In the last decade, several large multi-institutional neuroimaging studies have emerged, the chief amongst them being the Alzheimer's Disease Neuroimaging Initiative (ADNI). The data obtained from these studies are free to access for researchers, and are an invaluable resource in areas where getting a large enough cohort takes too long or becomes too expensive to fund. However, one should proceed with caution as the sample consists mostly of highly educated American Caucasians, reducing its generalisability to other countries. For those who have an interest in cross-ethnicity differences however, the ADNI dataset is ideal for this purpose. This thesis begins with a cross-sectional look at cognitively normal, elderly Hong Kong Chinese subjects and matched ADNI Caucasian ones. When comparing total cortical grey matter volumes and the summed volumes of cortex that are often associated with Alzheimer's disease, it was found that Chinese subjects had significantly smaller cortical volumes than American Caucasians, even after adjusting for brain volume, despite having similar cognitive test scores. Unable to control for extrinsic factors such as environment and culture, however, no strong conclusions could be made. The second study of this thesis consists of a replication of the first, this time using American Chinese and American Caucasian subjects, all long-time residents of San Francisco. The same results were found regarding total cortical grey matter volume, leading to the implication that the Chinese population have inherently smaller cortices than Caucasians, but with no obvious cognitive detriment. Having found that ethnicity can have an effect on brain structure, the focus then shifts to how the brain changes during healthy ageing. The concept of healthy ageing has been gaining in popularity in recent years, especially as more and more age-related diseases are being thought of as "pathological ageing". In order to help diagnose and monitor diseases related to ageing, it is therefore important to understand the trajectory and effects of normal ageing. As such, a pilot fMRI study was conducted to try and see how attention and increased vulnerability to interference from presented stimuli changed with age. The results from the pilot study matched generally well with the literature and opens up the door towards using cognitive paradigms in neuroimaging to act as baseline markers of cognitive function, which can then be correlated with other measures to paint a more detailed portrait of the healthy ageing brain. / published_or_final_version / Diagnostic Radiology / Doctoral / Doctor of Philosophy

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This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2- and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.

Consciousness and loss of consciousness is something we encounter in our everyday lives. Despite its commonplace in everyday life, scientists are still trying to understand and find reliable markers for it. In this work we use a data-driven K-means clustering approach to uncover the different functional patterns associated with different consciousness levels. We pursue this study using a high resolution optogenetic voltage image of the mouse brain waking up from anesthesia. The main questions we addressed in this study are: Can we identify signatures of conscious and unconsciousness from functional connectivity patterns? What is the nature of the different patterns that correspond to wakefulness and anesthesia? What is the nature of dynamics between these functional patterns in wakefulness and anesthesia? How does the anatomical connectivity support the observed functional patterns in wakefulness and anesthesia? Our results show that during anesthesia, the brain is characterized by a single dominant brain pattern with short range connections. Furthermore, we observed from our results that during anaesthesia the brain is characterized by minimal temporal exploration of the different brain configurations. Conversely, in awake state we observed the opposite. The brain pattern with long range connections are frequent in wakefulness. In addition, wakefulness is characterized by somewhat frequent temporal exploration of brain states. Our results show that analysis of functional connectivity patterns can be a useful tool for identifying specific and generalizable fingerprints of wakefulness and anaesthesia

