Gray matter volume of widespread cortical regions significantly predicts children's subtraction skill in a cross-validated model¶

Claim · All claims
Evidence · 1 study · associational r2 · q2 · i2 medium
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i2 A GMV-based LOOCV predictive model significantly predicted individual differences in subtraction performance (r = 0.3506). → Zhang 2024

Evidence¶

Zhang 2024¶

Zhang, D., Xie, Y., Wang, L. & Zhou, K. (2024). Structural and transcriptional signatures of arithmetic abilities in children. npj Science of Learning 9, 58. https://doi.org/10.1038/s41539-024-00270-6

q2 · i2 · associational · r2

Cross-sectional predictive-modeling analysis of structural MRI and CMAT behavioral data from 130 children (grades 3-8). The subtraction model's observed-predicted correlation was significant, "sub- traction: r = 0.3506", and confirmed by two permutation testing approaches.

"For both the subtraction and multip lication predictive model, the correlation between observed and predicted scores was signi ficant (sub- traction: r = 0.3506, P =4 . 3 2×1 0−6; multiplication: r = 0.2824, P = 0.0011"

Discussion¶

Related Claims¶

• Gray matter volume significantly predicts children's multiplication skill in a cross-validated model — related
• A GMV-based model significantly predicts visuospatial working memory, with brain-region overlap with the arithmetic models — related
• The relation between arithmetic skill and gray matter volume in the left IFG and left MTG remains significant after controlling for reading, vocabulary, verbal and non-verbal IQ — related
• Bayesian analyses provide evidence that arithmetic skill does not relate to gray matter volume in the left angular gyrus, intraparietal sulcus, or hippocampus — related