Oscillatory EEG Changes During Arithmetic Learning in Children

References

• Ansari, D., & Lyons, I. M. (2016). Cognitive neuroscience and mathematics learning: How far have we come? Where do we need to go? ZDM, 48(3), 379–383.
   Google Scholar
• Antonenko, P., Paas, F., Grabner, R., & van Gog, T. (2010). Using electroencephalography to measure cognitive load. Educational Psychology Review, 22(4), 425–438.
   Web of Science ®Google Scholar
• Arsalidou, M., Pawliw-Levac, M., Sadeghi, M., & Pascual-Leone, J. (2018). Brain areas associated with numbers and calculations in children: Meta-analyses of fMRI studies. Developmental Cognitive Neuroscience, 30, 239–250.
   PubMed Web of Science ®Google Scholar
• Artemenko, C., Soltanlou, M., Dresler, T., Ehlis, A.-C., & Nuerk, H.-C. (2018). The neural correlates of arithmetic difficulty depend on mathematical ability: Evidence from combined fNIRS and ERP. Brain structure and function, 223(6), 2561–2574.
   PubMed Web of Science ®Google Scholar
• Baroody, A. J. (1983). The development of procedural knowledge: An alternative explanation for chronometric trends of mental arithmetic. Developmental Review, 3(2), 225–230.
   Web of Science ®Google Scholar
• Bäuml, K.-H., Pastötter, B., & Hanslmayr, S. (2010). Binding and inhibition in episodic memory—Cognitive, emotional, and neural processes. Neuroscience & Biobehavioral Reviews, 34(7), 1047–1054.
   PubMed Web of Science ®Google Scholar
• Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57, 289–300.
   Google Scholar
• Bloechle, J., Huber, S., Bahnmueller, J., Rennig, J., Willmes, K., Cavdaroglu, S., … Klein, E. (2016). Fact learning in complex arithmetic—The role of the angular gyrus revisited. Human Brain Mapping, 37(9), 3061–3079.
   PubMed Web of Science ®Google Scholar
• Davidson, R. J., Jackson, D. C., & Larson, C. L. (2000). Human electroencephalography. In Handbook of Psychophysiology, eds. Cacioppo, J. T., Tassinary, L. G., & Berntson, G. G. (pp. 27–52). New York, NY, US: Cambridge University Press.
   Google Scholar
• De Smedt, B., Grabner, R. H., & Studer, B. (2009). Oscillatory EEG correlates of arithmetic strategy use in addition and subtraction. Experimental Brain Research, 195(4), 635–642.
   PubMed Web of Science ®Google Scholar
• Dimitriadis, S. I., Laskaris, N. A., & Micheloyannis, S. (2015). Transition dynamics of EEG-based network microstates during mental arithmetic and resting wakefulness reflects task-related modulations and developmental changes. Cognitive Neurodynamics, 9(4), 371–387.
   PubMed Web of Science ®Google Scholar
• Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U., Church, J. A., Miezin, F. M., … Petersen, S. E. (2009). Functional brain networks develop from a “local to distributed” organization. PLoS Computational Biology, 5(5), e1000381.
   PubMed Web of Science ®Google Scholar
• Fias, W. (1996). The importance of magnitude information in numerical processing: Evidence from the SNARC effect. Mathematical Cognition, 2(1), 95–110.
   Google Scholar
• Fischer, S., Wilhelm, I., & Born, J. (2007). Developmental differences in sleep’s role for implicit off-line learning: Comparing children with adults. Journal of Cognitive Neuroscience, 19(2), 214–227.
   PubMed Web of Science ®Google Scholar
• Galfano, G., Penolazzi, B., Fardo, F., Dhooge, E., Angrilli, A., & Umiltà, C. (2011). Neurophysiological markers of retrieval‐induced forgetting in multiplication fact retrieval. Psychophysiology, 48(12), 1681–1691.
   PubMed Web of Science ®Google Scholar
• Gevins, A., Smith, M. E., McEvoy, L., & Yu, D. (1997). High-resolution EEG mapping of cortical activation related to working memory: Effects of task difficulty, type of processing, and practice. Cerebral Cortex, 7(4), 374–385.
