This study investigated the hypothesis that severity of depressive symptoms following acute ischemic stroke is associated with degree of tissue infarction and severity of white matter changes (WMCs). It employed a novel quantitative region-based approach considering both infarction and WMCs. Of 54 ischemic stroke patients recruited, 50 (72.3 ± 12.8 years, 52.0% male) had useable CT scans. The typical patient was recruited within 3 weeks of their stroke (19.7 ± 31.0 days), exhibited minor cognitive impairment (MMSE score 25.8 ± 4.6), and had mild to moderate stroke severity (NIHSS score 6.5 ± 5.4). 28.0% of patients screened positive for clinical depression with a CES-D score ≥16. While neither degree of infarction nor severity of WMCs (ARWMC score) in the 12 brain regions correlated with depressive symptoms (CES-D score), stroke severity was a significant predictor of depressive symptoms. This stressor, related to physical disability, was a predominant predictor over lesion characteristics.

This study investigated the hypothesis that severity of depressive symptoms following acute ischemic stroke is associated with degree of tissue infarction and severity of white matter changes (WMCs). It employed a novel quantitative region-based approach considering both infarction and WMCs. Of 54 ischemic stroke patients recruited, 50 (72.3 ± 12.8 years, 52.0% male) had useable CT scans. The typical patient was recruited within 3 weeks of their stroke (19.7 ± 31.0 days), exhibited minor cognitive impairment (MMSE score 25.8 ± 4.6), and had mild to moderate stroke severity (NIHSS score 6.5 ± 5.4). 28.0% of patients screened positive for clinical depression with a CES-D score ≥16. While neither degree of infarction nor severity of WMCs (ARWMC score) in the 12 brain regions correlated with depressive symptoms (CES-D score), stroke severity was a significant predictor of depressive symptoms. This stressor, related to physical disability, was a predominant predictor over lesion characteristics.

Provoked Vestibulodynia (PVD) is the most common form of chronic vulvar pain, affecting 12% of women in the general population. Research has demonstrated that women with PVD display both allodynia and hyperalgesia to pain at vulvar and non-vulvar sites, as well as reduced psychosocial functioning. The goal of this study was to use a multi-method approach (interview, questionnaires, sensory testing, and fMRI) to examine group differences between women with PVD (N=15) and healthy control women (N=15). Results will allow for improved understanding of the interaction between psychosocial and neurobiological underpinnings of this disorder, which can contribute to the creation of better treatment strategies. Variables included psychophysical and psychosocial measures, as well as neural activations associated with painful pressure, painful words, and psychosocial functioning. Differences between subgroups of PVD, based on temporal onset, were also examined. There were no robust group differences in neural activation during the application of pain or pain words. This finding is consistent with many studies that match groups on pain intensity ratings, as opposed to amount of pressure applied. Painful pressures and painful words resulted in greater neural activation than neutral words or touch; however, there were no group differences for the word conditions. Women with PVD reported increased psychosocial dysfunction, including higher levels of anxiety and catastrophizing. Significant correlations were found between these psychosocial variables and areas of the brain associated with pain modulation and attention (e.g., PFC). Examination of PVD subgroups revealed differences in neural correlates of anxiety and catastrophizing during painful stimulation. This finding adds to the literature suggesting that women with primary PVD experience greater dysfunction than women with secondary PVD. Overall, these studies support findings of pain processing in the general pain literature, as well as supporting PVD as a chronic pain condition. They also add to the development of a greater understanding of the interaction between psychophysical and psychosocial components of chronic pain by examining their relationship with neural activations. Future research should examine brain functioning in PVD women pre- and post-treatment as well as examining neural correlates of other psychosocial variables that contribute to the pain experience (e.g., somatization). / Thesis (Ph.D, Psychology) -- Queen's University, 2013-01-30 09:14:09.652

