Atypical resting-state functional brain connectivity in children with developmental coordination disorder

Dyck, Dorine Van; Deconinck, Nicolas; Aeby, Alec; Baijot, Simon; Coquelet, Nicolas; Trotta, Nicola; Rovaï, Antonin; Goldman, Serge; Urbain, Charline; Wens, Vincent; Tiège, Xavier De

doi:10.1016/j.nicl.2021.102928

Cited by 5 publications

(8 citation statements)

References 117 publications

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“…For example, impaired implicit sequence learning has been reported in Developmental Coordination Disorder, Dyslexia, Parkinson's Disease and Schizophrenia (Clark & Lum, 2017). As predicted by the results of the current study, elevated resting state theta power has been found in each of these conditions (Dubbelink et al, 2013; Papagiannopoulou & Lagopoulos, 2016; Sponheim et al, 1994; van Dyck et al, 2022). Also, the effectiveness of interventions aimed at improving motor skills dependant on implicit learning, might be predicted by resting state theta.…”

Section: Discussionsupporting

confidence: 78%

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

Lum

Byrne

Barhoun

et al. 2023

Eur J of Neuroscience

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Neuroimaging resting state paradigms have revealed synchronised oscillatory activity is present even in the absence of completing a task or mental operation. One function of this neural activity is likely to optimise the brain's sensitivity to forthcoming information that, in turn, likely promotes subsequent learning and memory outcomes. The current study investigated whether this extends to implicit forms of learning. A total of 85 healthy adults participated in the study. Resting state electroencephalography was first acquired from participants before they completed a serial reaction time task. On this task, participants implicitly learnt a visuospatial‐motor sequence. Permutation testing revealed a negative correlation between implicit sequence learning and resting state power in the upper theta band (6–7 Hz). That is, lower levels of resting state power in this frequency range were associated with superior levels of implicit sequence learning. This association was observed at midline‐frontal, right‐frontal and left‐posterior electrodes. Oscillatory activity in the upper theta band supports a range of top‐down processes including attention, inhibitory control and working memory, perhaps just for visuospatial information. Our results may be indicating that disengaging theta‐supported top‐down attentional processes improves implicit learning of visuospatial‐motor information that is embedded in sensory input. This may occur because the brain's sensitivity to this type of information is optimally achieved when learning is driven by bottom‐up processes. Moreover, the results of this study further demonstrate that resting state synchronised brain activity influences subsequent learning and memory.

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Section: Discussionsupporting

confidence: 78%

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

Lum

Byrne

Barhoun

et al. 2023

Eur J of Neuroscience

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“…This regression model is closely related to a within-condition power regression of functional connectivity data, which in our experience tends to spuriously exacerbate connectivity differences across two conditions (unpublished data). That is why in past publications, we relied on regression designs that suppress specifically the effect of between-condition power changes in corresponding connectivity differences (Naeije et al, 2019; Sjøgård et al, 2020; Van Dyck et al, 2021a). Our present analysis demonstrates the usefulness of moving away from generic linear modeling and towards methodological developments that integrate neurophysiological data and physically motivated models of brain dynamics.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies also revealed their role in stimulus processing (Betti et al, 2018;Hawellek et al, 2013;Smith et al, 2009), task performance (O'Neill et al, 2015b;O'Neill et al, 2017;Quinn et al, 2018), learning and memory (Higgins et al, 2021;Mary et al, 2017;Van Dyck et al, 2021b), and in the pathophysiology of brain disorders Naeije et al, 2019;Puttaert et al, 2020;Sitnikova et al, 2018;Sjøgård et al, 2020;Van Dyck et al, 2021a;Van Schependom et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…A wealth of knowledge has accumulated on diverse aspects of their electrophysiology, such as the spectral specificity of resting-state networks (Brookes et al, 2014, 2016; Tewarie et al, 2016; Wens et al, 2014a), the existence of supra-second-scale dynamics underlying versatile global network topology (de Pasquale et al, 2012, 2016; Della Penna et al, 2019) and metastable cross-network couplings (Wens et al, 2019), or their relationship to sub-second bursts of transient brain oscillations (Baker et al, 2014; Coquelet et al, 2022; Seedat et al, 2020; Vidaurre et al, 2018). Several studies also revealed their role in stimulus processing (Betti et al, 2018; Hawellek et al, 2013; Smith et al, 2009), task performance (O’Neill et al, 2015b; O’Neill et al, 2017; Quinn et al, 2018), learning and memory (Higgins et al, 2021; Mary et al, 2017; Roshchupkina et al, 2022; Van Dyck et al, 2021b), and in the pathophysiology of brain disorders (Brookes et al, 2018; Naeije et al, 2019; Puttaert et al, 2020; Sitnikova et al, 2018; Sjøgård et al, 2020; Van Dyck et al, 2021a; Van Schependom et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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The dissociative role of bursting and non-bursting neural activity in the oscillatory nature of functional brain networks

