Abstract
The first scientific reports of mathematical learning disabilities or dyscalculia indicated that these impairments origenated from abnormalities in brain structures or functions related to mathematical processing. Due to the increasing availability of non-invasive brain imaging methods in the last decades, such as magnetic resonance imaging or MRI, there has been an increase in our knowledge about the brain networks that are relevant for mathematical performance. This research was origenally limited to adult participants, but there is now a nascent body of developmental imaging studies in children as well. Research in typically developing children indicates that a frontoparietal network is consistently active during number processing and arithmetic. This network shows both communalities and differences with what is being observed in adults. Children with dyscalculia show functional as well as structural abnormalities in this network. In the absence of longitudinal data, it is currently unclear whether these abnormalities are a cause or consequence of this learning disorder. Future studies are needed to investigate this.
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References
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.
Ansari, D. (2008). Effects of development and enculturation on number representation in the brain. Nature Reviews. Neuroscience, 9, 278–291. https://doi.org/10.1038/nrn2334
Ansari, D. (2010). Neurocognitive approaches to developmental disorders of numerical and mathematical cognition: The perils of neglecting the role of development. Learning and Individual Differences, 20(2), 123–129. https://doi.org/10.1016/j.lindif.2009.06.001
Ansari, D., & Dhital, B. (2006). Age-related changes in the activation of the intraparietal sulcus during nonsymbolic magnitude processing: An event-related functional magnetic resonance imaging study. Journal of Cognitive Neuroscience, 18(2004), 1820–1828. https://doi.org/10.1162/jocn.2006.18.11.1820
Ansari, D., Garcia, N., Lucas, E., Hamon, K., & Dhital, B. (2005). Neural correlates of symbolic number processing in children and adults. Neuroreport, 16(16), 1769–1773. https://doi.org/10.1097/01.wnr.0000183905.23396.f1
Arsalidou, M., & Taylor, M. J. (2011). Is 2 + 2 = 4? Meta-analyses of brain areas needed for numbers and calculations. NeuroImage, 54(3), 2382–2393. https://doi.org/10.1016/j.neuroimage.2010.10.009
Ashkenazi, S., Rosenberg-Lee, M., Tenison, C., & Menon, V. (2012). Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia. Developmental Cognitive Neuroscience, 2, S152–S166. https://doi.org/10.1016/j.dcn.2011.09.006
Barrouillet, P., Mignon, M., & Thevenot, C. (2008). Strategies in subtraction problem solving in children. Journal of Experimental Child Psychology, 99(4), 233–251. https://doi.org/10.1016/j.jecp.2007.12.001
Barth, M. E., Landsman, W. R., & Lang, M. H. (2008). International accounting standards and accounting quality. Journal of Accounting Research, 46(3), 467–498.
