Adaptive behaviours are vital skills that allow individuals to function independently and are potentially amenable to behavioural interventions. Previous research indicated that adaptive behaviours ...are reduced in children and adolescents with severe to profound VI, but it was unclear if this was also the case for children with mild to moderate VI.
The aim of the study was to assess differences in adaptive behaviour in children with congenital visual disorders and different levels of visual impairment and their influence on quality of life and everyday strengths and difficulties.
Questionnaires about adaptive behaviour, strengths and difficulties, and quality of life were completed by parents of school-age children with severe-to-profound VI (S/PVI, n = 9, 0.9 logMAR – light perception only), mild-to-moderate VI (MVI, n = 9, 0.1–0.7 logMAR), or typical sight (control, n = 18, −0.3 to 0.1 logMAR). Differences in questionnaire domains by the severity of VI and relationships between adaptive behaviour and quality of life were analysed in general linear models.
The questionnaire ratings indicated reduced adaptive behaviour, more difficulties, and reduced quality of life in children with S/PVI compared to typically-sighted peers. Effects were smaller for children with MVI, but indicated a significant reduction in quality of life compared to typically-sighted children. The effect of visual impairment on quality of life in school was partially mediated by adaptive behaviour.
Severe congenital visual impairment affects adaptive behaviour in children with verbal abilities in the typical range. This effect is less pronounced in children with mild-to-moderate VI, but still impacts on quality of life, particularly in school.
Literacy and numeracy are important skills that are typically learned during childhood, a time that coincides with considerable shifts in large‐scale brain organization. However, most studies ...emphasize focal brain contributions to literacy and numeracy development by employing case‐control designs and voxel‐by‐voxel statistical comparisons. This approach has been valuable, but may underestimate the contribution of overall brain network organization. The current study includes children (N = 133 children; 86 male; mean age = 9.42, SD = 1.715; age range = 5.92–13.75y) with a broad range of abilities, and uses whole‐brain structural connectomics based on diffusion‐weighted MRI data. The results indicate that academic attainment is associated with differences in structural brain organization, something not seen when focusing on the integrity of specific regions. Furthermore, simulated disruption of highly‐connected brain regions known as hubs suggests that the role of these regions for maintaining the architecture of the network may be more important than specific aspects of processing. Our findings indicate that distributed brain systems contribute to the etiology of difficulties with academic learning, which cannot be captured using a more traditional voxel‐wise statistical approach.
Reading and math performance in children who struggle in school is associated with the global organisation of the white matter connectome.
The role of vision and vision deprivation in the development of executive function (EF) abilities in childhood is little understood; aspects of EF such as initiative, attention orienting, inhibition, ...planning and performance monitoring are often measured through visual tasks. Studying the development and integrity of EF abilities in children with congenital visual impairment (VI) may provide important insights into the development of EF and also its possible relationship with vision and non-visual senses. The current study investigates non-visual EF abilities in 18 school-age children of average verbal intelligence with VI of differing levels of severity arising from congenital disorders affecting the eye, retina, or anterior optic nerve. Standard auditory neuropsychological assessments of sustained and divided attention, phonemic, semantic and switching verbal fluency, verbal working memory, and ratings of everyday executive abilities by parents were undertaken. Executive skills were compared to age-matched typically-sighted (TS) typically-developing children and across levels of vision (mild to moderate VI MVI or severe to profound VI SPVI). The results do not indicate significant differences or deficits on direct assessments of verbal and auditory EF between the groups. However, parent ratings suggest difficulties with everyday executive abilities, with the greatest difficulties in those with SPVI. The findings are discussed as possibly reflecting increased demands of behavioral executive skills for children with VI in everyday situations despite auditory and verbal EF abilities in the typical range for their age. These findings have potential implications for clinical and educational practices.
We utilized a community detection approach to longitudinally (a) identify distinct groups of children with common temperament profiles in infancy and at 2 and 3 years of age and (b) determine whether ...co‐occurrence of certain temperament traits may be early predictors of internalizing problems at 5 years of age. Seven hundred and seventy‐four infants (360 girls; 88.6% White, 9.8% Hispanic, and 1.6% other races) were recruited from the Boston area. Data collection spanned from 2012 to 2021. The analysis yielded three distinct groups of children with different temperament traits and was associated with significant variation in levels of internalizing symptoms and anxiety diagnosis rate. Our findings suggest that stable temperament “communities” can be detected in early childhood and may predict risk for psychopathology later in life.
