Shannon Cahalan received bachelor’s degrees in brain and cognitive sciences and psychology at the University of Rochester in 2019. Following her bachelor’s degree, she spent two years working as a lab coordinator for the Mathematics, Reasoning and Learning Lab and the Language, Behavior and Brain Imaging Lab at Rutgers University-Newark. At Rutgers, she studied the neural underpinnings of reading differences in autism. Additionally, she spent several months working as a research assistant at the Kessler Foundation’s Center for Traumatic Brain Injury Research. Cahalan’s Ph.D. project is focused on social and non-social learning in autism. She is using functional neuroimaging and computational modeling to examine social and non-social learning in autism and is especially interested in studying gender differences in autism. Her position is funded by the NIH project on social and non-social learning. As such, she is overseeing the larger project goals, as well as training and mentoring fellow research assistants and undergraduate student interns in the lab on a variety of tasks including neuropsychological testing and fMRI data analysis.

Principal Investigator: Gabriela Rosenblau

Fellows: Isabella Day & Elysia Colon

Undergraduate Fellow Project:

The proposed project for the SURFiN fellow at George Washington University (GW) will be situated within a larger NIH funded project on social and non-social learning in autism. Being part of this project will afford unique opportunities such as learning to administer clinical and behavioral measures as well as running functional magnetic resonance imaging (fMRI) visits and analyzing and presenting these data. The fellow will also have the opportunity to participate in trainings on neuropsychological assessments by our licensed clinical psychologist from Children’s National Hospital.

Within the larger study, the fellow’s specific project will examine individual differences and developmental changes in social learning across autistic and typically developing adolescents (aged 8-17 years old). By the start date, we expect to have successfully collected at least 30 fMRI data sets and data collection will be ongoing during their fellowship. Under the close mentorship of Shannon Cahalan, the graduate student overseeing the larger project, and with additional supervision of principal investigator Gabriela Rosenblau, the fellow will train in collecting, preprocessing and analyzing fMRI data. They will investigate how individual differences in social learning and their neural underpinnings are modulated by age, participants’ cognitive skills (measured with neuropsychological batteries) and social skills (measured with parent-report questionnaires). Fellows will be exposed to fMRI data collection with minors, state-of-the art neuroimaging analyses pipelines such as the fMRIprep preprocessing pipelines, hands-on training in statistical analysis and the efficient presentation of scientific results in a poster presentation. Fellows will acquire technical skills such as working with Python and Matlab scripts and they will be provided the opportunity to present study results at a GW-organized student conference and at an international conference, such as the Society for Neuroscience annual meeting.