Naming processes in reading and spelling disorders: An electrophysiological investigation

Bakos, Sarolta; Mehlhase, Heike; Landerl, Karin; Bartling, Jürgen; Schulte‐Körne, Gerd; Moll, Kristina

doi:10.1016/j.clinph.2019.11.017

Cited by 6 publications

(12 citation statements)

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“…Methodological difficulties in using traditional neurophysiological techniques to investigate the neural underpinning of dyslexia during serial RAN have hindered the development of studies in that direction ( Bakos et al, 2020 ; Christoforou et al, 2021a ). To help alleviate this problem, we proposed a novel computational approach for identifying neural components elicited during the serial RAN task.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Easson et al (2020) revealed significant contributions of fixation duration and saccade count to the prediction of naming speed performance. In addition, Bakos et al (2020) showed that EEG activity differed between 10-year-olds with reading difficulties and their counterparts at around 300 ms after stimulus presentation. This difference was evident in the left-occipital-temporal P2 component and was statistically significantly correlated to RAN performance, albeit small r (72) = 0.24, p < 0.04.…”

Section: Introductionmentioning

confidence: 99%

“…With regard to the former, two research approaches have been used, a componential (e.g., Georgiou et al, 2014 ) and a correlational (e.g., Papadopoulos et al, 2016 ) approach. With regard to the latter, data derived from fMRI studies (e.g., Cummine et al, 2015 ; Al Dahhan et al, 2020 ), electroencephalography (EEG) methods (e.g., Bakos et al, 2020 ) or more recently Fixation-Related Potentials (FRPs; e.g., Christoforou et al, 2021a ). Although the evidence shows that RAN predicts reading performance and that RAN taps into universal cognitive mechanisms involved in reading ( Papadopoulos et al, 2021 ), little is known about which neural components of RAN could better distinguish children with reading difficulties from typically developing peers.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, studies using eye-tracking (e.g., Easson et al, 2020 ) or electroencephalography (EEG) methods (e.g., Bakos et al, 2020 ) have provided additional evidence. Their results have focused on the RAN’s constituent components or the neurophysiological differences between children with reading difficulties and typically developing readers.…”

Section: Introductionmentioning

confidence: 99%

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RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed

Christoforou

Theodorou²,

Fella

et al. 2023

Front. Psychol.

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ObjectiveNaming speed, behaviorally measured via the serial Rapid automatized naming (RAN) test, is one of the most examined underlying cognitive factors of reading development and reading difficulties (RD). However, the unconstrained-reading format of serial RAN has made it challenging for traditional EEG analysis methods to extract neural components for studying the neural underpinnings of naming speed. The present study aims to explore a novel approach to isolate neural components during the serial RAN task that are (a) informative of group differences between children with dyslexia (DYS) and chronological age controls (CAC), (b) improve the power of analysis, and (c) are suitable for deciphering the neural underpinnings of naming speed.MethodsWe propose a novel machine-learning-based algorithm that extracts spatiotemporal neural components during serial RAN, termed RAN-related neural-congruency components. We demonstrate our approach on EEG and eye-tracking recordings from 60 children (30 DYS and 30 CAC), under phonologically or visually similar, and dissimilar control tasks.ResultsResults reveal significant differences in the RAN-related neural-congruency components between DYS and CAC groups in all four conditions.ConclusionRapid automatized naming-related neural-congruency components capture the neural activity of cognitive processes associated with naming speed and are informative of group differences between children with dyslexia and typically developing children.SignificanceWe propose the resulting RAN-related neural-components as a methodological framework to facilitate studying the neural underpinnings of naming speed and their association with reading performance and related difficulties.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed

Christoforou

Theodorou²,

Fella

et al. 2023

Front. Psychol.

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“…Homologous structures of abnormally activated hemisphere cortical regions are shown to be hyperactivated or under-activated in the right hemisphere [35,[49][50][51][52]. Furthermore, studies employing event-related potentials (ERP) have provided the temporal course of activation of anatomical structures during specific reading tasks (overt and covert reading and naming tasks) [53][54][55][56][57]. In both reading and naming tasks, the analysis of visual characteristics of words/pictures most likely occurs between 50 and 100 ms after stimulus presentation, while the perception of the word/object shape begins at approximately 150 ms and is regarded as a pre-lexical stage [53,[58][59][60][61][62][63][64][65][66].…”

Section: Introductionmentioning

confidence: 99%

Overt Word Reading and Visual Object Naming in Adults with Dyslexia: Electroencephalography Study in Transparent Orthography

Perkušić Čović,

Vujović,

Šoda

et al. 2024

Bioengineering

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The study aimed to investigate overt reading and naming processes in adult people with dyslexia (PDs) in shallow (transparent) language orthography. The results of adult PDs are compared with adult healthy controls HCs. Comparisons are made in three phases: pre-lexical (150–260 ms), lexical (280–700 ms), and post-lexical stage of processing (750–1000 ms) time window. Twelve PDs and HCs performed overt reading and naming tasks under EEG recording. The word reading and naming task consisted of sparse neighborhoods with closed phonemic onset (words/objects sharing the same onset). For the analysis of the mean ERP amplitude for pre-lexical, lexical, and post-lexical time window, a mixed design ANOVA was performed with the right (F4, FC2, FC6, C4, T8, CP2, CP6, P4) and left (F3, FC5, FC1, T7, C3, CP5, CP1, P7, P3) electrode sites, within-subject factors and group (PD vs. HC) as between-subject factor. Behavioral response latency results revealed significantly prolonged reading latency between HCs and PDs, while no difference was detected in naming response latency. ERP differences were found between PDs and HCs in the right hemisphere’s pre-lexical time window (160–200 ms) for word reading aloud. For visual object naming aloud, ERP differences were found between PDs and HCs in the right hemisphere’s post-lexical time window (900–1000 ms). The present study demonstrated different distributions of the electric field at the scalp in specific time windows between two groups in the right hemisphere in both word reading and visual object naming aloud, suggesting alternative processing strategies in adult PDs. These results indirectly support the view that adult PDs in shallow language orthography probably rely on the grapho-phonological route during overt word reading and have difficulties with phoneme and word retrieval during overt visual object naming in adulthood.

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Fixation-related potentials in naming speed: A combined EEG and eye-tracking study on children with dyslexia

Christoforou

Fella

Leppänen

et al. 2021

Clinical Neurophysiology

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Naming processes in reading and spelling disorders: An electrophysiological investigation

Cited by 6 publications

References 43 publications

RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed

RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed

Overt Word Reading and Visual Object Naming in Adults with Dyslexia: Electroencephalography Study in Transparent Orthography

Fixation-related potentials in naming speed: A combined EEG and eye-tracking study on children with dyslexia

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