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Liu J, Supekar K, El-Said D, de los Angeles C, Zhang Y, Chang H, Menon V. Neuroanatomical, transcriptomic, and molecular correlates of math ability and their prognostic value for predicting learning outcomes. SCIENCE ADVANCES 2024; 10:eadk7220. [PMID: 38820151 PMCID: PMC11141625 DOI: 10.1126/sciadv.adk7220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 04/29/2024] [Indexed: 06/02/2024]
Abstract
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.
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Affiliation(s)
- Jin Liu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kaustubh Supekar
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Dawlat El-Said
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlo de los Angeles
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yuan Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Hyesang Chang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
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Tablante J, Krossa L, Azimi T, Chen L. Dysfunctions associated with the intraparietal sulcus and a distributed network in individuals with math learning difficulties: An ALE meta-analysis. Hum Brain Mapp 2023; 44:2726-2740. [PMID: 36807960 PMCID: PMC10089103 DOI: 10.1002/hbm.26240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/26/2023] [Accepted: 02/09/2023] [Indexed: 02/23/2023] Open
Abstract
Math learning difficulty (MLD) is a learning disorder characterized by persistent impairments in the understanding and application of numbers independent of intelligence or schooling. The current study aims to review existing neuroimaging studies to characterize the neurobiological basis in MLD for their quantity and arithmetic dysfunctions. We identified a total of 24 studies with 728 participants through the literature. Using the activation likelihood estimate (ALE) method, we found that the most consistent neurobiological dysfunction in MLD was observed in the right intraparietal sulcus (IPS) with distinct patterns of the anterior and posterior aspects. Meanwhile, neurobiological dysfunctions were also observed in a distributed network including the fusiform gyrus, inferior temporal gyrus, insula, prefrontal cortex, anterior cingulate cortex, and claustrum. Our results suggest a core dysfunction in the right anterior IPS and left fusiform gyrus with atypically upregulated functions in brain regions for attention, working memory, visual processing, and motivation, serving as the neurobiological basis of MLD.
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Affiliation(s)
- Jonathan Tablante
- Neuroscience Program, Santa Clara University, Santa Clara, California, USA
| | - Lani Krossa
- Neuroscience Program, Santa Clara University, Santa Clara, California, USA
| | - Tannaz Azimi
- Neuroscience Program, Santa Clara University, Santa Clara, California, USA
| | - Lang Chen
- Neuroscience Program, Santa Clara University, Santa Clara, California, USA.,Department of Psychology, Santa Clara University, Santa Clara, California, USA
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McCaskey U, von Aster M, O’Gorman R, Kucian K. Persistent Differences in Brain Structure in Developmental Dyscalculia: A Longitudinal Morphometry Study. Front Hum Neurosci 2020; 14:272. [PMID: 32765241 PMCID: PMC7379856 DOI: 10.3389/fnhum.2020.00272] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 06/16/2020] [Indexed: 01/03/2023] Open
Abstract
Developmental dyscalculia (DD) is a learning disability affecting the acquisition of numerical-arithmetical skills. Affected people show persistent deficits in number processing, which are associated with aberrant brain activation and structure. Reduced gray matter has been reported in DD for the parietal cortex including the intraparietal sulcus (IPS), but also the frontal and occipito-temporal cortex. Furthermore, dyscalculics show white matter differences for instance in the inferior (ILF) and superior longitudinal fasciculus (SLF). However, the longitudinal development of these structural differences is unknown. Therefore, our goal was to investigate the developmental trajectory of gray and white matter in children with and without DD. In this longitudinal study, neuropsychological measures and T1-weighted structural images were collected twice with an interval of 4 years from 13 children with DD (8.2-10.4 years) and 10 typically developing (TD) children (8.0-10.4 years). Voxel-wise estimation of gray and white matter volumes was assessed using voxel-based morphometry for longitudinal data. The present findings reveal for the first time that DD children show persistently reduced gray and white matter volumes over development. Reduced gray matter was found in the bilateral inferior parietal lobes including the IPS, supramarginal gyri, left precuneus, cuneus, right superior occipital gyrus, bilateral inferior and middle temporal gyri, and insula. White matter volumes were reduced in the bilateral ILF and SLF, inferior fronto-occipital fasciculus (IFOF), corticospinal tracts, and right anterior thalamic radiation (ATR). Behaviorally, children with DD performed significantly worse in various numerical tasks at baseline and follow-up, corroborating persistent deficits in number processing. The present results are in line with the literature showing that children with DD have reduced gray and white matter volumes in the numerical network. Our study further sheds light on the trajectory of brain development, revealing that these known structural differences in the long association fibers and the adjacent regions of the temporal- and frontoparietal cortex persist in dyscalculic children from childhood into adolescence. In conclusion, our results underscore that DD is a persistent learning disorder accompanied by deficits in number processing and reduced gray and white matter volumes in number related brain areas.
