Influences of brain development and ageing on cortical interactive networks

Integrative Brain Dynamics in Childhood Bullying Victimization: Cognitive and Emotional Convergence Associated With Stress Psychopathology

Bullying victimization is a form of psychological stress that is associated with poor outcomes in the areas of mental health and learning. Although the emotional maladjustment and memory impairment following interpersonal stress are well documented, the mechanisms of complex cerebral dysfunctions have neither been outlined nor studied in depth in the context of childhood bullying victimization. As a contribution to the cross-disciplinary field of developmental psychology and neuroscience, we review the neuropathophysiology of early life stress, as well as general psychological stress to synthesize the data and clarify the versatile dynamics within neuronal networks linked to bullying victimization. The stress-induced neuropsychological cascade and associated cerebral networks with a focus on cognitive and emotional convergence are described. The main findings are that stress-evoked neuroendocrine reactivity relates to neuromodulation and limbic dysregulation that hinder emotion processing and executive functioning such as semantic cognition, cognitive flexibility, and learning. Developmental aspects and interacting neural mechanisms linked to distressed cognitive and emotional processing are pinpointed and potential theory-of-mind nuances in targets of bullying are presented. The results show that childhood stress psychopathology is associated with a complex interplay where the major role belongs to, but is not limited to, the amygdala, fusiform gyrus, insula, striatum, and prefrontal cortex. This interplay contributes to the sensitivity toward facial expressions, poor cognitive reasoning, and distress that affect behavioral modulation and emotion regulation. We integrate the data on major brain dynamics in stress neuroactivity that can be associated with childhood psychopathology to help inform future studies that are focused on the treatment and prevention of psychiatric disorders and learning problems in bullied children and adolescents.

The quantitative effect of blue lenses on pediatric photoparoxysmal response - An electroencephalographic cohort study

PURPOSE

To determine and quantify the effect of blue lenses (Z1) on photosensitivity (PS) suppression in patients aged 5-18 years with and without epilepsy.

METHODS

The retrospective cohort study was carried out in 100 pediatric patients aged 5-18 years with grade 4 PS assessed with EEG for medical indications. All EEG procedures were carried out and recordings assessed by two independent researchers. The study cohort was divided into groups with and without the diagnosis of epilepsy. The overall effect of the Z1 lenses on photoparoxysmal response (PPR) was determined by directly comparing the maximum discharge values in each patient without and with Z1 lenses in a within-subject design yielding the index of overall improvement (IOI). The differences in PS suppression by brain region and side were assessed by an additional between-subject comparison of age groups (below and above 14 years). Then, overall findings were compared with the PPR change criteria developed in 2006 by Capovilla (PPR disappearance, persistence, or attenuation) which warranted another subset analysis. Finally, in a between-subject design, we assessed whether the presence of epilepsy affects the intensity of PPR in children with PS, compared to non-epilepsy children.

RESULTS

The IOI in the entire cohort was 66.1±2.5% (P<0.001). There were no significant differences in IOI between the left and right hemispheres, between the age groups, and between the epilepsy and non-epilepsy groups, despite some qualitative variation. With reference to literature findings, whereas median IOI were comparable in PPR disappearance and attenuation subsets, they differed significantly from the median IOI in the PPR persistence subset.

CONCLUSION

Using Z1 lenses results in neither a complete PPR disappearance, nor a complete lack of effect. However, the correlation between the quantified PS suppression and the Z1 filter may be expected to become a valuable piece of information for both clinicians and manufacturers.

Affectionate Touch in the Context of Breastfeeding and Maternal Depression Influences Infant Neurodevelopmental and Temperamental Substrates

BACKGROUND

While numerous studies have demonstrated maternal depression's influence on infant brain development, few studies have examined the changes that occur as a consequence of co-occurring experiential factors that affect quality of mother and infant affectionate touch as well as infant temperament and neurophysiological systems. The aim of the study was to examine the interactive effects of maternal depression and breastfeeding on mother and infant affectionate touch and infant temperament and cortical maturation patterns across early development.

METHODS

113 mothers and their infants participated when infants were 1 and 3 months of age. Questionnaires to assess maternal depressive symptoms, feeding, and temperament were completed. Tonic EEG patterns (asymmetry and left and right activity) were collected and the dyads were video-recorded during feeding to assess mother and infant affectionate touch patterns.

RESULTS

Data analysis showed that EEG activity and mother-infant affectionate touch differed as a function of mood and feeding method. Notably, only infants of depressed mothers that bottle-fed showed right frontal EEG asymmetry and attenuated change in the left frontal region across 3 months. Breastfeeding positively impacted affectionate touch behaviors and was associated with increased left and decreased right frontal EEG activation even for depressed groups. Furthermore, a model incorporating physiology, maternal depression, touch, temperament, and feeding indicated significant prediction for infant affectionate touch (with breastfeeding and affectively positive temperament demonstrating the strongest prediction). Con-clusion: The findings suggest that breastfeeding and the infant's positive temperament influence mother-infant affectionate touch patterns and result in neuroprotective outcomes for infants, even those exposed to maternal depression within early development.

