Compressing movement information via principal components analysis (PCA): Contrasting outcomes from the time and frequency domains

PCA has become an increasingly used analysis technique in the movement domain to reveal patterns in data of various kinds (e.g., kinematics, kinetics, EEG, EMG) and to compress the dimension of the multivariate data set recorded. It appears that virtually all movement related PCA analyses have, however, been conducted in the time domain (PCA_t). This standard approach can be biased when there are lead-lag (phase-related) properties to the multivariate time series data. Here we show through theoretical derivation and analysis of simulated and experimental postural kinematics data sets that PCA_t and, PCA in the frequency domain (PCA_f), can lead to contrasting determinations of the dimension of a data set, with the tendency of PCA_t to overestimate the number of components. PCA_f also provides the possibility of obtaining amplitude and phase-difference spectra for each principal component that are uniquely suitable to reveal control mechanisms of the system. The bias in the PCA_t estimate of the number of components can have significant implications for the veracity of the interpretations drawn in regard to the dynamical degrees of freedom of the perceptual-motor system.     

Testing and modelling non‐normality within the one‐factor model

Maximum likelihood estimation in the one‐factor model is based on the assumption of multivariate normality for the observed data. This general distributional assumption implies three specific assumptions for the parameters in the one‐factor model: the common factor has a normal distribution; the residuals are homoscedastic; and the factor loadings do not vary across the common factor scale. When any of these assumptions is violated, non‐normality arises in the observed data. In this paper, a model is presented based on marginal maximum likelihood to enable explicit tests of these assumptions. In addition, the model is suitable to incorporate the detected violations, to enable statistical modelling of these effects. Two simulation studies are reported in which the viability of the model is investigated. Finally, the model is applied to IQ data to demonstrate its practical utility as a means to investigate ability differentiation.     

Examining the relationship between use of sexually explicit media and sexual risk behavior in a sample of men who have sex with men in Norway

The purpose of this study was to investigate consumption patterns of gay‐oriented sexually explicit media (SEM) among men who have sex with men (MSM) in Norway, with a particular emphasis on a possible relationship between gay SEM consumption and HIV risk behavior. Participants included 529 MSM living in Norway recruited online to complete a SEM consumption and sexual risk survey. Of the 507 participants who responded to the all items measuring exposure to SEM, 19% reported unprotected anal intercourse with a casual partner (UAI) in last 90 days, and 14% reported having had sero‐discordant UAI. Among those with UAI experience, 23% reported receptive anal intercourse (R‐UAI) and 37% reported insertive anal intercourse (I‐UAI). SEM consumption was found to be significantly associated with sexual risk behaviors. Participants with increased consumption of bareback SEM reported higher odds of UAI and I‐UAI after adjusting for other factors using multivariable statistics. MSM who started using SEM at a later age reported lower odds of UAI and I‐UAI than MSM who started earlier. Future research should aim at understanding how MSM develop and maintain SEM preferences and the relationship between developmental and maintenance factors and HIV sexual risk behavior.     

Behavioral Health Services Influence Medical Treatment Utilization Among Primary Care Patients with Comorbid Substance Use and Depression

Although research has shown benefits of integrating psychological care in primary care settings, it is unclear how this form of treatment impacts individuals with comorbid substance use and depression. The findings are also mixed concerning how frequently this comorbid population seeks primary care services. This study examined the associations between substance use, depression, and medical treatment utilization among 224 primary care patients. The aim of the investigation was twofold. First, to determine if depression increases medical treatment utilization among patients with substance use disorders; second, to evaluate if behavioral health treatment reduces medical service utilization. A moderated mediation model with bootstrapping analyses revealed that depression strengthened the relationship between substance use and primary care treatment utilization (both medical and behavioral health). The model also indicated that behavioral health services were associated with fewer primary care visits for individuals with comorbid substance use and depression. Clinical and social implications are discussed.     

The Recoverability of P-technique Factor Analysis

It seems that just when we are about to lay P–technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables—dynamic factor models—it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even though it does not explicitly model lagged information, P–technique's ability to recover the parameters of underlying dynamic processes involving lagged relations among the manifest variables is apparently robust and accurate. An empirical example is presented using 103 days of affective mood self-ratings from a young pregnant woman. Implications of the simulation and empirical findings are briefly discussed.     

