We study the neural representations of the human brain during rich and complex naturalistic stimulation.  
 

Narrative comprehension, for example, involves the integration of information over minute-long time scales within brain regions and neural communication over short and long range connections.
 

In the lab, our aim is to map neurocognitive representations and statistics of every brain region in response to different naturalistic stimuli, such as movies and stories. We study how these stimuli transform into short- and long-term memories, and how large-scale neural communication across brain regions shapes both local and large-scale neural representations.

 

​We analyze fMRI, ECoG, and eye-tracking experiments using machine and deep learning models to study shared representations across brains and machines. Our goal is to gain insights into neural representation principles of naturalistic stimuli and their short- and long-term memory traces in both healthy and impaired individuals. 

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