Event-related brain potentials study of arithmetic fact retrieval in children with different math achievement levels

REFERENCES

• Abreu-Mendoza, R. A., Chamorro, Y., & Matute, E. (2019). Psychometric properties of the WRAT math computation subtest in Mexican adolescents. Journal of Psychoeducational Assessment, 37(8), 957–972. https://doi.org/10.1177/0734282918809793
   Google Scholar
• Alexander, J. E., Bauer, L. O., Kuperman, S., O’Connor, S. J., Rohrbaugh, J., Porjesz, B., & Polich, J. (1996). Hemispheric differences for P300 amplitude from an auditory oddball task. International Journal of Psychophysiology, 21(2-3), 189–196. https://doi.org/10.1016/0167-8760(95)00047-X
   Google Scholar
• Alloway, T., & Copello, E. (2013). Working memory: The what, the Why, and the How. The Australian Educational and Developmental Psychologist, 30(2), 105–118. https://doi.org/10.1017/edp.2013.13
   Google Scholar
• Andersson, U. (2010). Skill development in different components of arithmetic and basic cognitive functions: Findings from a 3-year longitudinal study of children with different types of learning difficulties. Journal of Educational Psychology, 102(1), 115–134. https://doi.org/10.1037/a0016838
   Google Scholar
• Andersson, U., & Lyxell, B. (2007). Working memory deficit in children with mathematical difficulties: A general or specific deficit? Journal of Experimental Child Psychology, 96(3), 197–228. https://doi.org/10.1016/j.jecp.2006.10.001
   Google Scholar
• Arán Filippetti, V., & Richaud, M. C. (2016). A structural equation modeling of executive functions, IQ and mathematical skills in primary students: Differential effects on number production, mental calculus and arithmetical problems. Child Neuropsychology, 1–25. https://doi.org/10.1080/09297049.2016.1199665
   Google Scholar
• Ashcraft, M. H. (1992). Cognitive arithmetic: A review of data and theory. Cognition, 44(1-2), 75–106. https://doi.org/10.1016/0010-0277(92)90051-I
   Google Scholar
• Ashcraft, M. H., & Battaglia, J. (1978). Cognitive arithmetic: Evidence for retrieval and decision processes in mental addition. Journal of Experimental Psychology: Human Learning and Memory, 4(5), 527–538. doi:doi:10.1037/0278-7393.4.5.527
   Google Scholar
• Baddeley, A. D. (2006). Working memory: An overview. In S. J. Pickering (Ed.), Working memory and education (pp. 517–552). Academic Press.
   Google Scholar
• Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47–89). Academic Press.
   Google Scholar
• Baroody, A. J. (1994). An evaluation of evidence supporting fact-retrieval models. Learning and Individual Differences, 6(1), 1–36. https://doi.org/10.1016/1041-6080(94)90013-2
   Google Scholar
• Barrouillet, P., & Thevenot, C. (2013). On the problem-size effect in small additions: Can we really discard any counting-based account? Cognition, 128(1), 35–44. https://doi.org/10.1016/j.cognition.2013.02.018
   Google Scholar
• Barthélemy, Q., Mayaud, L., Renard, Y., Kim, D., Kang, S.-W., Gunkelman, J., & Congedo, M. (2017). Online denoising of eye-blinks in electroencephalography. Neurophysiologie Clinique, 47(5–6), 371–391. https://doi.org/10.1016/j.neucli.2017.10.059
   Google Scholar
