When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
Abstract
Sleep represents a considerable part of our lives and its important roles in cognition and health are constantly being emphasized by emerging research. Investigations of sleep’s role in human memory consolidation have primarily focused on correlative relationships with sleep architecture or characteristic patterns of electrical activity, such as brain oscillations. While non-invasive neuroimaging studies cannot provide direct causal evidence of oscillations' functional roles, emerging brain stimulation techniques fill this gap by allowing direct interaction with endogenous brain activity. Closed-loop auditory stimulation, which uses quiet sounds time-locked to neural events, shows promise in research and clinical applications, particularly for targeting neural events previously correlated with, and therefore hypothesized to be involved in learning and memory. The present thesis investigates the bidirectional relationship between auditory processing and sleep using a combination of electroencephalography, magnetoencephalography, and behavioural paradigms.
This dissertation comprises six studies. In our first studies (Chapters 2 and 3), which used source-localized magnetoencephalography, we demonstrated that cortical sources of auditory evoked responses are affected by sleep depth, while subcortical regions remain unaffected. We also identified the source of sleep-specific evoked responses that are involved in closed-loop auditory stimulation effects. The next study (Chapter 4) challenges a widely held assumption in sleep science by showing that auditory input can still reach the cortex during spindles and their refractory period. This finding is key to our goal of manipulating sleep spindles with sound. In the next group of studies (Chapters 5 and 6), we validated a deep learning-based tool to modulate neurophysiology by stimulating spindles in real-time, and explored the optimal timing for its delivery. This work established the foundation for our behavioural study. Finally, the last study (Chapter 7) assessed the behavioural effects of slow oscillation and spindle stimulation on simple laboratory tasks and on a complex, music-based learning task. We evaluated relationships between stimulation-evoked responses and memory performance across tasks. Our findings provide mechanistic insights into how non-invasive brain stimulation affects neurophysiology and memory and offer a framework for linking brain activity with its function.