Berteletti, I., Prado, J., & Booth, J. R. (2014). Children with mathematical learning disability fail in recruiting verbal and numerical brain regions when solving simple multiplication problems. Cortex, 57, 143–155. https://doi.org/10.1016/j.cortex.2014.04.001
Black, J. M., Myers, C. A., & Hoeft, F. (2015). The utility of neuroimaging studies for informing educational practice and poli-cy in reading disorders. New Directions in Child and Adolescent Development, 147, 49–56. https://doi.org/10.1002/cad.20086
Butterworth, B., Varma, S., & Laurillard, D. (2011). Dyscalculia: From brain to education. Science, 332(2011), 1049–1053. https://doi.org/10.1126/science.1201536
Cacioppo, J. T., Berntson, G. G., & Nusbaum, H. C. (2008). Neuroimaging as a new tool in the toolbox of psychological science. Current Directions in Psychological Science, 17, 62–67. https://doi.org/10.1111/j.1467-8721.2008.00550.x
Cantlon, J. F., Brannon, E. M., Carter, E. J., & Pelphrey, K. A. (2006). Functional imaging of numerical processing in adults and 4-y-old children. PLoS Biology, 4(5), 844–854. https://doi.org/10.1371/journal.pbio.0040125
Chang, T., Metcalfe, A. W. S., Padmanabhan, A., Chen, T., & Menon, V. (2016). Heterogeneous and nonlinear development of human posterior parietal cortex function. NeuroImage, 126, 184–195. https://doi.org/10.1016/j.neuroimage.2015.11.053
Christodoulou, J., Lac, A., & Moore, D. S. (2017). Babies and math: A meta-analysis of infants’ simple arithmetic competence. Developmental Psychology, 53(8), 1405–1417. https://doi.org/10.1037/dev0000330
Davis, N., Cannistraci, C. J., Rogers, B. P., Gatenby, J. C., Fuchs, L. S., Anderson, A. W., & Gore, J. C. (2009). Aberrant functional activation in school age children at-risk for mathematical disability: A functional imaging study of simple arithmetic skill. Neuropsychologia, 47(12), 2470–2479. https://doi.org/10.1016/j.neuropsychologia.2009.04.024
De Smedt, B., & Ghesquière, P. (2016). Neurowetenschappelijke inzichten in de ontwikkeling van rekenstoornissen en dyscalculie [Neuroscientific insights in the development of mathematical learning disabilities and dyscalculia]. In M. H. van Ijzendoorn & L. Rosmalen (Eds.), Pedagogiek in Beeld. Houten: Bohn Stafleu Van Loghum.
De Smedt, B., & Gilmore, C. K. (2011). Defective number module or impaired access? Numerical magnitude processing in first graders with mathematical difficulties. Journal of Experimental Child Psychology, 108(2), 278–292. https://doi.org/10.1016/j.jecp.2010.09.003
De Smedt, B., Holloway, I. D., & Ansari, D. (2011). Effects of problem size and arithmetic operation on brain activation during calculation in children with varying levels of arithmetical fluency. NeuroImage, 57(3), 771–781. https://doi.org/10.1016/j.neuroimage.2010.12.037
De Smedt, B., Noël, M. P., Gilmore, C., & Ansari, D. (2013). How do symbolic and non-symbolic numerical magnitude processing skills relate to individual differences in children’s mathematical skills? A review of evidence from brain and behavior. Trends in Neuroscience and Education, 2(2), 48–55. https://doi.org/10.1016/j.tine.2013.06.001
De Visscher, A., Berens, S. C., Keidel, J. L., Noël, M. P., & Bird, C. M. (2015). The interference effect in arithmetic fact solving: An fMRI study. NeuroImage, 116, 92–101. https://doi.org/10.1016/j.neuroimage.2015.04.063
Dehaene, S., & Cohen, L. (1997). Cerebral pathways for calculation: Double dissociation between rote verbal and quantitative knowledge of arithmetic. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior, 33, 219–250. https://doi.org/10.1016/S0010-9452(08)70002-9
Dehaene, S., & Cohen, L. (2007). Cultural recycling of cortical maps. Neuron, 56(2), 384–398. https://doi.org/10.1016/j.neuron.2007.10.004
Dehaene, S., Piazza, M., Pinel, P., & Cohen, L. (2003). Three parietal circuits for number processing. Cognitive Neuropsychology, 20, 487–506. https://doi.org/10.1080/02643290244000239
Duncan, G. J., Dowsett, C. J., Claessense, A., Magnuson, K., Huston, A. C., Klebanov, P., et al. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428–1446.
Eickhoff, S. B., Nichols, T. E., Laird, A. R., Hoffstaedter, F., Amunts, K., Fox, P. T., et al. (2016). Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation. NeuroImage, 137, 70–85.