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Affiliation(s)
- Ursina McCaskey
- Center for MR-Research, University Children’s Hospital, Zurich, Switzerland
- Children’s Research Center, University Children’s Hospital, Zurich, Switzerland
| | - Michael von Aster
- Center for MR-Research, University Children’s Hospital, Zurich, Switzerland
- Children’s Research Center, University Children’s Hospital, Zurich, Switzerland
- Clinic for Child and Adolescent Psychiatry, German Red Cross Hospitals, Berlin, Germany
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Ruth O’Gorman
- Center for MR-Research, University Children’s Hospital, Zurich, Switzerland
- Children’s Research Center, University Children’s Hospital, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Karin Kucian
- Center for MR-Research, University Children’s Hospital, Zurich, Switzerland
- Children’s Research Center, University Children’s Hospital, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
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Heidekum AE, Vogel SE, Grabner RH. Associations Between Individual Differences in Mathematical Competencies and Surface Anatomy of the Adult Brain. Front Hum Neurosci 2020; 14:116. [PMID: 32292335 PMCID: PMC7118203 DOI: 10.3389/fnhum.2020.00116] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 03/13/2020] [Indexed: 01/18/2023] Open
Abstract
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.
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Affiliation(s)
- Alexander E. Heidekum
- Educational Neuroscience, Institute of Psychology, University of Graz, Graz, Austria
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Wilkey ED, Cutting LE, Price GR. Neuroanatomical correlates of performance in a state-wide test of math achievement. Dev Sci 2018; 21:10.1111/desc.12545. [PMID: 28256036 PMCID: PMC5901957 DOI: 10.1111/desc.12545] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 12/01/2016] [Indexed: 11/30/2022]
Abstract
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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Affiliation(s)
- Eric D. Wilkey
- Department of Psychology & Human Development, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203
| | - Laurie E. Cutting
- Department of Special Education, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203
- Department of Psychology, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN, 37240
- Department of Pediatrics, Vanderbilt University School of Medicine, 2301 Vanderbilt Place, Nashville, TN, 37240
- Department of Radiology, Vanderbilt University School of Medicine, 2301 Vanderbilt Place, Nashville, TN, 37240
| | - Gavin R. Price
- Department of Psychology & Human Development, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203
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Kersey AJ, Cantlon JF. Primitive Concepts of Number and the Developing Human Brain. LANGUAGE LEARNING AND DEVELOPMENT : THE OFFICIAL JOURNAL OF THE SOCIETY FOR LANGUAGE DEVELOPMENT 2017; 13:191-214. [PMID: 30899202 PMCID: PMC6424528 DOI: 10.1080/15475441.2016.1264878] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Counting is an evolutionarily recent cultural invention of the human species. In order for humans to have conceived of counting in the first place, certain representational and logical abilities must have already been in place. The focus of this review is the origins and nature of those fundamental mechanisms that promoted the emergence of the human number concept. Five claims are presented that support an evolutionary view of numerical development: 1) number is an abstract concept with an innate basis in humans, 2) maturational processes constrain the development of humans' numerical representations between infancy and adulthood, 3) there is evolutionary continuity in the neural processes of numerical cognition in primates, 4) primitive logical abilities support verbal counting development in humans, and 5) primitive neural processes provide the foundation for symbolic numerical development in the human brain. We support these claims by examining current evidence from animal cognition, child development, and human brain function. The data show that at the basis of human numerical concepts are primitive perceptual and logical mechanisms that have evolutionary homologs in other primates and form the basis of numerical development in the human brain. In the final section of the review, we discuss some hypotheses for what makes human numerical reasoning unique by drawing on evidence from human and non-human primate neuroimaging research.
