An international team of researchers has developed a rather reliable test that predicts the future improvement of reading abilities in kids with dyslexia. The method uses functional MRI (fMRI) and diffusion tensor magnetic resonance imaging (DTI) to scan the brain, and data crunching software to interpret the data. The researchers hope that the finding will help parents and therapists uniquely identify which learning tools are best for each child.
From the announcement by Vanderbilt University :
The 45 children who took part in the study ranged in age from 11 to 14 years old. Each child first took a battery of tests to determine their reading abilities. Based on these tests, the researchers classified 25 children as having dyslexia, which means that they exhibited significant difficulty learning to read despite having typical intelligence, vision and hearing and access to typical reading instruction.
During the fMRI scan, the youths were shown pairs of printed words and asked to identify pairs that rhymed, even though they might be spelled differently. The researchers investigated activity patterns in a brain area on the right side of the head, near the temple, known as the right inferior frontal gyrus, noting that some of the children with dyslexia activated this area much more than others. DTI scans of these same children revealed stronger connections in the right superior longitudinal fasciculus, a network of brain fibers linking the front and rear of brain.
When the researchers once again administered the reading test battery to the youths two and a half years later, they found that the 13 youths showing the stronger activation pattern in the right inferior frontal gyrus were much more likely to have compensated for their reading difficulty than were the remaining 12 youths with dyslexia. When they combined the most common forms of data analysis across the fMRI and DTI scans, they were able to predict the youths’ outcomes years later with 72 percent accuracy.
The researchers then adapted algorithms used in artificial intelligence research to refine the brain activity data to create models that would predict the children’s later progress. Using this relatively new technique, the researchers could use the brain scanning data collected at the beginning of the study to predict with over 90 percent accuracy which children would go on to improve their reading skills two and a half years later.
In contrast, the battery of standardized, paper-and-pencil tests typically used by reading specialists did not aid in predicting which of the children with dyslexia would go on to improve their reading ability years later.
Open-access article in the Proceedings of the National Academy of Sciences (PNAS): “Neural systems predicting long-term outcome in dyslexia“
*This blog post was originally published at Medgadget*