The type of MRI used by Menon’s team is called an fMRI (functional magnetic resonance imaging), which measures changes in the flow of oxygenated blood from one part of the brain to another.
Like watching electricity flow between two points, the machine reveals how much one section of the brain is wired to other parts, “much like you might measure the synchronization of two different clocks,” Menon said. “The more tightly linked they are, the more learning benefits we see in these children.”
Menon believes the tighter the connections between the hippocampus and the prefrontal cortex — a part of the brain that influences decision-making and behavior — the more rapid the retrieval of stored knowledge.
The fact that a brain scan — rather than IQ or math scores — could predict how students would respond to tutoring also surprised Michael Posner, a cognitive neuroscientist at the University of Oregon
who was not involved in the study.
But Posner is convinced that the “variety of very modern imaging methods” used by Menon were accurate. “That’s one of the main reasons this study is important,” he said.
Posner was also surprised by the involvement of the hippocampus, rather than other regions of the brain, in learning math. “The hippocampus isn’t a system that one would’ve thought specific to mathematics,” Posner said.
“For me, the intriguing speculation is that the reason these areas are better in these children is not because they were born better, but because they had acquired important learning skills at an earlier age — and not necessarily mathematical skills,” Posner said. “It might say that our early education should be designed to make the child a successful learner, no matter what he or she learns.”
Menon said he hopes that someday brain MRIs — which would cost parents upward of $500 — will help guide educators about the best approaches for teaching math.
But Kobad Bugwadia, owner and director of the Mathnasium tutoring center in Campbell, isn’t so sure.
He said he thinks the results of the study are useful for understanding how the structure of the brain influences learning, but stops short of envisioning the scans as a way to predict math performance.
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