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Learning how we learn to read

Learning how we learn to read

Last week, as the 2014 Big Data in Biomedicine conference came to a close, a related story about the importance of computing across disciplines posted on the Stanford University homepage. The article describes research making use of the new Stanford Research Computing Center, or SRCC (which we blogged about here). We’re now running excerpts from that piece about the role computation, as well as big data, plays in medical advances.

letter - smallA love letter, with all of its associated emotions, conveys its message with the same set of squiggly letters as a newspaper, novel, or an instruction manual. How our brains learn to interpret a series of lines and curves into language that carries meaning or imparts knowledge is something psychology professor Brian Wandell, PhD, has been trying to understand.

Wandell hopes to tease out differences between the brain scans of kids learning to read normally and those who are struggling, and use that information to find the right support for kids who need help. “As we acquire information about the outcome of different reading interventions we can go back to our database to understand whether there is some particular profile in the child that works better with intervention 1, and a second profile that works better with intervention 2,“ said Wandell, who is also the Isaac and Madeline Stein Family Professor and a professor (by courtesy) of electrical engineering.

His team developed a way of scanning kids’ brains with magnetic resonance imaging then knitting the million collected samples together with complex algorithms that reveal how the nerve fibers connect different parts of the brain. “If you try to do this on your laptop, it will take half a day or more for each child,” he said. Instead, he uses powerful computers to reveal specific brain changes as kids learn to read.

Wandell is associate director of the Stanford Neurosciences Institute where he is leading the effort to develop a computing strategy – one that involves making use of SRCC rather than including computing space in their planned new building. He said one advantage of having faculty share computing space and systems is to speed scientific progress. “Our hope for the new facility is that it gives us the chance to set the standards for a better environment for sharing computations and data, spreading knowledge rapidly through the community,” he said.

Previously: Personal molecular profiling detects diseases earlier, New computing center at Stanford supports big data, Teaching an old dog new tricks: New faster and more accurate MRI technique quantifies brain matter, Study shows brain scans could help identify dyslexia in children before they start to read and Stanford study furthers understanding of reading disorders
Photo by Liz West

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