.g. we find unstable attractors, a phenomenon which would neither have been guessed nor understood without mathematical modelling and which many physicists consider an oxymoron. They can provide a neuronal network with a high degree of flexibility to adapt to permanently changing tasks. The tools and mathematical methods developed in studies of chaotic behaviour in the past can now help us clarify the dynamics and function of complex networks and spatially extended systems and reveal the biological role of dynamical phenomena like unstable attractors.

These methods lend themselves to applications in neuroscience from the level of single cells to the level of cell assemblies and large cortical networks, from the time scales of action potentials (milliseconds) to the time scales of learning and long-term memory (up to years). My work in the past has dealt among others with studies of stochastic resonance of single neurons under periodic and endogenous stimulation, detailed investigations of the properties, functions, and conditions of neuronal synchronization, and the development of neuronal maps in the visual cortex. We have elucidated the influence of the network topology on synchronization and other dynamical properties and demonstrated the existence of speed limits to network synchronization due to disordered connectivity. Besides, I am also focusing on other applications of nonlinear dynamics, e.g. for quantum chaos in semiconductor nanostructures and in mathematical models for the description and forecast of the spread of epidemics.

GGNB Geisel Figure 1Figure 1: Basins of attraction of synchronized states in a network of spiking neurons. These unstable attactors allow rapid switching and give the network a high degree of flexibility.



GGNB Geisel Figure 2


Figure 2: Analyzing the spreading of dollar bills as proxies allows us to uncover the statistical laws underlying human travel and to formulate new models to forecast the spreading of epidemics.


Homepage Department/Research Group

http://www.nld.ds.mpg.de



Selected Recent Publications


  • H. Degueldre, J. J. Metzger, T. Geisel, and R. Fleischmann (2016) Random Focusing of Tsunami Waves. Nature Physics 12:259-262.
  • M. Helmer, V. Kozyrev, V. Stephan, S. Treue, T. Geisel, and D. Battaglia (2016) Model-Free Estimation of Tuning Curves and their Attentional Modulation, Based on Sparse and Noisy Data. PLos One 11(1):e0146500.
  • A. Levina, J. M. Herrmann, and T. Geisel (2014) Theoretical neuroscience of self-organized criticality: from formal approaches to realistic models. In: Criticality in Neural Systems, edited by Dietmar Plenz, Ernst Niebur. Wiley-VCH Verlag, pages 417-436
  • F.Stollmeier, T. Geisel, and J. Nagler (2014) Prossible Origin of Stagnation and Variabitlity of Earth's Biodiversity. Phys. Rev. Lett. 112:228101.
  • D. Battaglia, A. Witt, F. Wolf, and T. Geisel (2012) Dynamic Effective Connectivity of Inter-Areal Brain Circuits. PLoS Comput. Biol. 8(3), e1002438.

  • H. Hennig, R. Fleischmann, and T. Geisel (2012) Musical rhythms: The science of being slightly off. Physics Today 65, 64-65.

  • Hennig H, Fleischmann R, Fredebohm A, Hagmayer Y, Nagler J, Witt A, Theis F, Geisel T (2011) The nature and perception of fluctuations in human musical rhythms. PLoS ONE 6(10):e26457.

  • Belik V, Geisel T, Brockmann D (2011) Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases. PHYSICAL REVIEW X 1(011001):1--5.

  • Metzger JJ, Fleischmann R, Geisel T (2010) Universal Statistics of Branched Flows. Phys. Rev. Lett. 105(2):020601.

  • Tchumatchenko T, Geisel T, Volgushev M, Wolf F (2010) Signatures of synchrony in pairwise count correlations. Front. Comput. Neurosci. doi:10.3389/neuro.10.001.2010.

  • Levina A, Herrmann JM, Geisel T (2009) Phase transitions towards criticality in a neural system with adaptive interactions. Phys. Rev. Lett. 102: 118110
  • Ng GS, Hennig H, Fleischmann R, Kottos T, Geisel T (2009) Avalanches of Bose-Einstein Condensates in Leaking Optical Lattices. New J. Phys. 11: 073045

  • Levina A, Herrmann JM, Geisel T (2007) Dynamical Synapses Causing Self-Organized Criticality in Neural Networks. Nature Physics, 3: 857-860

  • Brockmann D, Hufnagel L, Geisel T (2006) The Scaling Laws of Human Travel. Nature 439,462-465