Abstract

Previously conducted structural magnetic resonance imaging (MRI) studies on the neuroanatomical correlates of mathematical abilities and competencies have a number of methodological limitations. Besides small sample sizes, the majority of these studies have employed voxel-based morphometry (VBM) – a method that, although it is easily to implement, has some major drawbacks. Taking this into account, the current study is the first to investigate in a large sample of typically developed adults the associations between mathematical abilities and variations in brain surface structure by using surface-based morphometry (SBM). SBM is a method that also allows the investigation of brain morphometry by avoiding the pitfalls of VBM. Eighty-nine young adults were tested with a large battery of psychometric tests to measure mathematical competencies in four different areas: (1) simple arithmetic, (2) complex arithmetic, (3) higher-order mathematics and (4) numerical intelligence. In addition, we asked participants for their mathematics grade of their final school exam. Inside the MRI scanner, we collected high-resolution T1-weighted anatomical images from each subject. SBM analyses were performed with the computational anatomy toolbox (CAT12) and indices for cortical thickness, for cortical surface complexity, for gyrification and for sulcal depth were calculated. Further analyses revealed associations between (1) the cortical surface complexity of the right superior temporal gyrus and numerical intelligence, (2) the depth of the right central sulcus and adults’ ability to solve complex arithmetic problems and (3) the depth of the left parieto-occipital sulcus and adults’ higher-order mathematics competence. Interestingly, no relationships with previously reported brain regions were observed, thus, suggesting the importance of similar research to confirm the role of the brain regions found in this study.