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4 - Grasping the concept of number: How did the sapient mind move beyond approximation?

Published online by Cambridge University Press:  05 June 2012

Iain Morley
Affiliation:
The MacDonald Institute for Archaeological Research
Colin Renfrew
Affiliation:
The MacDonald Institute for Archaeological Research
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Summary

Introduction

When and how did humans begin to count? Where does arithmetic come from? Are humans innately endowed with arithmetical abilities or is human numerical cognition a strictly cultural achievement? To a large extent the answers to the preceding questions depend upon how precisely we define human numerical cognition and arithmetical abilities.

If by numerical cognition we refer to the property of approximation – that is, the capacity for a basic appreciation of changes in quantity and a simple number sense (oneness, twoness, and threeness) – then several lines of evidence in contemporary cognitive neurosciences clearly support the view that this can be considered to be an evolved, innate biological competence shared by human infants and other animals. For example, a number of studies show that both preverbal infants and animals are able to detect numerocities, discriminating between small sets of objects or sequences of sounds both within, but also beyond, the so-called subitizing range (up to three or four objects) (Antell & Keating 1983; Wynn 1996; Davis & Pérusse 1988; Brannon & Terrace 1998; 2000; 2002; Biro & Matsuzawa 2001) – provided that in the latter case the comparison ratios are large enough (i.e., infants were able to discriminate 8 from 16, but not 8 from 12 items) (Xu & Spelke 2000; Lipton & Spelke 2003). More characteristic might be the finding that infants as young as five months old (Wynn 1992), but also untrained rhesus monkeys, seem to have additive and subtractive expectations when they observe or choose between arrays containing small number of objects.

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The Archaeology of Measurement
Comprehending Heaven, Earth and Time in Ancient Societies
, pp. 35 - 42
Publisher: Cambridge University Press
Print publication year: 2010

