Why Mental Arithmetic Counts: Brain activation during single digit arithmetic predicts high-school math scores – Cover Page

Date: 2013-1-6

OPUSeJ reference number: OPUSeJ 201301061634WMA

Article: http://www.jneurosci.org/content/33/1/156.full.

Forum: http://www.opusej.org/library/why-mental-arithmetic-counts-brain-activation-during-single-digit-arithmetic-predicts-high-school-math-scores-forum/.

Title: Why Mental Arithmetic Counts: Brain activation during single digit arithmetic predicts high-school math scores

Authors: Gavin Price, Michele Mazzocco, Daniel Ansari,

Abstract: Do individual differences in the brain mechanisms for arithmetic underlie variability in high-school mathematical competence? Using functional magnetic resonance imaging (fMRI), we correlated brain responses to single digit calculation with standard scores on the Preliminary Scholastic Aptitude Test (PSAT) math subtest in high-school seniors. PSAT math scores, while controlling for PSAT Critical Reading scores, correlated positively with calculation activation in the left supramarginal gyrus and bilateral anterior cingulate cortex, brain regions known to be engaged during arithmetic fact retrieval. At the same time, greater activation in the right intraparietal sulcus (IPS) during calculation, a region established to be involved in numerical quantity processing, was related to lower PSAT math scores. These data reveal that the relative engagement of brain mechanisms associated with procedural versus memory-based calculation of single-digit arithmetic problems is related to high-school level mathematical competence, highlighting the fundamental role that mental arithmetic fluency plays the acquisition of higherlevel mathematical competence.

Author bio: G R. Price at the time of this study was at the Numerical Cognition Laboratory, Department of Psychology, Western University, London, Ontario, Canada and is currently at the Department of Psychology & Human Development, Peabody College, Vanderbilt University.

D Ansari iat the time of this study was at the Numerical Cognition Laboratory, Department of Psychology, Western University, London, Ontario, Canada and is currently Canada Research Chair in Developmental Cognitive Neuroscience, Department of Psychology, Brain and Mind Institute, Western University, London, Ontario, Canada.

M M M Mazzocco at the time of this study was at the Department of Psychiatry and Behavioral Sciences, and School of Education, Johns Hopkins University, Baltimore, Maryland, USA, and is currently at the Institute of Child Development, University of Minnesota.

Affiliations/disclaimers/funding/acknowledgements: Western University, London, Ontario, Canada and Johns Hopkins University, Baltimore, Maryland, USA. The authors declare no competing financial interests. This research was supported by funding from the Canadian Institutes of Health Research (CIHR), The Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Research Chairs Program (CRC) to DA, and Ontario Ministry of Research and Innovation (OMRI) Postdoctoral Fellowship to GRP. The authors would like to thank Carolyn Ahart who oversaw efforts to obtain the PSAT data, Kate Semeniak for assistance with collection of behavioral data, and Bea Goffin for proof reading the manuscript.

Subject: Science/neuroscience and Education/math aptitude

Keywords: functional magnetic resonance imaging (fMRI), Preliminary Scholastic Aptitude Test (PSAT), arithmetic, left supramarginal gyrus, bilateral anterior cingulate cortex, right intraparietal sulcus, brain, mathematical competence.

Language: English


Ashcraft MH (1982) “The development of mental arithmetic: A chronometric approach”. Developmental Review 2:213–236.

Botvinick MM, Cohen JD, Carter CS (2004) “Conflict monitoring and anterior cingulate cortex: an update”. Trends in cognitive sciences 8:539–546.

Carew TJ, Magsamen SH (2010) “Neuroscience and education: an ideal partnership for producing evidence-based solutions to Guide 21(st) Century Learning”. Neuron 67:685–688

Cho S, Ryali S, Geary DC, Menon V (2011) “How does a child solve 7+8? Decoding brain activity patterns associated with counting and retrieval strategies”. Developmental Science 5

Church J a, Balota D a, Petersen SE, Schlaggar BL (2011) “Manipulation of length and lexicality localizes the functional neuroanatomy of phonological processing in adult readers”. Journal of cognitive neuroscience 23:1475–1493

Cohen Kadosh R, Lammertyn J, Izard V (2008) “Are numbers special? An overview of chronometric, neuroimaging, developmental and comparative studies of magnitude representation”. Progress in Neurobiology 84:132–147.

