Resting State EEG Hemispheric Power Asymmetry in Children with Dyslexia

Papagiannopoulou, Eleni A.; Lagopoulos, Jim

doi:10.3389/fped.2016.00011

Cited by 36 publications

(35 citation statements)

References 53 publications

(52 reference statements)

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“…EEG spectral differences have been used to differentiate matched controls from those with pathological conditions like dyslexia (Galin et al, 1992;Papagiannopoulou and Lagopoulos, 2016), insomnia (Buysse et al, 2008), fibromyalgia (Gonzalez-Roldan et al, 2016), epilepsy (Adebimpe et al, 2015), adolescents with sports related concussions (Balkan et al, 2015), and Parkinson’s disease (Caviness et al, 2016). In the current study, μ-β amplitudes did not correlate with a behavioral measure of stuttering severity making it unclear how well μ-β amplitude defines the disorder.…”

Section: Discussionmentioning

confidence: 99%

EEG Mu ( µ ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

et al. 2017

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Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, these analyses can reveal stuttering-related sensorimotor processing differences in passive listening and auditory discrimination tasks which may be influenced by basal ganglia deficits.

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Section: Discussionmentioning

confidence: 99%

EEG Mu ( µ ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

et al. 2017

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“…However, this resource may be useful in future therapeutic or brain stimulation intervention trials [31].…”

Section: P300 Auditory Cognitive Evoked Potential As a Tool For Monitmentioning

confidence: 99%

“…Previous studies investigated the auditory P300 component in individuals with dyslexia and reported different results: increased latency and decreased amplitude when compared to controls [31], no significant changes observed for the P300 amplitude and increased latency in the dyslexic group [32], and no significant between-group differences in the P300 amplitude and latency [33].…”

Section: Introductionmentioning

confidence: 99%

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Effects of a Phonological Reading and Writing Remediation Program in Students with Dyslexia: Intervention for Specific Learning Disabilities

Ferraz¹,

Gonçalves²,

Freire³

et al. 2018

Folia Phoniatr Logop

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Objective: To determine the effects of a phonological remediation reading and writing program in individuals with dyslexia, through behavioral and objective evaluations. Patients and Methods: Twenty children diagnosed with dyslexia, aged 8–14 years, were included in this study. Group I (GI) was composed of 10 children who took part in the program, and group II (GII) consisted of 10 subjects who did not take the remediation. The pre-testing evaluated phonological awareness, rapid naming, working memory, reading and writing of words and nonwords, thematic writing, and auditory evoked potential – P300. The type of stimulus used was the speech (20% of rare stimulus and 80% of frequent stimulus), intensity of 80 dBNa. The rare stimulus was the syllable /da/, and the frequent stimulus was the syllable /ba/. Next, the Phonological Reading and Writing Remediation Program was applied in 24 cumulative sessions, twice a week, each with a duration of 30 min. In the post-testing (at the end of the program), all the tests of the pre-testing were reapplied. Results: There was a statistically significant difference (between pre- and post-testing) in phonological awareness, rapid naming, working memory, thematic writing, writing and reading words and nonwords, as well as in the latency of the P3 component of P300 in GI, while GII maintained the same difficulties. Conclusion: The phonological remediation program showed to be a therapeutic method of fast beneficial effects in written language of individuals with dyslexia. However, the wide age range and the size of the sample could be considered a limitation of this study – it interferes with the generalization of results.

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“…The recent fMRI studies in neurotypical adults implicate corticostriatal and hippocampal systems in language learning [27]. In the literature, it has been further shown that higher levels of slow brain waves in the Broca area (F7 and FC5) in the left hemisphere have a high correlation with linguistic learning disabilities [5], [6], [10], [21], [25], [26]. These studies have been completed 978-1-5386-1501-0/18/$31.00 c 2018 IEEE using laboratory EEG equipment with 32 or 64 electrodes.…”

Section: Introductionmentioning

confidence: 99%

Electroencephalographic identifiers of reading abilities in turkish language

Eroğlu

Çetin

Balcısoy

2018

2018 26th Signal Processing and Communications Applications Conference (SIU)

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Fluent reading requires learning the print knowledge of alphabet symbols (letters), rapid automatic naming and phonological awareness skills. In this study, electroencephalographic brain signals of 17 subjects were measured with an eMotiv EPOC+ headset before, during and after a computerbased training session. For the training, distorted letter prints were created by rotating Turkish letters 180 degrees along the y-axis. Using these distorted letters two different texts, each 150 words in length, were created. Subjects were asked to read these texts before and after the training session. We investigated whether there is an improvement in reading speed and a decrease in number of errors due to the computer-based training and whether we can correlate the success of training with any characteristic of any EEG brain signals. Based on our analysis of the EEG data collected throughout the experiment, we observed that the frequency modulation across resting states in the Theta at the Broca Area (F7 and FC5) predicts individual reading performance measures. Even though there exist a variety of studies indicating a relation of Theta band power and learning performance, EEG measurements with eMotiv EPOC+ had not been previously reported with a Turkish alphabet learning task.

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Resting State EEG Hemispheric Power Asymmetry in Children with Dyslexia

Cited by 36 publications

References 53 publications

EEG Mu ( µ ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

EEG Mu ( µ ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

Effects of a Phonological Reading and Writing Remediation Program in Students with Dyslexia: Intervention for Specific Learning Disabilities

Electroencephalographic identifiers of reading abilities in turkish language

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