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References

Andres, M., Davare, M., Pesenti, M., Olivier, E. & Seron, X., 2004. Number magnitude and grip aperture interaction. Neuroreport 15(18), 2773–2777.Google ScholarPubMed
Antell, S. E. & Keating, D. P., 1983. Perception of numerical invariance in neonates. Child Development 54, 697–701.CrossRefGoogle ScholarPubMed
Biro, D. & Matsuzawa, T., 2001. Chimpanzee numerical competence: Cardinal and ordinal skills, in Primate Origins of Human Cognition and Behavior, ed. Matsuzawa, T.. Tokyo & Berlin: Springer, 199–225.Google Scholar
Brannon, E. M. & Terrace, H. S., 1998. Ordering of the numerosities 1 to 9 by monkeys. Science 282(5389), 746–749.CrossRefGoogle ScholarPubMed
Brannon, E. M. & Terrace, H. S., 2000. Representation of the numerosities 1–9 by rhesus macaques (Macaca mulatta). Journal of Experimental Psychology: Animal Behavior and Processes 26, 31–49.Google Scholar
Brannon, E. M. & Terrace, H. S., 2002. The evolution and ontogeny of ordinal numerical ability, in The Cognitive Animal: Empirical and Theoretical Perspectives on Animal Cognition, eds. Bekoff, M., Allen, C. & Burhgardt, G. M.. Cambridge, MA: MIT Press, 197–204.Google Scholar
Butterworth, B., 1999. What Counts: How Every Brain Is Hardwired for Math. New York: Free Press.Google Scholar
Calabria, M. & Rossetti, Y., 2005. Interference between number processing and line bisection: A methodology. Neuropsychologia 43(5), 779–783.CrossRefGoogle ScholarPubMed
Clark, A., 2003. Natural-Born Cyborgs: Minds, Technologies and the Future of Human Intelligence. New York: Oxford University Press.Google Scholar
Davis, H. & Pérusse, R., 1988. Numerical competence in animals: Definitional issues, current evidence, and a new research agenda. Behavioural and Brain Sciences 11, 561–615.CrossRefGoogle Scholar
Dehaene, S., 1997. The Number Sense. New York: Oxford University Press.Google Scholar
Dehaene, S., 2005. Evolution of human cortical circuits for reading and arithmetic: The “neuronal recycling” hypothesis, in From Monkey Brain to Human Brain, eds. Dehaene, S., J-R.Duhamel, , Rizzolatti, G. & Hauser, M.. Cambridge, MA: MIT Press.Google Scholar
Dehaene, S. & Cohen, L., 1995. Towards an anatomical and functional model of number processing. Mathematical Cognition 1, 83–120.Google Scholar
Dehaene, S. Dehaene, S. & Cohen, L., 1997. Cerebral pathways for calculation: Double dissociation between rote verbal and quantitative knowledge or arithmetic. Cortex 33, 219–250.CrossRefGoogle ScholarPubMed
Dehaene, S., Dehaene-Lambertz, G. & Cohen, L. 1998. Abstract representation of numbers in the animal and human brain. Nature Neuroscience 21, 355–361.Google ScholarPubMed
Dehaene, S., Piazza, M., Pinel, P. & Cohen, L. 2003. Three parietal circuits for number processing. Cognitive Neuropsychology 20, 487–506.CrossRefGoogle ScholarPubMed
Dehaene, S., Spelke, E., Pinel, P., Stanescu, R & Tsivkin, S., 1999. Sources of mathematical thinking: Behavioral and brain-imaging evidence. Science 284, 970–974.CrossRefGoogle ScholarPubMed
Eger, E., Sterzer, P., Russ, M. O., Giraud, A. L. & Kleinschmidt, A., 2003. A supramodal number representation in human intraparietal cortex. Neuron 37, 719–725.CrossRefGoogle ScholarPubMed
Fauconnier, G. & Turner, M., 1998. Conceptual integration networks. Cognitive Science 22, 133–187.CrossRefGoogle Scholar
Fauconnier, G. & Turner, M., 2002. The Way We Think: Conceptual Blending and the Mind's Hidden Complexities. New York: Basic Books.
Feigenson, L., Dehaene, S. & Spelke, E. 2004. Core systems of number. Trends in Cognitive Sciences 8, 307–314.CrossRefGoogle Scholar
Gelman, R. & Butterworth, B., 2005. Number and language: How are they related?Trends in Cognitive Sciences 9, 6–10.CrossRefGoogle ScholarPubMed
Gelman, R. & Gallistel, C. R., 2004. Language and the origin of numerical concepts. Science 306, 441–443.CrossRefGoogle ScholarPubMed
Gordon, P., 2004. Numerical cognition without words: Evidence from Amazonia. Science 306, 496–499.CrossRefGoogle ScholarPubMed
Hubbard, E. M., Piazza, M., Pinel, P. & Dehaene, S., 2005. Interactions between number and space in parietal cortex. Nature Reviews (Neuroscience) 6, 435–448.CrossRefGoogle ScholarPubMed
Hutchins, E, 2005. Material anchors for conceptual blends. Journal of Pragmatics 37, 1555–1577.CrossRefGoogle Scholar
Ifrah, G. 1985. From One to Zero: A Universal History of Numbers. New York: Viking.Google Scholar
Iriki, A., 2005. A prototype of Homo faber: A silent precursor of human intelligence in the tool-using monkey brain, in From Monkey Brain to Human Brain, eds. Dehaene, S., J-R.Duhamel, , Rizzolatti, G. & Hauser, M.. Cambridge, MA: MIT Press, 253–271.Google Scholar
Isaacs, E. B., Edmonds, C. J., Lucas, A. & Gadian, D. G., 2001. Calculation difficulties in children of very low birthweight: A neural correlate. Brain 124, 1701–1707.CrossRefGoogle ScholarPubMed
