Graph analysis of EEG resting state functional networks in dyslexic readers

González, Gorka Fraga; Molen, Melle J. W. van der; Žarić, Gojko; Bonte, Milene; Tijms, Jurgen; Blomert, Leo; Stam, Cornelis J.; Molen, Maurits W. van der

doi:10.1016/j.clinph.2016.06.023

Cited by 149 publications

(141 citation statements)

References 60 publications

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“…The goal of the present study was to examine the organization of functional networks in dyslexics and typically reading adults, extending our previous findings in 3rd grade children (Fraga González et al, 2016). We used PLI to assess connectivity and MSTs to examine the topological properties of the network.…”

Section: Discussionsupporting

confidence: 54%

“…Our previous study reporting the results of MST analysis in dyslexic and typically reading children, we observed a somewhat different pattern of results (Fraga González et al, 2016). In that study, dyslexic children showed a less integrated tree configuration in theta, indicated by lower leaf number, degree and kappa, compared to typical readers.…”

Section: Discussionmentioning

confidence: 58%

“…We performed the current graph analysis following similar steps as in our previous study (Fraga González et al, 2016). A schematic of these steps is shown in Figure 1 The continuous EEG data were imported in EEGLAB v.12.5.4b, a Matlab-based open toolbox (Delorme and Makeig, 2004).…”

Section: Methodsmentioning

confidence: 99%

“…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%

“…We previously used MSTs in EEG resting-state data to compare dyslexic and typically reading children in 3rd grade (Fraga González et al, 2016). In that study, we obtained significant group differences in the theta (4–8 Hz) band for two graph metrics that suggested reduced network integration and less communication between network nodes in dyslexics compared to typical readers.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Discussionsupporting

confidence: 54%

Section: Discussionmentioning

confidence: 58%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Dyslexia

Archer

Pammer

2021

Encyclopedia of Life Sciences

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Dyslexia is a disorder characterised by difficulty in learning to read that cannot be attributed to secondary organic, mechanical or social circumstances. In other words, a child fails to learn to read at an age‐appropriate rate, irrespective of intelligence level, education or other neurological deficits. Notably, developmental dyslexia – which is the focus of this article – is distinct from acquired dyslexia, which occurs due to brain trauma. Numerous sensory and cognitive deficits contribute to dyslexia, including difficulties with auditory processing of speech sounds, visual processing and working memory. Current research is aimed at understanding the neurobiological cause of these cognitive deficits. Key Concepts Dyslexia is a universal and persistent form of low literacy in which a child fails to learn to read at an age‐appropriate rate. It is found across languages and is not associated with intelligence, age, education or other neurological deficits. Symptoms of dyslexia and their severity can vary significantly from one individual to the next. People with dyslexia have been found to have Impaired phonological processing – that is, a decreased perceptual sensitivity to sound‐segments in language. Difficulties with short‐term memory. Impaired visual processing. Spelling difficulties. Phonological dyslexia refers to difficulties in sounding words out and making phonological manipulations. Surface dyslexia refers to difficulties in developing and accessing a lexicon, that is a mental representation of words. Dyslexia is often confused with visual stress – the symptoms of which include words moving when attempting to read, shimmering or disappearing, words looking like they were carved into the page, lines or rivers through the text, and preferring to read under very low light levels. The exact aetiology of dyslexia is unknown; however, evidence indicates deficits in magnocellular‐dorsal stream processing in the visual domain and impaired brainwave function in the auditory domain. Several genetic mutations have also been identified in dyslexia. Current remedial interventions for dyslexia are educational and are aimed at improving cognitive deficits. Current research is aimed at identifying the neurobiological basis of dyslexia to aid the development of a treatment that targets the underlying neurobiological cause of dyslexia.

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Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling

Coronel‐Oliveros,

Gómez,

Ranasinghe

et al. 2024

Alzheimer's & Dementia

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INTRODUCTIONAlzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost‐effective technique for studying dementia globally, but lacks mechanistic models and produces non‐replicable results.METHODSWe developed a generative whole‐brain model that combines EEG source‐level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls).RESULTSMetaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings.DISCUSSIONThe results provide a novel agenda for developing mechanistic model‐inspired characterization and therapies in clinical, translational, and computational neuroscience settings.

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Graph analysis of EEG resting state functional networks in dyslexic readers

Cited by 149 publications

References 60 publications

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

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

Dyslexia

Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling

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