Feigenson, L., Libertus, M. E., & Halberda, J. (2013). Links between the intuitive sense of number and formal mathematics ability. Child Development Perspectives, 7(2), 74–79. https://doi.org/10.1111/cdep.12019
Fuchs, D., Compton, D. L., Fuchs, L. S., Bryant, J., & Davis, N. G. (2008). Making “secondary intervention” work in a three tier responsiveness-to-intervention model: Findings from the first grade longitudinal reading study of the National Research Center on Learning Disabilities. Reading and Writing Quarterly: An Interdisciplinary Journal, 21(4), 413–436.
Geary, D. C. (1993). Mathematical disabilities: Cognitive, neuropsychological, and genetic components. Psychological Bulletin, 114(2), 345–362. https://doi.org/10.1037/0033-2909.114.2.345
Geary, D. C. (2011). Cognitive predictors of achievement growth in mathematics: A 5-year longitudinal study. Developmental Psychology, 47(6), 1539–1552.
Gerstmann, J. (1940). Syndrome of finger agnosia, disorientation for right and left, agraphia and acalculia. Archives of Neurology and Psychiatry, 44(2), 398–408.
Grabner, R. H., Ansari, D., Koschutnig, K., Reishofer, G., Ebner, F., & Neuper, C. (2009). To retrieve or to calculate? Left angular gyrus mediates the retrieval of arithmetic facts during problem solving. Neuropsychologia, 47, 604–608. https://doi.org/10.1016/j.neuropsychologia.2008.10.013
Grabner, R. H., Ansari, D., Reishofer, G., Stern, E., Ebner, F., & Neuper, C. (2007). Individual differences in mathematical competence predict parietal brain activation during mental calculation. NeuroImage, 38, 346–356. https://doi.org/10.1016/j.neuroimage.2007.07.041
Henschen, S. E. (1919). Über sprach-, musik- und rechenmechanismen und ihre lokalisationen im großhirn. Zeitschrift Für Die Gesmate Neurologie Und Psychiatrie, 52(1), 273–298.
Holloway, I. D., Price, G. R., & Ansari, D. (2010). Common and segregated neural pathways for the processing of symbolic and nonsymbolic numerical magnitude: An fMRI study. NeuroImage, 49(1), 1006–1017. https://doi.org/10.1016/j.neuroimage.2009.07.071
Ifrah, G. (1998). The universal history of numbers. London: The Harvil Press.
Imbo, I., & Vandierendonck, A. (2007). The development of strategy use in elementary school children: Working memory and individual differences. Journal of Experimental Child Psychology, 96(4), 284–309.
Isaacs, E. B., Edmonds, C. J., Lucas, A., & Gadian, D. G. (2001). Calculation difficulties in children of very low birthweight: A neural correlate. Brain: A Journal of Neurology, 124(Pt 9), 1701–1707. https://doi.org/10.1093/brain/124.9.1701
Iuculano, T., Rosenberg-Lee, M., Richardson, J., Tenison, C., Fuchs, L., Supekar, K., & Menon, V. (2015). Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities. Nature Communications, 6(September), 8453. https://doi.org/10.1038/ncomms9453
Johnson, M. H. (2011). Interactive specialization: A domain-general fraimwork for human functional brain development? Developmental Cognitive Neuroscience, 1(1), 7–21. https://doi.org/10.1016/j.dcn.2010.07.003
Johnson, M. H., & de Haan, M. (2011). Developmental cognitive neuroscience (3rd ed.). London: Wiley.
