Hemispheric Differences in White Matter Microstructure between Two Profiles of Children with High Intelligence Quotient vs. Controls: A Tract-Based Spatial Statistics Study

Personal Income Performance Correlates with Brain Structural Network Modularity but Not Intelligence Quotient

Introduction: This study aims to use diffusion tensor imaging (DTI) in conjunction with brain graph techniques to define brain structural connectivity and investigate its association with personal income (PI) in individuals of various ages and intelligence quotients (IQ). Methods: MRI examinations were performed on 55 male subjects (mean age: 40.1 ± 9.4 years). Graph data and metrics were generated, and DTI images were analyzed using tract-based spatial statistics (TBSS). All subjects underwent the Wechsler Adult Intelligence Scale for a reliable estimation of the full-scale IQ (FSIQ), which includes verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index. The performance score was defined as the monthly PI normalized by the age of the subject. Results: The analysis of global graph metrics showed that modularity correlated positively with performance score (p = 0.003) and negatively with FSIQ (p = 0.04) and processing speed index (p = 0.005). No significant correlations were found between IQ indices and performance scores. Regional analysis of graph metrics showed modularity differences between right and left networks in sub-cortical (p = 0.001) and frontal (p = 0.044) networks. TBSS analysis showed greater axial and mean diffusivities in the high-performance group in correlation with their modular brain organization. Conclusion: This study showed that PI performance is strongly correlated with a modular organization of brain structural connectivity, which implies short and rapid networks, providing automatic and unconscious brain processing. Additionally, the lack of correlation between performance and IQ suggests a reduced role of academic reasoning skills in performance to the advantage of high uncertainty decision-making networks.

Is the Caudate, Putamen, and Globus Pallidus the Delusional Disorder's Trio? A Texture Analysis Study

BACKGROUND

The neurobiological basis of delusional disorder is less explored through neuroimaging techniques than in other psychotic disorders. This study aims to provide information about the neural origins of delusional disorder (DD) by examining the neuroanatomical features of some basal nuclei with magnetic resonance imaging (MRI) texture analysis.

MATERIALS AND METHODS

Twenty DD patients and 20 healthy individuals were included in the study. Globus pallidus, putamen, and caudate nuclei were selected individually with a region of interest (ROI) on the axial MRI images. The entire texture analysis algorithm applied to all selected ROIs was done with an in-house software. Nuclei on both sides were taken as separate samples.

RESULTS

There were no significant differences between groups in terms of age and gender. The average "mean, median and maximum" values of all three nuclei were decreased in DD patients. The small putamen area and the differences detected in different tissue parameters for all three nuclei in delusional disorder patients indicate that they differ in delusional disorder from normal controls (p < 0.05).

CONCLUSION

The differences detected in the texture parameters for all three nuclei indicate that there is something different in the DD from in the normal controls. Neuroimaging studies with larger samples and different techniques in the future may shed light on the etiology of delusional disorder.

From gifted to high potential and twice exceptional: A state-of-the-art meta-review

Despite the abundant literature on intelligence and high potential individuals, there is still a lack of international consensus on the terminology and clinical characteristics associated to this population. It has been argued that unstandardized use of diagnosis tools and research methods make comparisons and interpretations of scientific and epidemiological evidence difficult in this field. If multiple cognitive and psychological models have attempted to explain the mechanisms underlying high potentiality, there is a need to confront new scientific evidence with the old, to uproot a global understanding of what constitutes the neurocognitive profile of high-potential in gifted individuals. Another particularly relevant aspect of applied research on high potentiality concerns the challenges faced by individuals referred to as "twice exceptional" in the field of education and in their socio-affective life. Some individuals have demonstrated high forms of intelligence together with learning, affective or neurodevelopmental disorders posing the question as to whether compensating or exacerbating psycho-cognitive mechanisms might underlie their observed behavior. Elucidating same will prove relevant to questions concerning the possible need for differential diagnosis tools, specialized educational and clinical support. A meta-review of the latest findings from neuroscience to developmental psychology, might help in the conception and reviewing of intervention strategies.