Attention is a cognitive process essential to daily function. As attention encompasses an extremely broad array of cognitive subprocesses, there remains much to be discovered about the brain regions related to attention with neuroimaging. This thesis presents two studies that used functional magnetic resonance imaging to examine neural activity associated with different forms of attentional control. In the first study, we scanned healthy young adults while they performed the Stroop task, which measures selective attention, to investigate neural responses underlying unanticipated conflict detection. We found several regions across the frontal, parietal, and occipital lobes that became more active during states of unanticipated conflicts, relative to states of anticipated conflicts. These regions included the anterior cingulate, dorsolateral prefrontal cortex, angular gyrus, inferior parietal lobule, precuneus, lingual gyrus, and fusiform gyrus. Activity in these regions has previously been associated with attentional processes such as conflict detection, attention, orientation, and oddball detection. Our results therefore suggest that widespread areas of the cortex serve several cognitive processes involved in successfully monitoring and responding to unanticipated conflicts. In the second study, we tested young and cognitively healthy older adults with the Stroop task to determine whether aging affects the neural mechanisms underlying attentional lapses, defined as relatively longer response times. Like previous studies in young adults, we found regions in the default mode network exhibited greater activity as reaction time to stimuli increased. Attentional lapses were also preceded by decreased activity in regions related to attention, including the anterior cingulate and prefrontal cortices. Most importantly, young adults showed greater positive reaction time-modulated activity in default mode areas, while older adults exhibited greater positive reaction time-modulated activity in more prefrontal areas. Our results suggest that the neural correlates of attentional lapses change with healthy aging, reinforcing the idea of functional plasticity to maintain high cognitive function throughout the lifespan. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2013-08-22 11:33:32.418

Eating disorders are difficult to treat: there is still no NICE-approved first-line treatment for anorexia nervosa. In part this could be due to a lack of a compelling theoretical model to account for the development and dogged persistence of the illness. Sociocultural factors implicating western preoccupation with thinness and attractiveness are likely to play a contributory role, but cannot be by themselves causal in societies where such ideals are dominant. Recent theoretical models in neuroscience predict that predisposing neurobiological factors in early brain development may render some young people more vulnerable than others to universal psychosocial pressures, especially during adolescence. This dissertation reviews the existing evidence for abnormal neurobiological functioning in eating disorders, acknowledging that it is difficult to distinguish between the acute effects of starvation on the brain and possibly pre-existing underlying factors. Nevertheless, such empirical studies do support the development of a novel hypothesis implicating abnormal functioning of a neural network centred on the insula cortex in anorexia nervosa. The insula hypothesis is tested in a series of functional imaging studies using Single Positron Emission Computed Tomography (SPECT) indicating focal abnormalities in the temporal region that persist following weight restoration treatment and correlate with neuropsychological deficits. A subsequent study using higher resolution functional Magnetic Resonance Imaging (fMRI) lends further partial support to the insula hypothesis (in three out of four tasks) and also implicates additional brain structures in the basal ganglia. These findings, if replicated, could contribute to the development of novel therapeutic approaches to the treatment of anorexia nervosa, including realtime fMRI and mindfulness-based approaches, both of which have been shown to modulate insula activation. The studies presented here could hopefully also help to reduce the stigma and shame so often associated with eating disorders, for the benefit of sufferers and their families.

