Theory of Complex Systems and Neurophysics

Benjamin Lindner
My interests lie in applications of methods from nonlinear dynamics, stochastic processes, and information theory to complex systems, in particular in neuroscience and cell biology. I focus on developing analytical frameworks for these problems, which does not exclude occasional (mostly happy) encounters with experimental data and serious attempts to understand them in theoretical terms.

030-2093-82492 or 030-2093-7934 | benjamin.lindner(at)physik.hu-berlin.de | Homepage

Sandra Funk
I try to solve all the other issues apart from physics. Don't hesitate to contact our office.

030-2093-82490 or -82487 | officebl(at)bccn-berlin.de

Michael Zaks
I am interested in collective dynamics in ensembles of coupled systems that model physical and biological effects, like onset and breakdown of synchronous oscillations, symmetry breaking and mechanisms of clustering. Starting from simplified models and proceeding to more realistic ones, I apply methods of nonlinear dynamics to study the effects of coupling patterns, heterogeneity and system size upon transitions between different types of behavior.

030-2093-7608 | zaks(at)physik.hu-berlin.de

Ralf Tönjes
My primary research experience is on the effects of noise and heterogeneity in the transition to collective dynamics of coupled systems. As a Research Assistant in this group I try to contribute this experience to ongoing research projects and in support of the younger researchers.

030-2093-82480 | toenjes(at)physik.hu-berlin.de

Yagmur Kati
My primary research interests lie in exploring the intricate balance between equilibrium and non-equilibrium dynamics of nonlinear systems. Delving into disordered lattices, I seek to uncover the underlying principles governing classical and quantum chaos. Furthermore, my work encompasses the study of synchronization phenomena and the complexities of fluid dynamics. Presently, I am engaged in examining asynchronous network models to elucidate the emergent properties of these systems and their potential applications in various scientific disciplines.

030-2093-82482 | kati(at)physik.hu-berlin.de

Maria Schlungbaum
In my PhD thesis I study the signal detection in sensory neurons which are subject to two competing periodic signals of distinct frequencies and amplitudes. This kind of problem arises if we want to understand how several weakly electric fish communicate in natural situations, e.g. during courtship behavior (one female and two competing male fish). In collaboration with the experimental lab of Jan Benda in Tuebingen, I would like to understand how this cocktail-party problem is solved by the electro-sensory system of this species.

030-2093-82494 | maria.schlungbaum(at)bccn-berlin.de

Fabian Raff

Leander Dittrich
Neurons encode (sensory) stimuli into sequences of action potentials, known as spike trains. These spike trains also arise in the absence of stimuli. Analyzing the statistics of both regimes is necessary for understanding the displayed information filtering properties. My research focuses on fluctuation dissipation relations, which connect these statistics, in a two-stage neural network. The first stage consists of a population of neurons driven by a common stimulus. The second stage is a single neuron detecting simultaneous firing from those neurons. Similar networks comprise the initial stages of the neural processing chain for many sensory inputs.