The ascending cholinergic and serotonergic projections are central to cortical activation and normal behavior. The objective of this thesis was to determine whether unilaterally damaging both of these systems would disrupt the production of skilled movements on the contralateral side of the body. Rats received unilateral damage to either the ascending cholinergic, or serotonergic, or both projections. The respective lesions reduced neocortical leveles of acetylcholine and serotonin as assessed by acetylcholinesterase reactivity and immunohistochemical staining for serotonin. Subjects were assessed on a battery of sensorimotor tasks sensitive to neocortical integrity. The cholinergic lesion produced mild deficits on some taks but damage to both together did not abolish skilled movement. The impairments are decreased in relation to the severe effects of bilateral lesions. The results show that the sensorimotor cortex remains functional following deafferentation of both cholinergic and serotonergic afferents. / vii, 166 leaves : ill. ; 28 cm.

The aim of this thesis is to demonstrate that new and varied views of dementia surface when the concept of intersectionality is applied to dementia research; and that these perspectives pose challenges to our assumptions about what it is like to have dementia. Grounded theory research from a feminist and anti-oppression perspective was undertaken to explore the question of the relationships between older people‘s experiences of dementia and the intersections of gender, class, ‘race’, and ethnicity. During nine months of field research in Canada, interviews, participant observation, photography, and focus groups were undertaken with eight older people with dementia and their significant others. The participants ranged from multiply marginalized to multiply privileged on the basis of their ‘race’, ethnicity, gender, and class. The grounded theory arising from this research explains the complex nature of the relationships between the subjective experiences of older people living with dementia and the intersections of ethnicity, ‘race’, class, and gender. I argue that there is a connection between social location and lived experiences of dementia; and that these relationships can be observed across and within the categories of experiencing, othering, and theorising. Experiencing captures the diversity of older people’s experiences of dementia, which range from ‘not a big deal’ to ‘a nuisance’ to ‘hellish’: these views are associated with social location, with the multiply privileged older people holding the most negative views of dementia and the multiply marginalized older people dismissing the significance of dementia. Othering refers to the marginalisation to which people with dementia are subject: it is shown to be a marked feature of life with dementia and to be connected to social location, with the multiply privileged people being othered more often as a result of their dementia status; the more marginalised participants demonstrating resilience (as an acquired characteristic); and all being subject to both othering practices and enabling behaviours enacted by members of their social worlds, such as their significant others. The theorising category refers to people with dementia being active meaning makers who theorise about dementia: the outcome of this intellectual activity is shown to be related to social location, with the most privileged participants being the only ones to view dementia as a brain disease; and all others making strategic use of the normal aging theory to avoid marginalisation due to dementia. The result of the theorising done by older people with dementia is a dialectical theory of dementia that positions dementia as a bio-psycho-social phenomenon, disrupts the false dichotomy between normal and pathological, and integrates emic and etic perspectives on dementia.

Indiana University-Purdue University Indianapolis (IUPUI) / Dementia studies often collect multiple longitudinal neuropsychological measures in order to examine patients' decline across a number of cognitive domains. Dementia patients have shown considerable heterogeneities in individual trajectories of cognitive decline, with some patients showing rapid decline following diagnoses while others exhibiting slower decline or remain stable for several years. In the first part of this dissertation, a multivariate finite mixture latent trajectory model was proposed to identify longitudinal patterns of cognitive decline in multiple cognitive domains with multiple tests within each domain. The expectation-maximization (EM) algorithm was implemented for parameter estimation and posterior probabilities were estimated based on the model to predict latent class membership. Simulation studies demonstrated satisfactory performance of the proposed approach. In the second part, a simulation study was performed to compare the performance of information-based criteria on the selection of the number of latent classes. Commonly used model selection criteria including the Akaike information criterion (AIC), Bayesian information criterion (BIC), as well as consistent AIC (CAIC), sample adjusted BIC (SABIC) and the integrated classification likelihood criteria (ICLBIC) were included in the comparison. SABIC performed uniformly better in all simulation scenarios and hence was the preferred criterion for our proposed model. In the third part of the dissertation, the multivariate finite mixture latent trajectory model was extended to situations where the true latent class membership was known for a subset of patients. The proposed models were used to analyze data from the Uniform Data Set (UDS) collected from Alzheimer's Disease Centers across the country to identify various cognitive decline patterns among patients with dementia.

