DYNAMIC BRAIN PROCESSES OF READING COMPREHENSION
Reading comprehension is a complex neurobiological process. To comprehend a text, a reader’s brain needs to rapidly and flexibly coordinate communication across widespread brain networks. This communication allows readers to map a symbol to a sound, link the sound-symbol to its meaning, unite meaning across words and sentences, and ultimately build an internal representation of a text (i.e. a “situation model”). The ultimate goal of reading comprehension is to then encode relevant aspects of the situation model into long-term memory (i.e., transform “comprehension” to “learning”).
Learning from texts is one of the most complex forms of cognition, and it presents unique methodological challenges to literacy research. Brain research is one key avenue in which scientists can characterize reading comprehension: it has allowed for the identification of “hidden” reading comprehension processes that are not always captured by behavioral tests, and which are strongly predictive of reading comprehension outcomes. In some cases, these brain patterns are predictive of reading outcomes even in the absence of behavioral differences.
One key data challenge facing progress in brain-based reading comprehension characterization and enhancement is the need for high-definition neuroimaging to track dynamic processes across different types of texts. To capture the full complexity of reading comprehension, our work examines what rapid-brain network changes look like, as well as how those changes relate to long-term learning.
What are the real-time brain networks of reading comprehension?
While the brain networks responsible for reading comprehension operate on a millisecond (or less) level, brain imaging has previously been unable to keep up. Finding such data requires the unique use of high-dimensional neuroimaging data, as well as data reduction processes, to identify meaningful real-time brain signals. An MRI can tell us where processes occur, and an EEG can tell us when processes occur; however, no single modality can tell us both where and when processes occur in a data-driven manner.
Dr. Aboud's dissertation work directly addressed this challenge, and it has evolved into more dynamic operations at the NELL. By using a fused, independent-component analysis of MRI and EEG, we have been able to track adult reading comprehension brain networks at a millisecond level. We've found that in typical adults, sentence comprehension involves rapid trade-offs between widespread brain networks. These networks are related to meaning access, meaning integration, memory schema, semantic/syntactic re-appraisal, and conceptual coherence. Remember: this all takes place within one second of the sentence-final word. This work is the first to apply a fused MRI-EEG approach to language comprehension, and it has resulted in the most spatially- and temporally-refined tracking of language processes, to date.
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Our current projects use the fused MRI-EEG analysis to track real-time brain signals of reading comprehension over the course of a text. This research specifically focuses on how these signals change, and how those changes relate to reader- and text-based characteristics in adult readers.
How do our brains learn from texts over a longer period of time?
Previous literature has not explained the differences between momentary reading comprehension and longer-term learning. While readers may be able to build a situation model as they read for a few moments (“comprehension”), this may not result in long-term memory retention (“learning”). Our methods have invited readers to share what they have learned, not just read.
Of course, the definition of "learning" can vary among experiments. Previous work has demonstrated that written texts with increased-learning demand produce different dynamic brain signatures than texts with lower-learning demand. However, we noted that these projects failed to directly examine the brain signatures responsible for learning (i.e., which areas successfully encode information into long-term memory), nor did they employ high-definition neuroimaging to track where learning processes occurred.
Instead of identifying where short-term comprehension occurs, the NELL's current research scopes out the rapid brain dynamics of adults as they learn and remember new information from medical texts. Moreover, while other projects may examine a reader’s general reading comprehension ability through administering an achievement test and simple imaging, this project on the complex, real-time brain signatures of long-term learning. As we record a reader’s short- and long-term recollection of factual information, we can return to the individual’s high-definition MRI-EEG signature to the second they read the learned information. We can also compare that period to time points in which the individual failed to retain information.
Overall, our research aims to identify the individual-specific brain markers of learning in order to achieve holistic outcomes for readers. Once the appropriate targets for brain-based intervention have been scrutinized, specialists may be able to match a struggling reader to appropriate behavioral or cognitive interventions to improve literacy, and ultimately, life outcomes.
