Systematic survey of neurocognitive studies that examine connections between domain-general cognitive characteristics and mathematical processing

Abstract This systematic survey examines neurocognitive research on connections between mathematical processing and domain-general cognitive characteristics. From 1,798 initially identified papers, 83 studies met all inclusion criteria. We conducted a bibliometric analysis of temporal publication trends and leading journals, followed by a three-dimensional content analysis examining neurocognitive tools, mathematical characteristics, and domain-general cognitive characteristics across research designs, participant age groups, mathematical domains, and major findings. Analysis reveals predominant reliance on MRI (60%) and EEG (31%), with within-group mathematical task designs (70%) and between-group cognitive comparisons (60%) dominating approaches. Studies mainly focus on primary-school children (43%) and university students (39%), examining mostly arithmetic (63%) and number sense (33%). Critical gaps include underrepresentation of mid-to-high school students, limited investigation of mathematical abilities along the continuum, minimal use of advanced statistical methods, and infrequent separate neurocognitive assessment of cognitive processes. Seven key themes emerge from this research synthesis. First, developmental trajectories reveal qualitative neural reorganization rather than mere skill accumulation. Second, neural efficiency in high-performing students proves task-dependent. Third, working memory systems show distinct relevance for different mathematical processes. Fourth, domain-general and domain-specific mechanisms interact dynamically throughout child development. Fifth, different mathematical domains engage distinct neural mechanisms, suggesting differentiated instructional approaches. Sixth, objective neural indices reveal cognitive load as whole-brain resource competition. Seventh, exact arithmetic relies on language-dependent systems while approximate calculation employs language-independent magnitude processing. These findings demonstrate neuroscience’s potential for early identification of learning trajectories, precise diagnosis of processing difficulties, and evidence-based instructional differentiation - insights unattainable through behavioral observation alone.