Abstract
Background and Purpose
In recent years, there has been a growing interest in the study of resting neural networks in different neurological and mental disorders. While previous studies suggest that the default mode network (DMN) may be altered in dyscalculia, the study of resting-state networks in the development of numerical skills, especially in children with developmental dyscalculia (DD), is scarce and relatively recent. Based on this, this study examines differences in resting-state functional connectivity (rs-FC) data of children with DD using functional connectivity multivariate pattern analysis (fc-MVPA), a data-driven methodology that summarizes properties of the entire connectome.
Methods
We performed fc-MVPA on resting-state images of a sample composed of a group of children with DD (n = 19, 8.06 ± 0.87 years) and an age- and sex-matched control group of typically developing children (n = 23, 7.76 ± 0.46 years).
Results
Analysis of fc-MVPA showed significant differences between group connectivity profiles in two clusters allocated in both the right and left medial temporal gyrus. Post hoc effect size results revealed a decreased rs-FC between each temporal pole and the DMN in children with DD and an increased rs-FC between each temporal pole and the sensorimotor network.
Conclusions
Our results suggest an aberrant information flow between resting-state networks in children with DD, demonstrating the importance of these networks for arithmetic development.
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This post is Copyright: Roger Mateu‐Estivill,
Ana Adan,
Sergi Grau,
Xavier Rifà‐Ros,
Xavier Caldú,
Núria Bargalló,
Josep M. Serra‐Grabulosa | September 6, 2024
Wiley: Journal of Neuroimaging: Table of Contents