Analysis of anatomic variability in children with low mathematical skills

Zhi-gang, Han; Fuchs, Lynn S.; Davis, Nikki; Cannistraci, Christopher J.; Anderson, Adam W.; Gore, John C.; Dawant, Benoît M.

doi:10.1117/12.771214

Cited by 4 publications

(8 citation statements)

References 17 publications

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“…In contrast with previous literature linking structural integrity and functional activation patterns of the IPS with math achievement (Han et al., ; Isaacs et al., ; Lubin et al., ; Price et al., ; Ranpura et al., ; Rotzer et al., ), GM volume of the IPS was not related to TCAP math performance in the current study. The three regions observed in the present study are associated with a wide range of domain‐general cognitive abilities.…”

Section: Discussioncontrasting

confidence: 99%

“…The current study is the first to investigate the relationship between regional differences in GM volume and performance in grade-level mathematics as measured by a state-wide, school-based test of math achievement. We observed three regions in which greater regional GM volume was related to better performance on the TCAP math subtest when controlling for global brain volume, age, sex, and In contrast with previous literature linking structural integrity and functional activation patterns of the IPS with math achievement (Han et al, 2008;Isaacs et al, 2001;Lubin et al, 2013;Price et al, 2016;Ranpura et al, 2013;Rotzer et al, 2008), GM volume of the IPS was not related to TCAP math performance in the current study.…”

Section: Discussioncontrasting

confidence: 99%

“…In addition, activation of the left angular gyrus (AG) has been associated with the processing of numerical symbols (Price & Ansari, 2011), fluent retrieval of arithmetic facts (Delazer et al, 2005), and individual differences in math competence (Grabner et al, 2007). Several anatomical studies have identified structural abnormalities such as reduced grey matter (GM), abnormal sulcul geometry, and reduced white matter integrity in the bilateral IPS and surrounding white matter tracts in children with mathematical learning difficulties (Han et al, 2008;Isaacs, Edmonds, Lucas, & Gadian, 2001;Lubin et al, 2013;Rykhlevskaia, Uddin, Kondos, & Menon, 2009;Starke et al, 2013). More recently, increased GM volume of the left IPS has been shown to correlate with higher math scores in typically developing populations (Li, Hu, Wang, Weng, & Chen, 2013;Price, Wilkey, Yeo, & Cutting, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Neuroanatomical correlates of performance in a state‐wide test of math achievement

Wilkey

Cutting

Price

2017

Developmental Science

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The development of math skills is a critical component of early education and a strong indicator of later school and economic success. Recent research utilizing population-normed, standardized measures of math achievement suggest that structural and functional integrity of parietal regions, especially the intraparietal sulcus, are closely related to the development of math skills. However, it is unknown how these findings relate to in-school math learning. The present study is the first to address this issue by investigating the relationship between regional differences in grey matter (GM) volume and performance in grade-level mathematics as measured by a state-wide, school-based test of math achievement (TCAP math) in children from 3rd to 8th grade. Results show that increased GM volume in the bilateral hippocampal formation and the right inferior frontal gyrus, regions associated with learning and memory, is associated with higher TCAP math scores. Secondary analyses revealed that GM volume in the left angular gyrus had a stronger relationship to TCAP math in grades 3-4 than in grades 5-8 while the relationship between GM volume in the left inferior frontal gyrus and TCAP math was stronger for grades 5-8. These results suggest that the neuroanatomical architecture related to in-school math achievement differs from that related to math achievement measured by standardized tests, and that the most related neural structures differ as a function of grade level. We suggest, therefore, that the use of school-relevant outcome measures is critical if neuroscience is to bridge the gap to education.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Neuroanatomical correlates of performance in a state‐wide test of math achievement

