Arithmetic problem size modulates brain activations in females but not in males

• Published in: The European journal of neuroscience Vol. 58; no. 5; pp. 3299 - 3314
• Main Authors: Chen, Nai‐Feng, Chang, Ting‐Ting
• Format: Journal Article
• Language: English
• Published: France Wiley Subscription Services, Inc 01.09.2023
• Subjects: Brain mapping; Females; fMRI; Frontal gyrus; Functional magnetic resonance imaging; Gender; Intraparietal sulcus; logistic regression; machine learning; Magnetic resonance imaging; Males; Mathematical problems; Mathematics; Medical imaging; mental arithmetic; Neuroimaging; sex/gender effect; Young adults; fMRI; sex/gender effect; logistic regression; machine learning; mental arithmetic
• ISSN: 0953-816X; 1460-9568
• DOI: 10.1111/ejn.16100

Numerous empirical studies have reported that males and females perform equally well in mathematical achievement. However, still to date, very limited is understood about the brain response profiles that are particularly characteristic of males and females when solving mathematical problems. The present study aimed to tackle this issue by manipulating arithmetic problem size to investigate functional significance using functional magnetic resonance imaging (fMRI) in young adults. Participants were instructed to complete two runs of simple calculation tasks with either large or small problem sizes. Behavioural results suggested that the performance did not differ between females and males. Neuroimaging data revealed that sex/gender‐related patterns of problem size effect were found in the brain regions that are conventionally associated with arithmetic, including the left middle frontal gyrus (MFG), left intraparietal sulcus (IPS) and insula. Specifically, females demonstrated substantial brain responses of problem size effect in these regions, whereas males showed marginal effects. Moreover, the machine learning method implemented over the brain signal levels within these regions demonstrated that sex/gender is discriminable. These results showed sex/gender effects in the activating patterns varying as a function of the distinct math problem size, even in a simple calculation task. Accordingly, our findings suggested that females and males use two complementary brain resources to achieve equally successful performance levels and highlight the pivotal role of neuroimaging facilities in uncovering neural mechanisms that may not be behaviourally salient. In this fMRI study, we explore sex differences in brain activations during mathematical problem‐solving. Our findings elucidate discernible patterns of problem size effect within brain regions linked to arithmetic, with females displaying more pronounced responses than males. Machine learning analysis demonstrates the discriminability of sex based on brain signals from these regions, highlighting the complementary brain resources used by females and males to achieve comparable performance levels and emphasizing the importance of neuroimaging in uncovering underlying neural mechanisms.