Browsing by Subject "Dependence"
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Item Affective responses in cocaine-experienced rats reveal cue-induced drug craving and cocaine reward magnitude(2011-08) Maier, Esther Yvonne; Duvauchelle, Christine L.; Schallert, Timothy; Gonzales, Rueben A.; Gore, Andrea C.; Monfils, Marie H.The development and persistence of cocaine dependence are greatly influenced by emotional affect and cocaine associative learning. Cocaine is known to enhance nucleus accumbens (NAcc) dopamine, serve as a positive reinforcer and produce negative effects, such as anxiety that may influence cocaine intake behavior. In the first study, I investigated the effects of the anxiolytic, diazepam on NAcc dopamine levels and cocaine self-administration behavior. These are two factors associated with cocaine rewarding effects. Diazepam has no effect on NAcc dopamine, but affects cocaine self-administration. This supports the notion that decreasing the anxiogenic effects of cocaine increases the rewarding value in a dopamine independent manner. Therefore, increasing the aversive effects of cocaine might be a novel approach to fight cocaine dependence. In the second study, I studied cocaine-induced associative learning and changes in affect during cocaine conditioning and extinction. 50-kHz ultrasonic vocalizations (USVs) in rats are thought to reflect positive affect and occur upon appetitive stimuli and with cocaine delivery. First, I explored whether USVs might be elicited in anticipation of impending drug delivery. Shortly into conditioning, rats elicited USVs when placed in the cocaine-associated environment. USVs progressively increased, indicating a growing learned association between cocaine intake and cocaine-associated cues. This suggests that USVs may be a useful model for investigating cocaine craving and serve as a pharmacological target for interventions aimed to reduce cocaine craving and relapse. I then examined the effects of short-term deprivation of cocaine and cocaine cues on cocaine-conditioned USVs, which were both exaggerated after abstinence. The results may have clinical implications, in that intermittently avoiding cues or context may enhance drug cue salience and increase the probability of relapse. Motivational aspects of cocaine were assessed comparing commonly measured lever response rate and locomotion with cocaine-induced USVs during cocaine administration and extinction. In agreement with prevailing findings, lever responding for cocaine and cocaine-induced locomotor activity increased across conditioning sessions. However, the number of USVs evoked in response to cocaine infusion decreased with cocaine experience. These findings suggest growing tolerance to the rewarding properties of cocaine. These studies underscore the value of USV assessment during drug dependence studies.Item An analysis of school type and sources of funding in Taiwan's national higher education institutions: a resource dependence perspective(Texas Tech University, 2007-12) Chen Lay, Suh-Jen; Tallent-Runnels, Mary K.; Lan, William; Oliver, DianeSince the Ministry of Education (MOE) in Taiwan mandated that public higher education institutions (HEIs) implement the University Fund system in 1996, generating operating income has become the responsibility of the administration of the individual public HEI. The ability to generate income from alternative sources affects the development of public HEIs. The purpose of this study is to use the resource dependence theory to investigate the University Fund sources at 49 Taiwanese national colleges and universities. This research will explore whether different type institutions (General or Technological) rely differently on each of the operating income sources, and whether the effects of Type of Institution, Year, Source of funding, and the interaction of Type of Institution, Year, and Source of Funding are significantly different on the dependence on operating income resource. This study used archival data from the University Fund annual financial reports from the years 2001 to 2006 that are submitted to the MOE by the 49 national HEIs in Taiwan. To comprehensively examine the effects of variables of Type of Institution (General vs. Technological), Year (years from 2001 to 2006), and Source of Funding (tuition and fees, cooperative education income, extended education income, and government subsidies) on the dependence of the operating income resource, a repeated measures analysis of variance (ANOVA) with two within-subject factors, Year (6 levels) and Source of Funding (4 levels), and one between-subject factor of Type of Institution (2 levels) was conducted. The follow-up tests for the significant interaction effects and comparisons following up the significant main effects were computed. All tests were evaluated at the significance level of .05. The analysis provided information of both descriptive and inferential statistics to answer the research questions proposed. The results indicated that the main effects of Year and Source of Funding and the interaction effects between Type of Institution and Source of Funding and between Year and Source of