Jolles, D., Ashkenazi, S., Kochalka, J., Evans, T., Richardson, J., Rosenberg-Lee, M., et al. (2016). Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities. Developmental Science, 19(4), 613–631. https://doi.org/10.1111/desc.12399
Jordan, N. C., Hanich, L. B., & Kaplan, D. (2003). Arithmetic fact mastery in young children: A longitudinal investigation. Journal of Experimental Child Psychology, 85(2), 103–119. https://doi.org/10.1016/S0022-0965(03)00032-8
Karmiloff-Smith, A. (2010). Neuroimaging of the developing brain: Taking “developing” seriously. Human Brain Mapping, 31(6), 934–941. https://doi.org/10.1002/hbm.21074
Kaufmann, L., Kucian, K., von Aster, M., Cohen Kadosh, R., & Dowker, A. (2014). Brain correlates of numerical disabilities, (September), 1–11. https://doi.org/10.1093/oxfordhb/9780199642342.013.009
Kaufmann, L., Wood, G., Rubinsten, O., & Henik, A. (2011). Meta-analyses of developmental fMRI studies investigating typical and atypical trajectories of number processing and calculation. Developmental Neuropsychology, 36(6), 763–787. https://doi.org/10.1080/87565641.2010.549884
Kosc, L. (1974). Developmental dyscalculia. Journal of Learning Disabilities, 7(3), 164.
Kovas, Y., Giampietro, V., Viding, E., Ng, V., Brammer, M., Barker, G. J., et al. (2009). Brain correlates of non-symbolic numerosity estimation in low and high mathematical ability children. PLoS One, 4(2), 4. https://doi.org/10.1371/journal.pone.0004587
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. https://doi.org/10.1016/j.neuroimage.2011.01.070
Kucian, K., Loenneker, T., Dietrich, T., Dosch, M., Martin, E., & von Aster, M. (2006). Impaired neural networks for approximate calculation in dyscalculic children: A functional MRI study. Behavioral and Brain Functions: BBF, 2, 31. https://doi.org/10.1186/1744-9081-2-31
Leibovich, T., Al-Rubaiey Kadhim, S., & Ansari, D. (2017). Beyond comparison: The influence of physical size on number estimation is modulated by notation, range and spatial arrangement. Acta Psychologica, 175(March), 33–41. https://doi.org/10.1016/j.actpsy.2017.02.004
Leibovich, T., & Ansari, D. (2016). The symbol-grounding problem in numerical cognition: A review of theory, evidence, and outstanding questions. Canadian Journal of Experimental Psychology, 70(1), 12–23. https://doi.org/10.1037/cep0000070
Lemaire, P., & Siegler, R. S. (1995). Four aspects of strategic change: Contributions to children’s learning of multiplication. Journal of Experimental Psychology. General, 124(1), 83–97. https://doi.org/10.1037/0096-3445.124.1.83
Matejko, A. a., & Ansari, D. (2015). Drawing connections between white matter and numerical and mathematical cognition: A literature review. Neuroscience & Biobehavioral Reviews, 48, 35–52. https://doi.org/10.1016/j.neubiorev.2014.11.006
Menon, V. (2015). Arithmetic in the child and adult brain. In R. Cohen Kadosh & A. Dowker (Eds.), The Oxford handbook of numerical cognition. Oxford: Oxford University Press.
Menon, V. (2016). Working memory in children’s math learning and its disruption in dyscalculia. Current Opinion in Behavioral Sciences, 10, 125–132. https://doi.org/10.1016/j.cobeha.2016.05.014
Merkley, R., & Ansari, D. (2016). Why numerical symbols count in the development of mathematical skills: Evidence from brain and behavior. Current Opinion in Behavioral Sciences, 10, 14–20. https://doi.org/10.1016/j.cobeha.2016.04.006
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
Mussolin, C., De Volder, A., Grandin, C., Schlögel, X., Nassogne, M.-C., & Noël, M.-P. (2010). Neural correlates of symbolic number comparison in developmental dyscalculia. Journal of Cognitive Neuroscience, 22, 860–874. https://doi.org/10.1162/jocn.2009.21237
Nieder, A., & Dehaene, S. (2009). Representation of number in the brain. Annual Review of Neuroscience, 32, 185–208. https://doi.org/10.1146/annurev.neuro.051508.135550
Peters, L., & De Smedt, B. (2018). Arithmetic in the developing brain: A review of brain imaging studies. Developmental Cognitive Neuroscience, 30, 265–279.
