PI: Lang Chen
In my lab, we are generally interested in brain networks for knowledge representations using a combination of computational modeling and neuroimaging techniques. The LCCN has three main areas of research interest. First is the multimodal representations of concepts in the brain. Our experiences with objects and events are rich in different sensory modalities, and one important question is how the concepts are acquired and represented in cortical networks in the human brain. Currently, we are studying different types of concepts and representations, including daily objects, words, math, and social stimuli (faces). Second, we are interested in brain networks and representations that are important to understand cognitive deficits in children with clinical symptoms such as learning disabilities (e.g., dyslexia and dyscalculia) and autism. Third, we aim to establish deep neural network (DNN) models to understand the mechanisms of neurobiological disorders such as autism. Working in my lab involves data analysis of behavioral from both human subjects and DNN models as well as neuroimaging data (mostly fMRI). Also, you will, if you like, learn about using different programming languages. If you are interested, please complete this form.