CollegeBoard (2008) Who takes the PSAT/NMSQT?

De Smedt B, Holloway ID, Ansari D (2010) “Effects of problem size and arithmetic operation on brain activation during calculation in children with varying levels of arithmetical fluency”. NeuroImage 57:771–781

Dehaene S, Piazza M, Pinel P, Cohen L (2003) “Three Parietal Circuits for Number Processing”. Cognitive Neuropsychology 20:487–506.

Delazer M (2003) “Learning complex arithmetic—an fMRI study”. Cognitive Brain Research 18:76–88

Delazer M, Domahs F, Bartha L, Brenneis C, Lochy A, Trieb T, Benke T (2003) “Learning complex arithmetic–an fMRI study”. Brain Res Cogn Brain Res 18:76–88

Delazer M, Ischebeck a, Domahs F, Zamarian L, Koppelstaetter F, Siedentopf CM, Kaufmann L, Benke T, Felber S (2005) “Learning by strategies and learning by drill–evidence from an fMRI study”. NeuroImage 25:838–849  23

Dumontheil I, Klingberg T (2011) Brain Activity during a Visuospatial Working Memory Task Predicts Arithmetical Performance 2 Years Later. Cerebral cortex (New York, NY­: 1991)

Duncan GJ, Dowsett CJ, Claessens A, Magnuson K, Huston AC, Klebanov P, Pagani LS, Feinstein L, Engel M, Brooks-Gunn J, Sexton H, Duckworth K, Japel C (2007) “School readiness and later achievement”. Developmental psychology 43:1428–1446

Forman SD, Fitzgerald M, Eddy WF, Mintun MA, Noll DC (1995) “Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a clustersize threshold”. Magentic Resonance Medicine 33:636–647.

Friston KJ, Fletcher P, Joseph O, Holmes A, Rugg MD, Turner R (1998) “Event-related fMRI: characterizing differential responses”. Neuroimage 7:30–40.

Geary DC (1993) “Mathematical disabilities: cognitive, neuropsychological, and genetic components”. Psychol Bull 114:345–362

Geary DC, Brown SC, Samaranayake VA (1991) “Cognitive addition: A short longitudinal study of strategy choice and speed-of-processing differences in normal and mathematically disabled children”. 27:787–797.

Goebel R, Esposito F, Formisano E (2006) “Analysis of functional image analysis contest (FIAC) data with brainvoyager QX: From single-subject to cortically aligned group general linear model analysis and self-organizing group independent component analysis”. Human Brain Mapping 27:392–401.

Grabner RH, Ansari D, Koschutnig K, Reishofer G, Ebner F (2011) “The function of the left angular gyrus in mental arithmetic: Evidence from the associative confusion effect. Human brain mapping 000”. Available at: http://www.ncbi.nlm.nih.gov/pubmed/22125269.  [Accessed July 17, 2012].

Grabner RH, Ansari D, Koschutnig K, Reishofer G, Ebner F, Neuper C (2009) “To retrieve or to calculate? Left angular gyrus mediates the retrieval of arithmetic facts during problem solving. Neuropsychologia 47:604–608.

Grabner RH, Ansari D, Reishofer G, Stern E, Ebner F, Neuper C (2007) “Individual differences in mathematical competence predict parietal brain activation during mental calculation”. Neuroimage 38:346–356

Halberda J, Mazzocco MMM, Feigenson L (2008) “Individual differences in non-verbal number acuity correlate with maths achievement”. Nature 455:665–668.

Holloway ID, Price GR, Ansari D (2010) “Common and segregated neural pathways for the processing of symbolic and nonsymbolic numerical magnitude: An fMRI study”. Neuroimage 49:1006–1017.

Kim KK, Karunanayaka P, Privitera MD, Holland SK, Szaflarski JP (2011) “Semantic association investigated with functional MRI and independent component analysis”. Epilepsy & Behavior­: E&B 20:613–622.

Klein D, Braams BJ, Parker T, Quirk W, Wilson WS (2005) The State of Math Standards. Washington, D.C.