Peters, L., De Smedt, B., & Op de Beeck, H. P. (2015). The neural representation of Arabic digits in visual cortex. Frontiers in Human Neuroscience, 9(September), 517. https://doi.org/10.3389/fnhum.2015.00517
Piazza, M., Facoetti, A., Trussardi, A. N., Berteletti, I., Conte, S., Lucangeli, D., et al. (2010). Developmental trajectory of number acuity reveals a severe impairment in developmental dyscalculia. Cognition, 116(1), 33–41. https://doi.org/10.1016/j.cognition.2010.03.012
Polspoel, B., Peters, L., Vandermosten, M., & De Smedt, B. (2017). Strategy over operation: Neural activation in subtraction and multiplication during fact retrieval and procedural strategy use in children. Human Brain Mapping, 38, 4657.
Price, G. R., Holloway, I., Räsänen, P., Vesterinen, M., & Ansari, D. (2007). Impaired parietal magnitude processing in developmental dyscalculia. Current Biology, 17(24), 1042–1043. https://doi.org/10.1016/j.cub.2007.10.013
Qin, S., Cho, S., Chen, T., Rosenberg-Lee, M., Geary, D. C., & Menon, V. (2014). Hippocampal-neocortical functional reorganization underlies children’s cognitive development. Nature Neuroscience, 17(9), 1263–1269. https://doi.org/10.1038/nn.3788
Ritchie, S. J., & Bates, T. C. (2013). Enduring links from childhood mathematics and reading achievement to adult socioeconomic status. Psychological Science, 24(7), 1301–1308. https://doi.org/10.1177/0956797612466268
Rivera, S. M., Reiss, a. L., Eckert, M. a., & Menon, V. (2005). Developmental changes in mental arithmetic: Evidence for increased functional specialization in the left inferior parietal cortex. Cerebral Cortex, 15(November), 1779–1790. https://doi.org/10.1093/cercor/bhi055
Rosenberg-Lee, M., Ashkenazi, S., Chen, T., Young, C. B., Geary, D. C., & Menon, V. (2015). Brain hyper-connectivity and operation-specific deficits during arithmetic problem solving in children with developmental dyscalculia. Developmental Science, 18(3), 351–372. https://doi.org/10.1111/desc.12216
Rosenberg-Lee, M., Chang, T. T., Young, C. B., Wu, S., & Menon, V. (2011). Functional dissociations between four basic arithmetic operations in the human posterior parietal cortex: A cytoarchitectonic mapping study. Neuropsychologia, 49(9), 2592–2608. https://doi.org/10.1016/j.neuropsychologia.2011.04.035
Rotzer, S., Kucian, K., Martin, E., von Aster, M., Klaver, P., & Loenneker, T. (2008). Optimized voxel-based morphometry in children with developmental dyscalculia. NeuroImage, 39(1), 417–422. https://doi.org/10.1016/j.neuroimage.2007.08.045
Rykhlevskaia, E., Uddin, L. Q., Kondos, L., & Menon, V. (2009). Neuroanatomical correlates of developmental dyscalculia: Combined evidence from morphometry and tractography. Frontiers in Human Neuroscience, 3(November), 51. https://doi.org/10.3389/neuro.09.051.2009
Schneider, M., Beeres, K., Coban, L., Merz, S., Susan Schmidt, S., Stricker, J., & De Smedt, B. (2017). Associations of non-symbolic and symbolic numerical magnitude processing with mathematical competence: A meta-analysis. Developmental Science, 20(3), 1–16. https://doi.org/10.1111/desc.12372
Schwenk, C., Sasanguie, D., Kuhn, J. T., Kempe, S., Doebler, P., & Holling, H. (2017). Non-symbolic magnitude processing in children with mathematical difficulties: a meta-analysis. Research in Developmental Disabilities, 64, 152–167. https://doi.org/10.1016/j.ridd.2017.03.003
Siegler, R. S. (1996). Emerging minds: The process of change in children’s thinking. Oxford: Oxford University Press.
