Stanford School of Medicine study: Brain scans may predict math ability

25 Aug

Jacob Vigdor wrote the interesting Education Next article, Solving America’s Math Problem:

American public schools have made a clear trade-off over the past few decades. With the twin goals of improving the math performance of the average student and promoting equality, it has made the curriculum more accessible. The drawback to exclusive use of this more accessible curriculum can be observed among the nation’s top-performing students, who are either less willing or less able than their predecessors or their high-achieving global peers to follow the career paths in math, science, and engineering that are the key to innovation and job creation. In the name of preparing more of the workforce to take those jobs, we have harmed the skills of those who might have created them. Although there is some evidence of a payoff from this sacrifice, in the form of marginally better performance among average students, some of the strategies used to help these students have in fact backfired…

Not all children are equally prepared to embark on a rigorous math curriculum on the first day of kindergarten, and there are no realistic policy alternatives to change this simple fact. Rather than wish differences among students away, a rational policy for the 21st century will respond to those variations, tailoring lessons to children’s needs. This strategy promises to provide the next generation of prospective scientists and engineers with the training they need to create jobs, and the next generation of workers with the skills they need to qualify for them.

One way of looking at Vigdor’s conclusions is to ask whether high performance preschool programs and early intervention can affect student achievement?

Maggie Fox of NBC News reported in the story, Brain Scans May Predict Math Gains in Children, Study Finds:

Brain scans may be able to predict which kids are likely to improve their math skills in school and which ones are not, and they do it better than IQ or math tests, researchers reported Tuesday.
The researchers have been working with a group of kids who started getting brain scans at the age of 8, and who have followed up with tests into their mid-teens.

To their surprise, the researchers found that certain patterns of brain activity when the kids were not doing anything at all at age 8 predicted how much they would improve their math skills over the years. And these scans did so with far more accuracy than did intelligence tests, reading tests or math tests, they report in the Journal of Neuroscience.
While it’s far too soon to stick every kid into a brain scanner, the findings may eventually lead to ways to identify the children who’d benefit most from intensive math coaching, the researchers said….


• Abstract

J Neurosci. 2015 Aug 19;35(33):11743-50. doi: 10.1523/JNEUROSCI.0216-15.2015.
Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children’s Numerical Abilities.
Evans TM1, Kochalka J2, Ngoon TJ2, Wu SS2, Qin S2, Battista C2, Menon V3.
Author information
Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today’s technological society. Identification of cognitive and brain markers associated with long-term growth of children’s basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children’s gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties.
Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children’s math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions.
Copyright © 2015 the authors 0270-6474/15/3511743-08$15.00/0.
• Received January 15, 2015.
• Revision received July 15, 2015.
• Accepted July 15, 2015.

Here is the press release from Stanford:

Brain scans better forecast math learning in kids than do skill tests, study finds
Gray matter volume and connections between several brain regions better forecast 8-year-olds’ acquisition of math skills than their performance on standard math tests.
Vinod Menon and his colleagues found that scans of brain structures indicated which childen would be the best math learners over the next six years.

Brain scans from 8-year-old children can predict gains in their mathematical ability over the next six years, according to a new study from the Stanford University School of Medicine.
The research tracked 43 children longitudinally for six years, starting at age 8, and showed that while brain characteristics strongly indicated which children would be the best math learners over the following six years, the children’s performance on math, reading, IQ and memory tests at age 8 did not.

The study, published online Aug. 18 in The Journal of Neuroscience, moves scientists closer to their goal of helping children who struggle to acquire math skills.
“We can identify brain systems that support children’s math skill development over six years in childhood and early adolescence,” said the study’s lead author, Tanya Evans, PhD, postdoctoral scholar in psychiatry and behavioral sciences.

“A long-term goal of this research is to identify children who might benefit most from targeted math intervention at an early age,” said senior author Vinod Menon, PhD, professor of psychiatry and behavioral sciences. “Mathematical skills are crucial in our increasingly technological society, and our new data show which brain features forecast future growth in math abilities.”
At the start of the study, the children received structural and functional magnetic resonance imaging brain scans. None of the kids had neurological or psychiatric disorders, and their intelligence fell in a range considered normal for their age. The scans were conducted while the children lay quietly in the scanner; the scans measured brain structure and intrinsic functional connections between brain regions, and were not tied to performance on any particular math task.

The 8-year-olds also took standardized tests (given outside the scanner) to measure IQ, as well as reading, math and working-memory skills. All of the children returned for at least one follow-up assessment of these skills before age 14, and many children had other additional follow-ups.

Surprising results

The scientists were surprised by the extent and nature of the connections between brain regions that predicted the development of the children’s math skills. Greater volume and connectivity of two areas forecast skill development: the ventro-temporal occipital cortex, which is a brain region that supports visual object perception, and the intra-parietal sulcus, which helps people compare and make judgements about numbers, such as understanding that four is more than three. The strength of these regions’ interconnections with the prefrontal cortex was also predictive. The work identifies a network of brain areas that provides a scaffold for long-term math skill development in children, Menon said.

The 8-year-olds’ initial IQ, reading, working-memory and math scores did not predict long-term learning in math. The lack of predictive ability of standard math tests taken at age 8 suggests that brain features more precisely predict children’s math learning, Evans said. The brain scans capture many different aspects of information processing, thus better forecasting which children will fall behind and which will excel, Menon added.
Just because a child is currently struggling doesn’t necessarily mean he or she will be a poor learner in the future.
“Next, we are investigating how brain connections change over time in children who show large versus small improvements in math skills, and designing new interventions to help children improve their short-term learning and long-term skill acquisition,” Menon said. Although it is still impractical to give brain scans to children on a large scale, the team’s studies provide a baseline understanding of normal development that will help experts develop and validate remediation programs for children with learning disabilities, he noted.
In the meantime, the team’s findings suggest that parents and teachers should encourage children to exercise their mental math muscles. “Just because a child is currently struggling doesn’t necessarily mean he or she will be a poor learner in the future,” Evans said.

Other Stanford co-authors were research assistants John Kochalka, Tricia Ngoon and Sarah Wu; instructor Shaozheng Qin, PhD; and postdoctoral scholar Christian Battista, PhD.

All brain scans were conducted at the Richard M. Lucas Center for Imaging at the School of Medicine.
The research was funded by grants from the National Institutes of Health (grants HD047520, HD059205 and HD080367), Stanford’s Child Health Research Institute, the Lucile Packard Foundation for Children’s Health, Stanford’s Clinical and Translational Science Award (NIH grant UL1RR025744) and the Netherlands Organization for Scientific Research. Menon is a member of Stanford’s Child Health Research Institute.
Information about Stanford’s Department of Psychiatry and Behavioral Sciences, which also supported the research, is available at

Because the ranks of poor children are growing in the U.S., this study portends some grave challenges not only for particular children, but this society and this country. Adequate early learning opportunities and adequate early parenting is essential for proper development in children.


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Is an individualized program more effective in math learning?                                                                           

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