Inter-subject correlation during long narratives reveals widespread neural correlates of reading ability

Recent work using fMRI inter-subject correlation analysis has provided new information about the brain's response to video and audio narratives, particularly in frontal regions not typically activated by single words. This approach is very well suited to the study of reading, where narrative is central to natural experience. But since past reading paradigms have primarily presented single words or phrases, the influence of narrative on semantic processing in the brain – and how that influence might change with reading ability – remains largely unexplored. In this study, we presented coherent stories to adolescents and young adults with a wide range of reading abilities. The stories were presented in alternating visual and auditory blocks. We used a dimensional inter-subject correlation analysis to identify regions in which better and worse readers had varying levels of consistency with other readers. This analysis identified a widespread set of brain regions in which activity timecourses were more similar among better readers than among worse readers. These differences were not detected with standard block activation analyses. Worse readers had higher correlation with better readers than with other worse readers, suggesting that the worse readers had “idiosyncratic” responses rather than using a single compensatory mechanism. Close inspection confirmed that these differences were not explained by differences in IQ or motion. These results suggest an expansion of the current view of where and how reading ability is reflected in the brain, and in doing so, they establish inter-subject correlation as a sensitive tool for future studies of reading disorders.

Data Code

Author
David Jangraw
Emily Finn
Peter Bandettini
Nicole Landi
Haorui Sun
Fumiko Hoeft
Gang Chen
Kenneth Pugh
Peter Molfese
Keywords
Cognitive neuroscience
Neurology
Year of Publication
2023
Journal
NeuroImage
Volume
282
Number of Pages
120390
ISSN Number
1053-8119
DOI
10.1016/j.neuroimage.2023.120390