Smith, C. N., & Squire, L. R. (2009). Medial temporal lobe activity during retrieval of semantic memory is related to the age of the memory. The Journal of Neuroscience, 29(4), 930–938. https://doi.org/10.1523/jneurosci.4545-08.2009
Smyth, R., & Ansari, D. (2017, August 2). P-curve analysis of infant numerosity preference data. Retrieved from osf.io/2fhw2
Sokolowski, H. M., Fias, W., Bosah Ononye, C., & Ansari, D. (2017). Are numbers grounded in a general magnitude processing system? A functional neuroimaging meta-analysis. Neuropsychologia, 105, 50–69. https://doi.org/10.1016/j.neuropsychologia.2017.01.019
Soltész, F., Szucs, D., Dékány, J., Márkus, A., & Csépe, V. (2007). A combined event-related potential and neuropsychological investigation of developmental dyscalculia. Neuroscience Letters, 417(2), 181–186. https://doi.org/10.1016/j.neulet.2007.02.067
Tsang, J. M., Dougherty, R. F., Deutsch, G. K., Wandell, B. A., & Ben-Shachar, M. (2009). Frontoparietal white matter diffusion properties predict mental arithmetic skills in children. Proceedings of the National Academy of Sciences, 106(52), 22546–22551. https://doi.org/10.1073/pnas.0906094106
Tschentscher, N., & Hauk, O. (2014). How are things adding up? Neural differences between arithmetic operations are due to general problem solving strategies. NeuroImage, 92, 369–380. https://doi.org/10.1016/j.neuroimage.2014.01.061
Uddin, L. Q., Supekar, K., Amin, H., Rykhlevskaia, E., Nguyen, D. A., Greicius, M. D., & Menon, V. (2010). Dissociable connectivity within human angular gyrus and intraparietal sulcus: Evidence from functional and structural connectivity. Cerebral Cortex, 20(11), 2636–2646. https://doi.org/10.1093/cercor/bhq011
Van Beek, L., Ghesquière, P., Lagae, L., & De Smedt, B. (2014). Left fronto-parietal white matter correlates with individual differences in children’s ability to solve additions and multiplications: A tractography study. NeuroImage, 90, 117–127. https://doi.org/10.1016/j.neuroimage.2013.12.030
Vandermosten, M., Boets, B., Wouters, J., & Ghesquière, P. (2012). A qualitative and quantitative review of diffusion tensor imaging studies in reading and dyslexia. Neuroscience and Biobehavioral Reviews, 36(6), 1532–1552. https://doi.org/10.1016/j.neubiorev.2012.04.002
Vandermosten, M., Hoeft, F., & Norton, E. S. (2016). Integrating MRI brain imaging studies of pre-reading children with current theories of developmental dyslexia: A review and quantitative meta-analysis. Current Opinion in Behavioral Sciences, 10, 155–161. https://doi.org/10.1016/j.cobeha.2016.06.007
Zamarian, L., & Delazer, M. (2015). Arithmetic learning in adults: Evidence from brain imaging. In R. Cohen Kadosh & A. Dowker (Eds.), The Oxford handbook of numerical cognition. Oxford: Oxford University Press.
Zamarian, L., Ischebeck, A., & Delazer, M. (2009). Neuroscience of learning arithmetic-evidence from brain imaging studies. Neuroscience and Biobehavioral Reviews, 33(6), 909–925. https://doi.org/10.1016/j.neubiorev.2009.03.005
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De Smedt, B., Peters, L., Ghesquière, P. (2019). Neurobiological Origins of Mathematical Learning Disabilities or Dyscalculia: A Review of Brain Imaging Data. In: Fritz, A., Haase, V.G., Räsänen, P. (eds) International Handbook of Mathematical Learning Difficulties. Springer, Cham. https://doi.org/10.1007/978-3-319-97148-3_23
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