Lifespan Informatics & Neuroimaging Center
Innovation in data science and translational neuroscience to understand brain development and mental illness
ModelArray is a scalable R package for statistical analysis of fixel-wise data derived from diffusion MRI (and beyond). It supports linear and nonlinear modeling and is extensible to more models. Full documentation: https://pennlinc.github.io/ModelArray/
Establishing the Validity of CS-DSI
If you're a neuroscientist who wants to use DSI to look at some cool microstructural details but can't afford to add the extra 20 minutes of scan time to your protocol, compressed sensing might be your new best friend!
We show that CS-DSI schemes can generate white matter derivatives comparable to those generated by a full DSI scheme, allowing up to a 60% decrease in scan time with minimal loss in accuracy or reliability! This could allow both researchers and even clinicians to harness the advantages of DSI sequences that were previously impractical to deploy.
Development of Top-Down Cortical Propagations in Youth
Hierarchical processing requires activity propagating between higher and lower-order cortical areas. Here, we leveraged advances in neuroimaging and computer vision to describe propagations robustly ascend and descend the cortical hierarchy. Notably, top-down propagations become both more prevalent with cognitive control demands and with development in youth.
Ted is an Associate Professor in the Department of Psychiatry at the University of Pennsylvania Perelman School of Medicine. His research uses multi-modal neuroimaging to describe both normal and abnormal patterns of brain development, in order to better understand the origins of mental illnesses.