Neurophysiological Mechanisms underlying the Complex Dynamics of Propagating Waves in Neural Circuits

Abstract

Recent experimental studies have shown that the activity of neural circuits demonstrates spatiotemporal dynamics across multiple scales, including localized coherent patterns and propagating waves. This activity is associated with a wide range of phenomena, including cognitive processes such as vision, spatial awareness, and memory as well as pathological states such as seizures. The neural mechanisms that underlie and modulate these phenomena are currently an area of active research that could lead to a better understanding of how cognition emerges from brain activity as well as new treatments for diseases. In this thesis, we investigate two distinct models of neural circuits to elucidate the neurophysiological and circuit mechanisms underlying the emergence of neural spatiotemporal patterns. In chapter 1, we give a general background relevant to our work. In chapter 2, we apply a recently developed 2-D neural field model to reveal the fundamental importance of excitation and inhibition balance for propagating neural waves with complex dynamics. We demonstrate that changing the strength of excitation and inhibition can give rise to a rich repertoire of propagating neural waves. Near the critical point of transition from the rotating state to the traveling state, there are co-existing propagating waves of different types; the noise-induced switching dynamics between these waves are systematically characterized, as is the effect on the collective behaviour of multiple interacting patterns. In Chapter 3, we present a spiking network model consisting of Hodgkin-Huxley neurons with chemical and electrical coupling. We observe unique forms of spatiotemporal activity, including persistent stationary bumps and spreading waves of spontaneous activity that depend on the strength of gap junction coupling. We characterize the switching between different modes and show that the potential contribution from gap junctions towards dynamic behaviour in neural circuits is significant.