[en] Humans can effortlessly abstract numerical information from various codes and contexts. However, whether the access to the underlying magnitude information relies on common or distinct brain representations remains highly debated. Here, we recorded electrophysiological responses to periodic variation of numerosity (every five items) occurring in rapid streams of numbers presented at 6 Hz in randomly varying codes-Arabic digits, number words, canonical dot patterns and finger configurations. Results demonstrated that numerical information was abstracted and generalized over the different representation codes by revealing clear discrimination responses (at 1.2 Hz) of the deviant numerosity from the base numerosity, recorded over parieto-occipital electrodes. Crucially, and supporting the claim that discrimination responses reflected magnitude processing, the presentation of a deviant numerosity distant from the base (e.g., base "2" and deviant "8") elicited larger right-hemispheric responses than the presentation of a close deviant numerosity (e.g., base "2" and deviant "3"). This finding nicely represents the neural signature of the distance effect, an interpretation further reinforced by the clear correlation with individuals' behavioral performance in an independent numerical comparison task. Our results therefore provide for the first time unambiguously a reliable and specific neural marker of a magnitude representation that is shared among several numerical codes.
Disciplines :
Neurosciences & behavior
Author, co-author :
Marlair, Cathy; Institute of Psychology (IPSY) and Institute of Neuroscience (IoNS), Université Catholique de Louvain, Place Cardinal Mercier 10, 1348, Louvain-la-Neuve, Belgium. cathy.marlair@uclouvain.be
Crollen, Virginie; Institute of Psychology (IPSY) and Institute of Neuroscience (IoNS), Université Catholique de Louvain, Place Cardinal Mercier 10, 1348, Louvain-la-Neuve, Belgium
LOCHY, Aliette ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS) > Cognitive Science and Assessment ; Institute of Psychology (IPSY) and Institute of Neuroscience (IoNS), Université Catholique de Louvain, Place Cardinal Mercier 10, 1348, Louvain-la-Neuve, Belgium
External co-authors :
yes
Language :
English
Title :
A shared numerical magnitude representation evidenced by the distance effect in frequency-tagging EEG.
Fonds De La Recherche Scientifique - FNRS Fonds Spéciaux de Recherche
Funding text :
We are grateful to Florine Deconinck for her help in data collection. This work was supported by the Fonds de la Recherche Scientifique (FNRS, Belgium) under FRESH Grant n° FC38635 (CM) and by the “Seed funding” program (ADi/DB/10063.2018) of the UCLouvain Fonds Spécial de Recherche (FSR, Belgium) (VC).
Gallistel, C. R. & Gelman, R. Non-verbal numerical cognition: From reals to integers. Trends Cogn. Sci. 4, 59–65 (2000). DOI: 10.1016/S1364-6613(99)01424-2
Dehaene, S. The Number Sense: How the Mind Creates Mathematics, Revised and Updated (Oxford University Press, 2011).
Ansari, D. Effects of development and enculturation on number representation in the brain. Nat. Rev. Neurosci. 9, 278–291 (2008). DOI: 10.1038/nrn2334
Mundy, E. & Gilmore, C. K. Children’s mapping between symbolic and nonsymbolic representations of number. J. Exp. Child. Psychol. 103, 490–502 (2009). DOI: 10.1016/j.jecp.2009.02.003
Brankaer, C., Ghesquière, P. & De Smedt, B. Symbolic magnitude processing in elementary school children: A group administered paper-and-pencil measure (SYMP Test). Behav. Res. Methods 49, 1361–1373 (2017). DOI: 10.3758/s13428-016-0792-3
De Smedt, B., Noël, M.-P., Gilmore, C. & Ansari, D. 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 Neurosci. Educ. 2, 48–55 (2013). DOI: 10.1016/j.tine.2013.06.001
Kolkman, M. E., Kroesbergen, E. H. & Leseman, P. P. Early numerical development and the role of non-symbolic and symbolic skills. Learn. Instr. 25, 95–103 (2013). DOI: 10.1016/j.learninstruc.2012.12.001