   PubMed Web of Science ®Google Scholar
• Grabner, R. H., & De Smedt, B. (2011). Neurophysiological evidence for the validity of verbal strategy reports in mental arithmetic. Biological Psychology, 87(1), 128–136.
   PubMed Web of Science ®Google Scholar
• Grabner, R. H., & De Smedt, B. (2012). Oscillatory EEG correlates of arithmetic strategies: A training study. Frontiers in Psychology, 3, 428.
   PubMed Web of Science ®Google Scholar
• Harmony, T. A., Fernández, T. A., Silva, J., Bosch, J., Valdés, P., Fernández-Bouzas, A., … Rodrı́guez, D. (1999). Do specific EEG frequencies indicate different processes during mental calculation? Neuroscience Letters, 266(1), 25–28.
   PubMed Web of Science ®Google Scholar
• Hinault, T., & Lemaire, P. (2016). What does EEG tell us about arithmetic strategies? A review. International Journal of Psychophysiology, 106, 115–126.
   PubMed Web of Science ®Google Scholar
• Huber, S., Fischer, U., Moeller, K., & Nuerk, H.-C. (2013). On the interrelation of multiplication and division in secondary school children. Frontiers in Psychology, 4, 740.
   Web of Science ®Google Scholar
• Ischebeck, A., Zamarian, L., Egger, K., Schocke, M., & Delazer, M. (2007). Imaging early practice effects in arithmetic. Neuroimage, 36(3), 993–1003.
   PubMed Web of Science ®Google Scholar
• Ishihara, T., & Yoshii, N. (1972). Multivariate analytic study of EEG and mental activity in juvenile delinquents. Electroencephalography and Clinical Neurophysiology, 33(1), 71–80.
   PubMedGoogle Scholar
• Ishii, R., Canuet, L., Ishihara, T., Aoki, Y., Ikeda, S., Hata, M., … Nakahachi, T. (2014). Frontal midline theta rhythm and gamma power changes during focused attention on mental calculation: An MEG beamformer analysis. Frontiers in Human Neuroscience, 8, 406.
   PubMed Web of Science ®Google Scholar
• Jasper, H. H. (1958). The ten twenty electrode system of the international federation. Electroencephalography and Clinical Neurophysiology, 10, 371–375.
   Google Scholar
• Jensen, O., & Tesche, C. D. (2002). Frontal theta activity in humans increases with memory load in a working memory task. The European Journal of Neuroscience, 15(8), 1395–1399.
   PubMed Web of Science ®Google Scholar
• Kim, J. W., Kim, B. N., Lee, J., Na, C., Kee, B. S., Min, K. J., … Lee, Y. S. (2016). Desynchronization of theta-phase gamma-amplitude coupling during a mental arithmetic task in children with attention deficit/hyperactivity disorder. PloS one, 11(3), e0145288.
   PubMed Web of Science ®Google Scholar
• Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2), 169–195.
   PubMedGoogle Scholar
• Klimesch, W., Vogt, F., & Doppelmayr, M. (1999). Interindividual differences in alpha and theta power reflect memory performance. Intelligence, 27(4), 347–362.
   Web of Science ®Google Scholar
• Lee, H., Simpson, G. V., Logothetis, N. K., & Rainer, G. (2005). Phase locking of single neuron activity to theta oscillations during working memory in monkey extrastriate visual cortex. Neuron, 45(1), 147–156.
   PubMed Web of Science ®Google Scholar
• Lemaire, P. (2010). Cognitive strategy variations during aging. Current Directions in Psychological Science, 19(6), 363–369.
   Web of Science ®Google Scholar
• Lorch, R. F., & Myers, J. L. (1990). Regression analyses of repeated measures data in cognitive research. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 149–157.
   PubMed Web of Science ®Google Scholar
• Menon, V. (2010). Developmental cognitive neuroscience of arithmetic: Implications for learning and education. ZDM, 42(6), 515–525.
   PubMedGoogle Scholar
• Micheloyannis, S., Sakkalis, V., Vourkas, M., Stam, C. J., & Simos, P. G. (2005). Neural networks involved in mathematical thinking: Evidence from linear and non-linear analysis of electroencephalographic activity. Neuroscience Letters, 373(3), 212–217.