Introduction: Substance use disorders are often associated with widespread structural and functional abnormalities in the brain. The primary aim of this thesis was to reduce existing ambiguity and explore novel topics in the field of addictions neuroscience by conducting three human neuroimaging studies. Results: In the first study, individuals who used alcohol were found to have significant inverse associations between drinks in past week, frequency of heavy drinking, and cortical thickness in a majority of regions examined via MRI. These regions included the dorsolateral prefrontal cortex, the inferior frontal gyrus, and the precentral gyrus. In the second study, when we employed a novel MRI pulse sequence to examine intracortical myelin (ICM) in people with alcohol use disorder, we found that the alcohol use disorder group in fact had greater ICM signal than the control participants, leading us to hypothesize a potential inflammation response in the brain from the prolonged use of alcohol. Finally, in the third study, when we explored large-scale brain activity in a sample of people who use alcohol alone or in combination with other substances, we found that those who used three or more substances displayed the least amount of activation in the salience and temporal networks of the brain. A peculiar finding, however, was that dual users of alcohol and cannabis were found to have the most activation in these networks. Conclusions: Results demonstrate that, indeed, alcohol use is associated with structural and functional abnormalities in the brain. These studies have demonstrated cortical thinning and increased ICM signal in relation to alcohol use broadly. As well, this work has shown that polysubstance use is associated with alterations in various large-scale resting state brain networks. Future research should seek to conduct longitudinal work in order to clarify whether structural and functional brain abnormalities are a cause or a consequence of substance use. / Thesis / Doctor of Philosophy (PhD) / The aim of this thesis was to add to the existing literature surrounding neuroimaging in alcohol use disorder. First, we sought to expand the structural neuroimaging literature by conducting a study with a large sample size and examining the cortical thickness of a variety of brain regions in relation to characteristics of alcohol use. Second, we aimed to add to the structural neuroimaging literature again by examining a particular brain tissue in chronic alcohol users via a novel MRI pulse sequence. Finally, we sought to add to the functional neuroimaging literature by examining large-scale resting state brain networks in a sample of people who use alcohol alone or in combination with tobacco or other drugs (i.e., polysubstance users). Together, these studies have contributed new findings to the addictions neuroscience literature by revealing anatomical and functional brain correlates of alcohol and other substance misuse.

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The overall objective of this dissertation was to increase scientific understanding of brain reserve. Chapter 1 describes how brain reserve has come to be viewed in two distinct ways: differential expression of brain injury on the basis of individual differences in gross brain properties (neurological), or on the basis of lifespan patterns of complex mental activity (behavioural). Evidence in the Alzheimer???s disease and ageing literature has been extensive, yet with conflicting reports. In order to better evaluate this evidence, a systematic review of cohort studies is the focus of Chapter 2. Complex mental activity was found to be associated with reduced incidence of dementia and slowed rate of cognitive decline. Neurological brain reserve evidence was limited. A major task of this dissertation was to develop a more standard and complete behavioural brain reserve instrument. Chapter 3 relates the development of the Lifetime of Experiences Questionnaire (LEQ) in a group of 86 healthy elderly. The LEQ had adequate levels of internal consistency and reliability. In a validation test, higher LEQ scores were also found to predict attenuated cognitive decline over 18 months independent of covariates including premorbid IQ. Chapter 4 describes how both LEQ (as a measure of behavioural brain reserve) and intracranial volume (as a measure of neurological brain reserve) significantly predicted cognitive decline over three years in a sample of 70 aged subjects. Total LEQ was furthermore significantly correlated with hippocampal volume independent of intracranial volume, and this association mediated the relationship with cognitive decline. Behavioural brain reserve may therefore work by protecting individuals from hippocampal atrophy. The fifth chapter explores therapeutic and neurobiological aspects of behavioural brain reserve in a preliminary fashion. A randomized-control mental activity trial was run with 20 healthy elderly who received repeat magnetic resonance spectroscopy. Mental activity subjects were found to have selective and sustained upregulation of phosphocreatine metabolism in the hippocampal region, a finding of potential neuroprotective significance. Experience-dependent neuroplasticity is proposed as a unifying framework in the final chapter, allowing synthesis of the present findings and reconciliation of the neurological and behavioural approaches to brain reserve.

