659
Views
23
CrossRef citations to date
0
Altmetric
Articles

Error Detection Mechanism for Words and Sentences: A comparison between readers with dyslexia and skilled readers

&
Pages 33-45 | Published online: 03 Mar 2011
 

Abstract

The activity level of the error monitoring system for processing isolated versus contextual words in Hebrew was studied in adults with dyslexia and skilled readers while committing reading errors. Behavioural measures and event‐related potentials were measured during a lexical decision task using words in a list and sentences. Error‐related negativity (ERN/Ne) potentials following reading errors and correct‐related negativity for correct responses were detected in all conditions and participants. However, ERN/Ne amplitudes were smaller for those with dyslexia than for the skilled readers, and for reading sentences than for words in a list. These results support previous findings of lower activation of the error detection mechanism among dyslexics, and point to different activity levels for words and sentences. A theory on the underlying factors of dyslexia is proposed.

Acknowledgement

This study was supported by grant number 02 from the Edmond J. Safra Philanthropic Foundation. The Safra Foundation has no financial conflicts of interest such as direct or indirect financial benefits. No restrictions have been imposed on free access to, or publication of, the research data.

Notes

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 304.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.