Di Luca, S. & Pesenti, M. Finger numeral representations: More than just another symbolic code. Front. Psychol. 2, 272. 10.3389/fpsyg.2011.00272 (2011). DOI: 10.3389/fpsyg.2011.00272
Kreilinger, I. L., Roesch, S., Moeller, K. & Pixner, S. Mastery of structured quantities like finger or dice patterns predict arithmetic performance. Cogn. Process. 22, 93–104 (2021). DOI: 10.1007/s10339-020-00994-4
Halberda, J. & Feigenson, L. Developmental change in the acuity of the" Number Sense": The approximate number system in 3-, 4-, 5-, and 6-year-olds and adults. Dev. Psychol. 44, 1457–1465 (2008). DOI: 10.1037/a0012682
Holloway, I. D. & Ansari, D. Mapping numerical magnitudes onto symbols: The numerical distance effect and individual differences in children’s mathematics achievement. J. Exp. Child. Psychol. 103, 17–29 (2009). DOI: 10.1016/j.jecp.2008.04.001
Sasanguie, D., De Smedt, B., Defever, E. & Reynvoet, B. Association between basic numerical abilities and mathematics achievement. Br. J. Dev. Psychol. 30, 344–357 (2012). DOI: 10.1111/j.2044-835X.2011.02048.x
Marinova, M., Sasanguie, D. & Reynvoet, B. Numerals do not need numerosities: Robust evidence for distinct numerical representations for symbolic and non-symbolic numbers. Psychol. Res. 85, 764–776 (2021). DOI: 10.1007/s00426-019-01286-z
Dehaene, S., Dehaene-Lambertz, G. & Cohen, L. Abstract representations of numbers in the animal and human brain. Trends Neurosci. 21, 355–361 (1998). DOI: 10.1016/S0166-2236(98)01263-6
Moyer, R. S. & Landauer, T. K. Time required for judgements of numerical inequality. Nature 215, 1519–1520 (1967). DOI: 10.1038/2151519a0
Liu, R., Schunn, C. D., Fiez, J. A. & Libertus, M. E. The integration between nonsymbolic and symbolic numbers: Evidence from an EEG study. Brain Behav. 8, e00938. 10.1002/brb3.938 (2018). DOI: 10.1002/brb3.938
Reynvoet, B. & Sasanguie, D. The symbol grounding problem revisited: A thorough evaluation of the ANS mapping account and the proposal of an alternative account based on symbol–symbol associations. Front. Psychol. 7, 1581. 10.3389/fpsyg.2016.01581 (2016). DOI: 10.3389/fpsyg.2016.01581
Dehaene, S., Piazza, M., Pinel, P. & Cohen, L. Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487–506 (2003). DOI: 10.1080/02643290244000239
Nieder, A. Neural constraints on human number concepts. Curr. Opin. Neurobiol. 60, 28–36 (2020). DOI: 10.1016/j.conb.2019.10.003
Nieder, A. & Dehaene, S. Representation of number in the brain. Annu. Rev. Neurosci. 32, 185–208 (2009). DOI: 10.1146/annurev.neuro.051508.135550
Arsalidou, M. & Taylor, M. J. Is 2+2=4? Meta-analyses of brain areas needed for numbers and calculations. Neuroimage 54, 2382–2393 (2011). DOI: 10.1016/j.neuroimage.2010.10.009
Eger, E. et al. Deciphering cortical number coding from human brain activity patterns. Curr. Biol. 19, 1608–1615 (2009). DOI: 10.1016/j.cub.2009.08.047
Ansari, D., Garcia, N., Lucas, E., Hamon, K. & Dhital, B. Neural correlates of symbolic number processing in children and adults. NeuroReport 16, 1769–1773 (2005). DOI: 10.1097/01.wnr.0000183905.23396.f1
Holloway, I. D., Price, G. R. & Ansari, D. Common and segregated neural pathways for the processing of symbolic and nonsymbolic numerical magnitude: An fMRI study. Neuroimage 49, 1006–1017 (2010). DOI: 10.1016/j.neuroimage.2009.07.071
Pinel, P., Dehaene, S., Riviere, D. & LeBihan, D. Modulation of parietal activation by semantic distance in a number comparison task. Neuroimage 14, 1013–1026 (2001). DOI: 10.1006/nimg.2001.0913
Gebuis, T., Cohen Kadosh, R. & Gevers, W. Sensory-integration system rather than approximate number system underlies numerosity processing: A critical review. Acta Psychol. 171, 17–35 (2016). DOI: 10.1016/j.actpsy.2016.09.003
Norcia, A. M., Appelbaum, L. G., Ales, J. M., Cottereau, B. R. & Rossion, B. The steady-state visual evoked potential in vision research: A review. J. Vis. 15, 4. 10.1167/15.6.4 (2015). DOI: 10.1167/15.6.4
Guillaume, M., Mejias, S., Rossion, B., Dzhelyova, M. & Schiltz, C. A rapid, objective and implicit measure of visual quantity discrimination. Neuropsychologia 111, 180–189 (2018). DOI: 10.1016/j.neuropsychologia.2018.01.044
