, Volume 48, Issue 3, pp 379–383 | Cite as

Cognitive neuroscience and mathematics learning: how far have we come? Where do we need to go?

  • Daniel Ansari
  • Ian M. Lyons
Commentary Paper


In this commentary on the ZDM special issue: ‘Cognitive neuroscience and mathematics learning—revisited after 5 years’, we explore the progress that has been made since ZDM published a similar special issue in 2010. We consider the extent to which future frontiers and methodological concerns raised in the commentary on the 2010 issue by Grabner and Ansari have been addressed 5 years on. We identify areas of progress as well as issues that continue to require additional research and methodological innovation to make further progress. Finally, we discuss future directions that could lead to significant progress in the interdisciplinary crossroads between cognitive neuroscience and mathematics learning over the next 5 years.


Mathematics education Neuroscience Cognition Educational neuroscience 


  1. Ashcraft, M. H. (1995). Cognitive psychology and simple arithmetic: a review and summary of new directions. Mathematical Cognition, 1(1), 3–34.Google Scholar
  2. Babai, R., Nattiv, L., Stavy, R. (2016). Comparison of perimeters: improving students’ performance by increasing the salience of the relevant variable. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  3. Eden, G. F., Jones, K. M., Cappell, K., Gareau, L., Wood, F. B., Zeffiro, T. A., & Flowers, D. L. (2004). Neural changes following remediation in adult developmental dyslexia. Neuron, 44(3), 411–422. doi: 10.1016/j.neuron.2004.10.019.CrossRefGoogle Scholar
  4. Evans, T. M., Kochalka, J., Ngoon, T. J., Wu, S. S., Qin, S., Battista, C., & Menon, V. (2015). Brain structural integrity and intrinsic functional connectivity forecast 6 year longitudinal growth in children’s numerical abilities. Journal of Neuroscience, 35, 11743–11750.CrossRefGoogle Scholar
  5. Grabner R. H., & Ansari D. (2010). Promises and potential pitfalls of a ‘cognitive neuroscience of mathematics learning’. ZDM: the international journal on mathematics education, 42(6), 655–660.CrossRefGoogle Scholar
  6. Hoeft, Fumiko, McCandliss, B. D., Black, J. M., Gantman, A., Zakerani, N., Hulme, C., & Gabrieli, J. D. E. (2011). Neural systems predicting long-term outcome in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 108, 361–366. doi: 10.1073/pnas.1008950108.CrossRefGoogle Scholar
  7. Hoeft, F., Ueno, T., Reiss, A. L., Meyler, A., Whitfield-Gabrieli, S., Glover, G. H., & Gabrieli, J. D. (2007). Prediction of children’s reading skills using behavioral, functional, and structural neuroimaging measures. Behavioral Neuroscience, 121(3), 602–613.CrossRefGoogle Scholar
  8. Kucian, K., Grond, U., Rotzer, S., Henzi, B., Schönmann, C., Plangger, F., et al. (2011). Mental number line training in children with developmental dyscalculia. NeuroImage, 57(3), 782–795.CrossRefGoogle Scholar
  9. LeFevre, J. A., Sadesky, G. S., & Bisanz, J. (1996). Selection of procedures in mental addition: reassessing the problem size effect in adults. J Exp Psychol Learn Mem Cognit, 22(1), 216–230.CrossRefGoogle Scholar
  10. Leikin, R., Waisman, I., Leikin, M. (2016). Does solving insight-based problems differ from solving learning-based problems: some evidence from an ERP study. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  11. Logie, R. H., Gilhooly, K. J., & Wynn, V. (1994). Counting on working memory in arithmetic problem solving. Mem Cognit, 22(4), 395–410.CrossRefGoogle Scholar
  12. Merkley R, Shimi A, Scerif G (2016). Electrophysiological markers of newly acquired symbolic numerical representations: the role of magnitude and ordinal information. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  13. Obersteiner A, Tumpek C (2016). Measuring fraction comparison strategies with eye‑tracking. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  14. Poldrack, R. A. (2015). Is “efficiency” a useful concept in cognitive neuroscience? Developmental Cognitive Neuroscience, 11, 12–17.CrossRefGoogle Scholar
  15. Pollack C, Geurrero SL, Star JR (2016). Exploring mental representations for literal symbols using priming and comparison distance effects. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  16. Schillinger FL, De Smedt B, Grabner RH (2016). When errors count: an EEG study on numerical error monitoring under performance pressure. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  17. Shaywitz, B. A., Shaywitz, S. E., Blachman, B. A., Pugh, K. R., Fullbright, R. K., Skudlarski, P., & Gore, J. C. (2004). Development of left occipitotemporal systems for skilled reading in children after a phonologically- based intervention. Biological Psychiatry, 55(9), 926–933. doi: 10.1016/j.biopsych.2003.12.019.CrossRefGoogle Scholar
  18. Spüler, M., Walter, C., Rosenstiel, W., Gerjets, P., Moeller, K., Klein, E. (2016). EEG‑based prediction of cognitive workload induced by arithmetic: a step towards online adaptation in numerical learning. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  19. Supekar, K., Swigart, A. G., Tenison, C., Jolles, D. D., Rosenberg-Lee, M., Fuchs, L., & Menon, V. (2013). Neural predictors of individual differences in response to math tutoring in primary-grade school children. Proceedings of the National Academy of Sciences of the United States of America, 110(20), 8230–8235. doi: 10.1073/pnas.1222154110.CrossRefGoogle Scholar
  20. Vogel, S. E., Keller, C., Koschutnig, K., Reishofer, G., Ebner, F., Dohle, S., Siegrist, M., Grabner, R. H. (2016). The neural correlates of health risk perception in individuals with low and high numeracy. ZDM Mathematics Education, 48(3), this issue.Google Scholar
  21. Waisman, I., Leikin, M., Leikin, R. (2016). Brain activity associated with logical inferences in geometry: focusing on students with different levels of ability. ZDM Mathematics Education, 48(3), this issue.Google Scholar

Copyright information

© FIZ Karlsruhe 2016

Authors and Affiliations

  1. 1.Numerical Cognition Laboratory, Department of Psychology and Brain and Mind InstituteThe University of Western OntarioLondonCanada

Personalised recommendations