Numerical and mathematical processing skills has a long history
from the ancient classical Greeks Plato, Aristotle Frank, Mendel [1]
to the birth of modern psychology, with John Dewey [2], Conant [3],
O’Shea [4], suggesting that children learn numerical concepts by
reinforcement, not in an abstract way, by identifying similarities,
differences of empirical individual units, forming general concepts.
This essay follows through the recent evolution of neuroimaging
studies debate, sets the theoretical context of three dominant
theories that influenced the context of research tools/methods;
and how neuroscientific research has contributed uniquely to
the understanding of numerosity. The essay concludes with a
cogent argument that alternative research tools are necessary,
complimentary, and multidisciplinary research generates different
types/levels of new hypotheses, ensuing more reliable and valid
information which benefits individuals, educationalists and
society at large. Numerical processing (referring to arithmetic,
mathematics, geometry and advanced computation) is huge. The
paper is an eclectic review of the neurotypical findings of general
numerical processing only but excludes dyscalculia Menon [5].
The overwhelming research suggest that, numeracy is essential
for progress in all aspects of life. Understanding numbers is the
basis for developing arithmetic and mathematical skills of all
levels and types of applications Dehaene [6], Hurford [7]. Major
longitudinal research studies in the UK Bynner, Parsons [8], Donato
[9], documented the phenotypic and behavioural outcomes of
poor numerical skills and highlight the negative consequences on
men’s and women’s, employment opportunities, health outcomes,
social-civic involvement and overall quality of life Parsons, Banner
[10]. Finding out if specific numerical processing is actually an
observable brain process or not, is important to make stronger correlational claims, regarding relationships of numerosity and
language.
New neuroimaging tools are used to test existing and emerging
new theories and collect data that are impossible with surveys,
and experiments. However, without multimethod, multiparadigm
comparisons to make valid, reliable and nomological evaluations
of competing claims Goya, Pitre [11], Hsee [12], Hsee [13], Hagger
[14]. Three theoretical strands attempt to explain the development
of number processing, using different research approaches. The
first theory suggests that language is innate, culturally constructed
and absence impedes learning numerical concepts and knowledge
Chomsky [15], Hurford [16], Wiese [17], Spelke [18]. Their position
without neuroscientific data, is not supported empirically, of how,
when, and where language underpins numerical development. The
second theory suggests that children learn numerical concepts as
part of lexical acquisition and development of Theory of Mind (TOM)
Bloom [19], Clark [20-22]. TOM facilitates multiple perspective
taking, conceptual differentiation, through social interactions,
enabling nuanced meaning differentiation between words, symbols,
and number associations. However, Bloom and Clark, provide weak
empirical evidence that brain processing occurs this way, and fail to
account for alternative hypotheses.
The third theoretical position postulates a biological,
evolutionary, ontogenetic Carey [23], innate ability of ‘number
sense’ and processed in distinct brain areas Dehaene [24]. Innate,
numerical processing is present in all cultures with and without
dedicated number words Pica et al., 2004; Lasne [25]. Dehaene
and co-researchers, Dehaene [26], Dehaene & Cohen [27], Dehaene
[28] using neuroimaging data proposed that different numerical
formats are processed in different brain regions. First, visual Arabic numbers are processed by bilateral activity in inferior
ventral occipito-temporal areas; secondly, the inferior parietal
areas process analogical size, and approximate volume; and thirdly,
word numbers are processed in the left perisylvian areas Dehaene
[29]. Dehaene and colleagues, during a period of 20 years, carried
out extensive neuroscientific research to disentangle the effects of
language-dominant or spatial iconic representation of numerical
processing and whether there are specific brain regions innately
dedicated to non-verbal numerical processing Dehaene [29],
Dehaene [28], Pica et al., 2004; Agrillo [30], Lasne [25].
They claim that, innate numerical ability theory is evolutionary
Dehaene [28] Pica et al., 2004, and studied systematically
using different tasks to understand the conceptual processes of
numerical approximation, estimation, and manipulation related
to concrete examples, in non-numerically literate (Amazonian
Munduruku tribe) and literate western cultures McCrink [31]. To
support their theory, that numbers are language-independent
representations, Dehaene and colleagues, focused on the dedicated
biological brain networks, which are putatively responsible for
basic number processing. Their multimethod research produced
diverse but supporting evidence of evolutionary innate abilities in
animals, infants and adult humans, independent of other abilities.
Their neuroscientific research using a range of neuroscientific
tools, fMRI, MEG, EEG, and brain legions, suggests that the inferior
parietal region is implicated in number processing Dehaene [28];
King & Dehaene, 2014. This level of specificity of explanatory power
is only possible with neuroimaging and multimethod approaches.
The tripartite model by Dehaene [28] implicating the horizontal
segment of IPS, the left AG related to the perisylvian areas, and
the bilateral PPS, was further re-tested by Piazza [32], Cohen
Kardes [33], using fMRI, fMRA and ERP tools. These multimethod
findings have provided convergent validity evidence that the left
IPS processes numerical quantities irrespective of format (Arabic,
word, and mixed format), but the right IPS processes quantities
of Arabic numerals only. Nieder, Jacob [34,35], tested numerical
processing of magnitudes and Approximate Number Systems, with
primates using single cell-neuron methods and found converging
evidence that humans and animals can process numbers without
words, but using approximate estimates, activating different
populations of neurons bilaterally in the IPS and lateral PFC.