Does the brain sleep differently depending on intellectual abilities?

AIMS

To compare the children's sleep electroencephalogram according to their intellectual profile.

METHODS

Children were grouped according to their Wechsler Intelligence Scale for Children (WISC) scores (17 with normal intelligence quotient [IQ, NIQ] and 24 with high IQ [HIQ]). Comparisons of spectral power between groups and its relationship with WISC scores were assessed using analyses of variance and linear regression models, adjusted for age and sex.

RESULTS

Children with HIQ had more rapid eye movement (REM) sleep, especially late at night, and more power in slow-frequency bands during REM sleep than those with NIQ. There were also positive associations between the processing speed index and the spectral power in β bands in NREM sleep, and with the spectral power in α, σ, β, and γ bands in REM sleep, with different associations between groups.

CONCLUSION

The enhanced power in slow bands during REM sleep in children with HIQ overlaps with that of typical REM sleep oscillations thought to be involved in emotional memory consolidation. The dissimilar relationships between spectral power and WISC scores in NIQ and HIQ groups may underlie functional differences in brain activity related to cognitive efficiency, questioning the direction of the relationship between sleep and cognitive functioning.

White matter integrity assessment in spinocerebellar ataxia type 2 (SCA2) patients

AIM

To assess the burden of white matter (WM) damage in the cerebrum and cerebellum of spinocerebellar ataxia type 2 (SCA2) patients in an attempt to identify key regions affected by the neurodegenerative processes using diffusion tensor imaging (DTI).

MATERIALS AND METHODS

Nine SCA2 patients and 16 age-matched healthy controls were examined twice (SCA2 patients 3.6 ± 0.7 years and controls 3.3 ± 1.0 years apart) on the same 1.5 T scanner by acquiring T1-weighted and diffusion-weighted (b-value = 1,000 s/mm2) images. Using tract-based spatial statistics, DTI analysis on fractional anisotropy (FA), mean diffusivity (MD), axial (AD)/radial (RD) diffusivity was performed.

RESULTS

At baseline magnetic resonance imaging (MRI), FA was significantly decreased in SCA2 patients in the corticospinal tracts, inferior and superior cerebellar peduncles, middle cerebellar peduncles, cerebral peduncles, right superior and posterior corona radiata. RD was only significantly increased in SCA2 patients in the middle cerebellar peduncles. No significant AD and MD changes were observed. Tract-based spatial statistics (TBSS) analysis between SCA2 patients at baseline and at follow-up showed no significant changes in any of the DTI metrics.

CONCLUSIONS

DTI is a sensitive tool for following the progression of WM neurodegeneration and severity assessment in patients with SCA2. These findings add to a better understanding of the neurological underpinnings of the symptoms experienced by SCA2 patients.

Abstract Graphic Creativity, Feelings about School, and Engagement in the School Environment: What Are the Interindividual Differences between Gifted and Non-Gifted Children?

This study examines interindividual differences between gifted and non-gifted children in the school environment. Three distinct measurement tools were used to enable a multimodal approach of gifted and non-gifted children with abstract graphic creativity, feelings about school and engagement in the school environment being considered. The results obtained from 328 children (including 45 gifted children) revealed that the gifted children obtained scores significantly higher than non-gifted children in terms of self-determination, feelings about school, and creativity. In addition, a gap appears among gifted children between their significantly higher scores for motivation and intellectual skills versus standard scores for their socio-affective development. Such results are consistent with the idea of asynchronous development, which is characteristic of gifted children (cognitive and conative vs. socio-affective sphere), offering perspectives for more adapted support for these pupils in elementary school.

