Executive functions–based reading training engages the cingulo-opercular and dorsal attention networks

Nikolay Taran, Rola Farah, Carmel Gashri, Ester Gitman, Keri Rosch, Bradley L. Schlaggar, Tzipi Horowitz-Kraus

Research output: Contribution to journalArticlepeer-review


The aim of this study was to determine the effect of a computerized executive functions (EFs)– based reading intervention on neural circuits supporting EFs and visual attention. Seed-to-voxel functional connectivity analysis was conducted focusing on large-scale attention system brain networks, during an fMRI reading fluency task. Participants were 8-to 12-year-old English-speaking children with dyslexia (n = 43) and typical readers (n = 36) trained on an EFs-based reading training (n = 40) versus math training (n = 39). Training duration was 8 weeks. After the EFs-based reading intervention, children with dyslexia improved their scores in reading rate and visual attention (compared to math intervention). Neurobiologically, children with dyslexia displayed an increase in functional connectivity strength after the intervention between the cingulo-opercular network and occipital and precentral regions. Noteworthy, the functional connectivity indices between these brain regions showed a positive correlation with speed of processing and visual attention scores in both pretest and posttest. The results suggest that reading improvement following an EFs-based reading intervention involves neuroplastic connectivity changes in brain areas related to EFs and primary visual processing in children with dyslexia. Our results highlight the need for training underlying cognitive abilities supporting reading, such as EFs and visual attention, in order to enhance reading abilities in dyslexia.

Original languageEnglish
Pages (from-to)1452-1482
Number of pages31
JournalNetwork Neuroscience
Issue number4
StatePublished - 2023


  • Dyslexia
  • Executive functions
  • Functional connectivity
  • Intervention
  • Visual attention
  • fMRI

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Applied Mathematics
  • General Neuroscience
  • Computer Science Applications


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