Rosenberg-Lee [36], investigated the PPC in detail to identify the
specific cytoarchitecture for four calculations (+, -, *, %), and found
differences in processing these basic arithmetic tasks by the IPS,
SPL and AG. Converging neuroimaging findings using different
neuroimaging tools, augment the credibility of prior theoretical
positions. Hyde [37], using fNIRS, found that 6 months old babies’
right parietal areas, are specialised for number processing, before
language development and that this ability is lateralized with
environmental experiences. Artemenko [38] in a longitudinal
fNIRS study found that fronto-parietal network brain networks for
arithmetic are well established for adolescents. Amalric [39] found
that blind mathematicians process advanced mathematics in similar
brain networks as sighted without the visual experience. These
fine-grained differences of numerical developmental processing,
time duration, age differentiation, format presentation (numerals,
words), provide new information and new hypotheses, and models
which are impossible to test without neuroimaging (Table 1).
Table 1: Comparative context of research methods relevant to number processing.
The meta-analysis by Arsalidou [40], found that the core brain
regions for numerical processing are indeed the parietal regions
(IPS and precuneus), the insula, claustrum, the frontal cortex (e.g.,
superior and medial frontal gyri), and cingulate. However, the
developmentally changing networks and the function of typical and
atypical brains regarding all interconnected areas (bilateral frontal
(DLPFC, VLPFC), parietal (IPS, AG, SMG), occipito-temporal and
medial temporal, including HC areas) are not well understood yet,
according to Peters and De Smedt [41]. New ways of investigating
brain network hubs using resting-state fMRI can fine tune our
understanding of numerical connectivity Van Den Heuvel [42].
The impressive neuroscientific discoveries so far have
identified more brain areas and networks involved using, multimethod
neuroimaging approaches to discover causal relationships
(Amalrick et al., 2018). Glen [43] found that neuroplasticity and
active epigenetic input of numerical exposure/talk, can improve
and reverse some numerical deficiencies (Michels, et al., 2019).
De Muoi, et al., (in press), eye tracking can help educationalists
to identify appropriate individualised teaching methods to cope
with time pressure. Dillon [44] suggest that developing relevant
games to teach children numerical skills, and approximate
number systems have positive and long-lasting improvements
Khanum [45]. Researchers using tRNS, found improvements in
brain connectivity and numerical performance Popescu [46],
Pasqualotto [47]. Scientific advances are usually made sequentially
Kuhn [48], Lakatos [49], Popper [50]. Investigating genetic, and
epigenetics Kovas [51] are essential additions to neuroscientists.
Neuroimaging is essential but not sufficient, to achieve nomological
validity Hagger [52]. Combining new genetics with neuroscientific
research provide more power to advance our understanding and
models which can explain provisionally the etiology of genetic and
phenotypic numerical behaviours [53,54-75].
Hurford JR (1987) Language and Number: The Emergence of a Cognitive System. Blackwell, Oxford, UK.
Bynner J, Parsons S (1997) Does Numeracy Matter? Evidence from the National Child Development Study on the Impact of Poor Numeracy on Adult Life. Basic Skills Agency, England, UK.
Bynner J, Parsons S (2006) New Light on Literacy and Numeracy. National Research and Development Centre for Adult Literacy and Numeracy.
Gioia DA, Pitre E (1990) Multiparadigm Perspectives on Theory Building. Academy of Management Review 15(4): 584-602.
Hsee CK (1996) Attribute Evaluability: Its Implications for Joint-Separate Evaluation Reversals and Beyond. Organizational Behavior and Human Decision Processes 67(3): 247-257.
Cohen Kadosh R, Cohen Kadosh K, Kaas A, Henik A, Goebel R (2007) Notation-Dependent and -Independent Representations of Numbers in the Parietal Lobes. Neuron 53(2): 307-314.
Artemenko C, Soltanlou M, Ehlis AC, Nuerk HC, Dresler T (2018) The neural correlates of mental arithmetic in adolescents: a longitudinal fins study. Behavioral and Brain Functions 14(1): 1-13.
Adams JW, Barmby P, Mesoudi A (2017) The Nature and Development of Mathematics: Cross Disciplinary Perspectives on Cognition, Learning and Culture. Routledge, London.
Care E, Kim H, Anderson K, Gustafsson Wright E (2017) Skills for a Changing World: National Perspectives and the Global Movement. DC: The Brookings Institution Washington, US.
Day M, Boardman MC, Krueger NF (2017) Handbook of Research Methodologies and Design in Neuroentrepreneurship. Edward Elgar Publishing Ltd. Cheltenham, UK.
Dehaene S (2011) The Number Sense: How the Mind Creates Mathematics, Revised and Updated Edition. Oxford University Press, NY, USA.
Sabates R, Parsons S (2012) The contribution of basic skills to health-related outcomes during adulthood: evidence from the BCS70. Department for Business, Innovation and Skills, London, England.