• Campbell, J. I. D., Chen, Y., & Maslany, A. J. (2013). Retrieval-induced forgetting of arithmetic facts across cultures. Journal of Cognitive Psychology, 25(6), 759–773. https://doi.org/10.1080/20445911.2013.820191
   Google Scholar
• Campbell, J. I. D., & Thompson, V. A. (2012). Retrieval-induced forgetting of arithmetic facts. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(1), 118–129. https://doi.org/10.1037/a0025056
   Google Scholar
• Cárdenas, S. Y., Silva-Pereyra, J., Prieto-Corona, B., Castro-Chavira, S. A., & Fernández, T. (2021). Arithmetic processing in children with dyscalculia: An event-related potential study. PeerJ, 9, e10489. https://doi.org/10.7717/peerj.10489
   Google Scholar
• Chen, Y., & Campbell, J. I. D. (2018). “Compacted” procedures for adults’ simple addition: A review and critique of the evidence. Psychonomic Bulletin & Review, 25(2), 739–753. https://doi.org/10.3758/s13423-017-1328-2
   Google Scholar
• Chen, Y., Campbell, J. I. D., & Liu, C. (2013). The N3 is sensitive to odd–even congruency information in arithmetic fact retrieval. Experimental Brain Research, 225(4), 603–611. https://doi.org/10.1007/s00221-013-3404-9
   Google Scholar
• Conway, A. R., & Kovacs, K. (2013). Psychology of learning and motivation. Psychology of Learning and Motivation, 58, 233–270. https://doi.org/10.1016/B978-0-12-407237-4.00007-4
   Google Scholar
• Dehaene, S. (1992). Varieties of numerical abilities. Cognition, 44(1-2), 1–42. https://doi.org/10.1016/0010-0277(92)90049-N
   Google Scholar
• Dehaene, S., Molko, N., Cohen, L., & Wilson, A. J. (2004). Arithmetic and the brain. Current Opinion in Neurobiology, 14(2), 218–224. https://doi.org/10.1016/j.conb.2004.03.008
   Google Scholar
• De Rammelaere, S., Stuyven, E., & Vandierendonck, A. (1999). The contribution of working memory resources in the verification of simple mental arithmetic sums. Psychological Research, 62(1), 72–77. https://doi.org/10.1007/s004260050041
   Google Scholar
• De Rammelaere, S., Stuyven, E., & Vandierendonck, A. (2001). Verifying simple arithmetic sums and products: Are the phonological loop and the central executive involved? Memory & Cognition, 29(2), 267–273. https://doi.org/10.3758/BF03194920
   Google Scholar
• Deschuyteneer, M., Vandierendonck, A., & Muyllaert, I. (2006). Does solution of mental arithmetic problems such as 2 + 6 and 3 × 8 rely on the process of “memory updating”? Experimental Psychology, 53(3), 198–208. https://doi.org/10.1027/1618-3169.53.3.198
   Google Scholar
• de Smedt, B., & Boets, B. (2010). Phonological processing and arithmetic fact retrieval: Evidence from developmental dyslexia. Neuropsychologia, 48(14), 3973–3981. https://doi.org/10.1016/j.neuropsychologia.2010.10.018
   Google Scholar
• Desoete, A., Ceulemans, A., de Weerdt, F., & Pieters, S. (2012). Can we predict mathematical learning disabilities from symbolic and non-symbolic comparison tasks in kindergarten? Findings from a longitudinal study. British Journal of Educational Psychology, 82(Pt 1), 64–81. https://doi.org/10.1348/2044-8279.002002
   Google Scholar
• de Visscher, A., & Noël, M.-P. (2016). Progress in brain research. Progress in Brain Research, 227, 131–158. https://doi.org/10.1016/bs.pbr.2016.04.008
   Google Scholar
• Diagnostic and Statistical Manual of Mental Disorders, DSM-5. (2013). 5th ed., American Psychiatric Publishing.
