Working memory (WM) skills are closely associated with learning progress in key areas such as reading and mathematics across childhood. As yet, however, little is known about how the brain systems ...underpinning WM develop over this critical developmental period. The current study investigated whether and how structural brain correlates of components of the working memory system change over development. Verbal and visuospatial short‐term and working memory were assessed in 153 children between 5.58 and 15.92 years, and latent components of the working memory system were derived. Fractional anisotropy and cortical thickness maps were derived from T1‐weighted and diffusion‐weighted MRI and processed using eigenanatomy decomposition. There was a greater involvement of the corpus callosum and posterior temporal white matter in younger children for performance associated with the executive part of the working memory system. For older children, this was more closely linked with the thickness of the occipitotemporal cortex. These findings suggest that increasing specialization leads to shifts in the contribution of neural substrates over childhood, moving from an early dependence on a distributed system supported by long‐range connections to later reliance on specialized local circuitry. Our findings demonstrate that despite the component factor structure being stable across childhood, the underlying brain systems supporting working memory change. Taking the age of the child into account, and not just their overall score, is likely to be critical for understanding the nature of the limitations on their working memory capacity.
The paper investigated changing relationships between brain anatomy and working memory performance across developmental time. The results indicated that microstructure of the corpus callosum and posterior temporal white matter were more closely linked to performance associated with the executive component of working memory in younger children, while cortical thickness of a left temporal region was more important in adolescents.
Previous studies have identified localized associations between childhood environment – namely their socio-economic status (SES) – and particular neural structures. The primary aim of the current ...study was to test whether associations between SES and brain structure are widespread or limited to specific neural pathways. We employed advances in whole-brain structural connectomics to address this. Diffusion tensor imaging was used to construct whole-brain connectomes in 113 6−12 year olds. We then applied an adapted multi-block partial-least squares (PLS) regression to explore how connectome organisation is associated with childhood SES (parental income, education levels, and neighbourhood deprivation). The Fractional Anisotropy (FA) connectome was significantly associated with childhood SES and this effect was widespread. We then pursued a secondary aim, and demonstrated that the connectome mediated the relationship between SES and cognitive ability (matrix reasoning and vocabulary). However, the connectome did not significantly mediate SES relationships with academic ability (maths and reading) or internalising and externalising behavior. This multivariate approach is important for advancing our theoretical understanding of how brain development may be shaped by childhood environment, and the role that it plays in predicting key outcomes. We also discuss the limitations with this new methodological approach.
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.
► Attentional control abilities predict individual differences in VSTM capacity. ► Developmental increases in capacity are associated with fronto-parietal changes. ► The neural circuitry underlying ...VSTM capacity changes may be modified by training. ► The developmental and adult cognitive neuroscience of VSTM inform one another.
An ever increasing amount of research in the fields of developmental psychology and adult cognitive neuroscience explores attentional control as a driver of visual short-term and working memory capacity limits (“VSTM” and “VWM”, respectively). However, these literatures have thus far been disparate: they use different measures or different labels, and the constructs of interest often appear to be quite distinct. In the current review, we attempt to bridge these gaps across disciplines and explore the extent to which these two literatures might support one another. In order to do this, we explore five principal questions of interest to members of both communities: (1) To what extent are measures of VSTM, VWM and attentional control commensurate across the developmental and adult literatures? (2) To what extent do individual differences in attentional control account for why some children, just like some adults, show poorer VSTM and VWM capacity than others? (3) Can developmental improvements in VSTM and VWM capacity also be explained by differences in attentional control? (4) What novel insights can be gained by studying the developmental cognitive neuroscience of attention and VSTM and VWM? (5) Can visual short-term and working memory capacity be modulated by training and, if so, how can training effects inform the relationships between attention and VSTM? Throughout, we evaluate the central thesis that variability in attentional control, both between individuals and over development, is a driver of variability in VSTM and VWM capacity.
Inattention and hyperactivity are cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD). These characteristics have also been observed across a range of other neurodevelopmental ...conditions, such as autism and dyspraxia, suggesting that they might best be studied across diagnostic categories. Here, we evaluated the associations between inattention and hyperactivity behaviours and features of the structural brain network (connectome) in a large transdiagnostic sample of children (Centre for Attention, Learning, and Memory; n = 383). In our sample, we found that a single latent factor explains 77.6% of variance in scores across multiple questionnaires measuring inattention and hyperactivity. Partial Least-Squares (PLS) regression revealed that variability in this latent factor could not be explained by a linear component representing nodewise properties of connectomes. We then investigated the type and extent of neural heterogeneity in a subset of our sample with clinically-elevated levels of inattention and hyperactivity. Multidimensional scaling combined with k-means clustering revealed two neural subtypes in children with elevated levels of inattention and hyperactivity (n = 232), differentiated primarily by nodal communicability—a measure which demarcates the extent to which neural signals propagate through specific brain regions. These different clusters had similar behavioural profiles, which included high levels of inattention and hyperactivity. However, one of the clusters scored higher on multiple cognitive assessment measures of executive function. We conclude that inattention and hyperactivity are so common in children with neurodevelopmental difficulties because they emerge through multiple different trajectories of brain development. In our own data, we can identify two of these possible trajectories, which are reflected by measures of structural brain network topology and cognition.
