Resting-state EEG reveals global network deficiency in dyslexic children

Xue, Huidong; Wang, Zhiguo; Tan, Yufei; Yang, Hang; Fu, Wanlu; Xue, Licheng; Zhao, Jing

doi:10.1016/j.neuropsychologia.2020.107343

Cited by 27 publications

(38 citation statements)

References 67 publications

(87 reference statements)

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“…The lower levels of neural entrainment and connectivity may reflect the effects of a disrupted neural network structure and mixed patterns of connectivity abnormalities in children with dyslexia (Frye et al, 2012;Koyama et al, 2013). Similar effects were found in resting-state experiments, where typically developing children presented higher levels of connectivity than the children with dyslexia in the theta frequency band (Fraga González et al, 2016;Xue et al, 2020). Strong compensatory mechanisms seem to appear in later stages of development.…”

Section: Connectivitymentioning

confidence: 52%

“…Typical readers show a higher phase coherence at the age of 7 while children with dyslexia have a higher phase coherence at the age of 9. Higher levels of connectivity in beta oscillations for children older than 8 years with dyslexia have also been reported in resting-state studies (Xue et al, 2020) and are present in adolescence (Granados Barbero et al, 2021b) and in adulthood (Thiede et al, 2020). This later maturation of beta oscillations found with connectivity may trigger the compensatory mechanisms in the neural entrainment levels (SNRs) that appear in adolescents (Granados Barbero et al, 2021b) and adults (Helenius et al, 2002).…”

Section: Activity At 20 Hz (Beta Rhythm)mentioning

confidence: 68%

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Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Barbero

Ghesquière

Wouters

2022

Front. Comput. Neurosci.

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Different studies have suggested that during speech processing readers with dyslexia present atypical levels of neural entrainment as well as atypical functional hemispherical asymmetries in comparison with typical readers. In this study, we evaluated these differences in children and the variation with age before and after starting with formal reading instruction. Synchronized neural auditory processing activity was quantified based on auditory steady-state responses (ASSRs) from EEG recordings. The stimulation was modulated at syllabic and phonemic fluctuation rates present in speech. We measured the brain activation patterns and the hemispherical asymmetries in children at three age points (5, 7, and 9 years old). Despite the well-known heterogeneity during developmental stages, especially in children and in dyslexia, we could extract meaningful common oscillatory patterns. The analyses included (1) the estimations of source localization, (2) hemispherical preferences using a laterality index, measures of neural entrainment, (3) signal-to-noise ratios (SNRs), and (4) connectivity using phase coherence measures. In this longitudinal study, we confirmed that the existence of atypical levels of neural entrainment and connectivity already exists at pre-reading stages. Overall, these measures reflected a lower ability of the dyslectic brain to synchronize with syllabic rate stimulation. In addition, our findings reinforced the hypothesis of a later maturation of the processing of beta rhythms in dyslexia. This investigation emphasizes the importance of longitudinal studies in dyslexia, especially in children, where neural oscillatory patterns as well as differences between typical and atypical developing children can vary in the span of a year.

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Section: Connectivitymentioning

confidence: 52%

Section: Activity At 20 Hz (Beta Rhythm)mentioning

confidence: 68%

Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Barbero

Ghesquière

Wouters

2022

Front. Comput. Neurosci.

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“…Applying this method to resting-state EEG data, our child study revealed statistically significant group differences in the theta (4–8 Hz) band suggesting reduced network integration and less communication between network nodes in children with dyslexia compared to typical readers ( Fraga González et al, 2016 ). A similar study used the same approach on Chinese-speaking children of similar age and found differences between dyslexic and typical readers in the same direction but in MST metrics in the beta band ( Xue et al, 2020 ). They used shorter epoch length and a smaller montage with less electrodes compared to our previous study, which may have contributed to the differences in addition to the different alphabetic systems.…”

Section: Introductionmentioning

confidence: 93%

Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics

et al. 2021

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We performed an EEG graph analysis on data from 31 typical readers (22.27 ± 2.53 y/o) and 24 dyslexics (22.99 ± 2.29 y/o), recorded while they were engaged in an audiovisual task and during resting-state. The task simulates reading acquisition as participants learned new letter-sound mappings via feedback. EEG data was filtered for the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands. We computed the Phase Lag Index (PLI) to provide an estimate of the functional connectivity between all pairs of electrodes per band. Then, networks were constructed using a Minimum Spanning Tree (MST), a unique sub-graph connecting all nodes (electrodes) without loops, aimed at minimizing bias in between groups and conditions comparisons. Both groups showed a comparable accuracy increase during task blocks, indicating that they correctly learned the new associations. The EEG results revealed lower task-specific theta connectivity, and lower theta degree correlation over both rest and task recordings, indicating less network integration in dyslexics compared to typical readers. This pattern suggests a role of theta oscillations in dyslexia and may reflect differences in task engagement between the groups, although robust correlations between MST metrics and performance indices were lacking.

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“…Fraga González and others found dyslexic children to have a significantly lower leaf fraction and higher diameter in EEG theta band than typically reading children ( Fraga González et al, 2016 ), while Xue and others found no significant differences ( Xue et al, 2020 ). Fraga González and others found a higher kappa in dyslexic young adults ( Fraga González et al, 2018 ).…”

Section: Resultsmentioning

confidence: 97%

Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity

Blomsma

Rooy

Gerritse

et al. 2022

Network Neuroscience

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Brain network characteristics’ potential to serve as a neurological and psychiatric pathology biomarker has been hampered by the so-called thresholding problem. The minimum spanning tree (MST) is increasingly applied to overcome this problem. It is yet unknown whether this approach leads to more consistent findings across studies and converging outcomes of either disease-specific biomarkers or transdiagnostic effects. We performed a systematic review on MST analysis in neurophysiological and neuroimaging studies (N = 43) to study consistency of MST-metrics between different network sizes, and assessed disease specificity and transdiagnostic sensitivity of MST-metrics for neurological and psychiatric conditions. Analysis of data from control groups (12 studies) showed that MST leaf fraction but not diameter decreased with increasing network size. Studies showed a broad range in metric values, suggesting that specific processing pipelines affect MST topology. Contradicting findings remain in the inconclusive literature of MST brain network studies, but some trends were seen: 1) a more line-like organization characterizes neurodegenerative disorders across pathologies, and is associated with symptom severity and disease progression; 2) neurophysiological studies in epilepsy show frequency band specific MST alterations that normalize after successful treatment; and 3) less efficient MST topology in alpha band is found across disorders associated with attention impairments.

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Resting-state EEG reveals global network deficiency in dyslexic children

Cited by 27 publications

References 67 publications

Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Development of Atypical Reading at Ages 5 to 9 Years and Processing of Speech Envelope Modulations in the Brain

Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics

Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity

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