   Google Scholar
• Domahs, F., Domahs, U., Schlesewsky, M., Ratinckx, E., Verguts, T., Willmes, K., & Nuerk, H.-C. (2007). Neighborhood consistency in mental arithmetic: Behavioral and ERP evidence. Behavioral and Brain Functions, 3(1), 66. https://doi.org/10.1186/1744-9081-3-66
   Google Scholar
• Donchin, E., & Coles, M. G. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11(3), 357–427. https://doi.org/10.1017/S0140525X00058027
   Google Scholar
• Fukuda, K., Vogel, E., Mayr, U., & Awh, E. (2010). Quantity, not quality: The relationship between fluid intelligence and working memory capacity. Psychonomic Bulletin & Review, 17(5), 673–679. https://doi.org/10.3758/17.5.673
   Google Scholar
• Gärtner, M., Grimm, S., & Bajbouj, M. (2015). Frontal midline theta oscillations during mental arithmetic: Effects of stress. Frontiers in Behavioral Neuroscience, 9, 96–112. https://doi.org/10.3389/fnbeh.2015.00096
   Google Scholar
• 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
   Google Scholar
• Geary, D. C., Hamson, C., & Hoard, M. (2000). Numerical and arithmetical cognition: A longitudinal study of process and concept deficits in children with learning disability. Journal of Experimental Child Psychology, 77(3), 236–263. https://doi.org/10.1006/jecp.2000.2561
   Google Scholar
• Geary, D. C., Hoard, M. K., Byrd-Craven, J., Nugent, L., & Numtee, C. (2007). Cognitive mechanisms underlying achievement deficits in children With mathematical learning disability. Child Development, 78(4), 1343–1359. https://doi.org/10.1111/j.1467-8624.2007.01069.x
   Google Scholar
• Geary, D. C., Hoard, M. K., Nugent, L., & Bailey, D. H. (2012). Mathematical cognition deficits in children with learning disabilities and persistent low achievement: A five-year prospective study. Journal of Educational Psychology, 104(1), 206–223. https://doi.org/10.1037/a0025398
   Google Scholar
• Geary, D. C., & Moore, A. M. (2016). Cognitive and brain systems underlying early mathematical development. In M. Cappelletti, & W. Fias (Eds.), The Mathematical Brain Across the lifespan (1st edition, pp. 75–103). Elsevier. https://www.elsevier.com/books/the-mathematical-brain-across-the-lifespan/cappelletti/978-0-444-63698-0.
   Google Scholar
• Gómez-Velázquez, F. R., Berumen, G., & González-Garrido, A. A. (2015). Comparisons of numerical magnitudes in children with different levels of mathematical achievement. An ERP study. Brain Research, 1627, 189–200. https://doi.org/10.1016/j.brainres.2015.09.009
   Google Scholar
• Grabner, R. H., Brunner, C., Lorenz, V., Vogel, S. E., & de Smedt, B. (2022). Fact retrieval or compacted counting in arithmetic—A neurophysiological investigation of two hypotheses. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48(2), 199–212. https://doi.org/10.1037/xlm0000982
   Google Scholar
• Greiffenstein, M. F., & Baker, W. J. (2002). Neuropsychological and psychosocial correlates of adult arithmetic deficiency. Neuropsychology, 16(4), 451–458. https://doi.org/10.1037/0894-4105.16.4.451
   Google Scholar
• Grenier, A. E., Dickson, D. S., Sparks, C. S., & Wicha, N. Y. Y. (2020). Meaning to multiply: Electrophysiological evidence that children and adults treat multiplication facts differently. Developmental Cognitive Neuroscience, 46, 100873. https://doi.org/10.1016/j.dcn.2020.100873
   Google Scholar
• Guo, C., Lawson, A. L., Zhang, Q., & Jiang, Y. (2008). Brain potentials distinguish new and studied objects during working memory. Human Brain Mapping, 29(4), 441–452. https://doi.org/10.1002/hbm.20409
   Google Scholar
• Hecht, S. A. (2002). Counting on working memory in simple arithmetic when counting is used for problem solving. Memory & Cognition, 30(3), 447–455. https://doi.org/10.3758/BF03194945
   Google Scholar
• INEGI (National Institute for Statistic and Geographical Information). (2020). Quantifying the middle class in Mexico. https://www.inegi.org.mx/investigacion/cmedia/.