•Event related potential (ERP) paradigm using naturalistic active touch.•Haptic modulation of children’s ERP amplitude within 190 ms–250 ms and 310 ms–370 ms post stimulation.•Children’s response ...amplitudes decrease for congruent active touch.•Developmental audio-visual-haptic congruency effects over parietal cortex.•Active touch facilitates object size processing in children but not adults.
In order to increase perceptual precision the adult brain dynamically combines redundant information from different senses depending on their reliability. During object size estimation, for example, visual, auditory and haptic information can be integrated to increase the precision of the final size estimate. Young children, however, do not integrate sensory information optimally and instead rely on active touch. Whether this early haptic dominance is reflected in age-related differences in neural mechanisms and whether it is driven by changes in bottom-up perceptual or top-down attentional processes has not yet been investigated. Here, we recorded event-related-potentials from a group of adults and children aged 5–7 years during an object size perception task using auditory, visual and haptic information. Multisensory information was presented either congruently (conveying the same information) or incongruently (conflicting information). No behavioral responses were required from participants. When haptic size information was available via actively tapping the objects, response amplitudes in the mid-parietal area were significantly reduced by information congruency in children but not in adults between 190 ms–250 ms and 310 ms–370 ms. These findings indicate that during object size perception only children’s brain activity is modulated by active touch supporting a neural maturational shift from sensory dominance in early childhood to optimal multisensory benefit in adulthood.
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self‐organizing ...maps (SOMs)—a type of simple artificial neural network—to represent multivariate cognitive training data, and then tested whether the way tasks are represented changed as a result of training. The patterns of change we observed in the SOM weight matrices implied that the processes drawn upon to perform WM tasks changed following training. This was then combined with K‐means clustering to identify distinct groups of children who respond to the training in different ways. Firstly, the K‐means clustering was applied to an independent large sample (N = 616, Mage = 9.16 years, range = 5.16–17.91 years) to identify subgroups. We then allocated children who had been through cognitive training (N = 179, Mage = 9.00 years, range = 7.08–11.50 years) to these same four subgroups, both before and after their training. In doing so, we were able to map their improvement trajectories. Scores on a separate measure of fluid intelligence were predictive of a child's improvement trajectory. This paper provides an alternative approach to analysing cognitive training data that go beyond considering changes in individual tasks. This proof‐of‐principle demonstrates a potentially powerful way of distinguishing task‐specific from domain‐general changes following training and of establishing different profiles of response to training.
(a) Pre‐ and post‐ working memory (WM) training datasets from 179 children were used to train self‐organizing maps (SOM), a unsupervised machine learning algorithm that represents multivariate task relationships in a 2‐dimentional space, (b) WM task relationships as represented by SOM changed as a result of training, indicating that the processes drawn upon to perform these tasks were altered. Improvements might be due to task‐specific rather than domaingeneral enhancement and (c) There were differential improvement profiles among children and and independent measure of fluid intelligence at pre‐training is predictive of these profiles.
Network approaches that investigate the interaction between symptoms and behaviours have opened new ways of understanding psychological phenomena in health and disorder in recent years. In parallel, ...network approaches that characterise the interaction between brain regions have become the dominant approach in neuroimaging research. In this paper, we introduce a methodology for combining network psychometrics and network neuroscience. This approach utilises the information from the psychometric network to obtain neural correlates that are associated with each node in the psychometric network (network-based regression). Moreover, we combine the behavioural variables and their neural correlates in a joint network to characterise their interactions. We illustrate the approach by highlighting the interaction between the triad of autistic traits and their resting-state functional connectivity associations. To this end, we utilise data from 172 male autistic participants (10–21 years) from the autism brain data exchange (ABIDE, ABIDE-II) that completed resting-state fMRI and were assessed using the autism diagnostic interview (ADI-R). Our results indicate that the network-based regression approach can uncover both unique and shared neural correlates of behavioural measures. For instance, our example analysis indicates that the overlap between communication and social difficulties is not reflected in the overlap between their functional brain correlates.
The article introduces a method to combine common practices in network psychometrics and network neuroimaging. Namely, we use the unique variance in behavioural measures as regressors to identify unique neural correlates. This enables the description of brain-level and behavioural-level data into a joint network while keeping the dimensionality of the results manageable and interpretable. We illustrate this approach by showing the network of autistic traits and their correlates in resting-state functional connectivity.
