Oscillatory dynamics as a mechanism of integration in complex networks of neurons

The large-scale integrative mechanisms of the brain, the means by which the activity of functionally segregated neuronal regions are combined, are not well understood. There is growing agreement that a flexible mechanism of integration must be present in order to support the myriad changing cognitive demands under which we are placed. Neuronal communication through phase-coherent oscillation stands as the prominent theory of cognitive integration. The work presented in this thesis explores the role of oscillation and synchronisation in the transfer and integration of information in the brain. It is first shown that complex metastable dynamics suitable for modelling phase-coherent neuronal synchronisation emerge from modularity in networks of delay and pulse-coupled oscillators. Within a restricted parameter regime these networks display a constantly changing set of partially synchronised states where some modules remain highly synchronised while others desynchronise. An examination of network phase dynamics shows increasing coherence with increasing connectivity between modules. The metastable chimera states that emerge from the activity of modular oscillator networks are demonstrated to be synchronous with a constant phase relationship as would be required of a mechanism of large-scale neural integration. A specific example of functional phase-coherent synchronisation within a spiking neural system is then developed. Competitive stimulus selection between converging population encoded stimuli is demonstrated through entrainment of oscillation in receiving neurons. The behaviour of the model is shown to be analogous to well-known competitive processes of stimulus selection such as binocular rivalry, matching key experimentally observed properties for the distribution and correlation of periods of entrainment under differing stimuli strength. Finally two new measures of network centrality, knotty-centrality and set betweenness centrality, are developed and applied to empirically derived human structural brain connectivity data. It is shown that human brain organisation exhibits a topologically central core network within a modular structure consistent with the generation of synchronous oscillation with functional phase dynamics