Predicting young adults’ self-concept with couples’ coordination and intellectual mutuality in Qeshm County in Iran

The present study was intended to predict young adults’ self-concept according to couples’ coordination and intellectual mutuality. The study’s statistical population consists of Qeshm County high-school students and their parents, and their data was collected from March 2014 until August 2015. The sample of this descriptive-co relational study consisted of 200 individuals selected using the convenience sampling method. For data analysis, simple correlation and multivariate regression were used in the deductive section to predict and analyze the relationship between variables. This study used the Piers-Harris Children's Self-Concept Scale (CSCS) and the Iranian Couples’ Intellectual Mutuality and Coordination Questionnaire by Javedan (2013), as well as SPSS 21 for data analysis. The results showed a simple and multivariate relationship between the young adults’ self-concept and couples’ intellectual mutuality, and these variables were significant at the P≤0.01 level.

Theta and gamma activity is linked with affective and cognitive symptoms in Parkinson's disease

Background The progression of Parkinsons disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response. Methods 70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups. Results A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age. Limitations This study only reports on optimal dosage of dopaminergic treatment (on state) in PD and did not investigate at off medication. Conclusions Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behavior associations in PD with electrophysiological task paradigms.

A Combined Visualization Method for Multivariate Data Analysis. Application to Knee Kinematic and Clinical Parameters Relationships

This paper aims to analyze the correlation structure between the kinematic and clinical parameters of an end-staged knee osteoarthritis population. The kinematic data are a set of characteristics derived from 3D knee kinematic patterns. The clinical parameters include the answers of a clinical questionnaire and the patient’s demographic characteristics. The proposed method performs, first, a regularized canonical correlation analysis (RCCA) to evaluate the multivariate relationship between the clinical and kinematic datasets, and second, a combined visualization method to better understand the relationships between these multivariate data. Results show the efficiency of using different and complementary visual representation tools to highlight hidden relationships and find insights in data.