Knowledge of genetic cause in neurodevelopmental disorders can highlight molecular and cellular processes critical for typical development. Furthermore, the relative homogeneity of neurodevelopmental ...disorders of known genetic origin allows the researcher to establish the subsequent neurobiological processes that mediate cognitive and behavioral outcomes. The current study investigated white matter structural connectivity in a group of individuals with intellectual disability due to mutations in ZDHHC9. In addition to shared cause of cognitive impairment, these individuals have a shared cognitive profile, involving oromotor control difficulties and expressive language impairment. Analysis of structural network properties using graph theory measures showed global reductions in mean clustering coefficient and efficiency in the ZDHHC9 group, with maximal differences in frontal and parietal areas. Regional variation in clustering coefficient across cortical regions in ZDHHC9 mutation cases was significantly associated with known pattern of expression of ZDHHC9 in the normal adult human brain. The results demonstrate that a mutation in a single gene impacts upon white matter organization across the whole-brain, but also shows regionally specific effects, according to variation in gene expression. Furthermore, these regionally specific patterns may link to specific developmental mechanisms, and correspond to specific cognitive deficits.
Aim
To examine if congenital visual impairment is associated with differences in brain anatomy in children.
Method
Ten children (8–12y) with congenital disorders of the peripheral visual system with ...severe visual impairment (SVI; >0.8 logMAR) or mild‐to‐moderate visual impairment (MVI; 0.6–0.8 logMAR) were compared to 21 typically sighted comparison (TSC) children. Thalamus volume, grey matter density, white matter microstructure, and integrity of visual tracts were investigated in SVI, MVI, and TSC groups with anatomical and diffusion‐weighted magnetic resonance imaging.
Results
Compared to the TSC group, the SVI group had lower white matter integrity in tracts of the visual system (optic radiations: SVI 0.35±0.015, TSC 0.39±0.007 p=0.022; posterior corpus callosum: SVI 0.37±0.019; TSC 0.42±0.009 p=0.033) and lower left thalamus volume (SVI 4.37±0.087; TSC 4.99±0.339 p=0.015). Neuroanatomical differences were greater in the SVI group, while no consistent differences between the MVI and TSC group were observed.
Interpretation
Posterior tracts of the visual system are compromised in children with congenital visual impairment versus those who are typically sighted. The severity of visual input appears to have affected neuroanatomical development as significant reductions were only found in the SVI group.
What this paper adds
Severe visual impairment in mid‐childhood is associated with reduced integrity of visual pathways and reduced thalamus volume.
What this paper adds
Severe visual impairment in mid‐childhood is associated with reduced integrity of visual pathways and reduced thalamus volume.
This article is commented on by Bauer on page 16 of this issue.
There is increasing interest in applying connectivity analysis to brain measures (Rubinov and Sporns, 2010), but most studies have relied on fMRI, which substantially limits the participant groups ...and numbers that can be studied. High-density EEG recordings offer a comparatively inexpensive easy-to-use alternative, but require channel-level connectivity analysis which currently lacks a common analytic framework and is very limited in spatial resolution. To address this problem, we have developed a new technique for studies of network development that overcomes the spatial constraint and obtains functional networks of cortical areas by using EEG source reconstruction with age-matched average MRI templates (He et al., 1999). In contrast to previously reported channel-level analysis, this approach provides information about the cortical areas most likely to be involved in the network as well as their functional relationship (Babiloni et al., 2005; De Vico Fallani et al., 2007).
In this study, we applied source reconstruction with age-matched templates to task-free high-density EEG recordings in typically-developing children between 2 and 6years of age (O'Reilly, 2012). Graph theory was then applied to the association strengths of 68 cortical regions of interest based on the Desikan–Killiany atlas. We found linear increases of mean node degree, mean clustering coefficient and maximum betweenness centrality between 2years and 6years of age. Characteristic path length was negatively correlated with age. The correlation of the network measures with age indicates network development towards more closely integrated networks similar to reports from other imaging modalities (Fair et al., 2008; Power et al., 2010). We also applied eigenvalue decomposition to obtain functional modules (Clayden et al., 2013). Connection strength within these modules did not change with age, and the modules resembled hub networks previously described for MRI (Hagmann et al., 2010; Power et al., 2010). The high temporal resolution of EEG additionally allowed us to distinguish between frequency bands potentially reflecting dynamic coupling between different neural oscillators. Generally, network parameters were similar for networks based on different frequency bands, but frequency band did emerge as a significant factor for clustering coefficient and characteristic path length. In conclusion, the current analysis shows that source reconstruction of high-density EEG recordings with appropriate head models offers a valuable tool for estimating network parameters in studies of brain development. The findings replicate the pattern of closer functional integration over development described for other imaging modalities (Fair et al., 2008; Power et al., 2010).
•Network MRI is difficult with children, sensor analysis of EEG is hard to interpret.•EEG source reconstruction with children using age-matched average templates•Graph measures of cortical source networks correlate with age.•Development to more closely interconnected networks with stable core modules•Network analysis of EEG sources is useful for studies of brain network development.
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