Regensburg 2019 – scientific programme

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BP: Fachverband Biologische Physik

BP 15: Focus session: Collective Dynamics in Neural Networks

BP 15.1: Invited Talk

Wednesday, April 3, 2019, 09:30–10:00, H11

Statistical physics of correlated neuronal variability — •Moritz Helias — INM-6, Forschungszentrum Juelich, Germany — Condensed matter theory, RWTH Aachen University, Germany

Neuronal networks can be considered as many particle systems with interesting physical properties: They operate far from thermodynamic equilibrium and show correlated states of collective activity [1].

We here discuss recent progress in understanding the structure of these correlated states by methods from statistical physics and disordered systems [2,3,4].

Our analysis shows that the heterogeneity of the network connectivity enables critical dynamics that unfolds in a low-dimensional subspace. The structure of correlations predicted by this theory is found in line with massively parallel recordings from motor cortex [2]. We then demonstrate that networks in such regimes possess optimal capacity to memorize past input sequences [3]. We find that they operate in a hitherto unreported regime that combines instability on short time scales with asymptotically non-chaotic dynamics. As an outlook, we demonstrate how methods from field theory [4] help us understand the interplay of non-linearities and fluctuations that is vital to neuronal network dynamics.

1. Dahmen, Bos, Helias (2016) Phys. Rev. X 6, 031024; 2. Dahmen, Grün, Diesmann, Helias (2018) arXiv:1711.10930; 3. Goedeke, Helias (2018) Phys. Rev. X 8, 041029; 4. Kühn, Helias (2018) J Phys A 51, 37