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  Influence of spatial structure on data processing and phase transitions in neuronal networks

Levina, A. (2019). Influence of spatial structure on data processing and phase transitions in neuronal networks. Talk presented at Workshop W20: Phase Transitions in Brain Networks, 28th Annual Computational Neuroscience Meeting (CNS*2019). Barcelona, Spain. 2019-07-16.

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Levina, A1, 2, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Networks are backbones of the complex brain activity. Modern methods allow extracting more and more reliable functional and structural networks on different scales. One of the major challenges is to understand the relationship between the structure of the network and the properties of its dynamics. Using simple models and data analysis I am going to discuss, on the one hand, how the features of the networks are reflected in the dynamics of single units. And on the other hand, how the system's structure changes the nature of the phase transition in its dynamics.

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 Dates: 2019-07
 Publication Status: Published online
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Title: Workshop W20: Phase Transitions in Brain Networks, 28th Annual Computational Neuroscience Meeting (CNS*2019)
Place of Event: Barcelona, Spain
Start-/End Date: 2019-07-16

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Title: 28th Annual Computational Neuroscience Meeting (CNS*2019)
Source Genre: Proceedings
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