Data from: Simultaneously uncovering the patterns of the brain regions involved in different story reading subprocesses

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.