Numerical Transcoding Proficiency in 10-Year-Old Schoolchildren is Associated with Gray Matter Inter-Individual Differences: A Voxel-Based Morphometry Study

Neuroanatomical, transcriptomic, and molecular correlates of math ability and their prognostic value for predicting learning outcomes

Foundational mathematical abilities, acquired in early childhood, are essential for success in our technology-driven society. Yet, the neurobiological mechanisms underlying individual differences in children's mathematical abilities and learning outcomes remain largely unexplored. Leveraging one of the largest multicohort datasets from children at a pivotal stage of knowledge acquisition, we first establish a replicable mathematical ability-related imaging phenotype (MAIP). We then show that brain gene expression profiles enriched for candidate math ability-related genes, neuronal signaling, synaptic transmission, and voltage-gated potassium channel activity contributed to the MAIP. Furthermore, the similarity between MAIP gene expression signatures and brain structure, acquired before intervention, predicted learning outcomes in two independent math tutoring cohorts. These findings advance our knowledge of the interplay between neuroanatomical, transcriptomic, and molecular mechanisms underlying mathematical ability and reveal predictive biomarkers of learning. Our findings have implications for the development of personalized education and interventions.

Identifying the Neural Bases of Math Competence Based on Structural and Functional Properties of the Human Brain

Human populations show large individual differences in math performance and math learning abilities. Early math skill acquisition is critical for providing the foundation for higher quantitative skill acquisition and succeeding in modern society. However, the neural bases underlying individual differences in math competence remain unclear. Modern neuroimaging techniques allow us to not only identify distinct local cortical regions but also investigate large-scale neural networks underlying math competence both structurally and functionally. To gain insights into the neural bases of math competence, this review provides an overview of the structural and functional neural markers for math competence in both typical and atypical populations of children and adults. Although including discussion of arithmetic skills in children, this review primarily focuses on the neural markers associated with complex math skills. Basic number comprehension and number comparison skills are outside the scope of this review. By synthesizing current research findings, we conclude that neural markers related to math competence are not confined to one particular region; rather, they are characterized by a distributed and interconnected network of regions across the brain, primarily focused on frontal and parietal cortices. Given that human brain is a complex network organized to minimize the cost of information processing, an efficient brain is capable of integrating information from different regions and coordinating the activity of various brain regions in a manner that maximizes the overall efficiency of the network to achieve the goal. We end by proposing that frontoparietal network efficiency is critical for math competence, which enables the recruitment of task-relevant neural resources and the engagement of distributed neural circuits in a goal-oriented manner. Thus, it will be important for future studies to not only examine brain activation patterns of discrete regions but also examine distributed network patterns across the brain, both structurally and functionally.

Gray matter volume in left intraparietal sulcus predicts longitudinal gains in subtraction skill in elementary school

Although behavioral studies show large improvements in arithmetic skills in elementary school, we do not know how brain structure supports math gains in typically developing children. While some correlational studies have investigated the concurrent association between math performance and brain structure, such as gray matter volume (GMV), longitudinal studies are needed to infer if there is a causal relation. Although discrepancies in the literature on the relation between GMV and math performance have been attributed to the different demands on quantity vs. retrieval mechanisms, no study has experimentally tested this assumption. We defined regions of interests (ROIs) associated with quantity representations in the bilateral intraparietal sulcus (IPS) and associated with the storage of arithmetic facts in long-term memory in the left middle and superior temporal gyri (MTG/STG), and studied associations between GMV in these ROIs and children's performance on operations having greater demands on quantity vs. retrieval mechanisms, namely subtraction vs. multiplication. The aims of this study were threefold: First, to study concurrent associations between GMV and math performance, second, to investigate the role of GMV at the first time-point (T1) in predicting longitudinal gains in math skill to the second time-point (T2), and third, to study whether changes in GMV over time were associated with gains in math skill. Results showed no concurrent association between GMV in IPS and math performance, but a concurrent association between GMV in left MTG/STG and multiplication skill at T1. This association showed that the higher the GMV in this ROI, the higher the children's multiplication skill. Results also revealed that GMV in left IPS and left MTG/STG predicted longitudinal gains in subtraction skill only for younger children (approximately 10 years old). Whereas higher levels of GMV in left IPS at T1 predicted larger subtraction gains, higher levels of GMV in left MTG/STG predicted smaller gains. GMV in left MTG/STG did not predict longitudinal gains in multiplication skill. No significant association was found between changes in GMV over time and longitudinal gains in math. Our findings support the early importance of brain structure in the IPS for mathematical skills that rely on quantity mechanisms.

