Some people say that reading “Harry Potter and the Sorcerer’s Stone” taught them the importance of friends, or that easy decisions are seldom right. Carnegie Mellon University scientists used a chapter of that book to learn a different lesson: identifying what different regions of the brain are doing when people read.
Researchers from CMU’s Machine Learning Department performed functional magnetic resonance imaging (fMRI) scans of eight people as they read a chapter of that Potter book. They then analyzed the scans, cubic millimeter by cubic millimeter, for every four-word segment of that chapter. The result was the first integrated computational model of reading, identifying which parts of the brain are responsible for such subprocesses as parsing sentences, determining the meaning of words and understanding relationships between characters.
As Leila Wehbe, a Ph.D. student in the Machine Learning Department, and Tom Mitchell, the department head, report today in the online journal PLOS ONE, the model was able to predict fMRI activity for novel text passages with sufficient accuracy to tell which of two different passages a person was reading with 74 percent accuracy...