Wilkey

Cutting

Price

2017

Developmental Science

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“…In line with the functional results reported above, several studies have identified structural abnormalities, such as reduced grey matter volume and abnormal sulcal geometry, in the IPS in children with mathematical learning difficulties (Cappelletti & Price, 2014; Han et al, 2008; Isaacs, Edmonds, Lucas, & Gadian, 2001; Lubin et al, 2013; Molko et al, 2003; Rotzer et al, 2007; Rykhlevskaia, Uddin, Kondos, & Menon, 2009; Starke et al, 2013). These studies show that a failure to acquire age-appropriate math skills is associated with atypical structural integrity of the IPS, suggesting again that this region is a key mechanism in the development of math competence.…”

Section: Introductionsupporting

confidence: 61%

The relation between 1st grade grey matter volume and 2nd grade math competence

et al. 2016

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Mathematical and numerical competence is a critical foundation for individual success in modern society yet the neurobiological sources of individual differences in math competence are poorly understood. Neuroimaging research over the last decade suggests that neural mechanisms in the parietal lobe, particularly the intraparietal sulcus (IPS) are structurally aberrant in individuals with mathematical learning disabilities. However, whether those same brain regions underlie individual differences in math performance across the full range of math abilities is unknown. Furthermore, previous studies have been exclusively cross-sectional, making it unclear whether variations in the structure of the IPS are caused by or consequences of the development of math skills. The present study investigates the relation between grey matter volume across the whole brain and math competence longitudinally in a representative sample of 50 elementary school children. Results show that grey matter volume in the left IPS at the end of 1st grade relates to math competence a year later at the end of 2nd grade. Grey matter volume in this region did not change over that year, and was still correlated with math competence at the end of 2nd grade. These findings support the hypothesis that the IPS and its associated functions represent a critical foundation for the acquisition of mathematical competence.

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“…The DFM has been used (Kovacevic et al, 2004; Yoon et al, 2006; Han et al, 2008) as a measure of variability in a set of image volumes. If all the volumes in a set were exactly identical, the group atlas would be identical to the volumes, and the magnitude of the deformation field would be zero.…”

Section: Methodsmentioning

confidence: 99%

Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects

Zhi-gang

Thornton‐Wells

Dykens

et al. 2012

Magnetic Resonance Imaging

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Deformation Based Morphometry (DBM) is a widely used method for characterizing anatomical differences across groups. DBM is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a DBM atlas. Although several studies have compared non-rigid registration algorithms for segmentation tasks, few studies have compared the effect of the registration algorithms on group differences that may be uncovered through DBM. In this study, we compared group atlas creation and DBM results obtained with five well-established non-rigid registration algorithms using thirteen subjects with Williams Syndrome (WS) and thirteen Normal Control (NC) subjects. The five non-rigid registration algorithms include: (1) The Adaptive Bases Algorithm (ABA); (2) The Image Registration Toolkit (IRTK); (3) The FSL Nonlinear Image Registration Tool (FSL); (4) The Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. Results indicate that the choice of algorithm has little effect on the creation of group atlases. However, regions of differences between groups detected with DBM vary from algorithm to algorithm both qualitatively and quantitatively. The unique nature of the data set used in this study also permits comparison of visible anatomical differences between the groups and regions of difference detected by each algorithm. Results show that the interpretation of DBM results is difficult. Four out of the five algorithms we have evaluated detect bilateral differences between the two groups in the insular cortex, the basal ganglia, orbitofrontal cortex, as well as in the cerebellum. These correspond to differences that have been reported in the literature and that are visible in our samples. But our results also show that some algorithms detect regions that are not detected by the others and that the extent of the detected regions varies from algorithm to algorithm. These results suggest that using more than one algorithm when performing DBM studies would increase confidence in the results. Properties of the algorithms such as the similarity measure they maximize and the regularity of the deformation fields, as well as the location of differences detected with DBM, also need to be taken into account in the interpretation process.

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Analysis of anatomic variability in children with low mathematical skills

Cited by 4 publications

References 17 publications

Neuroanatomical correlates of performance in a state‐wide test of math achievement

Neuroanatomical correlates of performance in a state‐wide test of math achievement

The relation between 1st grade grey matter volume and 2nd grade math competence

Effect of nonrigid registration algorithms on deformation-based morphometry: a comparative study with control and Williams syndrome subjects

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