Associations Between Individual Differences in Mathematical Competencies and Surface Anatomy of the Adult Brain

Previously conducted structural magnetic resonance imaging (MRI) studies on the neuroanatomical correlates of mathematical abilities and competencies have several methodological limitations. Besides small sample sizes, the majority of these studies have employed voxel-based morphometry (VBM)-a method that, although it is easy to implement, has some major drawbacks. Taking this into account, the current study is the first to investigate in a large sample of typically developed adults the associations between mathematical abilities and variations in brain surface structure by using surface-based morphometry (SBM). SBM is a method that also allows the investigation of brain morphometry by avoiding the pitfalls of VBM. Eighty-nine young adults were tested with a large battery of psychometric tests to measure mathematical competencies in four different areas: (1) simple arithmetic; (2) complex arithmetic; (3) higher-order mathematics; and (4) numerical intelligence. Also, we asked participants for their mathematics grades for their final school exams. Inside the MRI scanner, we collected high-resolution T1-weighted anatomical images from each subject. SBM analyses were performed with the computational anatomy toolbox (CAT12) and indices for cortical thickness, for cortical surface complexity, for gyrification, and sulcal depth were calculated. Further analyses revealed associations between: (1) the cortical surface complexity of the right superior temporal gyrus and numerical intelligence; (2) the depth of the right central sulcus and adults' ability to solve complex arithmetic problems; and (3) the depth of the left parieto-occipital sulcus and adults' higher-order mathematics competence. Interestingly, no relationships with previously reported brain regions were observed, thus, suggesting the importance of similar research to confirm the role of the brain regions found in this study.

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

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.

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

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.

Proof of principle: Transformation approach alters caudate nucleus volume and structure-function associations

Brain magnetic resonance image (MRI) registration alters structure orientation, size, and/or shape. To determine whether linear registration methods (image transformation to 6, 9, and 12° of freedom) alter structural volume and cognitive associations, we examined transformation alterations to the caudate nucleus within individuals diagnosed with Parkinson's disease (PD) and demographically matched non-PD peers. Volumes from native and six were expected be significantly different from 9 and 12° of freedom methods. Caudate nucleus volumes were expected to be associated with measures of processing speed and mental flexibility, but the strength of the association based on transformation approach was unknown. MRI brain scans from individuals with Parkinson's disease (n = 40) and age-matched controls (n = 40) were transformed using 6, 9, and 12° of freedom to an average brain template. Correlations controlling for total intracranial volume assessed expected structural-behavioral associations. Volumetric: Raw 9 and 12° transformed volumes were significantly larger than native and 6° volumes. Only 9 and 12° volumes revealed group differences with PD less than controls. Intracranial volume considerations were essential for native and 6° between group comparisons. Structural-Behavioral: The 9 and 12° caudate nucleus volume transformations revealed the expected brain-behavioral associations. Linear registration techniques alter volumetric and cognitive-structure associations. The study highlights the need to communicate transformation approach and group intracranial volume considerations.