   PubMed Web of Science ®Google Scholar
• Micheloyannis, S., Vourkas, M., Tsirka, V., Karakonstantaki, E., Kanatsouli, K., & Stam, C. J. (2009). The influence of ageing on complex brain networks: A graph theoretical analysis. Human Brain Mapping, 30(1), 200–208.
   PubMed Web of Science ®Google Scholar
• Mizuhara, H., Wang, L.-Q., Kobayashi, K., & Yamaguchi, Y. (2004). A long-range cortical network emerging with theta oscillation in a mental task. Neuroreport, 15(8), 1233–1238.
   PubMed Web of Science ®Google Scholar
• Mizuhara, H., & Yamaguchi, Y. (2007). Human cortical circuits for central executive function emerge by theta phase synchronization. Neuroimage, 36(1), 232–244.
   PubMed Web of Science ®Google Scholar
• Nuerk, H.-C., Weger, U., & Willmes, K. (2001). Decade breaks in the mental number line? Putting the tens and units back in different bins. Cognition, 82(1), B25–B33.
   PubMed Web of Science ®Google Scholar
• Núñez-Peña, M. I., & Suárez-Pellicioni, M. (2012). Processing false solutions in additions: Differences between high-and lower-skilled arithmetic problem-solvers. Experimental Brain Research, 218(4), 655–663.
   PubMed Web of Science ®Google Scholar
• Oostenveld, R., & Praamstra, P. (2001). The five percent electrode system for high-resolution EEG and ERP measurements. Clinical Neurophysiology, 112(4), 713–719.
   PubMed Web of Science ®Google Scholar
• Petermann, F., Petermann, U., & Wechsler, D. (2007). Hamburg-Wechsler-Intelligenztest für Kinder-IV: HAWIK-IV. Bern: Huber.
   Google Scholar
• Peters, L., & De Smedt, B. (2018). Arithmetic in the developing brain: A review of brain imaging studies. Developmental Cognitive Neuroscience, 30, 265–279.
   PubMed Web of Science ®Google Scholar
• Pfurtscheller, G. (2001). Functional brain imaging based on ERD/ERS. Vision Research, 41(10), 1257–1260.
   PubMed Web of Science ®Google Scholar
• Pfurtscheller, G., & Da Silva, F. L. (1999). Event-related EEG/MEG synchronization and desynchronization: Basic principles. Clinical Neurophysiology, 110(11), 1842–1857.
   PubMed Web of Science ®Google Scholar
• Prado, J., Mutreja, R., & Booth, J. R. (2014). Developmental dissociation in the neural responses to simple multiplication and subtraction problems. Developmental Science, 17(4), 537–552.
   PubMed Web of Science ®Google Scholar
• Rocha, F. T., Rocha, A. F., Massad, E., & Menezes, R. (2005). Brain mappings of the arithmetic processing in children and adults. Cognitive Brain Research, 22(3), 359–372.
   PubMedGoogle Scholar
• Roediger, H. L., Dudai, Y., & Fitzpatrick, S. M. (2007). Science of memory: Concepts. New York, NY: Oxford University Press.
   Google Scholar
• RStudio Team (2016). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA, URL http://www.rstudio.com/.
   Google Scholar
• Sammer, G., Blecker, C., Gebhardt, H., Bischoff, M., Stark, R., Morgen, K., & Vaitl, D. (2007). Relationship between regional hemodynamic activity and simultaneously recorded EEG‐theta associated with mental arithmetic‐induced workload. Human Brain Mapping, 28(8), 793–803.
   PubMed Web of Science ®Google Scholar
• Sekeres, M. J., Moscovitch, M., & Winocur, G. (2017). Mechanisms of Memory Consolidation and Transformation. In Cognitive Neuroscience of Memory Consolidation eds. Axmacher N., & Rasch B. (pp. 17–44). Cham, Switzerland: Springer.
   Google Scholar
• Shrager, J., & Siegler, R. S. (1998). SCADS: A model of children’s strategy choices and strategy discoveries. Psychological Science, 9(5), 405–410.
