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Cooperation-induced Criticality in Neural Networks

The human brain is considered to be the most complex and powerful information-processing device in the known universe. The fundamental concepts behind the physics of complex systems motivate scientists to investigate the human brain as a collective property emerging from the interaction of thousand agents. In this dissertation, I investigate the emergence of cooperation-induced properties in a system of interacting units. I demonstrate that the neural network of my research generates a series of properties such as avalanche distribution in size and duration coinciding with the experimental results on neural networks both in vivo and in vitro. Focusing attention on temporal complexity and fractal index of the system, I discuss how to define an order parameter and phase transition. Criticality is assumed to correspond to the emergence of temporal complexity, interpreted as a manifestation of non-Poisson renewal dynamics. In addition, I study the transmission of information between two networks to confirm the criticality and discuss how the network topology changes over time in the light of Hebbian learning.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc283813
Date08 1900
CreatorsZare, Marzieh
ContributorsGrigolini, Paolo, Krokhin, Arkadii, Gross, Guenter, Kowalski, Jacek
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Zare, Marzieh, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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