Integration and segregation in whole-brain networks: implications for altered states of consciousness

To survive in an ever-changing environment, the brain must seamlessly integrate a rich stream of incoming information into coherent internal representations that can then be used to efficiently plan for action. The brain must also balance its ability to integrate information with a complementary capacity to segregate information into modules which perform specialized computations in local circuits. The central focus of this Thesis is to investigate the dynamical properties of the integration/segregation balance in functional MRI data collected in two distinct altered states of consciousness: slow-wave sleep, and a psychedelic experience induced by intravenously administering psilocybin; the psychoactive compound in ~magic mushrooms~. In Chapter 2, I implement a novel method for identifying highly integrative nodes in human brain networks from the persistent homology of fMRI data, as a complement to standard graph theoretical methods. I report that topologically central nodes in the 'persistence homological scaffold' have a combination of high betweenness-centrality and high participation coefficient, whilst simultaneously avoiding densely connected neighborhood clusters. In Chapter 3, I investigate dynamical... (continues)