Optimal Word Reading Rate as Evidenced by Frequency-tagging Electrophysiology

Fast periodic visual stimulation (FPVS) coupled with EEG has been used for a decade to measure word-selective neural responses in (a)typical adults and developmental readers. Here, we used this FPVS-EEG approach to evaluate suitable and optimal stimulation frequency rates for prelexical and lexical word-selective responses and relate these rates to typical reading speed and interindividual variability in reading performance. EEG was recorded in 41 healthy adults who viewed words inserted periodically (1 Hz) at four different stimulation frequency rates (4 Hz, 6 Hz, 10 Hz, and 20 Hz). At all these stimulation rates but the highest (20 Hz), we found typical left-lateralized, word-selective, occipitotemporal responses, larger for the prelexical (words in nonwords) than lexical (words in pseudowords) contrast. Although significant responses were found at all frequency rates, these responses were negligible at 20 Hz, without any evidence of left lateralization at this frequency. The largest occipitotemporal response was found at a 4 Hz base rate in both hemispheres for the prelexical contrast, with increased left lateralization for the lexical discrimination. Moreover, word-selective responses for this discrimination (lexical), only at 4 Hz, were related to reading speed. The optimal 4 Hz rate finding is in line with the mean reading speed for expert readers as assessed during text reading. Overall, these findings further validate and optimize the FPVS-EEG approach for rapid implicit measurement of word-selective neural responses.

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Publication Details

Journal
Journal of Cognitive Neuroscience
Published
2025-01-01
DOI
https://doi.org/10.1162/jocn_a_02286
Citations
8
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
10.02

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article

Optimal Word Reading Rate as Evidenced by Frequency-tagging Electrophysiology

Bruno Rossion, Aliette Lochy, Marion Marchive
8 citations
Journal of Cognitive Neuroscience
EEG and Brain-Computer Interfaces
10.02
article

Optimal Word Reading Rate as Evidenced by Frequency-tagging Electrophysiology

Bruno Rossion, Aliette Lochy, Marion Marchive
article en
8 citations

Abstract

Fast periodic visual stimulation (FPVS) coupled with EEG has been used for a decade to measure word-selective neural responses in (a)typical adults and developmental readers. Here, we used this FPVS-EEG approach to evaluate suitable and optimal stimulation frequency rates for prelexical and lexical word-selective responses and relate these rates to typical reading speed and interindividual variability in reading performance. EEG was recorded in 41 healthy adults who viewed words inserted periodically (1 Hz) at four different stimulation frequency rates (4 Hz, 6 Hz, 10 Hz, and 20 Hz). At all these stimulation rates but the highest (20 Hz), we found typical left-lateralized, word-selective, occipitotemporal responses, larger for the prelexical (words in nonwords) than lexical (words in pseudowords) contrast. Although significant responses were found at all frequency rates, these responses were negligible at 20 Hz, without any evidence of left lateralization at this frequency. The largest occipitotemporal response was found at a 4 Hz base rate in both hemispheres for the prelexical contrast, with increased left lateralization for the lexical discrimination. Moreover, word-selective responses for this discrimination (lexical), only at 4 Hz, were related to reading speed. The optimal 4 Hz rate finding is in line with the mean reading speed for expert readers as assessed during text reading. Overall, these findings further validate and optimize the FPVS-EEG approach for rapid implicit measurement of word-selective neural responses.

Journal of Cognitive NeuroscienceVol. 37(5)
University of Luxembourg (LU), Centre Hospitalier Régional et Universitaire de Nancy (FR), Université de Lorraine (FR), UCLouvain (BE)
Université de Lorraine, Agence Nationale de la Recherche, Fonds National de la Recherche Luxembourg
Openalex Percentile: Top 2%
EEG and Brain-Computer Interfaces
10.02
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