The Effect of Individual Differences in Factor Loadings on the Standard Factor Model

It is shown that the population-covariance matrix of a heterogeneous factor model may be indistinguishable from that of a standard factor model and that the standard likelihood-ratio goodness-of-fit statistic has but little power in detecting loading heterogeneity. The relation between loading heterogeneity and factor score reliability is studied and it is recommended that non-normality of the test-score distributions be tested to use factor scores with more confidence. Substantive justifications for the model assumptions and model-based methods to test specific hypotheses about the loading distribution, are discussed.     

Anticipation of subsequent demanding exercise increases the expression of haem oxygenase-1 mRNA in human lymphocytes

Oxidative stress induces the expression of the cytoprotective and anti-inflammatory protein haem oxygenase-1 (HO-1). In the present investigation, we show that anticipation of subsequent exercise elevates the expression of HO-1 mRNA in lymphocytes. A between-groups comparison of HO-1 mRNA expression in subjects about to complete a half marathon race vs. subjects who were asked to sit quietly in the laboratory showed an elevated expression of HO-1 mRNA prior to exercise (2.6-fold higher in subjects prior to the half marathon, P < 0.01). This observation led us to examine whether anticipation of subsequent exercise leads to differences in lymphocyte HO-1 mRNA expression within the same subjects. In a second experiment, the same individuals completed two trials, one exercise and one rest, approximately 2 weeks apart in a randomised cross-over design. Lymphocyte HO-1 mRNA expression was greater prior to exercise (1.4 +/- 0.3-fold higher in the exercise trial, P < 0.05). These results suggest that knowledge of subsequent demanding exercise may lead to an anticipatory induction of HO-1 mRNA. We tentatively propose that this process has evolved to prepare lymphocytes for subsequent exercise-induced oxidative stress although the mechanism remains to be elucidated.     

Misremembering emotion: Inductive category effects for complex emotional stimuli

Memories of objects are biased toward what is typical of the category to which they belong. Prior research on memory for emotional facial expressions has demonstrated a bias towards an emotional expression prototype (e.g., slightly happy faces are remembered as happier). We investigate an alternate source of bias in memory for emotional expressions – the central tendency bias. The central tendency bias skews reconstruction of a memory trace towards the center of the distribution for a particular attribute. This bias has been attributed to a Bayesian combination of an imprecise memory for a particular object with prior information about its category. Until now, studies examining the central tendency bias have focused on simple stimuli. We extend this work to socially relevant, complex, emotional facial expressions. We morphed facial expressions on a continuum from sad to happy. Different ranges of emotion were used in four experiments in which participants viewed individual expressions and, after a variable delay, reproduced each face by adjusting a morph to match it. Estimates were biased toward the center of the presented stimulus range, and the bias increased at longer memory delays, consistent with the Bayesian prediction that as trace memory loses precision, category knowledge is given more weight. The central tendency effect persisted within and across emotion categories (sad, neutral, and happy). This article expands the scope of work on inductive category effects to memory for complex, emotional stimuli.     

On the relation between the mean and the variance of a diffusion model response time distribution

Almost every empirical psychological study finds that the variance of a response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion model (e.g., Ratcliff (1978) Psychological Review, 85, 59-108; Ratcliff (2002). Psychonomic Bulletin & Review, 9, 278-291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion model RT distribution. Next, we study how systematic differences in two important diffusion model parameters simultaneously affect the mean and the variance of the diffusion model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.     

Cognitive neuroscience of self-regulation failure

Self-regulatory failure is a core feature of many social and mental health problems. Self-regulation can be undermined by failures to transcend overwhelming temptations, negative moods and resource depletion, and when minor lapses in self-control snowball into self-regulatory collapse. Cognitive neuroscience research suggests that successful self-regulation is dependent on top-down control from the prefrontal cortex over subcortical regions involved in reward and emotion. We highlight recent neuroimaging research on self-regulatory failure, the findings of which support a balance model of self-regulation whereby self-regulatory failure occurs whenever the balance is tipped in favor of subcortical areas, either due to particularly strong impulses or when prefrontal function itself is impaired. Such a model is consistent with recent findings in the cognitive neuroscience of addictive behavior, emotion regulation and decision-making.