Gender Differences in Neural Decision-Making: Cognitive Mechanisms, Educational Implications, and the Role of AI

Abstract

This narrative review synthesises evidence on gender-specific neurocognitive mechanisms underlying decision-making, emotional processing, and learning, and examines how AI-driven analyses can enhance personalised interventions. Drawing on EEG, fMRI, MEG, ERP, and eye-tracking studies, we show that women preferentially engage medial prefrontal and limbic networks, during semantic-relational and emotional tasks, whereas men recruit parietal-occipital circuits for visuospatial processing. Cultural context further shapes these patterns. AI applications, such as machine learning classifiers on neurophysiological data, improve the accuracy of gender-informed predictions, and support adaptive, neurodiversity-aware pedagogies. We conclude that integrating neuroscientific and AI insights can inform gender-sensitive educational design and decision-support systems, provided ethical safeguards against algorithmic bias and privacy breaches are in place.