Modeling fMRI data with parsing models 
Evaluating the fit of surprisal models to MEG data in children with and without ASD 
Comparing structure and non-structure-based models of linguistic expectations with EEG data
We study the cognitive and neural processes that derive meaning from speech and text. The long-term goals are to specify the algorithms by which linguistic input is converted in to mental representations of meaning, including sentence meanings (such as propositions), word meanings (such as concepts), and social aspects of meaning. We further aim to characterize the neural circuits that implement these algorithms. We use a whole range of tools, including EEG, fMRI, MEG, and behavioral data. We apply these tools with an emphasis on natural or “every-day” language comprehension.
There are a few places to get a “birds-eyed view” of our work:
Listen to Jon and Paul Middlebrooks of the Brain Inspired Podcast discuss all things brains, language, and AI
Read our 2022 review article in Annual Reviews of Linguistics
Check out the many current projects listed on Jon’s website
Of course, there are many places to go for a deeper dive:
- Take a look at the list of our latest publications
- For the newest stuff, check out talks and posters from lab members
- Our data are openly available; use it for your own research!