Kelly, A. M. C. & Garavan, H., 2005. Human functional neuroimaging of brain changes associated with practice. Cerebral Cortex 15, 1089–1102.CrossRefGoogle Scholar
Lakoff, G & Núñez, R. E.. 2000. Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being. New York: Basic Books.Google Scholar
Lee, K. M., 2000. Cortical areas differentially involved in multiplication and subtraction: A functional magnetic resonance imaging study and correlation with a case of selective acalculia. Annals of Neurology 48, 657–661.3.0.CO;2-K>CrossRefGoogle ScholarPubMed
Levy, L. M., Reis, I. L. & Grafman, J., 1999. Metabolic abnormalities detected by H-MRS in dyscalculia and dysgraphia. Neurology 53, 639–641.CrossRefGoogle Scholar
Lipton, J. S. & Spelke, E. S., 2003. Origins of number sense: Large-number discrimination in human infants. Psychological Science 14, 396–401.CrossRefGoogle ScholarPubMed
Malafouris, L., 2004. The cognitive basis of material engagement: Where brain, body and culture conflate, in Rethinking Materiality: The Engagement of Mind with the Material World, eds. DeMarrais, E., Gosden, C. & Renfrew, C.. Cambridge: McDonald Institute for Archaeological Research, 53–62.Google Scholar
Malafouris, L., 2005. Projections in Matter: Material Engagement and the Mycenaean Becoming. Unpublished PhD dissertation, Cambridge University.
Malafouris, L., 2007a. The sacred engagement: Outline of a hypothesis about the origin of human ‘religious intelligence’, in Cult in Context, Reconsidering Ritual in Archaeology, eds. Barrowclough, D. A. & Malone, C.Oxford: Oxbow Books, 198–205.Google Scholar
Malafouris, L., 2007b. Before and beyond representation: Towards an enactive conception of the Palaeolithic image, in Image and Imagination: A Global History of Figurative Representation, eds. Renfrew, C. & Morley, I.. Cambridge: McDonald Institute for Archaeological Research, 289–302.Google Scholar
Moyer, R. S. & Landauer, T. K., 1967. Time required for judgments of numerical inequality. Nature 215, 1519–1520.CrossRefGoogle ScholarPubMed
Neider, A., 2005. Counting on neurons: The neurobiology of numerical competence. Nature Reviews (Neuroscience) 6, 177–190.CrossRefGoogle Scholar
Pesenti, M., Thioux, M., Seron, X. & Volder, A., 2000. Neuroanatomical substrates of arabic number processing, numerical comparison and simple addition: A PET study. Journal of Cognitive Neuroscience 12, 461–479.CrossRefGoogle ScholarPubMed
Petersen, S. E., Mier, H., Fiez, J. A. & Raichle, M. E., 1998. The effects of practice on the functional anatomy of task performance. Proceedings of the National Academy of Sciences of the USA 95, 853–860.CrossRefGoogle ScholarPubMed
Pica, P., Lemer, C., Izard, V. & Dehaene, S., 2004. Exact and approximate arithmetic in an Amazonian indigene group. Science 306, 499–503.CrossRefGoogle Scholar
Pinel, P., Piazza, M., Bihan, D. & Dehaene, S., 2004. Distributed and overlapping cerebral representations of number, size, and luminance during comparative judgments. Neuron 41, 983–993.CrossRefGoogle ScholarPubMed
Poldrack, R. A., 2000. Imaging brain plasticity: Conceptual and methodological issues – a theoretical review. Neuroimage 12, 1–13.CrossRefGoogle ScholarPubMed
Schmandt-Besserat, D., 1992. Before Writing. Vol. I, From Counting to Cuneiform. Austin: University of Texas Press.Google Scholar
Schmandt-Besserat, D., 1996. How Writing Came About. Austin: University of Texas Press.Google Scholar
Simon, O., Mangin, J.-F., Cohen, L., Bihan, D. & Dehaene, S., 2002. Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron 33, 475–487.CrossRefGoogle ScholarPubMed
Varley, R. A., Klessinger, N. J. C., Romanowski, C. A. J. & Siegal, M., 2005. Agrammatic but numerate. PNAS 102(9) 3519–3524.CrossRefGoogle ScholarPubMed
Wynn, K., 1992. Addition and subtraction by human infants. Nature 358, 749–750.CrossRefGoogle ScholarPubMed
Wynn, K., 1996. Infants' individuation and enumeration of actions. Psychological Science 7, 164–169.CrossRefGoogle Scholar
Xu, F. 2003. Numerosity discrimination in infants: Evidence for two subsystems of representation. Cognition, 89, B15–B29.CrossRefGoogle Scholar
Xu, F. & Spelke, E.S.. 2000. Large number discrimination in 6-month-old infants. Cognition, 74, B1–B11.CrossRefGoogle ScholarPubMed
Zebian, S., 2005. Linkages between number concepts, spatial thinking, and directionality of writing: The SNARC effect and the reverse SNARC effect in English and Arabic monoliterates, biliterates and illiterate Arabic speakers. Journal of Cognition and Culture 5(1–2), 165–90.CrossRefGoogle Scholar
Zorzi, M., Priftis, K. & Umilta, C., 2002. Neglect disrupts the mental number line. Nature 417, 138–139.CrossRefGoogle ScholarPubMed

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