Goh, CWC; (2014) Nocturnal oscillations: Understanding the brain through sleep. Doctoral thesis , UCL (University College London).

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Abstract

This thesis explores the nature of sleep oscillations using behavioral and neurophysiological measures. The first experiment examines how the magnitude of different spectral frequencies in the sleep electroencephalography affect individual’s subjective emotional experience of positive and negative moods, as well as the emotional detriment associated with a full night of sleep deprivation, and its recovery after a daytime nap. The change in positive and negative moods across a night’s sleep is predicted by the magnitude of different oscillatory activity during rapid-eye-movement (REM) and non-REM (NREM) sleep. Experiment 2 uses EEG with simultaneous functional magnetic resonance imaging (fMRI) to examine the blood oxygen level dependent (BOLD) signal changes associated with sleep stage changes, and specifically investigates the functional connectivity changes within the basal ganglia network that occur across an early, slow-wave-rich sleep cycle. In NREM sleep, the functional connectivity of the globus pallidus and the striatum (composed of the putamen and caudate nucleus) show patterns supporting the tripartite division model, and lend support to existing studies of information processing during sleep, especially in the motor domain. Experiment 3 seeks to validate the hypothesis that different frequencies of oscillatory activity within the brain will differentially modulate the spatial profile of BOLD activity. This is achieved with applying transcranial alternating current stimulation (tACS) during fMRI acquisition, by artificially inducing oscillations of different frequencies in the brain while measuring the BOLD signal changes associated with the oscillatory activity. Stimulation to the primary visual cortex led to BOLD activity increases, relative to baseline, in different neural networks depending on the frequency of stimulation. The three experiments presented in the thesis shed light on the nature of neural network modulations caused by ongoing oscillatory activity, and bridge the gap between electrophysiological and haemodynamic findings of sleep-dependent information processing.

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