Dresden 2017 – scientific programme

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BP: Fachverband Biologische Physik

BP 30: Posters - Neurosciences

BP 30.1: Poster

Tuesday, March 21, 2017, 14:00–16:00, P2-OG1

Self-organized criticality in a binary neural network model with local rules — •Stefan Landmann and Stefan Bornholdt — Institute for Theoretical Physics, University of Bremen, D-28359 Bremen, Germany

Since the seminal work of Beggs and Plenz [1] which gave strong evidence for criticality in neural systems there is a growing interest in how criticality may emerge in neural networks.
Extending previous work of our group [2,3] we present and investigate a simple but biologically plausible neural network model which exhibits self-organized criticality (SOC). Based on local rules only the network evolves towards criticality, showing typical power-law distributed avalanche statistics. This behavior is independent of initial conditions and robust under noise. Due to its biological plausibility the model could help to understand mechanisms leading to criticality in neural systems.

J. M. Beggs and D. Plenz, Journal of Neuroscience 23(35): 11167 (2003)
S. Bornholdt and T. Rohlf, Phys. Rev. E 67: 066118 (2003)
M. Rybarsch and S. Bornholdt, PLoS ONE 9(4): e93090 (2014)