Georges, C., Guillaume, M. & Schiltz, C. A robust electrophysiological marker of spontaneous numerical discrimination. Sci. Rep. 10, 18376. 10.1038/s41598-020-75307-y (2020). DOI: 10.1038/s41598-020-75307-y
Van Rinsveld, A. et al. The neural signature of numerosity by separating numerical and continuous magnitude extraction in visual cortex with frequency-tagged EEG. Proc. Natl. Acad. Sci. USA 117, 5726–5732 (2020). DOI: 10.1073/pnas.1917849117
Guillaume, M., Poncin, A., Schiltz, C. & Van Rinsveld, A. Measuring spontaneous and automatic processing of magnitude and parity information of Arabic digits by frequency-tagging EEG. Sci. Rep. 10, 22254. 10.1038/s41598-020-79404-w (2020). DOI: 10.1038/s41598-020-79404-w
Marinova, M. et al. Automatic integration of numerical formats examined with frequency-tagged EEG. Sci. Rep. 11, 21405. 10.1038/s41598-021-00738-0 (2021). DOI: 10.1038/s41598-021-00738-0
Mandler, G. & Shebo, B. J. Subitizing: An analysis of its component processes. J. Exp. Psychol. Gen. 111, 1–22 (1982). DOI: 10.1037/0096-3445.111.1.1
Feigenson, L., Dehaene, S. & Spelke, E. Core systems of number. Trends Cogn. Sci. 8, 307–314 (2004). DOI: 10.1016/j.tics.2004.05.002
Sullivan, J. & Barner, D. Inference and association in children’s early numerical estimation. Child Dev. 85, 1740–1755 (2014). DOI: 10.1111/cdev.12211
Hutchison, J. E., Ansari, D., Zheng, S., De Jesus, S. & Lyons, I. M. The relation between subitizable symbolic and non-symbolic number processing over the kindergarten school year. Dev. Sci. 23, e12884. 10.1111/desc.12884 (2019). DOI: 10.1111/desc.12884
van den Berg, F. C., De Weerd, P. & Jonkman, L. M. Number-related brain potentials are differentially affected by mapping novel symbols on small versus large quantities in a number learning task. J. Cogn. Neurosci. 32, 1263–1275 (2020). DOI: 10.1162/jocn_a_01546
Marlair, C., Lochy, A., Buyle, M., Schiltz, C. & Crollen, V. Canonical representations of fingers and dots trigger an automatic activation of number semantics: An EEG study on 10-year-old children. Neuropsychologia 157, 107874. 10.1016/j.neuropsychologia.2021.107874 (2021). DOI: 10.1016/j.neuropsychologia.2021.107874
Marinova, M., Sasanguie, D. & Reynvoet, B. Symbolic estrangement or symbolic integration of numerals with quantities: Methodological pitfalls and a possible solution. PLoS ONE 13, e0200808. 10.1371/journal.pone.0200808 (2018). DOI: 10.1371/journal.pone.0200808
Piazza, M., Pinel, P., Le Bihan, D. & Dehaene, S. A magnitude code common to numerosities and number symbols in human intraparietal cortex. Neuron 53, 293–305 (2007). DOI: 10.1016/j.neuron.2006.11.022
Dehaene, S. The organization of brain activations in number comparison: Event-related potentials and the additive-factors method. J. Cogn. Neurosci. 8, 47–68 (1996). DOI: 10.1162/jocn.1996.8.1.47
Crollen, V., Castronovo, J. & Seron, X. Under- and over-estimation: A bi-directional mapping process between symbolic and non-symbolic representations of number?. Exp. Psychol. 58, 39–49 (2010). DOI: 10.1027/1618-3169/a000064
Regan, D. Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine (Elsevier, 1989).
Rossion, B. Understanding face perception by means of human electrophysiology. Trends Cogn. Sci. 18, 310–318 (2014). DOI: 10.1016/j.tics.2014.02.013
Liu-Shuang, J., Norcia, A. M. & Rossion, B. An objective index of individual face discrimination in the right occipito-temporal cortex by means of fast periodic oddball stimulation. Neuropsychologia 52, 57–72 (2014). DOI: 10.1016/j.neuropsychologia.2013.10.022
Lochy, A., Van Reybroeck, M. & Rossion, B. Left cortical specialization for visual letter strings predicts rudimentary knowledge of letter-sound association in preschoolers. Proc. Natl. Acad. Sci. USA 113, 8544–8549 (2016). DOI: 10.1073/pnas.1520366113
Retter, T. L. & Rossion, B. Uncovering the neural magnitude and spatio-temporal dynamics of natural image categorization in a fast visual stream. Neuropsychologia 91, 9–28 (2016). DOI: 10.1016/j.neuropsychologia.2016.07.028