EEG Resting-State Brain Topological Reorganization as a Function of Age

Resting state connectivity has been increasingly studied to investigate the effects of aging on the brain. A reduced organization in the communication between brain areas was demonstrated by combining a variety of different imaging technologies (fMRI, EEG, and MEG) and graph theory. In this paper, we propose a methodology to get new insights into resting state connectivity and its variations with age, by combining advanced techniques of effective connectivity estimation, graph theoretical approach, and classification by SVM method. We analyzed high density EEG signals recorded at rest from 71 healthy subjects (age: 20–63 years). Weighted and directed connectivity was computed by means of Partial Directed Coherence based on a General Linear Kalman filter approach. To keep the information collected by the estimator, weighted and directed graph indices were extracted from the resulting networks. A relation between brain network properties and age of the subject was found, indicating a tendency of the network to randomly organize increasing with age. This result is also confirmed dividing the whole population into two subgroups according to the age (young and middle-aged adults): significant differences exist in terms of network organization measures. Classification of the subjects by means of such indices returns an accuracy greater than 80%.

PPREMO: a prospective cohort study of preterm infant brain structure and function to predict neurodevelopmental outcome

BACKGROUND

More than 50 percent of all infants born very preterm will experience significant motor and cognitive impairment. Provision of early intervention is dependent upon accurate, early identification of infants at risk of adverse outcomes. Magnetic resonance imaging at term equivalent age combined with General Movements assessment at 12 weeks corrected age is currently the most accurate method for early prediction of cerebral palsy at 12 months corrected age. To date no studies have compared the use of earlier magnetic resonance imaging combined with neuromotor and neurobehavioural assessments (at 30 weeks postmenstrual age) to predict later motor and neurodevelopmental outcomes including cerebral palsy (at 12-24 months corrected age). This study aims to investigate i) the relationship between earlier brain imaging and neuromotor/neurobehavioural assessments at 30 and 40 weeks postmenstrual age, and ii) their ability to predict motor and neurodevelopmental outcomes at 3 and 12 months corrected age.

METHODS/DESIGN

This prospective cohort study will recruit 80 preterm infants born ≤ 30 week's gestation and a reference group of 20 healthy term born infants from the Royal Brisbane & Women's Hospital in Brisbane, Australia. Infants will undergo brain magnetic resonance imaging at approximately 30 and 40 weeks postmenstrual age to develop our understanding of very early brain structure at 30 weeks and maturation that occurs between 30 and 40 weeks postmenstrual age. A combination of neurological (Hammersmith Neonatal Neurologic Examination), neuromotor (General Movements, Test of Infant Motor Performance), neurobehavioural (NICU Network Neurobehavioural Scale, Premie-Neuro) and visual assessments will be performed at 30 and 40 weeks postmenstrual age to improve our understanding of the relationship between brain structure and function. These data will be compared to motor assessments at 12 weeks corrected age and motor and neurodevelopmental outcomes at 12 months corrected age (neurological assessment by paediatrician, Bayley scales of Infant and Toddler Development, Alberta Infant Motor Scale, Neurosensory Motor Developmental Assessment) to differentiate atypical development (including cerebral palsy and/or motor delay).

DISCUSSION

Earlier identification of those very preterm infants at risk of adverse neurodevelopmental and motor outcomes provides an additional period for intervention to optimise outcomes.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12613000280707. Registered 8 March 2013.

Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence

BACKGROUND AND PURPOSE

A number of studies have associated the adult intelligence quotient with the structure and function of the bilateral parieto-frontal networks, whereas the relationship between intelligence quotient and parieto-frontal network function has been found to be relatively weak in early childhood. Because both human intelligence and brain function undergo protracted development into adulthood, the purpose of the present study was to provide a better understanding of the development of the parieto-frontal network-intelligence quotient relationship.

MATERIALS AND METHODS

We performed independent component analysis of resting-state fMRI data of 84 children and 50 adolescents separately and then correlated full-scale intelligence quotient with the spatial maps of the bilateral parieto-frontal networks of each group.

RESULTS

In children, significant positive spatial-map versus intelligence quotient correlations were detected in the right angular gyrus and inferior frontal gyrus in the right parieto-frontal network, and no significant correlation was observed in the left parieto-frontal network. In adolescents, significant positive correlation was detected in the left inferior frontal gyrus in the left parieto-frontal network, and the correlations in the frontal pole in the 2 parieto-frontal networks were only marginally significant.