Sleep and Psychosocial Characteristics of Children with Narcolepsy According to Their Intellectual Profile: A Case–Control Study

Adequate intellectual abilities are a protective factor for psychosocial adjustments in chronic disorders. The main objective of this study was to assess the cognitive abilities, sleep, and psychosocial characteristics of children with narcolepsy compared to controls, according to their intellectual profile. Children underwent a polysomnography, completed an intellectual ability assessment, and filled out standardized questionnaires. The group with an intelligence quotient (IQ) in the area of high intellectual potential (high IQ, HIQ) consisted of 25 children with narcolepsy (HIQ-N, 40% boys, median age 11.5 years, 48% with obesity, 60% under treatment) and 25 controls (HIQ-C, 68% boys, median age 11.7 years). Compared to HIQ-C, HIQ-N had a lower perceptual reasoning index and fewer conduct disorders. The group with an IQ in the normal range (NIQ) consisted of 22 children with narcolepsy (NIQ-N, 55% boys, median age 12.1 years, 59% with obesity, 64% under treatment) and 21 controls (NIQ-C, 68% boys, median age 10 years). NIQ-N presented the same intellectual profile as NIQ-C but reported more school difficulties. In children with HIQ, those with narcolepsy appear to have a different cognitive profile than controls. NIQ seems to predict a greater impact of narcolepsy on daily-life functioning.

Regional Brain Fusion: Graph Convolutional Network for Alzheimer's Disease Prediction and Analysis

Alzheimer's disease (AD) has raised extensive concern in healthcare and academia as one of the most prevalent health threats to the elderly. Due to the irreversible nature of AD, early and accurate diagnoses are significant for effective prevention and treatment. However, diverse clinical symptoms and limited neuroimaging accuracy make diagnoses challenging. In this article, we built a brain network for each subject, which assembles several commonly used neuroimaging data simply and reasonably, including structural magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and amyloid positron emission tomography (PET). Based on some existing research results, we applied statistical methods to analyze (i) the distinct affinity of AD burden on each brain region, (ii) the topological lateralization between left and right hemispheric sub-networks, and (iii) the asymmetry of the AD attacks on the left and right hemispheres. In the light of advances in graph convolutional networks for graph classifications and summarized characteristics of brain networks and AD pathologies, we proposed a regional brain fusion-graph convolutional network (RBF-GCN), which is constructed with an RBF framework mainly, including three sub-modules, namely, hemispheric network generation module, multichannel GCN module, and feature fusion module. In the multichannel GCN module, the improved GCN by our proposed adaptive native node attribute (ANNA) unit embeds within each channel independently. We not only fully verified the effectiveness of the RBF framework and ANNA unit but also achieved competitive results in multiple sets of AD stages' classification tasks using hundreds of experiments over the ADNI clinical dataset.

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.

White matter microarchitecture and structural network integrity correlate with children intelligence quotient

The neural substrate of high intelligence performances remains not well understood. Based on diffusion tensor imaging (DTI) which provides microstructural information of white matter fibers, we proposed in this work to investigate the relationship between structural brain connectivity and intelligence quotient (IQ) scores. Fifty-seven children (8–12 y.o.) underwent a MRI examination, including conventional T1-weighted and DTI sequences, and neuropsychological testing using the fourth edition of Wechsler Intelligence Scale for Children (WISC-IV), providing an estimation of the Full-Scale Intelligence Quotient (FSIQ) based on four subscales: verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI). Correlations between the IQ scores and both graphs and diffusivity metrics were explored. First, we found significant correlations between the increased integrity of WM fiber-bundles and high intelligence scores. Second, the graph theory analysis showed that integration and segregation graph metrics were positively and negatively correlated with WISC-IV scores, respectively. These results were mainly driven by significant correlations between FSIQ, VCI, and PRI and graph metrics in the temporal and parietal lobes. In conclusion, these findings demonstrated that intelligence performances are related to the integrity of WM fiber-bundles as well as the density and homogeneity of WM brain networks.