This thesis presents research focused on developing statistical methods with emphasis on tools that can be used for the analysis of data in neuroimaging studies and cognitive science. The first contribution addresses the problem of determining the location and dynamics of brain activity when electromagnetic signals are collected using magnetoencephalography (MEG) and electroencephalography (EEG). We formulate a new spatiotemporal model that jointly models MEG and EEG data as a function of unobserved neuronal activation. To fit this model we derive an efficient procedure for simultaneous point estimation and model selection based on the iterated conditional modes algorithm combined with local polynomial smoothing. The methodology is evaluated through extensive simulation studies and an application examining the visual response to scrambled faces. In the second contribution we develop a Bayesian spatial model for imaging genetics developed for analyses examining the influence of genetics on brain structure as measured by MRI. We extend the recently developed regression model of Greenlaw et al. (\textit{Bioinformatics}, 2017) to accommodate more realistic correlation structures typically seen in structural brain imaging data. We allow for spatial correlation in the imaging phenotypes obtained from neighbouring regions in the same hemisphere of the brain and we also allow for correlation in the same phenotypes obtained from different hemispheres (left/right) of the brain. This correlation structure is incorporated through the use of a bivariate conditional autoregressive spatial model. Both Markov chain Monte Carlo (MCMC) and variational Bayes approaches are developed to approximate the posterior distribution and Bayesian false discovery rate (FDR) procedures are developed to select SNPs using the posterior distribution while accounting for multiplicity. The methodology is evaluated through an analysis of MRI and genetic data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and we show that the new spatial model exhibits improved performance on real data when compared to the non-spatial model of Greenlaw et al. (2017). In the third and final contribution we develop and investigate tools for the analysis of binary data arising from repeated measures designs. We propose a Bayesian approach for the mixed-effects analysis of accuracy studies using mixed binomial regression models and we investigate techniques for model selection. / Graduate

Understanding the mechanisms of poor decision making and risk behavior in adolescence is an important goal. Two important features of adolescence relevant to these concerns are the saliency of social acceptance and increased frequency of making decisions in the company of peers. The current study examines individual differences in susceptibility to peer influence and the effect of positive and negative social contexts on adolescent decision making. Fifty-five adolescents (11.2-17.6 years of age) completed measures of social susceptibility and risk behavior and subsequently underwent functional magnetic resonance imaging while completing a simulated driving game in three conditions: alone, while being watched by peers, and after an event of social exclusion. Individual differences in susceptibility to peers predicted a decrease in adaptive decision making following exclusion by peers. Adolescents with greater self-reported engagement in substance use, risky sexual behavior, and aggressive behavior performed worse on the game following social exclusion. Neuroimaging results showed relatively greater activation in the striatum during risky decisions (Go through a yellow light) in the peer condition compared to the social exclusion condition. Whole-brain and region of interest analyses revealed a significant decrease in striatal activity during Go decisions following social exclusion. Adolescents who were more susceptible to peer influence and engaged in more risk behavior evidenced the greatest decreases in striatal activity after social exclusion. Results suggest that susceptibility to peer influence interacts with the experience of social exclusion to produce maladaptive decision making in adolescents. More broadly, the results demonstrate that individual differences and social contexts are both important factors affecting adolescent decisions and that changes in momentary levels of social acceptance can influence the quality of adolescent decisions in social situations. These findings suggest that the explanatory power of existing models of adolescent decision making could be extended by exploring individual differences in decision making within and across social contexts, including peer influence and social exclusion, to provide a more comprehensive account of which adolescents are prone to making poor decisions and when.

The purpose of this thesis is threefold: 1) A behavioral examination of the role of diacritics in Arabic, 2) A functional magnetic resonance imaging (fMRI) investigative study of diacritics in Arabic, and 3) An optimization algorithm for brain mapping and detecting brain function. Firstly, the role of diacritics in Arabic was examined behaviorally. The stimulus was a lexical decision task (LDT) that constituted of low, mid, and high frequency words and nonwords; with and without diacritics. Results showed that the presence of vowel diacritics slowed reaction time but did not affect word recognition accuracy. The longer reaction times for words with diacritics versus without diacritics suggest that the diacritics may contribute to differences in word recognition strategies. Secondly, an Event-related fMRI experiment of lexical decisions associated with real words with versus without diacritics in Arabic readers was done. Real words with no diacritics yielded shorter response times and stronger activation than with real words with diacritics in the hippocampus and middle temporal gyrus possibly reflecting a search from among multiple meanings associated with these words in a semantic store. In contrast, real words with diacritics had longer response times than real words without diacritics and activated the insula and frontal areas suggestive of phonological and semantic mediation in lexical retrieval. Both the behavioral and fMRI results in this study appear to support a role for diacritics in reading in Arabic. The third research work in this thesis is an optimization algorithm for fMRI data analysis. Current data-driven approaches for fMRI data analysis, such as independent component analysis (ICA), rely on algorithms that may have low computational expense, but are much more prone to suboptimal results. In this work, a genetic algorithm (GA) based on a clustering technique was designed, developed, and implemented for fMRI ICA data analysis. Results for the algorithm, GAICA, showed that although it might be computationally expensive; it provides global optimum convergence and results. Therefore, GAICA can be used as a complimentary or supplementary technique for brain mapping and detecting brain function by way of fMRI.