   Google Scholar
• Jost, K., Hennighausen, E., & Rösler, F. (2003). Comparing arithmetic and semantic fact retrieval: Effects of problem size and sentence constraint on event-related brain potentials. Psychophysiology, 40(6), 1000–1000. https://doi.org/10.1111/1469-8986.00119
   Google Scholar
• Kok, A. (2001). On the utility of P3 amplitude as a measure of processing capacity. Psychophysiology, 38(3), 557–577. https://doi.org/10.1017/S0048577201990559
   Google Scholar
• LeFevre, J.-A., Bisanz, J., Daley, K. E., Buffone, L., Greenham, S. L., & Sadesky, G. S. (1996). Multiple routes to solution of single-digit multiplication problems. Journal of Experimental Psychology: General, 125(3), 284–306. https://doi.org/10.1037/0096-3445.125.3.284
   Google Scholar
• Logie, R. H., & Baddeley, A. D. (1987). Cognitive processes in counting. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(2), 310–326. https://doi.org/10.1037/0278-7393.13.2.310
   Google Scholar
• Luciano, M., Wright, M. J., Smith, G. A., Geffen, G. M., Geffen, L. B., & Martin, N. G. (2001). Genetic covariance among measures of information processing speed, working memory, and IQ. Behavior Genetics, 31(6), 581–592. https://doi.org/10.1023/A:1013397428612
   Google Scholar
• McCloskey, M., Caramazza, A., & Basili, A. (1985). Cognitive mechanisms in number processing and calculation: Evidence from dyscalculia. Brain and Cognition, 4(2), 171–196. https://doi.org/10.1016/0278-2626(85)90069-7
   Google Scholar
• McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–260. https://doi.org/10.1006/jecp.1999.2516
   Google Scholar
• Mishra, S. P. (1981). Reliability and validity of the WRAT with Mexican-American children. Psychology in the Schools, 18(2), 154–158. https://doi.org/10.1002/1520-6807(198104)18:2<154::AID-PITS2310180207>3.0.CO;2-J
   Google Scholar
• Nemeth, L., Werker, K., Arend, J., Vogel, S., & Lipowsky, F. (2019). Interleaved learning in elementary school mathematics: Effects on the flexible and adaptive use of subtraction strategies. Frontiers in Psychology, 10, 86. https://doi.org/10.3389/fpsyg.2019.00086
   Google Scholar
• Niedeggen, M., & Rösler, F. (1999). N400 effects reflect activation spread during retrieval of arithmetic facts. Psychological Science, 10(3), 271–276. https://doi.org/10.1111/1467-9280.00149
   Google Scholar
• Niedeggen, M., Rösler, F., & Jost, K. (1999). Processing of incongruous mental calculation problems: Evidence for an arithmetic N400 effect. Psychophysiology, 36(3), 307–324. https://doi.org/10.1017/S0048577299980149
   Google Scholar
• Noel, M. P., Robert, A., & Brysbaert, M. (1998). Discussion. Cognition, 67(3), 365–373. https://doi.org/10.1016/S0010-0277(98)00038-9
   Google Scholar
• Núñez-Peña, M. I., & Escera, C. (2007). An event-related brain potential study of the arithmetic split effect. International Journal of Psychophysiology, 64(2), 165–172. https://doi.org/10.1016/j.ijpsycho.2007.01.007
   Google Scholar
• Núñez-Peña, M. I., & Honrubia-Serrano, M. L. (2004). P600 related to rule violation in an arithmetic task. Cognitive Brain Research, 18(2), 130–141. https://doi.org/10.1016/j.cogbrainres.2003.09.010
   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. https://doi.org/10.1007/s00221-012-3058-z
   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. https://doi.org/10.1016/j.dcn.2017.05.002
   Google Scholar
• Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128–2148. https://doi.org/10.1016/j.clinph.2007.04.019
   Google Scholar
• Polich, J. (2011). Neuropsychology of P300. In S. J. Luck, & E. S. Kappenman (Eds.), Oxford handbook of event-related potential components (pp. 159–188). Oxford University Press.