The Bayesian network (BN) formalism is a powerful representation for encoding domains characterised by uncertainty. However, before it can be used it must first be constructed, which is a major challenge for any real-life problem. There are two broad approaches, namely the hand-crafted approach, which relies on a human expert, and the data-driven approach, which relies on data. The former approach is useful, however issues such as human bias can introduce errors into the model. We have conducted a literature review of the expert-driven approach, and we have cherry-picked a number of common methods, and engineered a framework to assist non-BN experts with expert-driven construction of BNs. The latter construction approach uses algorithms to construct the model from a data set. However, construction from data is provably NP-hard. To solve this problem, approximate, heuristic algorithms have been proposed; in particular, algorithms that assume an order between the nodes, therefore reducing the search space. However, traditionally, this approach relies on an expert providing the order among the variables --- an expert may not always be available, or may be unable to provide the order. Nevertheless, if a good order is available, these order-based algorithms have demonstrated good performance. More recent approaches attempt to ''learn'' a good order then use the order-based algorithm to discover the structure. To eliminate the need for order information during construction, we propose a search in the entire space of Bayesian network structures --- we present a novel approach for carrying out this task, and we demonstrate its performance against existing algorithms that search in the entire space and the space of orders. Finally, we employ the hand-crafting framework to construct models for the task of diagnosis in a ''real-life'' medical domain, dementia diagnosis. We collect real dementia data from clinical practice, and we apply the data-driven algorithms developed to assess the concordance between the reference models developed by hand and the models derived from real clinical data.

It was hypothesized that 192 IgG-saporin lesions of the basal forebrain cholinergic system (BFCS) would disrupt differential reinforcement of low rate (DRL) learning in an uncued DRL task, but would not impair acquisition and performance in the cued version of the task. Results suggest that BFCS lesions impair vigilance to the external cues despite continued practice in the cued DRL, whereas continuous attention to internally produced cues recovers with extended practice in the uncued DRL.

Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer's disease (AD) is the most common form of dementia defined by loss in memory and cognitive abilities severe enough to interfere significantly with daily life activities. Amnestic mild cognitive impairment (MCI) is a clinical condition in which an individual has memory deficits not normal for the individual's age, but not severe enough to interfere significantly with daily functioning. Every year, approximately 10-15% of individuals with MCI will progress to dementia. Currently, there is no treatment to slow or halt AD progression, but research studies are being conducted to identify causes that can lead to its earlier diagnosis and treatment. Genetic variation plays a key role in the development of AD, but not all genetic factors associated with the disease have been identified. Copy number variants (CNVs), a form of genetic variation, are DNA regions that have added genetic material (duplications) or loss of genetic material (deletions). The regions may overlap one or more genes possibly affecting their function. CNVs have been shown to play a role in certain diseases. At the start of this work, only one published study had examined CNVs in late-onset AD and none had examined MCI. In order to determine the possible involvement of CNVs in AD and MCI susceptibility, genome-wide CNV analyses were performed in participants from three cohorts: the ADNI cohort, the NIA-LOAD/NCRAD Family Study cohort, and a unique cohort of clinically characterized and neuropathologically verified individuals. Only participants with DNA samples extracted from blood/brain tissue were included in the analyses. CNV calls were generated using genome-wide array data available on these samples. After detailed quality review, case (AD and/or MCI)/control association analyses including candidate gene and genome-wide approaches were performed. Although no excess CNV burden was observed in cases compared to controls in the three cohorts, gene-based association analyses identified a number of genes including the AD candidate genes CHRFAM7A, RELN and DOPEY2. Thus, the present work highlights the possible role of CNVs in AD and MCI susceptibility warranting further investigation. Future work will include replication of the findings in independent samples and confirmation by molecular validation experiments.