Alcoholism has been linked to cognitive, behavioral, and emotional defects, and damage to the cerebellum has been associated with aspects of these impairments. However, little is known about the role of damage to specific cerebellar subregions in the deficits, nor about possible gender differences in alcoholism-related cerebellar abnormalities. In this study, volumetric analyses of specific cerebellar regions were performed in relation to the interactions of alcoholism, gender, and measures of drinking history. Structural brain scans of 44 alcoholics (23 men) and 39 nonalcoholic controls (18 men) were obtained using T1 magnetic resonance imaging at 3T. Scans were manually labeled according to cerebellar features, using methodology developed at the Center for Morphometric Analyses, Massachusetts General Hospital, Boston. Each lobule was parcellated and mediolateral divisions were delineated. In addition to measuring total cerebellar gray and white matter, along with the anterior and posterior lobes, we also measured volumes for a priori regions of interest that have been shown to correspond to functions impaired in alcoholism: emotion, executive functions, working memory, motor abilities, and spatial abilities. Total cerebellar white matter volume was observed to be smaller in alcoholic than in nonalcoholic participants, but this difference was not observed for total gray matter volume. Moreover, the volumes of the cortical parcellation units we selected varied with drinking history, including negative associations between (a) years of heavy drinking, and (b) volumes of the anterior and flocculonodular lobes, and of the spinocerebellar region. The negative association between anterior volume and years of heavy drinking was driven primarily by alcoholic men. Additionally, we observed that white and gray cerebellar volumes for alcoholic women were significantly larger than for alcoholic men, but this pattern of gender differences was not significant for the control group. The identification of drinking-related abnormalities in cerebellar subregions builds upon prior findings in other regions of the brain, and lays a foundation that can be utilized to inform how cerebro-cerebellar networks are perturbed in this pathological condition. The results also provide estimates of how individual differences in drinking history can predict cerebellar volumes, and how the impact of drinking differs for men and women.

A thorough delineation of the extent of processing possible without visual awareness is necessary to elucidate the neural mechanisms of visual awareness. Despite extensive research, it is presently unclear whether invisible stimuli can undergo advanced processing. To introduce existing work on this topic, previous behavioral efforts to investigate the extent of processing possible without visual awareness and the psychophysical methods used to render stimuli invisible, such as visual masking and interocular suppression-based techniques, are discussed. Physiological evidence that provide support for and against the possibility that advanced information processing can occur without visual awareness are addressed. The basics of multivariate pattern classification techniques are outlined. The potential of using multivariate pattern classification analyses in conjunction with neuroimaging in the temporal domain to investigate whether advanced processing can occur without visual awareness is discussed. An original study using electroencephalography (EEG) and pattern classification techniques to investigate the extent of processing possible without visual awareness is outlined. The results of the analyses reveal that a pattern classifier did not extract neural signatures of categorical processing from EEG recordings when participants viewed an image that remained invisible for the duration of its presentation. In contrast, the results from a second experiment reveal that the pattern classifier was able to decode the category of invisible images from the EEG time series when the images would eventually become visible. The results provide support for the idea that under certain circumstances, such as when the depth of interocular suppression is reduced, advanced processing for invisible stimuli can occur. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection