Altered temporal correlations in resting-state connectivity fluctuations in children with reading difficulties detected via MEG

Dimitriadis, Stavros I.; Laskaris, Nikolaos A.; Simos, Panagiotis G.; Micheloyannis, Sifis; Fletcher, Jack Μ.; Rezaie, Roozbeh; Papanicolaou, Andrew C.

doi:10.1016/j.neuroimage.2013.06.036

Cited by 85 publications

(109 citation statements)

References 77 publications

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“…The present study is compatible with the findings of a recent MEG (Dimitriadis et al, 2013) study, which also reported reduced global network measures in dyslexia. However, the current study is inconsistent with a recent structural network study of Chinese dyslexia based on gray matter volume data (Liu et al, 2015), which reported significantly increased local efficiency combined with a tendency of decreased global efficiency in the structural network of dyslexic children.…”

Section: Abnormal Global Network Properties Mainly In the Thickness Nsupporting

confidence: 93%

“…Additionally, the authors reported increased right-hemisphere connectivity and persistent connectivity to inferior frontal gyrus, reflecting a compensatory mechanism for poor reading in dyslexics. Another study (Dimitriadis et al, 2013), applying a magnetoencephalography (MEG) approach to investigate resting state brain networks, demonstrated that global and local network measures were Forty children participated in this study; these children were recruited from two primary schools in Beijing. Six children were excluded from analysis due to head movement (two children) or failures in image processing (four children).…”

Section: Introductionmentioning

confidence: 99%

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More bilateral, more anterior: Alterations of brain organization in the large-scale structural network in Chinese dyslexia

Ding

et al. 2016

NeuroImage

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Section: Abnormal Global Network Properties Mainly In the Thickness Nsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

More bilateral, more anterior: Alterations of brain organization in the large-scale structural network in Chinese dyslexia

Ding

et al. 2016

NeuroImage

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“…In addition, reading abilities have been linked to abnormal resting-state connectivity between visual areas for word recognition and the dorsal attention network (Vogel et al, 2012). Finally, several studies also found differences in the organization of long-range connectivity in electroencephalography (EEG) oscillatory activity of dyslexics, suggesting reduced global efficiency (Vourkas et al, 2011; Dimitriadis et al, 2013; Fraga González et al, 2016). The present study focuses on network properties revealing the organization of widespread functional connectivity in adult dyslexics relative to the connectivity pattern exhibited by typical readers.…”

Section: Introductionmentioning

confidence: 99%

EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis

González

Smit

Molen

et al. 2018

Front. Hum. Neurosci.

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Developmental dyslexia may involve deficits in functional connectivity across widespread brain networks that enable fluent reading. We investigated the large-scale organization of electroencephalography (EEG) functional networks at rest in 28 dyslexics and 36 typically reading adults. For each frequency band (delta, theta alpha and beta), we assessed functional connectivity strength with the phase lag index (PLI). Network topology was examined using minimum spanning tree (MST) graphs derived from the functional connectivity matrices. We found significant group differences in the alpha band (8–13 Hz). The graph analysis indicated more interconnected nodes, in dyslexics compared to typical readers. The graph metrics were significantly correlated with age in dyslexics but not in typical readers, which may indicate more heterogeneity in maturation of brain networks in dyslexics. The present findings support the involvement of alpha oscillations in higher cognition and the sensitivity of graph metrics to characterize functional networks in adult dyslexia. Finally, the current results extend our previous findings on children.

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“…Network metrics computed over different instantiations of the functional connectivity graph (FCG) can provide a quantitative view of the reconfigurable brain. At a more elaborate level, network metric time series (NMTS) can be formed which encapsulate the dynamical changes of functional dependencies computed over time-varying FCGs (TVFCGs) (Dimitriadis et al 2010b(Dimitriadis et al , 2013b.…”

Section: Introductionmentioning

confidence: 99%

Transition dynamics of EEG-based network microstates during mental arithmetic and resting wakefulness reflects task-related modulations and developmental changes

2015

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We studied how maturation influences the organization of functional brain networks engaged during mental calculations and in resting state. Surface EEG measurements from 20 children (8-12 years) and 25 students (21-26 years) were analyzed. Interregional synchronization of brain activity was quantified by means of Phase Lag Index and for various frequency bands. Based on these pairwise estimates of functional connectivity, we formed graphs which were then characterized in terms of local structure [local efficiency (LE)] and overall integration (global efficiency). The overall data analytic scheme was applied twice, in a static and time-varying mode. Our results showed a characteristic trend: functional segregation dominates the network organization of younger brains. Moreover, in childhood, the overall functional network possesses more prominent small-world network characteristics than in early acorrect in xmldulthood in accordance with the Neural Efficiency Hypothesis. The above trends were intensified by the time-varying approach and identified for the whole set of tested frequency bands (from δ to low γ). By mapping the time-indexed connectivity patterns to multivariate timeseries of nodal LE measurements, we carried out an elaborate study of the functional segregation dynamics and demonstrated that the underlying network undergoes transitions between a restricted number of stable states, that can be thought of as "network-level microstates". The rate of these transitions provided a robust marker of developmental and task-induced alterations, that was found to be insensitive to reference montage and independent component analysis denoising.

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Altered temporal correlations in resting-state connectivity fluctuations in children with reading difficulties detected via MEG

Cited by 85 publications

References 77 publications

More bilateral, more anterior: Alterations of brain organization in the large-scale structural network in Chinese dyslexia

More bilateral, more anterior: Alterations of brain organization in the large-scale structural network in Chinese dyslexia

EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis

Transition dynamics of EEG-based network microstates during mental arithmetic and resting wakefulness reflects task-related modulations and developmental changes

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