Right Prefrontal Cortex Responds to Item Familiarity During a Memory Encoding Task

In a previous word-pair encoding study (Dolan & Fletcher, 1997), we examined the effect of introducing novelty, either in studied words or in their mutual associations. A left medial temporal lobe (MTL) sensitivity to novel words and left prefrontal cortex (PFC) to novel associations was observed. In this further report on the data, we explored the extent to which the right PFC, more generally implicated in retrieval operations (Fletcher, Frith, & Rugg, 1997), was sensitive to these manipulations. Specifically, we characterised changes associated with increasing familiarity of study material. We demonstrate that the response in right ventrolateral PFC is preferentially sensitive to a condition in which all material was familiar (that is, in which all material had been presented prior to scanning). A more dorsal region in right PFC was found to be relatively more active in association with a condition in which one item in the pair was familiar but was paired with a novel associate. Our results suggest that sensitivity to stimulus familiarity is expressed in right PFC, even within the context of an encoding task. The data also provide further evidence for functional heterogeneity within right PFC, with a more ventral region responding to familiarity of complete word pairs and a more dorsal region responding to familiar single words occurring in the context of new associative relationships.     

The criminal and personality profile of patients with schizophrenia and comorbid psychopathic traits

Sixty-one male forensic patients who met the DSM-IV criteria for schizophrenia were categorised into high and low psychopathic trait groups using the Psychopathy Checklist: Screening Version. The groups were compared on their criminal history, symptom profile, personality style, risk scores and subsequent institutional violence. Patients with high scores on the PCL:SV had a greater number of previous convictions and were more likely to have a family history of criminality. The high psychopathy-scoring group had higher levels of Positive and Negative Syndrome Scale grandiose and hostile symptomatology, and higher scores on trait impulsivity and aggression. They also had a more coercive, less compliant interpersonal style than the low-psychopathy scoring group. The high-psychopathy scoring group were more likely to be involved in institutional aggression and had higher levels of risk for violence. Patients with schizophrenia and high levels of comorbid psychopathy have a distinctive interpersonal style that may contribute to their greater risk of disruptive institutional behaviour.     

Fitting multivariage normal finite mixtures subject to structural equation modeling

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the differences between the components in the mixture. Within the general model, individual parameters can be subjected to equality, nonlinear and simple bounds constraints. Confidence intervals are based on the inverse of the Hessian and on the likelihood profile. Several illustrations are given and results of a simulation study concerning the confidence intervals are reported.     

Counsellors' responses to clients' non-attendance at counselling sessions

Although there has been some study of clients who miss psychotherapy appointments, very little attention has been given to therapists' responses in such circumstances. A questionnaire survey of student counsellors working in British higher education institutions invited them to consider whether or not they would initiate any further contact with each of eight hypothetical non-attenders, described in case vignettes. It was predicted that responses would be influenced both by the subjects' theoretical approach to counselling and by their level of interpersonal dependency, as measured with the Interpersonal Dependency Inventory (Hirschfeld et al., 1977). It was found that the majority of counsellors were not subject to institutional guidelines about contacting non-attenders, and that responses ranged from contacting none to contacting all of the clients. Psychodynamic counsellors were found to be significantly more likely to initiate contact than were humanistic counsellors. There were no significant correlations between contact scores and intepersonal dependency scores but women were significantly more likely to initiate contact than were men. Many of the psychodynamic subjects had commented on their therapeutic use of written communications to interpret non-attendance to their clients.     

A framework for ML estimation of parameters of (mixtures of) common reaction time distributions given optional truncation or censoring

We present a framework for distributional reaction time (RT) analysis, based on maximum likelihood (ML) estimation. Given certain information relating to chosen distribution functions, one can estimate the parameters of these distributions and of finite mixtures of these distributions. In addition, left and/or right censoring or truncation may be imposed. Censoring and truncation are useful methods by which to accommodate outlying observations, which are a pervasive problem in RT research. We consider five RT distributions: the Weibull, the ex-Gaussian, the gamma, the log-normal, and the Wald. We employ quasi-Newton optimization to obtain ML estimates. Multicase distributional analyses can be carried out, which enable one to conduct detailed (across or within subjects) comparisons of RT data by means of loglikelihood difference tests. Parameters may be freely estimated, estimated subject to boundary constraints, constrained to be equal (within or over cases), or fixed. To demonstrate the feasibility of ML estimation and to illustrate some of the possibilities offered by the present approach, we present three small simulation studies. In addition, we present three illustrative analyses of real data.     

EZ does it! Extensions of the EZ-diffusion model

In this rejoinder, we address two of Ratcliff’s main concerns with respect to the EZ-diffusion model (Ratcliff, 2008). First, we introduce “robust-EZ,” a mixture model approach to achieve robustness against the presence of response contaminants that might otherwise distort parameter estimates. Second, we discuss an extension of the EZ model that allows the estimation of starting point as an additional parameter. Together with recently developed, user-friendly software programs for fitting the full diffusion model (Vandekerckhove & Tuerlinckx, 2007; Voss & Voss, 2007), the development of the EZ model and its extensions is part of a larger effort to make diffusion model analyses accessible to a broader audience, an effort that is long overdue.     

The power to detect sex differences in IQ test scores using Multi-Group Covariance and Means Structure Analyses

Research into sex differences in general intelligence, g, has resulted in two opposite views. In the first view, a g-difference is nonexistent, while in the second view, g is associated with a male advantage. Past research using Multi-Group Covariance and Mean Structure Analysis (MG-CMSA) found no sex difference in g. This failure raised the question whether the g-difference is truly absent or whether MG-CMSA lacked statistical power to detect it. The present study used the likelihood ratio test to investigate the power to detect a g-difference in the WAIS-III factor structure with MG-CMSA. Various situations were examined including those reported in the literature. Results showed that power varies greatly among different scenarios. The scenarios based on previous results were associated with power coefficients of about 0.5–0.6. Implications of these findings are discussed in the light of research into sex differences in IQ.     

Heteroscedastic one‐factor models and marginal maximum likelihood estimation

In the present paper, a general class of heteroscedastic one‐factor models is considered. In these models, the residual variances of the observed scores are explicitly modelled as parametric functions of the one‐dimensional factor score. A marginal maximum likelihood procedure for parameter estimation is proposed under both the assumption of multivariate normality of the observed scores conditional on the single common factor score and the assumption of normality of the common factor score. A likelihood ratio test is derived, which can be used to test the usual homoscedastic one‐factor model against one of the proposed heteroscedastic models. Simulation studies are carried out to investigate the robustness and the power of this likelihood ratio test. Results show that the asymptotic properties of the test statistic hold under both small test length conditions and small sample size conditions. Results also show under what conditions the power to detect different heteroscedasticity parameter values is either small, medium, or large. Finally, for illustrative purposes, the marginal maximum likelihood estimation procedure and the likelihood ratio test are applied to real data.     

The Price of Pain and the Value of Suffering

ABSTRACT— Estimating the financial value of pain informs issues as diverse as the market price of analgesics, the cost-effectiveness of clinical treatments, compensation for injury, and the response to public hazards. Such valuations are assumed to reflect a stable trade-off between relief of discomfort and money. Here, using an auction-based health-market experiment, we show that the price people pay for relief of pain is strongly determined by the local context of the market, that is, by recent intensities of pain or immediately disposable income (but not overall wealth). The absence of a stable valuation metric suggests that the dynamic behavior of health markets is not predictable from the static behavior of individuals. We conclude that the results follow the dynamics of habit-formation models of economic theory, and thus, this study provides the first scientific basis for this type of preference modeling.