The Looking Glass for Intelligence Quotient Tests: The Interplay of Motivation, Cognitive Functioning, and Affect

Intelligence quotient testing in children with hearing loss: A systematic review

OBJECTIVE

The objective of the current study is to perform a systematic review of the research literature to evaluate the impact of hearing loss on intelligence quotient (IQ) scores in pediatric patients.

DATA SOURCES

Ovid MEDLINE, EMBASE, CINAHL, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched from their inception up to December 21st, 2021.

REVIEW METHODS

Studies evaluating neurocognitive testing and hearing loss in children aged 21 years old or younger who had not undergone auditory rehabilitation were included in the study. Two independent reviewers evaluated titles, abstracts, and full texts for all included studies.

RESULTS

The literature search yielded 3199 studies of which 431 studies underwent full-text screening. 21 studies were ultimately selected for inclusion and contained a total of 1716 pediatric patients assessed through 13 different validated tests of intelligence. Six studies included both hearing impaired (HI) and normal hearing (NH) patients, and IQ testing results.

CONCLUSION

The results of this large systematic review demonstrate that hearing impaired children may perform lower than their age-matched normal hearing peers on IQ testing across a battery of IQ testing modalities.

Cognitive enrichment through art: a randomized controlled trial on the effect of music or visual arts group practice on cognitive and brain development of young children

BACKGROUND

The optimal stimulation for brain development in the early academic years remains unclear. Current research suggests that musical training has a more profound impact on children's executive functions (EF) compared to other art forms. What is crucially lacking is a large-scale, long-term genuine randomized controlled trial (RCT) in cognitive neuroscience, comparing musical instrumental training (MIP) to another art form, and a control group (CG). This study aims to fill this gap by using machine learning to develop a multivariate model that tracks the interconnected brain and EF development during the academic years, with or without music or other art training.

METHODS

The study plans to enroll 150 children aged 6-8 years and randomly assign them to three groups: Orchestra in Class (OC), Visual Arts (VA), and a control group (CG). Anticipating a 30% attrition rate, each group aims to retain at least 35 participants. The research consists of three analytical stages: 1) baseline analysis correlating EF, brain data, age, gender, and socioeconomic status, 2) comparison between groups and over time of EF brain and behavioral development and their interactions, including hypothesis testing, and 3) exploratory analysis combining behavioral and brain data. The intervention includes intensive art classes once a week, and incremental home training over two years, with the CG receiving six annual cultural outings.

DISCUSSION

This study examines the potential benefits of intensive group arts education, especially contrasting music with visual arts, on EF development in children. It will investigate how artistic enrichment potentially influences the presumed typical transition from a more unified to a more multifaceted EF structure around age eight, comparing these findings against a minimally enriched active control group. This research could significantly influence the incorporation of intensive art interventions in standard curricula.

TRIAL REGISTRATION

The project was accepted after peer-review by the Swiss National Science Foundation (SNSF no. 100014_214977) on March 29, 2023. The study protocol received approval from the Cantonal Commission for Ethics in Human Research of Geneva (CCER, BASEC-ID 2023-01016), which is part of Swiss ethics, on October 25, 2023. The study is registered at clinicaltrials.gov (NCT05912270).

Cognitive Functioning of Preadolescent Gymnasts, Including Bioelectrical Brain Activity

Our main aim in this study was to investigate cognitive functioning in young gymnasts. The study group consisted of 86 children, aged 10-12 years: (a) a criterion group of 41 juvenile athletes (M_age = 11.23; SD_age = 0.93) who trained six times per week; and (b) a comparison group of 45 children (M_age = 11.11; SD_age = 0.61) who were not involved competitively in sports but who were mostly quite physically active. We measured attention, memory processes, and bioelectrical brain activity in the central region (Cz; where there are connections to motor control, movement, and sensation). We found significant differences between our two participant groups in short-term memory, deferred naming memory, and long-term memory of visual material. Children who practiced gymnastics had a better attention span than those who did not, and children who were non-athletes but who undertook physical activity more frequently than five times per week had a different theta/sensory motor rhythm (SMR) brain wave ratio (with SMR higher), meaning that they felt calmer and more relaxed.

Pre-post intervention exploring cognitive function and relationships with weight loss, intervention adherence and dropout

Objective

To evaluate the association between baseline cognitive function, intervention dropout, adherence and 3-month weight loss (WL) when controlling for confounding demographic variables.

Methods

107 (Mage = 40.9 yrs.), BMI in the overweight and obese range (BMI = 35.6 kg/m²), men (N = 17) and women (N = 90) completed a 3-month WL intervention. Participants attended weekly behavioral sessions, comply with a reduced calorie diet, and complete 100 min of physical activity (PA)/wk. Cognitive function tasks at baseline included Flanker (attention), Stroop (executive control) and working memory, demographics, body weight and cardiovascular fitness were assessed at baseline. Session attendance, adherence to PA and diet were recorded weekly.

Results

Baseline attention was positively correlated with age (p < .05), education (p < .05), attendance (p < .05), diet (p < .05) and PA (p < .05). Baseline executive control (p < .05) and working memory (p < .05) were each associated with % WL. Baseline executive control (p < .01) and working memory (p < .001) were also each associated with education. ANOVA indicated that baseline attention (p < .01) was associated with WL, specifically for comparing those who achieved 5-10% WL (p < .01) and those who achieved greater than 10% WL (p < .01) to those who dropped.

