Dr. Tatjana Tchumatchenko
|Max Planck Institute for Brain Research
60438 Frankfurt am Main
Our research focuses on the computational modeling and mathematical analysis of single neurons, neuronal populations and recurrent networks. We employ analytic tools and computer simulations to investigate how single neurons and populations respond to their synaptic inputs, and how they interact to give rise to functioning neuronal circuits. Areas of particular interest include the role of synaptic adaptation, information representation, response time scales and the temporal and cross neuronal correlations. - See more at: http://www.brain.mpg.de/research/tchumatchenko-mpr-group/#sthash.Jk2fokhk.dpuf
We employ a combination of analytical techniques that include linear and non-linear differential equations and their solutions via linear perturbation theory, stochastic integrals (e.g correlated Gaussian ensemble), Fokker Planck formalism, interacting stochastic processes. On the computational side we use numerical simulations and modern programming languages.
Dettner, S. Münzberg, T. Tchumatchenko, Temporal pairwise spike correlations fully capture single-neuron information, Nature Communications 7, 13805 doi: 10.1038/ncomms13805 (2016)