Magnetic resonance imaging (MRI) is a valuable imaging technique. It provides excellent soft tissue contrast and multi-parametric non-invasive imaging protocols. Among those various techniques, diffusion MRI measures the water diffusion properties of biological tissue. It is a useful tool in characterizing various brain tissue microstructures quantitatively. With its rapid development, it is emerging that subtle changes can be probed by diffusion tensor imaging (DTI) quantitation. The objectives of this doctoral work are to access the subtle microstructural alterations in rodent brains due to hemodynamic changes, fear conditioning and sleep deprivation using in vivo DTI. With the improved reproducibility and specificity achieved by using advanced post-processing and animal preparation procedures, in vivo DTI is expected to be useful to explore the underlying biological mechanisms for posttraumatic stress disorder and memory deficit following sleep loss in human. Firstly, as DTI could be influenced by the presence of water molecules in brain vasculature, for better understand the reproducibility and sensitivity of in vivo DTI measurements, conventional DTI protocol was applied to a well-controlled rat model of hypercapnia. Our data demonstrated that diffusivities increased in whole brain, gray and white matter regions in response to hypercapnia. These results indicate that in vivo DTI quantitation in brain can be interfered by vascular factors on the order of few percents. Cautions should be taken in designing and interpreting quantitative DTI studies as all DTI indices can be potentially confounded by physiologic conditions, cerebrovascular and hemodynamic characteristics. Secondly, recent DTI studies have shown detection of long-term neural plasticity weeks to months following relatively extensive periods of training in animals. However, rapid plasticity within a short period (24 hours) after learning is important for observing the time course of training-evoked changes and narrow down candidate mechanisms. Fear conditioning (FC), which typically occurs over a short timescale (in minutes), was selected as a paradigm for investigation. Using voxel-wise repeated measures analysis, FA was found to increase in amygdala and decrease in hippocampus 1-hour post-FC, and it reversed in both regions 1-day post-FC. Results indicate that DTI can detect rapid microstructural changes in brain regions known to mediate fear conditioning in vivo. DTI indices could be explored as a translational tool to capture potential early biological changes in individuals at risk for developing post-traumatic stress disorder. Thirdly, in vivo DTI was employed to access regional specific microstructural changes following rapid eye movement sleep deprivation (SD), and explore possible temporal differentiation of these changes. With voxel-base analysis, MD is found to decrease in post-SD time points in bilateral hippocampi and cerebral cortex. The distributions of these clusters exhibited differentiable layer specific patterns, which were pointing to dentate gyrus and CA1 layer in hippocampus, and parietal cortex and barrel field layers in cerebral cortex. Results indicate that in vivo DTI is capable to detect microstructural changes in specific layers and reveal temporal distinction between them. These specific layers are possibly more susceptible to sleep loss, and the temporal distinction of changes between these layers might underlie learning and memory decline after SD. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique for monitoring of brain functional activity. It uses near-infrared (NIR) light to get the information related to brain hemodynamic response as most of the tissues in the brain are transparent to NIR light. The main goal of this study was to design, implement and evaluate a continuous-wave near-infrared spectroscopy (CW-NIRS) system for human’s brain cognitive functions. This system is portable, and works with a small rechargeable battery; thus, it may be used for bedside monitoring. In our CW-NIRS system, we used 3 multi-wavelength LEDs and 8 photodiodes (with built-in amplifiers) resulting in 12 channels (voxels). The collected signals of these 12 channels, at a sampling rate of 15 Hz, can be used for 2D image reconstruction to monitor functional brain activity. All LEDs and photodiodes are placed on a flexible printed circuit board (PCB), which covers the forehead to measure hemodynamic response of the prefrontal cortex. We also developed a software in MATLAB for analysis of optical signals recorded by our CW-NIRS system. This software provides 2D image reconstruction and monitoring of changes in concentration of oxygenated ([HbO2]) and deoxygenated ([HbR]) hemoglobin as well as the total hemoglobin ([HbT]) for the 12 channels over the prefrontal cortex (forehead). The software has also an embedded statistical analysis option for analyzing the collected signals and displaying the results. The developed CW-NIRS system was evaluated on 14 individuals (24±3 years old) on two common cognitive tasks: verbal fluency task (VFT) and color distinction task (CDT). In both tests, we observed that as the cognitive task begins [HbO2] and [HbT] increase and [HbR] decreases, after a few seconds delay. Furthermore, at the end of the tasks as subjects close their eyes in the second rest state, all three hemodynamic signals converge toward baseline ([HbO2] and [HbT] decrease and [HbR] increases). Also, the difference between hemodynamic signals at the rest state and task state was highly significant (p < 9.95e-11) in all 12 channels and in both cognitive tasks. The results confirm the ability of the designed CW-NIRS system to detect functional brain activities.