Sleep of Children with High Potentialities: A Polysomnographic Study

The involvement of sleep in cognitive functioning is well known, but only a few studies have examined objective sleep parameters in children with high intellectual potential (HP). The main objective of this study was to compare sleep characteristics of 33 children with high intellectual potentialities (HP) (median 10 years old, 64% of boys) compared to 25 controls (median 11 years old, 64% of boys) and assess the difference between children with a homogeneous vs. a heterogeneous intelligence quotient (IQ) (i.e., a difference ≥15 points between verbal and non-verbal IQ). All children underwent a one-night polysomnography, an evaluation of intellectual quotient (IQ) and filled standardized questionnaires. Using non-parametric tests to compare groups’ characteristics, we found that children with HP had more heterogeneous IQ, more rapid eyes movement (REM) sleep and tended to have less stage 1 sleep than controls. They also had more insomnia and sleep complaints. The high amount of REM sleep in children with HP could be advantageous for learning and could partially explain their gift. This study highlights the necessity of investigating sleep disorders in children with HP during clinical routine and reinforces the hypothesis of the involvement of nocturnal sleep, and especially REM sleep, in daytime cognition and behavior.

The neural code of intelligence: From correlation to causation

Research into the neural underpinning of intelligence has mainly adopted a construct perspective: trying to find structural and functional brain characteristics that would accommodate the psychological concept of g. Few attempts have been made to explain intelligence exclusively based on brain characteristics - the brain perspective. From a methodological viewpoint the brain intelligence relation has been studied by means of correlational and interventional studies. The later providing a causal elucidation of the brain - intelligence relation. The best neuro-anatomical predictor of intelligence is brain volume showing a modest positive correlation with g, explaining between 9 to 16% of variance. The most likely explanation was that larger brains, containing more neurons, have a greater computational power and in that way allow more complex cognitive processing. Correlations with brain surface, thickness, convolution and callosal shape showed less consistent patterns. The development of diffusion tensor imaging has allowed researchers to look also into the microstructure of brain tissue. Consistently observed was a positively correlation between white matter integrity and intelligence, supporting the idea that efficient information transfer between hemispheres and brain areas is crucial for higher intellectual competence. Based on functional studies of the brain intelligence relationship three theories have been put forward: the neural efficiency, the P-FIT and the multi demand (MD) system theory. On the other hand, The Network Neuroscience Theory of g, based on methods from mathematics, physics, and computer science, is an example for the brain perspective on neurobiological underpinning of intelligence. In this framework network flexibility and dynamics provide the foundation for general intelligence. With respect to intervention studies the most promising results have been achieved with noninvasive brain stimulation and behavioral training providing tentative support for findings put forward by the correlational approach. To date the best consensus based on the diversity of results reported would be that g is predominantly determined by lateral prefrontal attentional control of structured sensory episodes in posterior brain areas. The capacity of flexible transitions between these network states represents the essence of intelligence - g.

Pre- and Post-therapy Assessment of Clinical Outcomes and White Matter Integrity in Autism Spectrum Disorder: Pilot Study

Objective: This pilot study aims to identify white matter (WM) tract abnormalities in Autism Spectrum Disorders (ASD) toddlers and pre-schoolers by Diffusion Tensor Imaging (DTI), and to correlate imaging findings with clinical improvement after early interventional and Applied Behavior Analysis (ABA) therapies by Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP). Methods: DTI scans were performed on 17 ASD toddlers/pre-schoolers and seven age-matched controls. Nine ASD patients had follow-up MRI 12 months following early intervention and ABA therapy. VB-MAPP was assessed and compared at diagnosis, 6 and 12 months after therapies. Tract-Based Spatial Statistics (TBSS) was used to measure fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial (RD) diffusivity. Results: VB-MAPP scores improved at 6 and 12 months after early intervention and ABA therapy compared to scores at baseline. TBSS analysis showed significant FA decrease and/or RD increase in ASD patients before therapy vs. controls in inferior fronto-occipital fasciculi, uncinate fasciculi, left superior fronto-occipital fasciculus, forceps minor, left superior fronto-occipital fasciculus, right superior longitudinal fasciculus, corona radiate bilaterally, and left external capsule. A significantly FA increase in 21 tracts and ROIs is reported in post- vs. pre-therapy DTI analysis. Conclusion: DTI findings highlighted ASD patient WM abnormalities at diagnosis and confirmed the benefits of 12 months of early intervention and ABA therapy on clinical and neuro imaging outcomes.

