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Title: An Odyssey with complexity and network science : from the brain to social organisation
Author: Expert, Paul
ISNI:       0000 0004 2724 3256
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2011
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Complexity science is the study of systems that give rise to a priori unexpected macroscopic patterns, at different scales, emerging from the simple microscopic rules governing the evolution of the system. Method to explore complex systems are based on tools from a wide range of sciences, including statistical mechanics. Recently, the study of the emerging properties of complex systems has been enriched by a new toolbox derived by an extension of graph theory, namely, complex network science. We use both approaches to investigate two complex systems, the human brain and the communications patterns of a social network. The brain could be considered as an archetypical complex system; its fundamental constituting units, the neurones, communicate via simple inhibitory and excitatory interactions. These give rise to an extraordinarily rich hierarchical complex system, the human mind, that enables one to apprehend and interact with the universe. Understanding how the brain functions is essential, both for the general knowledge of humanity, but also for medical purposes; a better understanding of brain functions could lead to finding cures. We investigate the dynamics of brain activity at the smallest scale accessible by functional Magnetic Resonance Imaging, the voxel, while subjects are at the resting-state. We apply real-space renormalisation from the statistical mechanics toolbox, and our findings confirm that brain dynamics displays characteristic signatures of a critical system. At a coarser level, we study the structural differences in the functional networks of a healthy cohort and one made of people at-risk of developing a mental disorder during a verbal fluency task. We find that a key brain region plays a different role in the network organisation of the two populations, which is in agreement with previous findings on the disease schizophrenia. Finally, we investigate community structure in complex systems. Social interactions in humans are also a prime example of a system with emerging structure, the nature of which is dependent on the types of interactions between individuals. We use and develop new methods for community detection to uncover structures due to spatial and linguistic interactions in a mobile phone network.
Supervisor: Christensen, Kim ; Jensen, Henrik Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral