A bit skeptic: Brain activity can be used to predict reading success up to 2 years in advance

This is a study that is both interesting and a bit… well, scary and/or making me skeptic: by measuring brainwaves, it is possible to predict what a child’s reading level will be years in advance, according to research from Binghamton University, State University of New York. The longitudinal study on 75 children did try to measure a lot. Why am I skeptic? Well, it’s rather correlational than clear causal. But also the prediction is one thing, but what can we do with the prediction? The researchers state that it could help to detect pupils who need extra help early, but again: isn’t that assuming that we can alter something? There is also the question how absolute the prediction is and if this is the cheapest solution in the long run. Don’t get me wrong, it’s not my goal to undermine this study, but just some thoughts.

From the press release:

Binghamton University researchers Sarah Laszlo and Mallory Stites measured the brain activity of children and then compared it to their report cards, their vocabulary and other signs of reading success two years later, as part of the National Science Foundation-funded Reading Brain Project. Laszlo and Stites used event-related potentials (ERPs) to determine that brain activity was different in children who showed reading success in later years than in children that did not.

“Your brain is what allows you to do everything, from math to designing buildings to making art,” said Laszlo, associate professor of psychology at Binghamton University. “If we look at what the brain is doing during reading, it is a really good predictor of how reading will develop.”

The children read a list of words silently to themselves. Every so often they would come across their own name to make sure they were understanding the text and paying attention. Children that had better report cards tended to show different patterns of activity during both phonological (sound) and semantic (meaning) processing..

“Phonological processing is the ability to sound things out and semantic processing is knowing what words mean,” said Laszlo. “Like being able to link the word fish with a slimy creature that swims underwater.”

Other factors were included when measuring the reading success of students, such as their teachers, their parents’ encouragement, their age and the amount that they read at home.

“The thing that is really valuable about this is that once kids starting having trouble with reading, they start needing extra help, which can be hard and stigmatizing for the child and often not effective,” said Laszlo. “By using long-range predictions about success, we can give them the extra help they need before they fall behind.”

The team is currently working on a paper to record the findings from the first four years of this research. At the end of the fifth year, Laszlo and her team will look back to see what predictions can be made regarding ERP’s and reading progress.

The paper, “Time will tell: A longitudinal investigation of brain-behavior relationships during reading development,” was published in Psychophysiology.

Abstract of the study:

ERPs are a powerful tool for the study of reading, as they are both temporally precise and functionally specific. These are essential characteristics for studying a process that unfolds rapidly and consists of multiple, interactive subprocesses. In work with adults, clear, specific models exist linking components of the ERP with individual subprocesses of reading including orthographic decoding, phonological processing, and semantic access (e.g., Grainger & Holcomb, 2009). The relationships between ERP components and reading subprocesses are less clear in development; here, we address two questions regarding these relationships. First, we ask whether there are ERP markers that predict future reading behaviors across a longitudinal year. Second, we ask whether any relationships observed between ERP components and reading behavior across time map onto the better-established relationships between ERPs and reading subprocesses in adults. To address these questions, we acquired ERPs from children engaging in a silent reading task and then, a year later, collected behavioral assessments of their reading ability. We find that ERPs collected in Year 1 do predict reading behaviors a year later. Further, we find that these relationships do conform, at least to some extent, to relationships between ERP components and reading subprocesses observed in adults, with, for example, N250 amplitude in Year 1 predicting phonological awareness in Year 2, and N400 amplitude in Year 1 predicting vocabulary in Year 2.


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