NEURAL CORRELATES OF NUMERICAL COGNITION IN GIFTED AND NON-GIFTED ADOLESCENTS: A MAGNETOENCEPHALOGRAPHY STUDY WITH IMPLICATIONS FOR NEUROPEDAGOGY

Tania Badarne, Mina Teicher

Abstract


The present study employs magnetoencephalography (MEG) to examine event-related potential (ERP) differences between gifted and non-gifted adolescents during mathematical tasks involving numerical enumeration and simple addition. Drawing on the framework of neuropedagogy — an emerging interdisciplinary field that bridges brain science, cognitive science, and educational practice — the research investigates which cortical regions are differentially activated when children engage with counting, enumeration, and digit identification. Forty-three participants aged 12 to 15 years were allocated to four groups defined by giftedness classification and sex. MEG data were preprocessed using Fieldtrip (MATLAB) and subjected to independent component analysis (ICA) for artifact removal; features extracted from region-of-interest (ROI)-averaged waveforms included peak amplitude, root mean square (RMS), mean absolute amplitude, peak latency, and spectral power across the alpha, beta, gamma, delta, and theta frequency bands. Group-level analyses using t-tests with false discovery rate (FDR) correction revealed that gifted children exhibited reliably higher occipital amplitude measures when all trials were pooled, a pattern that intensified specifically during addition (SUM) trials. Across both groups, digit identification consistently elicited greater oscillatory amplitude than addition — particularly in beta and gamma bands over parietal, frontal, and temporal ROIs — consistent with the lower computational demands of perceptual relative to arithmetic processing. By-digit analyses, treated as exploratory, suggested that larger digits (7 and 8) elicited greater neural effort than smaller ones, and that gifted children showed distinct occipital latency profiles for specific digits. These findings contribute to growing evidence that numerical cognition recruits differentially organized cortical networks in gifted learners and carry direct implications for evidence-based instructional design.

Keywords


neuropedagogy, magnetoencephalography, numerical cognition, gifted learners, event-related potentials, mathematical education, occipital cortex

Full Text:

PDF

References


Ansari, D., Smedt, B., & Grabner, R. H. (2011). Neuroeducation: A critical overview of an emerging field. Neuroethics, 5, 105–117. https://doi.org/10.1007/s12152-011-9119-3

Andres, M., Seron, X., & Olivier, E. (2007). Contribution of hand motor circuits to counting. Journal of Cognitive Neuroscience, 19(4), 563–576. https://doi.org/10.1162/jocn.2007.19.4.563

Bowers, J. S. (2016). The practical and principled problems with educational neuroscience. Psychological Review, 123(5), 600–612. http://dx.doi.org/10.1037/rev0000025

Brown, T. T., & Daly, A. J. (2016). Welcome to educational neuroscience. Educational Neuroscience. https://doi.org/10.1177/2377616116632069

Bruer, J. T. (1997). Education and the brain: A bridge too far. Educational Researcher, 26(8), 4–16. https://doi.org/10.3102/0013189X026008004

Butterworth, B. (2005). The development of arithmetical abilities. Journal of Child Psychology and Psychiatry, 46(2), 3–18. https://doi.org/10.1111/j.1469-7610.2004.00374.x

Chen, Y. H., Saby, J., Kuschner, E., Gaetz, W., Edgar, J. C., & Roberts, T. P. L. (2019). Magnetoencephalography and the infant brain. NeuroImage, 189, 445–458. https://doi.org/10.1016/j.neuroimage.2019.01.059

Cohen-Kadosh, R., Henik, A., Rubinsten, O., Mohr, H., Van-de-Ven, V., Zorzi, M., Hendler, T., Goebel, R., & Lioden, D. E. J. (2005). Are numbers special? The comparison systems of the human brain investigated by fMRI. Neuropsychologia, 43(9), 1238–1248. https://doi.org/10.1016/j.neuropsychologia.2004.12.017

