title: Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses.
abstract: Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.
authors.affiliation: Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States.
authors.forename: Leila
authors.initials: L
authors.lastname: Wehbe
authors.affiliation: School of Electronics, Electrical Engineering and Computer Science, Queen's University, Belfast, United Kingdom.
authors.forename: Brian
authors.initials: B
authors.lastname: Murphy
authors.affiliation: Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, Karnataka, India.
authors.forename: Partha
authors.initials: P
authors.lastname: Talukdar
authors.affiliation: Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States.
authors.forename: Alona
authors.initials: A
authors.lastname: Fyshe
authors.affiliation: Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States.
authors.forename: Aaditya
authors.initials: A
authors.lastname: Ramdas
authors.affiliation: Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States.
authors.forename: Tom
authors.initials: T
authors.lastname: Mitchell
mesh_terms: D000293:Adolescent; D000328:Adult; D001288:Attention; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D001931:Brain Mapping; D032882:Comprehension / Q000502:physiology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007802:Language; D008279:Magnetic Resonance Imaging; D008297:Male; D011939:Mental Recall / Q000502:physiology*; D011932:Reading