Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Neuroscience

Supervisor

Owen, Adrian M.

Abstract

The function of sleep is a longstanding mystery of the brain. By contrast, the function of resting state networks (RSNs) is one of its most recent mysteries. The relationship between RSNs and neuronal activity has been unclear since RSNs were discovered during the advent of functional magnetic resonance imaging (fMRI). Somewhat paradoxically, investigating these enigmatic phenomena in parallel can help to illuminate the function of both. The three studies described as part of this thesis all involve an evaluation of RSN dynamics across wakefulness and sleep. They are all based on the same dataset, derived from an experimental paradigm in which healthy, non sleep-deprived participants (N=36, 21 female) slept in an MRI scanner, as their brain activity was recorded using simultaneous electroencephalography (EEG)-fMRI. An independent component analysis (ICA) was performed in the first study. Spatial boundaries of components in each sleep stage were compared with those of wakefulness, in the first attempt to catalogue RSNs across all healthy alternate functional modes of the brain. Against expectations, all non-wake-RSN components were positively identified as noise. This indicated that sleep is supported by much the same RSN architecture as wakefulness, despite the unique operations performed during sleep. In the second study, between-RSN functional connectivity (FC) dynamics were evaluated across wakefulness and sleep, in order to determine whether they reflect known cortical neurophysiological dynamics. This was confirmed, highlighting the connection between RSNs and neuronal activity. Moreover, the dynamic pattern suggested that one of the functions of sleep may be to homeostatically counterbalance wakefulness RSN FC. A further pattern, indicating increased FC of “higher-order” RSNs (e.g., default mode network), suggested that slow wave sleep might manifest an altered, rather than a reduced state of awareness, in contrast to historical depictions. Finally, the third study correlated frequency-banded oscillatory activity, as measured by EEG, with RSN activity, as measured with fMRI. This was done in order to track changes in representations of frequency-banded neuronal activity in each RSN across stages. It was discovered that the pattern of frequency band representation dynamics reflects the aforementioned cortical neurophysiological dynamics, further strengthening the connection between RSNs and neuronal activity.

Summary for Lay Audience

We spend a third of our lives disconnected from reality in a strange state called sleep. However it is presently unclear why it should be necessary for the sleeping brain to isolate itself in this way. One means of understanding why is to examine changes in brain network activity during sleep. A special set of “resting state” networks are particularly useful to understanding sleep because they have already been associated with known functions during wakefulness, for example, the processing of visual information. By observing communication changes amongst these networks, we can make use of these known associations to infer what the brain might be doing during sleep. This thesis makes use of data from a single experiment in which brain activity was recorded from sleeping participants. The first study found that the resting state networks that are consistently identifiable in wake are also consistently present during sleep, with no new networks appearing, despite the unique functions of sleep. This finding was foundational for the studies that followed however, because communication amongst these networks could be examined during sleep without having to consider changes to the networks themselves. The second study further discovered that this communication largely changes in a predictable manner, consistent with what is known about changes to brain chemistry during sleep. Moreover, the changes seem to reverse the patterns found in wakefulness, during deep sleep. This suggests that the function of deep sleep may be to “reset” brain activity closer towards a baseline pattern, so that the brain might be better prepared for the need to adapt and to create new patterns the following day. It is possible that this resetting process requires the brain to be isolated during sleep. Unexpectedly, deep sleep was also found to involve increased activity in networks associated with complex information processing, possibly suggesting that the brain might be more consciously aware during this stage than previously suspected. Finally, the third study found that, beyond the activity of the networks themselves, representing the collective activity of billions of neurons, subset neuronal populations appear to largely change their activity according to the aforementioned predictions.

Available for download on Thursday, August 26, 2021

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