Gender Similarities Dominate Mathematical Cognition at the Neural Level: A Japanese fMRI Study Using Advanced Wavelet Analysis and Generative AI

Tatsuru Kikuchi

Papers from arXiv.org

Abstract: Recent large scale behavioral studies suggest early emergence of gender differences in mathematical performance within months of school entry. However, these findings lack direct neural evidence and are constrained by cultural contexts. We conducted functional magnetic resonance imaging (fMRI) during mathematical tasks in Japanese participants (N = 156), employing an advanced wavelet time frequency analysis to examine dynamic brain processes rather than static activation patterns. Wavelet decomposition across four frequency bands (0.01-0.25 Hz) revealed that neural processing mechanisms underlying mathematical cognition are fundamentally similar between genders. Time frequency analysis demonstrated 89.1% similarity in dynamic activation patterns (p = 0.734, d = 0.05), with identical temporal sequences and frequency profiles during mathematical processing. Individual variation in neural dynamics exceeded group differences by 3.2:1 (p $

Date: 2025-07
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