Dubinsky, J. M., Guzey, S. S., Schwartz, M. S., Roehrig, G., MacNabb, C., Schmied, A., & Ellingson, C. (2019). Contributions of neuroscience knowledge to teachers and their practice. Neuroscientist, 25(5), 394–407. https://doi.org/10.1177/1073858419835447

Dubinsky, J. M., Roehrig, G., & Varma, S. (2013). Infusing neuroscience into teacher professional development. Educational Researcher, 42(6), 317–329. https://doi.org/10.3102/0013189X13499403

Friedman, I. A., Grobgeld, E., & Teichman-Weinberg, A. (2019). Imbuing education with brain research can improve teaching and enhance productive learning. Psychology, 10(02), 122–131. https://doi.org/10.4236/psych.2019.102010

Fuson, K. (1982). An analysis of the counting on solution procedure in addition. In T. Carpenter, J. Moser, & T. Romberg (Eds.), Addition and subtraction: A cognitive perspective (pp. 67–81). https://doi.org/10.4324/9781003046585-6

Fuson, K. (1992). Relationships between counting and cardinality from age 2 to age 8. In Pathways to Number (pp. 127–150). Retrieved from https://psycnet.apa.org/record/1992-97947-006

Gelman, R., & Gallistel, C. R. (1978). The child's understanding of number. Harvard University Press. Retrieved from https://books.google.ro/books/about/The_Child_s_Understanding_of_Number.html?id=YjhEBe129H0C&redir_esc=y

Ginsburg, H. P. (1997). Mathematics learning disabilities: A view from developmental psychology. Journal of Learning Disabilities, 30, 20–33. https://doi.org/10.1177/002221949703000102

Ginsburg, H. P., & Seo, H. P. (2004). Mathematics learning disabilities: A view from developmental psychology. Journal of Learning Disabilities, 30, 20–33. https://doi.org/10.1177/002221949703000102

Hook, C. J., & Farah, M. J. (2013). Neuroscience for educators: What are they seeking, and what are they finding? Neuroethics, 6(2), 331–341. https://doi.org/10.1007/s12152-012-9159-3

Howard-Jones, P. A. (2014). Neuroscience and education: Myths and messages. Nature Reviews Neuroscience, 15(12), 817–824. https://doi.org/10.1038/nrn3817

Johnsrude, I., & Hauk, O. (2005). Neuroimaging: techniques for examining human brain function. In N. Braisby (Ed.), Cognitive Psychology: A Methods Companion (pp. 105–137). Oxford University Press.

Luzzatto, E., & Rusu, A. S. (2019). Pre-service teachers' self-efficacy and attitudes regarding using motifs from neuroeducation in education and teaching. Educatia 21, (17), 41–48. https://doi.org/10.24193/ed21.2019.17.04

Mazzocco, M. M. M., & Thomson, R. E. (2005). Kindergarten predictors of math learning disability. Learning Disabilities Research and Practice, 20, 142–155. https://doi.org/10.1111/j.1540-5826.2005.00129.x

Michels, L., O'Gorman, R., & Kucian, K. (2018). Functional hyperconnectivity vanishes in children with developmental dyscalculia after numerical intervention. Developmental Cognitive Neuroscience, 30, 291–303. https://doi.org/10.1016/j.dcn.2017.03.005

Molko, N., Cachia, A., Rivière, D., Mangin, J., Bruandet, M., Le Bihan, D., Cohen, L., & Dehaene, S. (2003). Functional and structural alterations of the intraparietal sulcus in a developmental dyscalculia of genetic origin. Neuron, 40(4), 847–858. https://doi.org/10.1016/s0896-6273(03)00670-6

Naccache, L., & Dehaene, S. (2001). The priming method: Imaging unconscious repetition priming reveals an abstract representation of number in the parietal lobes. Cerebral Cortex, 11(10), 966–974. https://doi.org/10.1093/cercor/11.10.966

Papanicolaou, A. C. (1998). Fundamentals of functional brain imaging: A guide to the methods and their applications to psychology and behavioral neuroscience. Lisse, The Netherlands: Swets & Zeitlinger.