Significance

Results suggest that stronger baseline attention is associated with completion of a 3-mo. WL intervention. Executive control and working memory are associated with amount of WL achieved.

NCT registration

US NIH Clinical Trials, NCT01664715.

Big data, machine learning, and population health: predicting cognitive outcomes in childhood

The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a complex public health issue rooted in the social determinants of health, exacerbated by inequity, characterised by intergenerational transmission, and which will continue unabated without novel approaches to address it. Early life, the period of optimal neuroplasticity, presents a window of opportunity for early intervention to improve cognitive development. Unfortunately for many, this window will be missed, and intervention may never occur or occur only when overt signs of cognitive delay manifest. In this review, we explore the potential value of ML and big data analysis in the early identification of children at risk for poor cognitive outcome, an area where there is an apparent dearth of research. We compare and contrast traditional statistical methods with ML approaches, provide examples of how ML has been used to date in the field of neurodevelopmental disorders, and present a discussion of the opportunities and risks associated with its use at a population level. The review concludes by highlighting potential directions for future research in this area. IMPACT: To date, the application of machine learning to address population health challenges in paediatrics lags behind other clinical applications. This review provides an overview of the public health challenge we face in addressing disparities in childhood cognitive development and focuses on the cornerstone of early intervention. Recent advances in our ability to collect large volumes of data, and in analytic capabilities, provide a potential opportunity to improve current practices in this field. This review explores the potential role of machine learning and big data analysis in the early identification of children at risk for poor cognitive outcomes.

Cataloging the potential SNPs (single nucleotide polymorphisms) associated with quantitative traits, viz. BMI (body mass index), IQ (intelligence quotient) and BP (blood pressure): an updated review

Background

Single nucleotide polymorphism (SNP) variants are abundant, persistent and widely distributed across the genome and are frequently linked to the development of genetic diseases. Identifying SNPs that underpin complex diseases can aid scientists in the discovery of disease-related genes by allowing for early detection, effective medication and eventually disease prevention.

Main body

Various SNP or polymorphism-based studies were used to categorize different SNPs potentially related to three quantitative traits: body mass index (BMI), intelligence quotient (IQ) and blood pressure, and then uncovered common SNPs for these three traits. We employed SNPedia, RefSNP Report, GWAS Catalog, Gene Cards (Data Bases), PubMed and Google Scholar search engines to find relevant material on SNPs associated with three quantitative traits. As a result, we detected three common SNPs for all three quantitative traits in global populations: SNP rs6265 of the BDNF gene on chromosome 11p14.1, SNP rs131070325 of the SL39A8 gene on chromosome 4p24 and SNP rs4680 of the COMT gene on chromosome 22q11.21.

Conclusion

In our review, we focused on the prevalent SNPs and gene expression activities that influence these three quantitative traits. These SNPs have been used to detect and map complex, common illnesses in communities for homogeneity testing and pharmacogenetic studies. High blood pressure, diabetes and heart disease, as well as BMI, schizophrenia and IQ, can all be predicted using common SNPs. Finally, the results of our work can be used to find common SNPs and genes that regulate these three quantitative features across the genome.

Gray Matter Volume in the Developing Frontal Lobe and Its Relationship With Executive Function in Late Childhood and Adolescence: A Community-Based Study

Background: During late childhood and adolescence, the frontal lobe undergoes critical developmental changes, affecting a wide range of executive functions significantly. Conversely, abnormality in the maturation of the frontal lobe during this period may result in a limited ability to effectively use various executive functions. However, at present, it is still unclear how the structural development of the frontal lobe is associated with different aspects of executive functions during this developmental period. To fill the gap in evidence, we aimed to elucidate gray matter volume (GMV) in the frontal lobe and its relationship with multiple aspects of executive functions in late childhood and adolescence. Methods: We recruited our participants aged between 6 and 17 years to assess GMV in the frontal lobe and its relationship with different domains of executive functions in late childhood and adolescence. We used the voxel-based morphometry-DARTEL procedure to measure GMVs in multiple frontal sub-regions and Stroop test and Advanced Test of Attention (ATA) to measure executive functions. We then conducted partial correlation analyses and performed multiple comparisons with different age and sex groups. Results: Overall, 123 participants took part in our study. We found that many regional GMVs in the frontal lobe were negatively correlated with ATA scores in participants in late childhood and positively correlated with ATA scores in participants in adolescence. Only a few correlations of the GMVs with Stroop test scores were significant in both age groups. Although most of our results did not survive false discovery rate (FDR) correction (i.e., FDR <0.2), considering their novelty, we discussed our results based on uncorrected p-values. Our findings indicate that the frontal sub-regions that were involved in attentional networks may significantly improve during late childhood and become stabilized later in adolescence. Moreover, our findings with the Stroop test may also present the possibility of the later maturation of higher-order executive functioning skills. Conclusion: Although our findings were based on uncorrected p-values, the novelty of our findings may provide better insights into elucidating the maturation of the frontal lobe and its relationship with the development of attention networks in late childhood and adolescence.