Unraveling Brain Functional Connectivity of encoding and retrieval in the context of education

Human memory is an enigmatic component of cognition which many researchers have attempted to comprehend. Accumulating studies on functional connectivity see brain as a complex dynamic unit with positively and negatively correlated networks in perfect coherence during a task. We aimed to examine coherence of network connectivity during visual memory encoding and retrieval in the context of education. School Educated (SE) and College Educated (CE) healthy volunteers (n = 60) were recruited and assessed for visual encoding and retrieval. Functional connectivity using seed to voxel based connectivity analysis of the posterior cingulate cortex (PCC) was evaluated. We noticed that there were reciprocal dynamic changes in both dorsolateral prefrontal cortex (DLPFC) region and PCC regions during working memory encoding and retrieval. In agreement with the previous studies, there were more positively correlated regions during retrieval compared to encoding. The default mode network (DMN) networks showed greater negative correlations during more attentive task of visual encoding. In tune with the recent studies on cognitive reserve we also found that number of years of education was a significant factor influencing working memory connectivity. SE had higher positive correlation to DLPFC region and lower negative correlation to DMN in comparison with CE during encoding and retrieval.     

Standard errors and confidence intervals for correlations corrected for indirect range restriction: A simulation study comparing analytic and bootstrap methods

A frequent topic of psychological research is the estimation of the correlation between two variables from a sample that underwent a selection process based on a third variable. Due to indirect range restriction, the sample correlation is a biased estimator of the population correlation, and a correction formula is used. In the past, bootstrap standard error and confidence intervals for the corrected correlations were examined with normal data. The present study proposes a large-sample estimate (an analytic method) for the standard error, and a corresponding confidence interval for the corrected correlation. Monte Carlo simulation studies involving both normal and non-normal data were conducted to examine the empirical performance of the bootstrap and analytic methods. Results indicated that with both normal and non-normal data, the bootstrap standard error and confidence interval were generally accurate across simulation conditions (restricted sample size, selection ratio, and population correlations) and outperformed estimates of the analytic method. However, with certain combinations of distribution type and model conditions, the analytic method has an advantage, offering reasonable estimates of the standard error and confidence interval without resorting to the bootstrap procedure's computer-intensive approach. We provide SAS code for the simulation studies.     

No Relationship Between Joint Position Sense and Force Sense at the Shoulder

In practice, a single test is used to quantify an individual's proprioception. Previous studies have not found a correlation between joint position sense (JPS) and force sense (FS), which are submodalities of proprioception. The purpose of the present study is to determine if root mean square (RMS) error in JPS and FS are related at the shoulder, controlling for external load and elevation angle. Active shoulder angle and force reproduction protocols were performed. No correlation was found between JPS and FS (r = –.019, p = .941) nor were any individual angle and load combinations significant. The main effect for angle in JPS was significant (p < .001). Follow-up contrast demonstrated a significant (p < .001) decrease in RMS error with increased elevation. A significant load by angle interaction was found for FS (p = .014). Follow-up simple effects tests by angle demonstrated RMS error decreased with load at 50° and 70° but not at 90°. By load, RMS error only decreased for 120% between 50° and 90°. JPS and FS demonstrate different behavior with load and angle. This differing behavior is more likely responsible for the lack of correlation than angle and load differences in JPS and FS protocols.     

Intuitive Covariation Assessment of the Illusory Correlation

Most of the research concerned with the illusory correlation is modeled after the seminal work of D. L. Hamilton and R. K. Gifford (1976). However, S. A. Haslam and C. McGarty (1994) have voiced concerns over the dependent measures used within this paradigm. Therefore, in this study, the authors tested a new dependent variable that has high face validity. This measure was modeled after the work of J. R. McGahan and R. Wight (1989) and consisted of a set of propositional statements representing either the illusory correlation, the contingency opposite the illusory correlation, or the noncontingency. A second purpose of this study was to validate other studies that have used dependent measures modeled after the work of J. R. McGahan and R. Wight (1989). Demonstrating that this measure can be used to detect a well-documented phenomenon (i.e., the illusory correlation) would strengthen the results and conclusions from other studies. To this end, results from 2 experiments indicate that this measure does provide a valid alternative to those measures that are commonly used in illusory correlation studies. The results thereby give credence to other studies that have used similar dependent measures.     

