Regensburg 2019 – scientific programme
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BP: Fachverband Biologische Physik
BP 12: Poster II
BP 12.54: Poster
Tuesday, April 2, 2019, 14:00–16:00, Poster B2
Topological reinforcement as a principle of modularity emergence in brain networks — •Fabrizio Damicelli1, Claus-Christian Hilgetag1,3, Marc-Thorsten Hütt2, and Arnaud Messé1 — 1Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Germany — 2Department of Life Science and Chemistry, Jacobs University Bremen, Germany — 3Department of Health Sciences, Boston University, USA
The self-organization of modular structure in brain networks is mechanistically poorly understood. We propose a simple plasticity model based on a fundamental principle, the Topological Reinforcement (TR), which promotes connections between nodes with high neighborhood similarity. This mechanism systematically evolves synthetic random networks toward a modular architecture by enhancing initial weak "proto-modules". Moreover, we show that this topological selection principle can also be implemented in biological neural networks evolving in a Hebbian fashion, where what "fires together, wires together" and, under proper conditions, the results were consistent between both scenarios, i.e., TR and Hebbian rule. We propose the selective reinforcement of topological overlap as a fundamental principle guiding the emergence of modular structure in brain networks. This bridges the gap between previous pure generative and activity based models of modularity emergence in brain networks, offering a common underlying principle at the topological level.