Cordier

Mary

Ghinst

et al. 2022

Preprint

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Electrophysiological measures of functional connectivity can be affected by the power bias, i.e., variations in their estimation due to variations in the signal-to-noise ratio (SNR) rather than in genuine neural interactions. Intrinsic functional networks emerge at rest from magnetoencephalography (MEG) amplitude connectivity mostly within the α and β frequency bands, where the SNR of MEG recordings is coincidentally maximal. This raises the question, is the spectral specificity of these networks really driven by neural oscillatory dynamics or is it an artifact due to the power bias? Here, we present a detailed theoretical analysis of the power bias in amplitude connectivity allowing to disentangle the neural part of connectivity from the nonlinear SNR dependence of estimated amplitude connectivity (as well as from the contribution of noise correlations). On this basis, we developed a new correction technique involving a SNR-dependent renormalization of amplitude connectivity, which we validated using synthetic data. We then applied the technique to resting-state MEG data and quantified to what extent the power bias affects the spectral content of intrinsic functional brain couplings. We demonstrated the absence of such effect, which was explained by the observation in synthetic data that the power bias is very reduced at the sufficiently high SNRs found in resting-state MEG recordings. Comparison with a classical linear regression technique highlights the importance of our nonlinear correction to reach this conclusion. Our analysis thus confirms the crucial role of neural oscillations for the spontaneous emergence of intrinsic brain functional networks.

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“…These sessions took place with the same investigator (DVD) in two Belgian hospitals (Brussels), the CUB Hôpital Erasme (DCD = 30/50; TD = 31/31) and the Hôpital Universitaire des Enfants Reine Fabiola (DCD = 20/50). This study was part of a longer experimental protocol, and some children (DCD = 38/50; TD = 31/31) also underwent a magnetoencephalography/electroencephalography investigation ( Van Dyck et al, 2020 , 2022 ) and a procedural learning task ( Van Dyck et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Cognitive, perceptual, and motor profiles of school-aged children with developmental coordination disorder

et al. 2022

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Developmental coordination disorder (DCD) is a heterogeneous condition. Besides motor impairments, children with DCD often exhibit poor visual perceptual skills and executive functions. This study aimed to characterize the motor, perceptual, and cognitive profiles of children with DCD at the group level and in terms of subtypes. A total of 50 children with DCD and 31 typically developing (TD) peers (7–11 years old) underwent a comprehensive neuropsychological (15 tests) and motor (three subscales of the Movement Assessment Battery for Children-2) assessment. The percentage of children with DCD showing impairments in each measurement was first described. Hierarchical agglomerative and K-means iterative partitioning clustering analyses were then performed to distinguish the subtypes present among the complete sample of children (DCD and TD) in a data-driven way. Moderate to large percentages of children with DCD showed impaired executive functions (92%) and praxis (meaningless gestures and postures, 68%), as well as attentional (52%), visual perceptual (46%), and visuomotor (36%) skills. Clustering analyses identified five subtypes, four of them mainly consisting of children with DCD and one of TD children. These subtypes were characterized by: (i) generalized impairments (8 children with DCD), (ii) impaired manual dexterity, poor balance (static/dynamic), planning, and alertness (15 DCD and 1 TD child), (iii) impaired manual dexterity, cognitive inhibition, and poor visual perception (11 children with DCD), (iv) impaired manual dexterity and cognitive inhibition (15 DCD and 5 TD children), and (v) no impairment (25 TD and 1 child with DCD). Besides subtle differences, the motor and praxis measures did not enable to discriminate between the four subtypes of children with DCD. The subtypes were, however, characterized by distinct perceptual or cognitive impairments. These results highlight the importance of assessing exhaustively the perceptual and cognitive skills of children with DCD.

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Atypical resting-state functional brain connectivity in children with developmental coordination disorder

Cited by 5 publications

References 117 publications

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

The dissociative role of bursting and non-bursting neural activity in the oscillatory nature of functional brain networks

Cognitive, perceptual, and motor profiles of school-aged children with developmental coordination disorder

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