In the last 20 years, neuroimaging methods like electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have made strides in providing new measures of infant cognition. Yet, task-based fMRI has not made the same progress. Indeed, fMRI’s value might be greater in infants than adults, given that there are so few options for assessing the mind in infants. We strive to push forward methods for conducting fMRI with awake, behaving infants. As part of this effort, I have published a protocol for collecting large quantities of high-quality data from infants and released the data and software associated with this project.

Beyond infant fMRI, our team aims to push the limits of what information can be found in brain data. We also seek to disseminate these findings broadly and create pedagogical materials for the democratization of these methods.


Ellis, C. T., Skalaban, L. J., Yates, T. S., Bejjanki, V. R., Córdova, N. I., & Turk-Browne, N. B. (2020). Re-imagining fMRI for awake behaving infants. Nature Communications, 11, 4523. Paper, experiment_menu (display) code, infant_neuropipe_(analysis) code, Data

Ellis, C. T., Baldassano, C., Schapiro, A. C., Cai, M. B., Cohen, J. D. (2020). Facilitating open-science with realistic fMRI simulation: validation and application. PeerJ, 8, e8564. Paper, Code

Ellis, C. T., Lesnick, M., Henselman-Petrusek, G., Keller, B., & Cohen, J. D. (2019). Feasibility of topological data analysis for event-related fMRI, Network Neuroscience, 3 (3), 695-706. Paper, Code