Early math achievement and functional connectivity in the fronto-parietal network

In this study we test the hypothesis that the functional connectivity of the frontal and parietal regions that children recruit during a basic numerical task (matching Arabic numerals to arrays of dots) is predictive of their math test scores (TEMA-3; Ginsburg, 2003). Specifically, we tested 4-11-year-old children on a matching task during fMRI to localize a fronto-parietal network that responds more strongly during numerical matching than matching faces, words, or shapes. We then tested the functional connectivity between those regions during an independent task: natural viewing of an educational video that included math topics. Using this novel natural viewing method, we found that the connectivity between frontal and parietal regions during task-independent free-viewing of educational material is correlated with children's basic number matching ability, as well as their scores on the standardized test of mathematical ability (the TEMA). The correlation between children's mathematics scores and fronto-parietal connectivity is math-specific in the sense that it is independent of children's verbal IQ scores. Moreover, a control network, selective for faces, showed no correlation with mathematics performance. Finally, brain regions that correlate with subjects' overall response times in the matching task do not account for our number- and math-related effects. We suggest that the functional intersection of number-related frontal and parietal regions is math-specific.

[1]  Michelle Hampson,et al.  Connectivity–behavior analysis reveals that functional connectivity between left BA39 and Broca's area varies with reading ability , 2006, NeuroImage.

[2]  S. Dehaene,et al.  A Magnitude Code Common to Numerosities and Number Symbols in Human Intraparietal Cortex , 2007, Neuron.

[3]  Daniel Ansari,et al.  Developmental Specialization in the Right Intraparietal Sulcus for the Abstract Representation of Numerical Magnitude , 2010, Journal of Cognitive Neuroscience.

[4]  Elizabeth S Spelke,et al.  Preschool children's mapping of number words to nonsymbolic numerosities. , 2005, Child development.

[5]  Analysis of FIAC data with BrainVoyager QX : From single subject to cortically aligned group GLM analysis , 2022 .

[6]  Daniel Ansari,et al.  Age-related Changes in the Activation of the Intraparietal Sulcus during Nonsymbolic Magnitude Processing: An Event-related Functional Magnetic Resonance Imaging Study , 2006, Journal of Cognitive Neuroscience.

[7]  Mert R. Sabuncu,et al.  The influence of head motion on intrinsic functional connectivity MRI , 2012, NeuroImage.

[8]  Ron Dumont,et al.  Test of Early Mathematics Ability–Third Edition , 2008 .

[9]  Justin Halberda,et al.  Individual differences in non-verbal number acuity correlate with maths achievement , 2008, Nature.

[10]  Melissa L. Allen,et al.  Kaufman Brief Intelligence Test , 2021, Encyclopedia of Autism Spectrum Disorders.

[11]  R. Malach,et al.  Intersubject Synchronization of Cortical Activity During Natural Vision , 2004, Science.

[12]  S. Petersen,et al.  Developmental changes in human cerebral functional organization for word generation. , 2005, Cerebral cortex.

[13]  T. Hare,et al.  Changes in cerebral functional organization during cognitive development , 2005, Current Opinion in Neurobiology.

[14]  J. Talairach,et al.  Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .

[15]  Karl J. Friston,et al.  Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[16]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Daniel Ansari,et al.  Neural correlates of symbolic number processing in children and adults , 2005, Neuroreport.

[18]  E. Bullmore,et al.  Mapping Motor Inhibition: Conjunctive Brain Activations across Different Versions of Go/No-Go and Stop Tasks , 2001, NeuroImage.

[19]  Rainer Goebel,et al.  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 , 2006, Human brain mapping.

[20]  M. Corbetta,et al.  Learning sculpts the spontaneous activity of the resting human brain , 2009, Proceedings of the National Academy of Sciences.

[21]  Andreas Nieder,et al.  A Labeled-Line Code for Small and Large Numerosities in the Monkey Prefrontal Cortex , 2007, The Journal of Neuroscience.

[22]  T. Klingberg,et al.  Maturation of White Matter is Associated with the Development of Cognitive Functions during Childhood , 2004, Journal of Cognitive Neuroscience.

[23]  S. Dehaene,et al.  Abstract representations of numbers in the animal and human brain , 1998, Trends in Neurosciences.

[24]  A. Kleinschmidt,et al.  A Supramodal Number Representation in Human Intraparietal Cortex , 2003, Neuron.

[25]  Vinod Menon,et al.  What Difference Does a Year of Schooling Make? Maturation of Brain Response and Connectivity between 2nd and 3rd Grades during Arithmetic Problem Solving , 2022 .

[26]  A. Nieder.  Prefrontal cortex and the evolution of symbolic reference , 2009, Current Opinion in Neurobiology.

[27]  Archana Venkataraman,et al.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. , 2010, Journal of neurophysiology.

[28]  S. Dehaene,et al.  THREE PARIETAL CIRCUITS FOR NUMBER PROCESSING , 2003, Cognitive neuropsychology.

[29]  Kristina M. Visscher,et al.  Functional Neuroanatomical Differences Between Adults and School-Age Children in the Processing of Single Words , 2002, Science.

[30]  L. Hildman,et al.  Kaufman Brief Intelligence Test , 1993 .

[31]  Philippe Pinel,et al.  Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcus , 2004, Neuron.

[32]  Elizabeth M. Brannon,et al.  The Neural Development of an Abstract Concept of Number , 2009, Journal of Cognitive Neuroscience.

[33]  Jonathan D. Cohen,et al.  A Developmental Functional MRI Study of Prefrontal Activation during Performance of a Go-No-Go Task , 1997, Journal of Cognitive Neuroscience.

[34]  V Menon,et al.  Cerebral Cortex doi:10.1093/cercor/bhi055 Developmental Changes in Mental Arithmetic: Evidence for Increased Functional Specialization in the Left Inferior Parietal Cortex , 2005 .

[35]  Y. Miyashita,et al.  Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI. , 1999, Brain : a journal of neurology.

[36]  E. J. Carter,et al.  Functional Imaging of Numerical Processing in Adults and 4-y-Old Children , 2006, PLoS biology.

[37]  David J. Freedman,et al.  Representation of the Quantity of Visual Items in the Primate Prefrontal Cortex , 2002, Science.

[38]  Edward E. Smith,et al.  Temporal dynamics of brain activation during a working memory task , 1997, Nature.

[39]  J. Gabrieli,et al.  Immature Frontal Lobe Contributions to Cognitive Control in Children Evidence from fMRI , 2002, Neuron.

[40]  Sarah Durston,et al.  A shift from diffuse to focal cortical activity with development. , 2006, Developmental science.