Predictors of quality of life enjoyment and satisfaction in individuals living with HIV and AIDS in a resource-constrained setting in South Africa

The burden of HIV disease is concentrated in sub-Saharan Africa, particularly in South Africa (SA). Whilst there have been many studies conducted on the biomedical and socio-psychological aspects of HIV and AIDS, insufficient attention has been paid to the quality of life of those infected with the virus. The primary purpose of the study was to determine the predictors of quality of life enjoyment and satisfaction (Q-LES) among individuals infected with HIV. A battery of questionnaires, which included the Hospital Anxiety and Depression Scale (HADS) and the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), were administered to 121 participants. Data was analysed using SPSS. Of the total sample (n = 121), 74% were females. The study found that a large proportion (49.5%) of the sample within the age group 25–49 years old experienced psychological distress. Those who were not on antiretroviral treatment (ART) were significantly affected (66%). Psychological distress was significantly prevalent among HIV positive individuals and also the strongest predictor of Q-LES among these individuals.     

Intraclass Correlation Associated with Therapists: Estimates and Applications in Planning Psychotherapy Research

It is essential that outcome research permit clear conclusions to be drawn about the efficacy of interventions. The common practice of nesting therapists within conditions can pose important methodological challenges that affect interpretation, particularly if the study is not powered to account for the nested design. An obstacle to the optimal design of these studies is the lack of data about the intraclass correlation coefficient (ICC), which measures the statistical dependencies introduced by nesting. To begin the development of a public database of ICC estimates, the authors investigated ICCs for a variety outcomes reported in 20 psychotherapy outcome studies. The magnitude of the 495 ICC estimates varied widely across measures and studies. The authors provide recommendations regarding how to select and aggregate ICC estimates for power calculations and show how researchers can use ICC estimates to choose the number of patients and therapists that will optimize power. Attention to these recommendations will strengthen the validity of inferences drawn from psychotherapy studies that nest therapists within conditions.     

The effect of affine transformation on redundancy analysis

Canonical redundancy analysis provides an estimate of the amount of shared variance between two sets of variables and provides an alternative to canonical correlation. The proof that the total redundancy is equal to the average squared multiple correlation coefficient obtained by regressing each variable in the criterion set on all variables in the predictor set is generalized to the case in which there are a larger number of criterion than predictor variables. It is then shown that the redundancy for the criterion set of variables is invariant under affine transformation of the predictor variables, but not invariant under transformation of the criterion variables.     

Four Covariance Structure Models for Canonical Correlation Analysis: A COSAN Modeling Approach

The mathematical connection between canonical correlation analysis (CCA) and covariance structure analysis was first discussed through the Multiple Indicators and Multiple Causes (MIMIC) approach. However, the MIMIC approach has several technical and practical challenges. To address these challenges, a comprehensive COSAN modeling approach is proposed. Specifically, we define four COSAN-CCA models to correspond with four possible combinations of the data to be analyzed and the unique parameters to be estimated. In terms of the data, one can analyze either the unstandardized or standardized variables. In terms of the unique parameters, one can estimate either the weights or loadings. Besides the unique parameters of each COSAN-CCA model, all four COSAN-CCA models also estimate the canonical correlations as their common parameters. Taken together, the four COSAN-CCA models provide the correct point estimates and standard error estimates for all commonly used CCA parameters. Two numeric examples are used to compare the standard error estimates obtained from the MIMIC approach and the COSAN modeling approach. Moreover, the standard error estimates from the COSAN modeling approach are validated by a simulation study and the asymptotic theory. Finally, software implementation and future extensions are discussed.     

Dominance and competence face to face: Dissociations obtained with a reverse correlation approach

The article explores whether the traits representing the dimensions underlying the structure of facial and non-facial impressions are similarly mapped in the face space. Two studies examine whether the trustworthiness-by-dominance and the warmth-by-competence two-dimensional models overlap in face perception. In Study 1 (N = 200), we used a reverse-correlation task to obtain classification images (CIs) reflecting how each dimension is mapped onto a face. Results show that the similarity between CIs was higher between warmth and trustworthiness than between competence and dominance. In Study 2 (N = 31) the evaluations of each CI on each social dimension show a higher dissociation between dominance and competence than between trustworthiness and warmth. These results, obtained at both perceptual and judgment levels, suggest that there is only a partial correspondence between the two models that seems to be driven by the relationship that the competence and dominance dimensions establish with valence.