Research Overview

My research investigates the neural mechanisms underlying mathematical thinking, with particular emphasis on numerical cognition and fraction processing. I use advanced electrophysiological methods (EEG/ERP) combined with behavioral experiments to understand how the brain processes mathematical information.

Research Questions

How does the brain represent and process numerical information? What neural mechanisms underlie mathematical learning difficulties? How can neuroscientific findings inform mathematics education?

Current Projects

Multivariate EEG Decoding of Fraction Processing

Understanding how people access fraction magnitude is crucial for mathematics education, as fractions represent a fundamental gateway to higher-level mathematical concepts. This project applies cross-generalization decoding techniques to test whether neural representations of fraction magnitude are abstract or tied to specific surface forms. We examine whether brain patterns learned from one fraction notation (e.g., 2/4) can successfully predict equivalent fractions in different forms (e.g., 3/6, 4/8).

Equation-Graph Semantic Violation Experiment

This research investigates whether mathematical equation-graph mismatches trigger the same N400 neural signature (~400ms post-stimulus) as traditional language-based semantic violations. Participants view linear equations followed by coordinate graphs and judge whether they match. This extends N400 studies from linguistic to mathematical domains, testing whether semantic processing mechanisms are domain-general or domain-specific.

Research Methods

  • EEG/ERP: Recording brain electrical activity during mathematical tasks
  • Multivariate Pattern Analysis: Advanced decoding techniques for neural data
  • Cross-generalization Decoding: Testing abstract vs. specific neural representations
  • Behavioral Experiments: Measuring reaction times and accuracy in mathematical tasks

Research Impact

This work has implications for:

  • Educational Practice: Informing mathematics curriculum and teaching methods
  • Learning Disabilities: Understanding neural basis of mathematical difficulties
  • Cognitive Theory: Advancing models of numerical cognition and semantic processing

For Prospective Students

Undergraduate research opportunities are available in the lab. Students gain experience in:

  • EEG data collection and analysis
  • Experimental design and programming
  • Statistical analysis and scientific writing
  • Conference presentations and publication

For Faculty and Collaborators

My research program combines rigorous neuroscientific methods with educationally relevant questions. I welcome collaborations in educational neuroscience, cognitive psychology, mathematics education, and developmental science.

For detailed information about current lab activities, team members, and resources, visit the Lab page.