   Google Scholar
• Prieto-Corona, B., Rodríguez-Camacho, M., Silva-Pereyra, J., Marosi, E., Fernández, T., & Guerrero, V. (2010). Event-related potentials findings differ between children and adults during arithmetic-fact retrieval. Neuroscience Letters, 468(3), 220–224. https://doi.org/10.1016/j.neulet.2009.10.094
   Google Scholar
• Pritchard, W. S. (1981). Psychophysiology of P300. Psychological Bulletin, 89(3), 506–540. https://doi.org/10.1037/0033-2909.89.3.506
   Google Scholar
• Restle, F. (1970). Speed of adding and comparing numbers. Journal of Experimental Psychology, 83(2, Pt.1), 274–278. https://doi.org/10.1037/h0028573
   Google Scholar
• Rivera, B., & Soylu, F. (2021). Incongruity in fraction verification elicits N270 and P300 ERP effects. Neuropsychologia, 161, 108015. https://doi.org/10.1016/j.neuropsychologia.2021.108015
   Google Scholar
• Romo-Vázquez, R., Vélez-Pérez, H., Ranta, R., Louis Dorr, V., Maquin, D., & Maillard, L. (2012). Blind source separation, wavelet denoising and discriminant analysis for EEG artefacts and noise cancelling. Biomedical Signal Processing and Control, 7(4), 389–400. https://doi.org/10.1016/j.bspc.2011.06.005
   Google Scholar
• Rösler, F., Clausen, G., & Sojka, B. (1986). The double-priming paradigm: A tool for analyzing the functional significance of endogenous event-related brain potentials. Biological Psychology, 22(3), 239–232. https://doi.org/10.1016/0301-0511(86)90029-3
   Google Scholar
• Sattler, J. M. (2008). Assessment of children: Cognitive foundations (5th Edición). Jerome M. Sattler. Publisher, Inc.
   Google Scholar
• 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), e12372. https://doi.org/10.1111/desc.12372
   Google Scholar
• Seitz, K., & Schumann-Hengsteler, R. (2000). Mental multiplication and working memory. European Journal of Cognitive Psychology, 12(4), 552–570. https://doi.org/10.1080/095414400750050231
   Google Scholar
• Serra-Grabulosa, J. M., Adan, A., Pérez-Pàmies, J., Lachica, J., & Membrives, S. (2010). Bases neurales del procesamiento numérico y del cálculo. Revista de Neurología, 50(1), 39–46. https://doi.org/10.33588/rn.5001.2009271
   Google Scholar
• Seyler, D. J., Kirk, E. P., & Ashcraft, M. H. (2003). Elementary subtraction. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(6), 1339–1352. https://doi.org/10.1037/0278-7393.29.6.1339
   Google Scholar
• Siegler, R. S. (1988). Strategy choice procedures and the development of multiplication skill. Journal of Experimental Psychology: General, 117(3), 258–275. https://doi.org/10.1037/0096-3445.117.3.258
   Google Scholar
• Simmons, F. R., Willis, C., & Adams, A.-M. (2012). Different components of working memory have different relationships with different mathematical skills. Journal of Experimental Child Psychology, 111(2), 139–155. https://doi.org/10.1016/j.jecp.2011.08.011
   Google Scholar
• Soltanlou, M., Pixner, S., & Nuerk, H.-C. (2015). Contribution of working memory in multiplication fact network in children may shift from verbal to visuo-spatial: A longitudinal investigation. Frontiers in Psychology, 6, 1062. https://doi.org/10.3389/fpsyg.2015.01062
   Google Scholar
• Szűcs, D., & Csépe, V. (2004). Access to numerical information is dependent on the modality of stimulus presentation in mental addition: A combined ERP and behavioral study. Cognitive Brain Research, 19(1), 10–27. https://doi.org/10.1016/j.cogbrainres.2003.11.002
   Google Scholar
