17 research outputs found

    Narcissism, personality and personality pathology

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    This thesis used the methods of differential, cognitive and theoretical psychology to investigate the relationships between pathological narcissism and maladaptive personality and behaviour in general, and to attempt the beginnings of construct validation of M. Scott Peck's proposed `evil' subtype of the DSM -IV Narcissistic Personality Disorder in particular. After a review of theoretical and empirical contributions to the psychology of narcissism, two empirical studies were conducted. In the first, joint self- report survey research using 338 subjects investigated the psychometric structure of narcissism, normal and abnormal personality, and constructs theoretically related to narcissism. Item -level exploratory principal components analysis and confirmatory factor analysis resulted in new subscales for the Narcissistic Personality Inventory. Scale -level exploratory principal components analysis of the combined questionnaires found evidence for a five - factor structure of abnormal personality. One of the five factors was related to narcissistic will to power and low agreeableness; another was related to narcissistic self - love and extraversion. Confirmatory factor analysis of a subset of the data found fair fit for the model.The second study investigated the relationships between narcissism, compartmentalisation, splitting, attribution style and response to disconfirming feedback. No evidence was found to support the hypothesis that narcissists have compartmentalised self -concepts. Moderate test -retest and alternate -form reliability data were obtained for the card -sort task used to assess compartmentalisation. No evidence was found that narcissists use splitting to translocate unwanted self -aspects onto others. Narcissistic dominance was associated with claiming personal credit for positive outcomes, while narcissistic vulnerability was associated with self -blame for negative events. Multiple regression with interaction terms indicated that the relationship between narcissism and response to disconfirming feedback is a function of other personality traits such as neuroticism, and may have opposite effects in different personalities and circumstances. Zero -order correlations suggested significant roles for splitting, narcissistic grandiosity and idealisation, and 12 NEO -PI -R facet -level variables in response to disconfirming feedback.Peck's proposed subtype of narcissistic personality disorder is theoretically distinguished from psychopathy by the use of self- deception to defend the conscience against guilt for the consequences of one's actions, rather than the absence of conscience that characterises psychopathy. Self- deception is among the most difficult and controversial topics in philosophical psychology. Theoretical chapters approached the issue with historical and literary examples, argued that splitting may be a fundamental basis of much self -deception, offered a model of malignant narcissism within the Schematic Propositional Associative Analogue Representation Systems (SPAARS) theory, and addressed the issue in the philosophy of science of whether the proposed personality disorder is a natural or social kind

    White Matter Heritability Using Diffusion Tensor Imaging in Neonatal Brains

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    Understanding genetic and environmental effects on white matter development in the first years of life is of great interest, as it provides insights into the etiology of neurodevelopmental disorders. In this study, the genetic and environmental effects on white matter were estimated using data from 173 neonatal twin subjects. Diffusion tensor imaging scans were acquired around 40 days after birth and were non-rigidly registered to a group-specific atlas and parcellated into 98 ROIs. A model of additive genetic, and common and specific environmental variance components was used to estimate overall and regional genetic and environmental contributions to diffusion parameters of fractional anisotropy, radial diffusivity, and axial diffusivity. Correlations between the regional heritability values and diffusion parameters were also examined. Results indicate that individual differences in overall white matter microstructure, represented by the average diffusion parameters over the whole brain, are heritable, and estimates are higher than found in studies in adults. Estimates of genetic and environmental variance components vary considerably across different white matter regions. Significant positive correlations between radial diffusivity heritability and radial diffusivity values are consistent with regional genetic variation being modulated by maturation status in the neonatal brain: the more mature the region is, the less genetic variation it shows. Common environmental effects are present in a few regions that tend to be characterized by low radial diffusivity. Results from the joint diffusion parameter analysis suggest that multivariate modeling approaches might be promising to better estimate maturation status and its relationship with genetic and environmental effects

    Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction

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    © 2020 American Chemical Society. Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future

    Comparing factor, class, and mixture models of cannabis initiation and DSM cannabis use disorder criteria, including craving, in the Brisbane longitudinal twin study

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    Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use

    Genetic and environmental influences of white and gray matter signal contrast: a new phenotype for imaging genetics?

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    The estimation of cortical thickness is in part dependent on the degree of contrast in T1 signal intensity between white matter and gray matter along the cortical mantle. The ratio of white matter to gray matter signal (WM/GM contrast) has been found to vary as a function of age and Alzheimer's disease status, suggesting a biological component to what might otherwise be labeled as a nuisance variable. The aim of the present study was to determine if measures of WM/GM contrast are genetically influenced, as well as the degree to which this phenotype may be related to the genetic and environment determinants of cortical thickness. Participants were 514 male twins (130 monozygotic, 97 dizygotic pairs, and 60 unpaired individuals) from the Vietnam Era Twin Study of Aging. Ages ranged from 51 to 59 years. Measures of WM/GM contrast and cortical thickness were derived for 66 cortical regions of interest (ROI) using FreeSurfer-based methods. Univariate and bivariate twin analyses were used in order to estimate the heritability of WM/GM contrast, as well as the degree of shared genetic and environmental variance between WM/GM contrast and cortical thickness. WM/GM contrast was found to be significantly heritable in the majority of ROIs. The average heritability across individual ROIs was highest in the occipital lobe (.50), and lowest in the cingulate cortex (.24). Significant phenotypic correlations between WM/GM contrast and cortical thickness were observed for most of the ROIs. The majority of the phenotypic correlations were negative, ranging from ?.11 to ?.54. Of the 66 associations, only 17 significant genetic correlations were found, ranging from ?.16 to ?.34, indicating small amounts of shared genetic variance. The majority of the phenotypic correlations were accounted for by small unique environmental effects common between WM/GM contrast and cortical thickness. These findings demonstrate that like cortical thickness, WM/GM contrast is a genetically influenced brain structure phenotype. The lack of significant genetic correlations with cortical thickness suggests that this measure potentially represents a unique source of genetic variance, one that has yet to be explored by the field of imaging genetics
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