Prof. Dr. Fred Wolf
Towards a theory of efficient stimulus encoding at auditory synapses,
Self-Organization and optimization in the evolution of visual cortical circuits,
Modelling the role of neural oscillations in information routing,
Dynamics of neuronal action potential encoding,
The encoding bandwidth of the cortical gateway,
A synthetic neurobiology approach to orientation selectivity,
Nano-physiology of the action potential generator,
Attractor basins of stable state sequences in balanced circuits of spiking neurons,
Precision measurement and dynamical switching of visual cortical architecture,
The Synaptic Nanomachine Underlying Auditory Encoding,
Neuronal sodium channels: surface density and kinetics,
Phase space structure and chaos of pulse-coupled network dynamical systems,
Stochastic terminal dynamics in Epithelial cell intercalation,
Biophysics of action potential generation,
Genetic assimilation of visual cortical architecture
Am Faßberg 17
||My work focuses on selected problems in neurobiology and biophysics that are interesting and challenging from a theoretical physics perspective because
(1) they require the development of mathematical theory and computational methods in neuroscience and biology and
(2) they are mature enough to enable precise quantitative experiments.
The topics range from the formulation and development of novel mathematical approaches tailored to the specifics of neuronal systems dynamics, over the development of analysis methods for turning biological experimental observations into theoretically informative quantitative data, to the development of experimental paradigms specifically designed to provide insight into cooperative and dynamical aspects of nervous system function. To enable a direct interaction of theory and experiment, many projects are pursued in close collaboration with experimental biological research groups around the world.
Currently three problems are at the core of my research agenda:
• The self-organization of neuronal circuits in the visual cortex. In this system our analyses demonstrate that biological neural networks follow apparently universal quantitative laws which require the development of adequate mathematical theories of neuronal self-organization. Several lines of evidence indicate that non-local interactions characteristic of neuronal circuits lead to qualitatively novel types of dynamics in such systems (e.g. Kaschube et al. PNAS 2009, Keil et al. PNAS 2010, Kaschube et al. Science 2010, Keil et al. Science 2012).
• The dynamics of large networks of pulse-coupled neurons and its impact on the representation of sensory information. Here the ergodic theory of network dynamical systems provides a natural language that links details of the network dynamics to information representation and decay (e.g. Monteforte & Wolf PRL 2010; Junek et al. Neuron 2010; Monteforte & Wolf. Phys. Rev. X. 2012).
• The biophysical nature and dynamics of high-bandwidth action potential encoding mechanisms in biological neurons. This problem requires the integration of concepts from non-equilibrium statistical physics with the biophysics of membranes and ion channels. Its solution is essential for the construction of a next generation of dynamically realistic network models (e.g. Naundorf et al. Nature 2006, Tchumatchenko et al. PRL 2010, Wei & Wolf PRL 2011, Tchumatchenko et al. J.Neurosci. 2011; Huang et al. PLoS One 2012).