A Review of Multidimensional Scaling (MDS) and its Utility in Various Psychological Domains

This paper aims to provide a non-technical overview of multidimensional scaling (MDS) so that a broader population of psychologists, in particular, will consider using this statistical procedure. A brief description regarding the type of data used in MDS, its acquisition and analyses via MDS is provided. Also included is a commentary on the unique challenges associated with assessing the output of MDS. Our second aim, by way of discussing representative studies, is to highlight and evaluate the utility of this method in various domains in psychology

Recognition of masked and unmasked facial expressions in males and females and relations with mental wellness

BackgroundWhile the effects of mask wearing/facial occlusion are known to impair facial expression recognition, little is known about the role of mental wellness on facial expression recognition, as well as the influence of sex on misattribution errors (i.e., confusions between emotions). In this large study, we aimed to address the relation between facial expression recognition and loneliness, perceived stress, anxiety, and depression symptoms in male and female adults.MethodsWe assessed the influence of mask-wearing on facial expression recognition [i.e., accuracy and response time (RT)] via an online study in N = 469 adult males and females across Canada.ResultsExpectedly, recognition was impaired under masked conditions (i.e., lower accuracy, longer RTs, more misattribution errors). Females were faster and more accurate than males, with less misattribution errors. A novel finding was that people with higher perceived stress were less accurate at identifying masked fearful faces. Perceived stress influenced the relation between sex and RT to masked happy faces; males with high stress scores were slower to recognize masked happy faces, the opposite was true for females. Finally, this study was among the first to show that higher loneliness predicted shorter RT to unmasked faces.ImpactOur results show that facial expression recognition is impaired by mask-wearing, and that sex and mental health features are important predictors of performance. Such insight could be detrimental in certain sectors of the population (e.g., health care or education), and inform policies being adopted in future pandemics

A Therapeutic Potential of Vitamin D in Asthma Control

In 2019, according to WHO estimates, 262 million people were affected by asta, resulting in 455,000 deaths. Asthma, is a chronic inflammatory disease of the airways that causes reversible bronchoconstriction, making it difficult for patients to breathe. Exacerbations of the disease can be caused by a variety of factors but share similar symptoms such as wheezing, coughing, shortness of breath and chest tightness. Severe asthma exacerbations are defined as symptoms that do not respond to inhaled medications and improve only after oral or intravenous steroid administration. Asthma-related deaths often occur during exacerbations. Vitamin D, which is produced naturally in the body and found in some foods, is a steroid-derived vitamin. Adequate doses of this vitamin, administered through medication or supplements, can be used to maintain its proper levels in the organism. Vitamin D is essential for regulating calcium levels in the body and for bone remodeling. It also has immunomodulatory effects, affecting both innate and adaptive immunity. This partly explains its association with changes in the airway epithelium that occur as a result of inflammation in asthma. The study aims to summarize the current knowledge on the relationship of vitamin D with asthma symptom control. The present study is based on literature available in scientific databases from 2013-2016, such as PubMed, Corchane Library and Google Scholar, using the following keywords: "vitamin D" and "asthma." Vitamin D deficiency is prevalent in children and adults worldwide. A critical analysis of the literature reveals that the therapeutic administration of vitamin D has no apparent advantage in treating asthma, especially in children. Nevertheless, for adults with mild asthma, vitamin D supplementation shows promise for improved outcomes. However, there is a pressing need for large-scale clinical trials to determine the efficacy and safety of this therapeutic approach for both age groups

Brain responses in aggression-prone individuals: A systematic review and meta-analysis of functional magnetic resonance imaging (fMRI) studies of anger- and aggression-eliciting tasks

Reactive aggression in response to perceived threat or provocation is part of humans' adaptive behavioral repertoire. However, high levels of aggression can lead to the violation of social and legal norms. Understanding brain function in individuals with high levels of aggression as they process anger- and aggression-eliciting stimuli is critical for refining explanatory models of aggression and thereby improving interventions. Three neurobiological models of reactive aggression - the limbic hyperactivity, prefrontal hypoactivity, and dysregulated limbic-prefrontal connectivity models - have been proposed. However, these models are based on neuroimaging studies involving mainly non-aggressive individuals, leaving it unclear which model best describes brain function in those with a history of aggression. We conducted a systematic literature search (PubMed and Psycinfo) and Multilevel Kernel Density meta-analysis (MKDA) of nine functional magnetic resonance imaging (fMRI) studies (eight included in the between-group analysis [i.e., aggression vs. control groups], five in the within-group analysis). Studies examined brain responses to tasks putatively eliciting anger and aggression in individuals with a history of aggression alone and relative to controls. Individuals with a history of aggression exhibited greater activity in the superior temporal gyrus and in regions comprising the cognitive control and default mode networks (right posterior cingulate cortex, precentral gyrus, precuneus, right inferior frontal gyrus) during reactive aggression relative to baseline conditions. Compared to controls, individuals with a history of aggression exhibited increased activity in limbic regions (left hippocampus, left amygdala, left parahippocampal gyrus) and temporal regions (superior, middle, inferior temporal gyrus), and reduced activity in occipital regions (left occipital cortex, left calcarine cortex). These findings lend support to the limbic hyperactivity model in individuals with a history of aggression, and further indicate altered temporal and occipital activity in anger- and aggression-eliciting conditions involving face and speech processing

Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data

Background: Individuals with major depressive disorder (MDD) vary in their response to antidepressants. However, identifying objective biomarkers, prior to or early in the course of treatment that can predict antidepressant efficacy, remains a challenge.Methods: Individuals with MDD participated in a 12-week antidepressant pharmacotherapy trial. Electroencephalographic (EEG) data was collected before and 1 week post-treatment initiation in 51 patients. Response status at week 12 was established with the Montgomery-Asberg Depression Scale (MADRS), with a ≥50% decrease characterizing responders (N = 27/24 responders/non-responders). We used a machine learning (ML)-approach for predicting response status. We focused on Random Forests, though other ML methods were compared. First, we used a tree-based estimator to select a relatively small number of significant features from: (a) demographic/clinical data (age, sex, individual item/total MADRS scores at baseline, week 1, change scores); (b) scalp-level EEG power; (c) source-localized current density (via exact low-resolution electromagnetic tomography [eLORETA] software). Second, we applied kernel principal component analysis to reduce and map important features. Third, a set of ML models were constructed to classify response outcome based on mapped features. For each dataset, predictive features were extracted, followed by a model of all predictive features, and finally by a model of the most predictive features.Results: Fifty eLORETA features were predictive of response (across bands, both time-points); alpha1/theta eLORETA features showed the highest predictive value. Eighty-eight scalp EEG features were predictive of response (across bands, both time-points), with theta/alpha2 being most predictive. Clinical/demographic data consisted of 31 features, with the most important being week 1 “concentration difficulty” scores. When all features were included into one model, its predictive utility was high (88% accuracy). When the most important features were extracted in the final model, 12 predictive features emerged (78% accuracy), including baseline scalp-EEG frontopolar theta, parietal alpha2 and frontopolar alpha1.Conclusions: These findings suggest that ML models of pre- and early treatment-emergent EEG profiles and clinical features can serve as tools for predicting antidepressant response. While this must be replicated using large independent samples, it lays the groundwork for research on personalized, “biomarker”-based treatment approaches

A Therapeutic Potential of Vitamin D in Asthma Control

In 2019, according to WHO estimates, 262 million people were affected by asta, resulting in 455,000 deaths. Asthma, is a chronic inflammatory disease of the airways that causes reversible bronchoconstriction, making it difficult for patients to breathe. Exacerbations of the disease can be caused by a variety of factors but share similar symptoms such as wheezing, coughing, shortness of breath and chest tightness. Severe asthma exacerbations are defined as symptoms that do not respond to inhaled medications and improve only after oral or intravenous steroid administration. Asthma-related deaths often occur during exacerbations. Vitamin D, which is produced naturally in the body and found in some foods, is a steroid-derived vitamin. Adequate doses of this vitamin, administered through medication or supplements, can be used to maintain its proper levels in the organism. Vitamin D is essential for regulating calcium levels in the body and for bone remodeling. It also has immunomodulatory effects, affecting both innate and adaptive immunity. This partly explains its association with changes in the airway epithelium that occur as a result of inflammation in asthma. The study aims to summarize the current knowledge on the relationship of vitamin D with asthma symptom control. The present study is based on literature available in scientific databases from 2013-2016, such as PubMed, Corchane Library and Google Scholar, using the following keywords: "vitamin D" and "asthma." Vitamin D deficiency is prevalent in children and adults worldwide. A critical analysis of the literature reveals that the therapeutic administration of vitamin D has no apparent advantage in treating asthma, especially in children. Nevertheless, for adults with mild asthma, vitamin D supplementation shows promise for improved outcomes. However, there is a pressing need for large-scale clinical trials to determine the efficacy and safety of this therapeutic approach for both age groups

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response

IntroductionTo date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response.MethodsResting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients.ResultsResponders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization.DiscussionOur single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability.Clinical trial registrationhttps://clinicaltrials.gov, identifier NCT00519428