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

The brain must balance integrating information across regions with segregating it into specialized modules. This thesis examines that balance in two altered states of consciousness: slow-wave sleep and the psychedelic experience from psilocybin. Using fMRI data, a novel method identifies highly integrative brain nodes based on persistent homology, which have high betweenness-centrality and participation coefficient but avoid dense clusters. Global synchrony and metastability decrease in slow-wave sleep while chimeraness increases; opposite effects occur under psilocybin. Psilocybin increases occurrence of a globally coherent functional connectivity state and decreases occupancy of a fronto-parietal control network.

Study at a glance

Abstract

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 changes in global measures of functional integration and segregation derived from fMRI data. Synchrony, metastability and chimeraness metrics are computed separately in slow-wave sleep and in the psychedelic state. It is found that global synchrony and metastability are reduced in slow-wave sleep relative to a wakeful rest baseline, whilst chimeraness is increased. Diametrically opposite effects on each measure are observed in the psychedelic state. Chapter 4 characterizes the brain’s dynamical landscape from a system-level perspective under psilocybin by computing the fractional occupancy and transition probabilities of specific functional network states over time. An increase in the probability of occurrence of a globally coherent functional connectivity state is observed, alongside a strong decrease in the fractional occupancy of a fronto-parietal control network. In Chapter 5, I further characterize the capacity of brain areas to dynamically broadcast regional activity signals locally or globally in both deep sleep and the psychedelic state. The results notably show that intrinsic activity perturbations in a given brain area are more likely to propagate strictly locally in slow-wave sleep than during wakeful rest. In the psychedelic state, the size of integration cascades elicited by local perturbations over time is significantly more variable than during the baseline scan. The experimental findings presented in this Thesis indicate that alterations in consciousness level and/or contents are accompanied by temporally-dependent changes in the brain’s integration and segregation balance, promoting cross-modular integration in the psychedelic state, and functionally segregated brain dynamics in slow-wave sleep.