• Roger Mateu-Estivill, Ana Adan, Sergi Grau, Xavier Rifà-Ros, Xavier Caldú, Núria Bargalló, and Josep M Serra-Grabulosa.
• Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain.
• J Neuroimaging. 2024 Nov 1; 34 (6): 694703694-703.

Background And PurposeIn 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.MethodsWe 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).ResultsAnalysis 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.ConclusionsOur results suggest an aberrant information flow between resting-state networks in children with DD, demonstrating the importance of these networks for arithmetic development.© 2024 The Author(s). Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.

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