Funding were significant. The dependence order was the same for both types of HEI. The source of government subsidies was the highest, tuition and fees the second, cooperative education income the third, and extended education income the last among the four sources of funding. The dependence on operating income had significant change across the years 2001 to 2006 and revealed a decreasing trend in both types of HEIs as well as the national HEIs. The dependence on operating income resources revealed significantly different associations with the four sources of funding for national HEIs in Taiwan. General HEIs had higher dependence on cooperative and extended education income than did Technological HEIs, but General HEIs had lower dependence on tuition and fees than did the Technological HEIs. Both types of HEIs had the same dependence on government subsidies.Item Coefficient of intrinsic dependence: a new measure of association(Texas A&M University, 2005-08-29) Liu, Li-yu DaisyTo detect dependence among variables is an essential task in many scientific investigations. In this study we propose a new measure of association, the coefficient of intrinsic dependence (CID), which takes value in [0,1] and faithfully reflects the full range of dependence for two random variables. The CID is free of distributional and functional assumptions. It can be easily implemented and extended to multivariate situations. Traditionally, the correlation coefficient is the preferred measure of association. However, it's effectiveness is considerably compromised when the random variables are not normally distributed. Besides, the interpretation of the correlation coefficient is difficult when the data are categorical. By contrast, the CID is free of these problems. In our simulation studies, we find that the ability of the CID in differentiating different levels of dependence remains robust across different data types (categorical or continuous) and model features (linear or curvilinear). Also, the CID is particularly effective when the dependence is strong, making it a powerful tool for variable selection. As an illustration, the CID is applied to variable selection in two aspects: classification and prediction. The analysis of actual data from a study of breast cancer gene expression is included. For the classification problem, we identify a pair of genes that best classify a patient's prognosis signature, and for the prediction problem, we identify a pair of genes that best relates to the expression of a specific gene.Item Ethanol dependence in Drosophila larvae(2013-08) Robinson, Brooks Gregory; Atkinson, Nigel (Nigel S.)Addiction to alcohol is a disease of changed behavior that is uniquely human in it's complexity. Because of this, researchers have strived to develop animal models of individual endophenotypes of alcoholism in hopes that the larger picture will eventually come into focus. Recent studies in Drosophila have shown that many complex alcohol-related behaviors are conserved in this genetic model system. The series of projects presented in this dissertation outline the first account of physiological ethanol dependence in Drosophila. We first show that Drosophila larvae are able to form conditioned associations between an aversive heat stimulus and an attractive odor. We then show that an acute, low-dose ethanol exposure disrupts this learning ability. Finally, we present data that demonstrate that larvae adapt to the presence of chronic ethanol to the point that they only perform normally in the learning assay when ethanol is present in the animal. We then propose that the major mechanism for this dependence involves ethanol regulating the acetylation level and therefore expression level of a large number of genes by inhibiting histone deacetylase enzymes. These experiments set the groundwork for the analysis of a network of genes, connected through interactions with histone deacetylase enzymes, that are involved in producing ethanol dependence.Item Generalizing the multivariate normality assumption in the simulation of dependencies in transportation systems(2010-05) Ng, Man Wo; Waller, S. Travis; Hasenbein, John J.By far the most popular method to account for dependencies in the transportation network analysis literature is the use of the multivariate normal (MVN) distribution. While in certain cases there is some theoretical underpinning for the MVN assumption, in others there is none. This can lead to misleading results: results do not only depend on whether dependence is modeled, but also how dependence is modeled. When assuming the MVN distribution, one is limiting oneself to a specific set of dependency structures, which can substantially limit validity of results. In this report an existing, more flexible, correlation-based approach (where just marginal distributions and their correlations are specified) is proposed, and it is demonstrated that, in simulation studies, such an approach is a generalization of the MVN assumption. The need for such generalization is particularly critical in the transportation network modeling literature, where oftentimes there exists no or insufficient data to estimate probability