Neuropsychological Profile of Intellectually Gifted Children: A Systematic Review

Family Functioning and Internalizing and Externalizing Problems in Gifted Children

INTRODUCTION

Although gifted children can express high cognitive skills, they can also show socioemotional difficulties. Drawing from Olson's circumplex model, the present paper assessed the role of family functioning in internalizing and externalizing problems in gifted children.

MATERIALS AND METHODS

362 mothers and their 362 gifted children were included. The unbalanced subscales of the FACES IV-disengagement, enmeshment, rigidity, and chaos-and the CBCL were administered to mothers. The children completed the WISC-IV.

RESULTS

The model predicting internalizing problems was significant and explained 5.6% of the variance. Only rigidity had an independent and positive effect on internalizing problems in gifted children over and above sociodemographic variables and QI, whereas disengagement, enmeshment, and chaos were not associated with internalizing problems. The model predicting externalizing problems was significant and explained 10% of the variance. Again, rigidity was the only variable that had an independent and positive effect on externalizing problems in gifted children over and above sociodemographic variables and QI, whereas disengagement, enmeshment, and chaos were not associated with externalizing problems in this population.

DISCUSSION

Rigid families with a low ability to change in conditions that require readjustment appear to increase the risk of both internalizing and externalizing problems in gifted children. Although further studies are needed to support these preliminary findings, parental support interventions aimed at increasing flexibility appear to be useful.

Intelligence and Executive Functions: A Comprehensive Assessment of Intellectually Gifted Children

OBJECTIVE

Executive functions (EFs) play a key role in cognitive and behavioral functioning. Their multiple forms and implications for daily life behaviors mean they are sometimes equated with intelligence. Several elements even suggest that intellectually gifted children (IGC) may present better executive functioning than typical developing children (TDC, children with intelligence in the average range). However, no study has ever completely tested this hypothesis by a comprehensive assessment of EFs in IGC.

METHOD

Results of 30 IGC and 35 TDC aged from 6 to 16 years old were compared through a comprehensive assessment of EFs (inhibition, flexibility, and planning), comprising performance-based and daily life measures.

RESULTS

IGC did not differ from TDC in EF performance-based measures. However, they scored higher in parents' and some teachers' ratings, suggesting higher indicators of difficulties in daily life.

CONCLUSIONS

Contrary to expectations, high intellectual level does not appear to be associated with superior EFs. Surprisingly, parents and teachers of IGC reported more complaints about their executive functioning in everyday life. We put forward different hypotheses to explain this contrast. Further research is needed to better understand this phenomenon, in which neuropsychology has a fundamental role to play.

Decrease in cognitive performance and increase of the neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios with higher doses of antipsychotics in women with schizophrenia: a cross-sectional study

BACKGROUND

We explored the relationship between symptoms, cognitive performance, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) (three markers of inflammation), and antipsychotic dose (in chlorpromazine units) in male and female patients with schizophrenia.

METHODS

We conducted a cross-sectional analysis in patients with schizophrenia of the complete blood count and the results of neuropsychological testing, using the Welch t-test to compare groups and the Pearson test for correlations.

RESULTS

We found that the NLR and the PLR are higher among women with schizophrenia when compared with men. In women, the NLR and the PLR correlate positively with antipsychotic drug dose and inversely with a working memory test (Direct Digit Span). Higher doses of antipsychotics are associated with worse working and semantic memory and mental flexibility in the women in our sample.

CONCLUSION

Higher doses of antipsychotics were associated with worse working and semantic memory and mental flexibility in women with schizophrenia. No such correlations were present in men, suggesting that, in female patients, cognitive performance deteriorates as the antipsychotic dose is increased, a finding that could be mediated by inflammatory mechanisms, given the demonstrated relationship to biomarkers of inflammation - e.g., the NLR and the PLR.

TRIAL REGISTRATION

NCT03788759 (ClinicalTrials.gov).

Graph Empirical Mode Decomposition-Based Data Augmentation Applied to Gifted Children MRI Analysis

Gifted children and normal controls can be distinguished by analyzing the structural connectivity (SC) extracted from MRI data. Previous studies have improved classification accuracy by extracting several features of the brain regions. However, the limited size of the database may lead to degradation when training deep neural networks as classification models. To this end, we propose to use a data augmentation method by adding artificial samples generated using graph empirical mode decomposition (GEMD). We decompose the training samples by GEMD to obtain the intrinsic mode functions (IMFs). Then, the IMFs are randomly recombined to generate the new artificial samples. After that, we use the original training samples and the new artificial samples to enlarge the training set. To evaluate the proposed method, we use a deep neural network architecture called BrainNetCNN to classify the SCs of MRI data with and without data augmentation. The results show that the data augmentation with GEMD can improve the average classification performance from 55.7 to 78%, while we get a state-of-the-art classification accuracy of 93.3% by using GEMD in some cases. Our results demonstrate that the proposed GEMD augmentation method can effectively increase the limited number of samples in the gifted children dataset, improving the classification accuracy. We also found that the classification accuracy is improved when specific features extracted from brain regions are used, achieving 93.1% for some feature selection methods.