Papanicolaou, A. C., & Tarkka, I. M. (1996). Magnetoencephalography. In E. D. Bigler (Ed.), Neuroimaging I: Basic science (Human Brain Function series, pp. 161–163). Boston, MA: Springer. https://doi.org/10.1007/978-1-4899-1701-0_8

Resnick, L. B. (1989). Developing mathematical knowledge. American Psychologist, 44(2), 69–162. https://doi.org/10.1037/0003-066X.44.2.162

Rowley, H. A., & Roberts, T. P. L. (1995). < cite index="68-1">Functional localization by magnetoencephalography. Neuroimaging Clinics of North America, 5(4), 695–710..

Sato, M., Cattaneo, L., Rizzolatti, G., & Galles, V. (2007). Numbers within our hands: Modulation of corticospinal excitability of hand muscles during numerical judgment. Journal of Cognitive Neuroscience, 19(4), 684–693. https://doi.org/10.1162/jocn.2007.19.4.684

Sarrasin, J. B., et al. (2018). Effects of teaching the concept of neuroplasticity to induce a growth mindset on motivation, achievement, and brain activity: A meta-analysis. Trends in Neuroscience and Education, 12, 22–31. https://doi.org/10.1016/j.tine.2018.07.003

Serpati, L., & Loughan, A. R. (2012). Teacher perceptions of neuroeducation: A mixed methods survey of teachers in the United States. Mind, Brain, and Education, 174–176. https://doi.org/10.1111/j.1751-228X.2012.01153.x

Shuman, M., & Kanwisher, N. (2004). Numerical magnitude in the human parietal lobe: Tests of representational generality and domain specificity. Neuron, 44(4), 557–569. https://doi.org/10.1016/j.neuron.2004.10.008

Siegler, R. S., & Robinson, M. (1982). The development of numerical understanding. In H. W. Rees & L. P. Lipsitt (Eds.), Advances in child development and behavior (Vol. 16). Academic Press. Retrieved from https://books.google.com.bo/books?id=Z89JAQAACAAJ&source=gbs_book_other_versions_r&cad=3

Stabio, J. B., & Feiler, M. E. (2018). Three pillars of educational neuroscience from three decades of literature. Trends in Neuroscience and Education, 13, 17–25. https://doi.org/10.1016/j.tine.2018.11.001

Starkey, P., Spelke, E. S., & Gelman, R. (1990). Numerical abstraction by human infants. Cognition, 36, 97–127. https://doi.org/10.1016/0010-0277(90)90001-z

Temple, E., & Posner, M. I. (1998). Brain mechanisms of quantity are similar in 5-year-old children and adults. Proceedings of the National Academy of Sciences USA, 95(13), 7836–7841. https://doi.org/10.1073/pnas.95.13.7836

Thomas, M. S. C., Ansary, D., & Knowland, V. C. P. (2019). Annual research review: Education neuroscience – progress and prospects. Journal of Child Psychology and Psychiatry, 60(4), 477–492. https://doi.org/10.1111/jcpp.12973

Zur, O., & Gelman, R. (2004). Young children can add and subtract by predicting and checking. Early Childhood Research Quarterly, 19, 121–137. https://doi.org/10.1016/j.ecresq.2004.01.003




DOI: http://dx.doi.org/10.46827/ejes.v13i9.6961

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Tania Badarne, Mina Teicher

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2015-2026. European Journal of Education Studies (ISSN 2501 - 1111) is a registered trademark of Open Access Publishing Group. All rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library (Biblioteca Nationala a Romaniei). All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All authors who send their manuscripts to this journal and whose articles are published on this journal retain full copyright of their articles. All the research works published on this journal are meeting the Open Access Publishing requirements and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License (CC BY 4.0).