• Szűcs, D., & Csépe, V. (2005). The effect of numerical distance and stimulus probability on ERP components elicited by numerical incongruencies in mental addition. Cognitive Brain Research, 22(2), 289–300. https://doi.org/10.1016/j.cogbrainres.2004.04.010
   Google Scholar
• Szűcs, D., & Soltész, F. (2010). Event-related brain potentials to violations of arithmetic syntax represented by place value structure. Biological Psychology, 84(2), 354–367. https://doi.org/10.1016/j.biopsycho.2010.04.002
   Google Scholar
• Taghizadeh, S., Hashemi, T., Jahan, A., & Nazari, M. A. (2021). The neural differences of arithmetic verification performance depend on math skill: Evidence from event-related potential. Neuropsychopharmacology Reports, 41(1), 73–81. https://doi.org/10.1002/npr2.12158
   Google Scholar
• Thevenot, C., & Barrouillet, P. (2020). Are small additions solved by direct retrieval from memory or automated counting procedures? A rejoinder to Chen and Campbell (2018). Psychonomic Bulletin & Review, 27(6), 1416–1418. https://doi.org/10.3758/s13423-020-01818-4
   Google Scholar
• Thevenot, C., Barrouillet, P., Castel, C., & Uittenhove, K. (2016). Ten-year-old children strategies in mental addition: A counting model account. Cognition, 146, 48–57. https://doi.org/10.1016/j.cognition.2015.09.003
   Google Scholar
• Threlfall, J. (2002). Flexible mental calculation. Educational Studies in Mathematics, 50(1), 29–47. https://doi.org/10.1023/A:1020572803437
   Google Scholar
• Träff, U. (2013). The contribution of general cognitive abilities and number abilities to different aspects of mathematics in children. Journal of Experimental Child Psychology, 116(2), 139–156. https://doi.org/10.1016/j.jecp.2013.04.007
   Google Scholar
• Uittenhove, K., Thevenot, C., & Barrouillet, P. (2016). Fast automated counting procedures in addition problem solving: When are they used and why are they mistaken for retrieval? Cognition, 146, 289–303. https://doi.org/10.1016/j.cognition.2015.10.008
   Google Scholar
• Vanbinst, K., & de Smedt, B. (2016). Individual differences in children’s mathematics achievement: The roles of symbolic numerical magnitude processing and domain-general cognitive functions. In M. Cappelletti, & W. Fias (Eds.), The Mathematical Brain Across the lifespan (1st edition, pp. 105–130). Elsevier. https://www.elsevier.com/books/the-mathematical-brain-across-the-lifespan/cappelletti/978-0-444-63698-0.
   Google Scholar
• Wang, Y., Kong, J., Tang, X., Zhuang, D., & Li, S. (2000). Event-related potential N270 is elicited by mental conflict processing in human brain. Neuroscience Letters, 293(1), 17–20. https://doi.org/10.1016/S0304-3940(00)01480-4
   Google Scholar
• Wechsler, D. (2007). Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). Mexican standardized version. El Manual Moderno.
   Google Scholar
• Wilkinson, G. S., & Robertson, G. J. (2006). WRAT 4 Wide Range Achievement test. Psychological Assessment Resources.
   Google Scholar
• Xenidou-Dervou, I., van Lieshout, E. C. D. M., & van der Schoot, M. (2014). Working memory in nonsymbolic approximate arithmetic processing: A dual-task study with preschoolers. Cognitive Science, 38(1), 101–127. https://doi.org/10.1111/cogs.12053
   Google Scholar
• Zbrodoff, N. J., & Logan, G. D. (1990). On the relation between production and verification tasks in the psychology of simple arithmetic. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 83–97. https://doi.org/10.1037/0278-7393.16.1.83
   Google Scholar