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Nemmi F, Helander E, Helenius O, Almeida R, Hassler M, Räsänen P, Klingberg T. Behavior and neuroimaging at baseline predict individual response to combined mathematical and working memory training in children. Dev Cogn Neurosci 2016; 20:43-51. [PMID: 27399278 PMCID: PMC6987694 DOI: 10.1016/j.dcn.2016.06.004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Revised: 06/28/2016] [Accepted: 06/28/2016] [Indexed: 01/06/2023] Open
Abstract
Mathematical performance is highly correlated with several general cognitive abilities, including working memory (WM) capacity. Here we investigated the effect of numerical training using a number-line (NLT), WM training (WMT), or the combination of the two on a composite score of mathematical ability. The aim was to investigate if the combination contributed to the outcome, and determine if baseline performance or neuroimaging predict the magnitude of improvement. We randomly assigned 308, 6-year-old children to WMT, NLT, WMT + NLT or a control intervention. Overall, there was a significant effect of NLT but not WMT. The WMT + NLT was the only group that improved significantly more than the controls, although the interaction NLTxWM was non-significant. Higher WM and maths performance predicted larger benefits for WMT and NLT, respectively. Neuroimaging at baseline also contributed significant information about training gain. Different individuals showed as much as a three-fold difference in their responses to the same intervention. These results show that the impact of an intervention is highly dependent on individual characteristics of the child. If differences in responses could be used to optimize the intervention for each child, future interventions could be substantially more effective.
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Affiliation(s)
- Federico Nemmi
- Department of Neuroscience, Karolinska Institutet, Retzius Väg 8, 17177 Stockholm, Sweden
| | - Elin Helander
- Department of Neuroscience, Karolinska Institutet, Retzius Väg 8, 17177 Stockholm, Sweden
| | - Ola Helenius
- National Centre for Mathematics Education, University of Gothenburg, Box 160, 40530 Gothenburg, Sweden
| | - Rita Almeida
- Department of Neuroscience, Karolinska Institutet, Retzius Väg 8, 17177 Stockholm, Sweden
| | - Martin Hassler
- Department of Psychology, Uppsala University, Uppsala, Box 1225, 75142, Sweden
| | - Pekka Räsänen
- Niilo Mäki Institute, Jyväskylä, Asemakatu 4, 40100, Finland
| | - Torkel Klingberg
- Department of Neuroscience, Karolinska Institutet, Retzius Väg 8, 17177 Stockholm, Sweden.
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Price GR, Wilkey ED, Yeo DJ, Cutting LE. The relation between 1st grade grey matter volume and 2nd grade math competence. Neuroimage 2016; 124:232-237. [PMID: 26334946 PMCID: PMC4651751 DOI: 10.1016/j.neuroimage.2015.08.046] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2015] [Revised: 07/27/2015] [Accepted: 08/20/2015] [Indexed: 11/25/2022] Open
Abstract
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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Affiliation(s)
- Gavin R Price
- Department of Psychology & Human Development, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA
| | - Eric D Wilkey
- Department of Psychology & Human Development, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA
| | - Darren J Yeo
- Department of Psychology & Human Development, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA
| | - Laurie E Cutting
- Department of Special Education, Peabody College, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA.
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Individual differences in cognitive performance and brain structure in typically developing children. Dev Cogn Neurosci 2015; 14:1-7. [PMID: 26046425 PMCID: PMC6989807 DOI: 10.1016/j.dcn.2015.05.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 04/30/2015] [Accepted: 05/01/2015] [Indexed: 11/20/2022] Open
Abstract
Individual differences in cognitive patterning is informative in understanding one's cognitive strengths and weaknesses. However, little is known about the difference in brain structures relating to individual differences in cognitive patterning. In this study, we classified typically developing children (n=277; age range, 5-16 years) into subtypes with k-means cluster analysis along with factor index scores using the Wechsler Intelligence Scale for Children (Third Edition). We then applied voxel-based morphometry to investigate whether significant gray-matter-volume differences existed among subtypes of cognitive patterns. Depending on the level of performance and cognitive patterning, we obtained six subtypes. One subtype that generally scored below average showed larger volume in the right middle temporal gyrus than the other five. On the other hand, two subtypes that achieved average levels of performance showed reverse-patterned factor index scores (one scored higher in Verbal Comprehension and Freedom from Distractibility, and the other scored lower in these two factor index scores) and had smaller volume in the right middle temporal gyrus than the other subtypes. From these results, we concluded that cognitive discrepancy was also obvious in typically developing children and that differences in cognitive patterning are represented in brain structure.
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