Decoding letter position in word reading

Ori Ossmy, Michal Ben-Shachar, Roy Mukamel*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A fundamental computation underlying visual word recognition is the ability to transform a set of letters into a visual word form. Neuropsychological data suggest that letter position within a word may be independently affected by brain damage, resulting in a dissociable subtype of peripheral dyslexia. Here we used functional magnetic resonance imaging and supervised machine learning techniques to classify letter position based on activation patterns evoked during reading Hebrew words. Across the entire brain, activity patterns in the left intraparietal sulcus provided the best classification accuracy (80%) with respect to letter position. Importantly, the same set of voxels that showed highest classification performance of letter position using one letter-of-interest also showed highest classification performance using a different letter-of-interest. A functional connectivity analysis revealed that activity in these voxels co-varied with activity in the Visual Word Form Area, confirming cross-talk between these regions during covert reading. The results converge with reports of patients with acquired letter position dyslexia, who suffer from left occipito-parietal lesions. These findings provide direct and novel evidence for the role of left IPS within the reading network in processing relative letter positions.

Original languageEnglish
Pages (from-to)74-83
Number of pages10
StatePublished - Oct 2014


FundersFunder number
Human Frontiers Science Project
Israeli Center of Research Excellence
Human Frontier Science ProgramCDA00078/2011-C
United States-Israel Binational Science Foundation2011314
Israel Science Foundation2043/13, 1771/13


    • FMRI
    • Letter position
    • Pattern analysis
    • Reading


    Dive into the research topics of 'Decoding letter position in word reading'. Together they form a unique fingerprint.

    Cite this