Brain Signatures of Science Text Comprehension
Our Reading Brain project examines how readers of different ages and reading abilities comprehend scientific texts, and the neurocognitive mechanisms underlying successful comprehension. Our aim is to understand the critical variables, including the interaction between cognitive and linguistic abilities of the reader and knowledge structure of the text, that impact individual differences in reading comprehension. We have collected a large amount of functional and structural MRI, eye tracking, and behavioral data from school-aged monolingual English-speaking children, college-aged monolingual English-speaking adults, and bilingual Chinese-English adults.
We are making the data collected from this project available to the larger research community on OpenNeuro, in three datasets.
L1 Adult Dataset:
OpenNeuro link. Our methods document for the L1 Adults Monolingual population can be viewed here.
L2 Adult Dataset:
L1 Children Dataset:
(available at a later date)
Check out our video below to see the experimental process with which we collected our data.
Publications
Hsu, C.-H., Schloss, B., Clariana, R., & Li, P. (2019). Neurocognitive signatures of naturalistic reading of scientific texts: A fixation-related fMRI study. Scientific Reports, 9: 10678.
Li, P., & Clariana, R. (2019). Reading comprehension in L1 and L2: An integrative approach. Journal of Neurolinguistics, 50, 94-105.
Follmer, J., Fang, S., Clariana, R., Meyer, B., & Li, P (2018). What predicts adult readers’ understanding of STEM texts? Reading and Writing: An Interdisciplinary Journal, 31, 185-214.
OpenNeuro Data Sharing
Yu, A., Schloss, B., Hsu, C., Ma, L., Chang, C., Scotto, M., Seyfried, F., & Li, P. (2019). The Reading Brain Project: An open science data-sharing initiative. Poster presented at the 26th Annual Meeting of the Cognitive Neuroscience Society, San Francisco, March, 2019.
Researchers
Ping Li (PI), Roy Clariana and Bonnie Meyer (Co-PIs). Chun-Ting Hsu, Benjamin Schloss, Anya Yu, Friederike Seyfried, Lindsey Ma, and Marissa Scotto (Current Members).
Acknowledgements
We would like to acknowledge the generous support from the National Science Foundation through the NCS program (#1633817, #1533625), and members of the Brain, Language, and Computation Lab who have contributed to this project in the past in various capacities: Jake Follmer, Chih-ting Chang, Jennifer Legault, Jing Yang, Shin-Yi Fang (former graduate students or postdocs), Rose Yuratovac (former lab manager), and Tanner Quiggle, Shara Chopra and Ahmed Yumna (former undergraduate students). We also thank the Center for NMR Research of Penn State Milton S. Hershey Medical Center that has enabled the smooth collection of data reported here (Emma Cartisano, YunQing Li, Sebastian Rupprecht, Chris Sica, Qing X. Yang, Jeff Vesek, and Jian-li Wang).