   Web of Science ®Google Scholar
• Siegler, R. S. (1996). Emerging minds: The process of change in children’s thinking. New York, NY: Oxford University Press.
   Google Scholar
• Siegler, R. S., & Shrager, J. (1984). Strategy choices in addition and subtraction: How do children know what to do? In Origins of cognitive skills, ed. Sophian, C. (pp. 229–293). Hillsdale, NJ: Erlbaum
   Google Scholar
• Skrandies, W., & Klein, A. (2015). Brain activity and learning of mathematical rules—Effects on the frequencies of EEG. Brain Research, 1603, 133–140.
   PubMed Web of Science ®Google Scholar
• Soltanlou, M., Artemenko, C., Dresler, T., Haeussinger, F. B., Fallgatter, A. J., Ehlis, A.-C., & Nuerk, H.-C. (2017). Increased arithmetic complexity is associated with domain-general but not domain-specific magnitude processing in children: A simultaneous fNIRS-EEG study. Cognitive, Affective, & Behavioral Neuroscience, 17(4), 724–736.
   PubMed Web of Science ®Google Scholar
• Soltanlou, M., Artemenko, C., Ehlis, A. C., Huber, S., Fallgatter, A. J., Dresler, T., & Nuerk, H. C. (2018). Reduction but no shift in brain activation after arithmetic learning in children: A simultaneous fNIRS-EEG study. Scientific Reports, 8(1), 1707.
   PubMedGoogle Scholar
• Soltanlou, M., Jung, S., Roesch, S., Ninaus, M., Brandelik, K., Heller, J., … Moeller, K. (2017). Behavioral and neurocognitive evaluation of a web-platform for game-based learning of orthography and numeracy. In Informational Environments, eds. Buder J., & Hesse F. (pp. 149–176). Cham, Switzerland: Springer.
   Google Scholar
• Sporns, O. (2011). Networks of the brain. Cambridge, MA: MIT press.
   Google Scholar
• Stam, C. J., van Walsum, A.-M. V. C., & Micheloyannis, S. (2002). Variability of EEG synchronization during a working memory task in healthy subjects. International Journal of Psychophysiology, 46(1), 53–66.
   PubMed Web of Science ®Google Scholar
• Szűcs, D., & Goswami, U. (2007). Educational neuroscience: Defining a new discipline for the study of mental representations. Mind, Brain, and Education, 1(3), 114–127.
   Web of Science ®Google Scholar
• Tadel, F., Baillet, S., Mosher, J. C., Pantazis, D., & Leahy, R. M. (2011). Brainstorm: A user-friendly application for MEG/EEG analysis. Computational Intelligence and Neuroscience, 2011, 8.
   Google Scholar
• Tesche, C., Uusitalo, M., Ilmoniemi, R., Huotilainen, M., Kajola, M., & Salonen, O. (1995). Signal-space projections of MEG data characterize both distributed and well-localized neuronal sources. Electroencephalography and Clinical Neurophysiology, 95(3), 189–200.
   PubMedGoogle Scholar
• Von Aster, M. (2000). Developmental cognitive neuropsychology of number processing and calculation: Varieties of developmental dyscalculia. European Child & Adolescent Psychiatry, 9(2), S41–S57.
   Google Scholar
• Welch, P. D. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70–73.
   Google Scholar
• Wood, G., Willmes, K., Nuerk, H.-C., & Fischer, M. H. (2008). On the cognitive link between space and number: A meta-analysis of the SNARC effect. Psychology Science, 50(4), 489–525.
   Google Scholar
• Zamarian, L., Ischebeck, A., & Delazer, M. (2009). Neuroscience of learning arithmetic—Evidence from brain imaging studies. Neuroscience & Biobehavioral Reviews, 33(6), 909–925.
   PubMed Web of Science ®Google Scholar
• Zhuang, P., Toro, C., Grafman, J., Manganotti, P., Leocani, L., & Hallett, M. (1997). Event-related desynchronization (ERD) in the alpha frequency during development of implicit and explicit learning. Electroencephalography and Clinical Neurophysiology, 102(4), 374–381.
   PubMedGoogle Scholar