distributions, so that sensitivity analyses assuming different dependence structures could be extremely valuable. However, the proposed method has its own drawbacks. For example, it is again not able to exhaust all possible dependence forms and it relies on some not-so-known properties of the correlation coefficient.Item Mesocorticolimbic adaptations in synaptic plasticity underlie the development of alcohol dependence(2012-08) Jeanes, Zachary Marvin; Morrisett, Richard A.Synaptic alterations in the nucleus accumbens (NAc) are crucial for the aberrant reward-associated learning that forms the foundation of drug dependence. Glutamatergic synaptic plasticity in the NAc has been implicated in several behavioral responses to psychomotor stimulating agents, such as cocaine and amphetamine, yet no studies, at present, have investigated its modulation by ethanol. We demonstrated that both in vitro and in vivo ethanol treatment significantly disrupts normal synaptic functioning in medium spiny neurons (MSNs) of the NAc shell. Utilizing whole-cell voltage clamp recording techniques, synaptic conditioning (low frequency stimulation with concurrent postsynaptic depolarization) reliably depressed (NAc-LTD) AMPA-mediated excitatory postsynaptic currents (EPSCs). Acute ethanol exposure inhibited the depression of AMPA EPSCs differentially with increasing concentrations, but this inhibitory action of ethanol was reversed by a D1-like dopamine receptor agonist. When examined 24 hours following a single bout of in vivo chronic intermittent ethanol (CIE) vapor exposure, NAc-LTD was absent and instead synaptic potentiation (LTP) was reliably observed. We further investigated CIE-induced modulation of NAc-LTD by distinguishing between the two subpopulations of MSNs in the NAc, D1 receptor-expressing (D1+) and D2 receptor-expressing (D1-). We determined that NAc-LTD is expressed solely in D1+ but not D1- MSNs. In addition, 24 hours following a repeated regimen of in vivo CIE exposure NAc-LTD is completely occluded in D1+ MSNs, while D1- MSNs are able to express LTD. Complete recovery of normal synaptic plasticity expression in both D1+ and D1- MSNs does not occur until two weeks of withdrawal from CIE vapor exposure. To our knowledge, this is the first demonstration of a reversal in the cell type-specificity of synaptic plasticity in the NAc shell, as well as, the gradual recovery of the pre-drug exposure plasticity state following extended withdrawal. This study suggests that NAc-LTD is cell type-specific and highly sensitive to both acute and chronic ethanol exposure. We believe these observations also highlight the adaptability of NAc MSNs to the effects of long-term ethanol exposure. A change in these synaptic processes may constitute a neural adaptation that contributes to the induction and/or expression of alcohol dependence.Item Multivariate real options valuation(2011-05) Wang, Tianyang; Dyer, James S.; Tompaidis, Efstathios; Muthuraman, Kumar; Bickel, J. E.; Butler, John C.; Garlappi, LorenzoThis dissertation research focuses on modeling and evaluating multivariate uncertainties and the dependency between the uncertainties. Managing risk and making strategic decisions under uncertainty is critically important for both individual and corporate success. In this dissertation research, we present two new methodologies, the implied binomial tree approach and the dependent decision tree approach, to modeling multivariate decision making problems with practical applications in real options valuation. First, we present the implied binomial tree approach to consolidate the representation of multiple sources of uncertainty into univariate uncertainty, while capturing the impact of these uncertainties on the project’s cash flows. This approach provides a nonparametric extension of the approaches in the literature by allowing the project value to follow a generalized diffusion process in which the volatility may vary with time and with the asset prices, therefore offering more modeling flexibility. This approach was motivated by the Implied Binomial Tree (IBT) approach that is widely used to value complex financial options. By constructing the implied recombining binomial tree in a way so as to be consistent with the simulated market information, we extended the finance-based IBT method for real options valuation — when the options are contingent on the value of one or more market related uncertainties that are not traded assets. Further, we present a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows multiple dependent uncertainties with arbitrary marginal distributions to be represented in a decision tree with a sequence of conditional probability distributions. This general framework could be naturally applied in decision analysis and real options valuations, as well as in more general applications of dependent probability trees. While this approach to modeling dependencies can be based on several popular copula families as we illustrate, we focus on the use of the normal copula and present an efficient computational method for multivariate decision and risk analysis that can be standardized for convenient application.