CONCLUSIONS

The present findings not only support the critical role of the parieto-frontal networks for intelligence but indicate that the relationship between intelligence quotient and the parieto-frontal network in the right hemisphere has been well established in late childhood, and that the relationship in the left hemisphere was also established in adolescence.

Enhanced effective connectivity in mild occipital stroke patients with hemianopia

Plasticity-based spontaneous recovery and rehabilitation intervention of stroke-induced hemianopia have drawn great attention in recent years. However, the underlying neural mechanism remains unknown. This study aims to investigate brain network disruption and reorganization in hemianopia patients due to mild occipital stroke. Resting-state networks were constructed from 12 hemianopia patients with right occipital infarct by partial directed coherence analysis of multi-channel electroencephalograms. Compared with control subjects, the patients presented enhanced connectivity owing to newly formed connections. Compensational connections mostly originated from the peri-infarct area and targeted contralesional frontal, central, and parietal cortices. These new ipsilesional-to-contralesional inter-hemispheric connections coordinately presented significant correlation with the extent of vision loss. The enhancement of connectivity might be the neural substrate for brain plasticity in stroke-induced hemianopia and may shed light on plasticity-based recovery or rehabilitation.

Lifespan differences in cortico-striatal resting state connectivity

Distinctive cortico-striatal circuits that serve motor and cognitive functions have been recently mapped based on resting state connectivity. It has been reported that age differences in cortico-striatal connectivity relate to cognitive declines in aging. Moreover, children in their early teens (i.e., youth) already show mature motor network patterns while their cognitive networks are still developing. In the current study, we examined age differences in the frontal-striatal "cognitive" and "motor" circuits in children and adolescence, young adults (YAs), and older adults (OAs). We predicted that the strength of the "cognitive" frontal-striatal circuits would follow an inverted "U" pattern across age; children and OAs would have weaker connectivity than YAs. However, we predicted that the "motor" circuits would show less variation in connectivity strength across the lifespan. We found that most areas in both the "cognitive" and "motor" circuits showed higher connectivity in YAs than children and OAs, suggesting general inverted "U"-shaped changes across the lifespan for both the cognitive and motor frontal-striatal networks.

Representational pseudoneglect: a review

Pseudoneglect, the tendency to be biased towards the left-hand side of space, is a robust and consistent behavioural observation best demonstrated on the task of visuospatial line bisection, where participants are asked to centrally bisect visually presented horizontal lines at the perceived centre. A number of studies have revealed that a representational form of pseudoneglect exists, occurring when participants are asked to either mentally represent a stimulus or explore a stimulus using touch in the complete absence of direct visuospatial processing. Despite the growing number of studies that have demonstrated representational pseudoneglect there exists no current and comprehensive review of these findings and no discussion of a theoretical framework into which these findings may fall. An important gap in the current representational pseudoneglect literature is a discussion of the developmental trajectory of the bias. The focus of the current review is to outline studies that have observed representational pseudoneglect in healthy participants, consider a theoretical framework for these observations, and address the impact of lifespan factors such as cognitive ageing on the phenomenon.

Functional connectivity between parietal and frontal brain regions and intelligence in young children: the Generation R study

It has been shown in adults that individual differences in intelligence are related to the integrity of the interaction between parietal and frontal brain regions. Since connectivity between distant brain regions strengthens during childhood, it is unclear when in the course of development this relationship emerges. Thus, the goal of this study was to determine whether parietal-frontal functional connectivity is associated with intelligence in young children. We performed independent component analyses on resting-state fMRI data of 115 children (6-8 years old) to select seed and target regions for a seed/target region correlation analysis. We found that higher nonverbal intelligence was associated with increased functional connectivity between right parietal and right frontal regions, and between right parietal and dorsal anterior cingulate regions. The association between intelligence and functional connectivity between certain brain regions was stronger in girls than boys. In conclusion, we found that connectivity between the parietal and frontal lobes is critically involved in intelligence in young children.

Aged-related changes in brain activity classification with respect to age by means of graph indexes

Recent studies have investigated changes in the human brain network organization during the normal aging. A reduction of the connectivity between brain areas was demonstrated by combining neuroimaging technologies and graph theory. Clustering, characteristic path length and small-worldness are key topological measures and they are widely used in literature. In this paper we propose a new methodology that combine advanced techniques of effective connectivity estimation, graph theoretical approach and classification by SVM method. EEG signals recording during rest condition from 20 young subjects and 20 mid-aged adults were studied. Partial Directed Coherence was computed by means of General Linear Kalman Filter and graph indexes were extracted from estimated patterns. At last small-worldness was used as feature for the SVM classifier. Results show that topological differences of brain networks exist between young and mid-aged adults: small-worldness is significantly different between the two populations and it can be used to classify the subjects with respect to age with an accuracy of 69%.

A hybrid CPU-GPU accelerated framework for fast mapping of high-resolution human brain connectome

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson's Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states.