Changes in cortical thickness in 6-year-old children open their mind to a global vision of the world

Even if objectively presented with similar visual stimuli, children younger than 6 years of age exhibit a strong attraction to local visual information (e.g., the trees), whereas children older than 6 years of age, similar to adults, exhibit a visual bias toward global information (e.g., the forest). Here, we studied the cortical thickness changes that underlie this bias shift from local to global visual information. Two groups, matched for age, gender, and handedness, were formed from a total of 30 children who were 6 years old, and both groups performed a traditional global/local visual task. The first group presented a local visual bias, and the other group presented a global visual bias. The results indicated that, compared with the local visual bias group, children with a global visual bias exhibited (1) decreased cortical thickness in the bilateral occipital regions and (2) increased cortical thickness in the left frontoparietal regions. These findings constitute the first structural study that supports the view that both synaptic pruning (i.e., decreased cortical thickness) and expansion mechanisms (i.e., increased cortical thickness) cooccur to allow healthy children to develop a global perception of the visual world.

Altered structural covariance of the striatum in functional dyspepsia patients

BACKGROUND

Functional dyspepsia (FD) is thought to be involved in dysregulation within the brain-gut axis. Recently, altered striatum activation has been reported in patients with FD. However, the gray matter (GM) volumes in the striatum and structural covariance patterns of this area are rarely explored. The purpose of this study was to examine the GM volumes and structural covariance patterns of the striatum between FD patients and healthy controls (HCs).

METHODS

T1-weighted magnetic resonance images were obtained from 44 FD patients and 39 HCs. Voxel-based morphometry (VBM) analysis was adopted to examine the GM volumes in the two groups. The caudate- or putamen-related regions identified from VBM analysis were then used as seeds to map the whole brain voxel-wise structural covariance patterns. Finally, a correlation analysis was used to investigate the effects of FD symptoms on the striatum.

KEY RESULTS

The results showed increased GM volumes in the bilateral putamen and right caudate. Compared with the structural covariance patterns of the HCs, the FD-related differences were mainly located in the amygdala, hippocampus/parahippocampus (HIPP/paraHIPP), thalamus, lingual gyrus, and cerebellum. And significant positive correlations were found between the volumes in the striatum and the FD duration in the patients.

CONCLUSIONS & INFERENCES

These findings provided preliminary evidence for GM changes in the striatum and different structural covariance patterns in patients with FD. The current results might expand our understanding of the pathophysiology of FD.

Individual structural differences in left inferior parietal area are associated with schoolchildrens' arithmetic scores

Arithmetic skill is of critical importance for academic achievement, professional success and everyday life, and childhood is the key period to acquire this skill. Neuroimaging studies have identified that left parietal regions are a key neural substrate for representing arithmetic skill. Although the relationship between functional brain activity in left parietal regions and arithmetic skill has been studied in detail, it remains unclear about the relationship between arithmetic achievement and structural properties in left inferior parietal area in schoolchildren. The current study employed a combination of voxel-based morphometry (VBM) for high-resolution T1-weighted images and fiber tracking on diffusion tensor imaging (DTI) to examine the relationship between structural properties in the inferior parietal area and arithmetic achievement in 10-year-old schoolchildren. VBM of the T1-weighted images revealed that individual differences in arithmetic scores were significantly and positively correlated with the gray matter (GM) volume in the left intraparietal sulcus (IPS). Fiber tracking analysis revealed that the forceps major, left superior longitudinal fasciculus (SLF), bilateral inferior longitudinal fasciculus (ILF) and inferior fronto-occipital fasciculus (IFOF) were the primary pathways connecting the left IPS with other brain areas. Furthermore, the regression analysis of the probabilistic pathways revealed a significant and positive correlation between the fractional anisotropy (FA) values in the left SLF, ILF and bilateral IFOF and arithmetic scores. The brain structure-behavior correlation analyses indicated that the GM volumes in the left IPS and the FA values in the tract pathways connecting left IPS were both related to children's arithmetic achievement. The present findings provide evidence that individual structural differences in the left IPS are associated with arithmetic scores in schoolchildren.