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study

The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

Tissue plasminogen activator promotes white matter integrity and functional recovery in a murine model of traumatic brain injury

Recombinant tissue plasminogen activator (tPA) is a Food and Drug Administration-approved thrombolytic treatment for ischemic stroke. tPA is also naturally expressed in glial and neuronal cells of the brain, where it promotes axon outgrowth and synaptic plasticity. However, there are conflicting reports of harmful versus neuroprotective effects of tPA in acute brain injury models. Furthermore, its impact on white matter integrity in preclinical traumatic brain injury (TBI) has not been thoroughly explored, although white matter disruption is a better predictor of long-term clinical outcomes than focal lesion volumes. Here we show that the absence of endogenous tPA in knockout mice impedes long-term recovery of white matter and neurological function after TBI. tPA-knockout mice exhibited greater asymmetries in forepaw use, poorer sensorimotor balance and coordination, and inferior spatial learning and memory up to 35 d after TBI. White matter damage was also more prominent in tPA knockouts, as shown by diffusion tensor imaging, histological criteria, and electrophysiological assessments of axon conduction properties. Replenishment of tPA through intranasal application of the recombinant protein in tPA-knockout mice enhanced neurological function, the structural and functional integrity of white matter, and postinjury compensatory sprouting in corticofugal projections. tPA also promoted neurite outgrowth in vitro, partly through the epidermal growth factor receptor. Both endogenous and exogenous tPA protected against white matter injury after TBI without increasing intracerebral hemorrhage volumes. These results unveil a previously unappreciated role for tPA in the protection and/or repair of white matter and long-term functional recovery after TBI.

Brain Maturation, Cognition and Voice Pattern in a Gender Dysphoria Case under Pubertal Suppression

Introduction: Gender dysphoria (GD) (DMS-5) is a condition marked by increasing psychological suffering that accompanies the incongruence between one's experienced or expressed gender and one's assigned gender. Manifestation of GD can be seen early on during childhood and adolescence. During this period, the development of undesirable sexual characteristics marks an acute suffering of being opposite to the sex of birth. Pubertal suppression with gonadotropin releasing hormone analogs (GnRHa) has been proposed for these individuals as a reversible treatment for postponing the pubertal development and attenuating psychological suffering. Recently, increased interest has been observed on the impact of this treatment on brain maturation, cognition and psychological performance.

Objectives: The aim of this clinical report is to review the effects of puberty suppression on the brain white matter (WM) during adolescence. WM Fractional anisotropy, voice and cognitive functions were assessed before and during the treatment. MRI scans were acquired before, and after 22 and 28 months of hormonal suppression.

Methods: We performed a longitudinal evaluation of a pubertal transgender girl undergoing hormonal treatment with GnRH analog. Three longitudinal magnetic resonance imaging (MRI) scans were performed for diffusion tensor imaging (DTI), regarding Fractional Anisotropy (FA) for regions of interest analysis. In parallel, voice samples for acoustic analysis as well as executive functioning with the Wechsler Intelligence Scale (WISC-IV) were performed.

Results: During the follow-up, white matter fractional anisotropy did not increase, compared to normal male puberty effects on the brain. After 22 months of pubertal suppression, operational memory dropped 9 points and remained stable after 28 months of follow-up. The fundamental frequency of voice varied during the first year; however, it remained in the female range.

Conclusion: Brain white matter fractional anisotropy remained unchanged in the GD girl during pubertal suppression with GnRHa for 28 months, which may be related to the reduced serum testosterone levels and/or to the patient's baseline low average cognitive performance.Global performance on the Weschler scale was slightly lower during pubertal suppression compared to baseline, predominantly due to a reduction in operational memory. Either a baseline of low average cognition or the hormonal status could play a role in cognitive performance during pubertal suppression. The voice pattern during the follow-up seemed to reflect testosterone levels under suppression by GnRHa treatment.