Learning a new word requires discrimination between a novel sequence of sounds and similar known words. We investigated whether semantic information facilitates the acquisition of new phonological ...representations in adults and whether this learning enhancement is modulated by overnight consolidation. Participants learned novel spoken words either consistently associated with a visual referent or with no consistent meaning. An auditory oddball task tested discrimination of these newly learned phonological forms from known words. The MMN, an electrophysiological measure of auditory discrimination, was only elicited for words learned with a consistent semantic association. Immediately after training, this semantic benefit on auditory discrimination was linked to explicit learning of the associations, where participants with greater semantic learning exhibited a larger MMN. However, although the semantic-associated words continued to show greater auditory discrimination than nonassociated words after consolidation, the MMN was no longer related to performance in learning the semantic associations. We suggest that the provision of semantic systematicity directly impacts upon the development of new phonological representations and that a period of offline consolidation may promote the abstraction of these representations.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The triple network model of psychopathology posits that altered connectivity between the Salience (SN), Central Executive (CEN), and Default Mode Networks (DMN) may underlie neurodevelopmental ...conditions. However, this has yet to be tested in a transdiagnostic sample of young people.
We investigated this in 175 children (60 girls) that represent a heterogeneous population who are experiencing neurodevelopmental difficulties in cognition and behavior, and 60 comparison children (33 girls). Hyperactivity/impulsivity and inattention were assessed by parent-report. Resting-state functional Magnetic Resonance Imaging data were acquired and functional connectivity was calculated between independent network components and regions of interest. We then examined whether connectivity between the SN, CEN and DMN was dimensionally related to hyperactivity/impulsivity and inattention, whilst controlling for age, gender, and motion.
Hyperactivity/impulsivity was associated with increased functional connectivity between the SN, CEN, and DMN in at-risk children, whereas it was associated with decreased functional connectivity between the CEN and DMN in comparison children. These effects replicated in an adult parcellation of brain function and when using increasingly stringent exclusion criteria for in-scanner motion.
Triple network connectivity characterizes transdiagnostic neurodevelopmental difficulties with hyperactivity/impulsivity. We suggest that this may arise from delayed network segregation, difficulties sustaining CEN activity to regulate behavior, and/or a heightened developmental mismatch between neural systems implicated in cognitive control relative to those implicated in reward/affect processing.
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.
Behavioural difficulties are seen as hallmarks of many neurodevelopmental conditions. Differences in functional brain organisation have been observed in these conditions, but little is known about ...how they are related to a child’s profile of behavioural difficulties. We investigated whether behavioural difficulties are associated with how the brain is functionally organised in an intentionally heterogeneous and transdiagnostic sample of 957 children aged 5–15. We used consensus community detection to derive data-driven profiles of behavioural difficulties and constructed functional connectomes from a subset of 238 children with resting-state functional Magnetic Resonance Imaging (fMRI) data. We identified three distinct profiles of behaviour that were characterised by principal difficulties with hot executive function, cool executive function, and learning. Global organisation of the functional connectome did not differ between the groups, but multivariate patterns of connectivity at the level of Intrinsic Connectivity Networks (ICNs), nodes, and hubs significantly predicted group membership in held-out data. Fronto-parietal connector hubs were under-connected in all groups relative to a comparison sample and children with hot vs cool executive function difficulties were distinguished by connectivity in ICNs associated with cognitive control, emotion processing, and social cognition. This demonstrates both general and specific neurodevelopmental risk factors in the functional connectome.
•We derived 3 behavioural profiles in 799 neurodevelopmentally at-risk children.•Namely, difficulties in hot executive function (EF), cool EF, and learning.•Global organisational properties of the functional connectome did not differ.•Connector hubs were more globally integrated in controls than at-risk groups.•Hot and cool EF groups differed in regional and network connectivity.
•We used a continuous performance measure VSTM in children aged between 7 and 12.•This was combined with a probabilistic mixture model.•Older children were more likely to remember the target, but ...were no more precise.•Mixture model parameters corresponded to differences in standardized WM and STM.
Our ability to retain visuospatial information over brief periods of time is severely limited and develops gradually. In childhood, visuospatial short-term and working memory are typically indexed using span-based measures. However, whilst these standardized measures have been successful in characterizing developmental and individual differences, each individual trial only provides a binary measure of a child’s performance—they are either correct or incorrect. Here we used a novel continuous report paradigm, in combination with probabilistic modeling, to explore developmental and individual differences in how likely children were to recall memoranda, and how precisely they could report them. Taking this approach revealed a number of novel findings: (i) a concurrent processing demand negatively impacted upon both of these parameters, increasing the guessing rate and making children less precise; (ii) older children (aged 10–12, N=20) were significantly less likely to guess, but when they did remember the target were no more precise in reporting it than younger children (aged 7–9, N=20); (iii) children’s performance on standardized short-term and working memory tasks was significantly associated with both the guessing likelihood, and the precision of target responding, on the continuous report task. In short, we show that continuous report paradigms can offer interesting insight into processes that underlie developmental and individual differences in visuospatial memory in childhood.
PDF