Libertus ME, Feigenson L, Halberda J (2011) “Preschool acuity of the approximate number system correlates with school math ability”. Developmental Science: DOI: 10.1111/j.14677687.2011.01080.x.

Mazzocco MMM, Devlin KT, McKenney SJ (2008) “Is it a fact? Timed arithmetic performance of children with mathematical learning disabilities (MLD) varies as a function of how MLD is defined”. Developmental neuropsychology 33:318–344.

Mazzocco MMM, Feigenson L, Halberda J (2011) “Preschoolers’ Precision of the Approximate Number System Predicts Later School Mathematics Performance” Santos L, ed. PLoS ONE 6:e23749 Available at: http://dx.plos.org/10.1371/journal.pone.0023749.  [Accessed September 15, 2011].

Mazzocco MMM, Myers GF (2003) “Complexities in identifying and defining mathematics learning disability in the primary school-age years”. Annals of Dyslexia 53:218–253.

Menon V, Rivera SM, White CD, Glover GH, Reiss AL (2000) Dissociating Prefrontal and Parietal Cortex Activation during Arithmetic Processing. Online 365:357–365.

Moyer RS, Landauer TK (1967) “Time required for judgements of numerical inequality”. Nature 215:1519–1520.

Mussolin C, De Volder A, Grandin C, Schlogel X, Nassogne MC, Noel MP (2009) “Neural Correlates of Symbolic Number Comparison in Developmental Dyscalculia”. Journal of cognitive neuroscience:1–15.

NAS (2007) Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future. (Committee on Prospering in the Global Economy of the 21st Century and Committee on Science, Engineering and PP, ed). Washington, D.C: National Academy Press.

OECD (2010) The High Cost of Low Education Performance: The Long-Run Economic Impact of Improving Educational Outcomes. Paris.

Ostad SA (1998) “Developmental differences in solving simple arithmetic word problems and simple number-fact problems: A comparison of mathematically normal and mathematically disabled children”. Mathematical Cognition 4. 25.

Parsons S, Bynner J (2005) “Does numeracy matter more?” NRDC (National Research and Development Centre for adult literacy and numeracy) [aRCK].

Pinel P, Dehaene S, Rivière D, LeBihan D (2001) “Modulation of parietal activation by semantic distance in a number comparison task”. NeuroImage 14:1013–1026.

Price GR, Holloway I, Räsänen P, Vesterinen M, Ansari D (2007) “Impaired parietal magnitude processing in developmental dyscalculia”. Current Biology 17:1042–1043.

Rivera SM, Reiss AL, Eckert MA, Menon V (2005) “Developmental Changes in Mental Arithmetic­: Evidence for Increased Functional Specialization in the Left Inferior Parietal Cortex”. Cerebral Cortex:1779–1790.

Rueckert L, Lange N, Partiot A, Appollonio I, Litvan I, Le Bihan D, Grafman J (1996) “Visualizing cortical activation during mental calculation with functional MRI”. Neuroimage 3:97–103.

Russell RL, Ginsburg HP (1984) “Cognitive analysis of children’s mathematical difficulties”. Cognition & Instruction 1:217–244.

Talairach J, Tournoux P (1988) Co-planar atlas of the human brain. New York: Thieme.

Updegraff KA, Eccles JS, Barber BA, O’Brien KM (1996) “Course Enrollment As Self Regulatory Behaviour: Who takes optional high school math courses?” 1Learning and Individual Differences 8:239–259.

Wiener M, Hamilton R, Turkeltaub P, Matell MS, Coslett HB (2010a) “Fast forward: supramarginal gyrus stimulation alters time measurement”. Journal of cognitive neuroscience 22:23–31.

Wiener M, Turkeltaub PE, Coslett HB (2010b)”Implicit timing activates the left inferior parietal cortex”. Neuropsychologia 48:3967–3971.


1) Price, GR , Mazzocco, MMM & Ansari, D, 2013, “Why Mental Arithmetic Counts: Brain Activation during Single Digit Arithmetic Predicts High School Math Scores”, The Journal for Neuroscience 33:1, 156-163. doi: 10.1523/JNEUROSCI.2936-12.2013.http://www.jneurosci.org/content/33/1/156.full.


Leave a Reply