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

Levina, A

Datensatz

DATENSATZ AKTIONENEXPORT

Zur Ablage hinzufügen

Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben

Vortrag

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

MPG-Autoren

/persons/resource/persons173580

Levina, A
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

Externe Ressourcen

https://www.cnsorg.org/assets/CNS_Meetings/CNS2019/CNS%2A2019ProgramBook.pdf
(Inhaltsverzeichnis)

Volltexte (beschränkter Zugriff)

Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.

Volltexte (frei zugänglich)

Es sind keine frei zugänglichen Volltexte in PuRe verfügbar

Ergänzendes Material (frei zugänglich)

Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar

Zitation

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.

Zitierlink: https://hdl.handle.net/21.11116/0000-0004-3F4A-4

Zusammenfassung

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.