Lifespan Informatics & Neuroimaging Center
Innovation in data science and translational neuroscience to understand brain development and mental illness
Our research uses advanced analytics to integrate complex brain images and rich behavioral data. Ultimately, we seek to map normal brain development and understand how alterations in brain maturation increase risk of psychiatric illness.
Network Development Supports the Emergence of Hierarchy and Cognition
Using multi-scale personalized functional networks in a large sample of youth, we demonstrate that developmental shifts in inter-network coupling systematically adhered to and strengthened a functional hierarchy of cortical organization. Furthermore, we demonstrate that network maturation had clear behavioral relevance: the development of coupling in unimodal and transmodal networks dissociably mediated the emergence of executive function.
Curation of BIDS (CuBIDS)
CuBIDS is a neuroinformatics workflow and open-source Python-based software package designed to facilitate reproducible curation of neuroimaging data. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad––a version control software package for data––to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS also helps users summarize, categorize, and visualize the metadata heterogeneity present in their BIDS data, test pipelines on their dataset's entire parameter space, and perform metadata-based quality control. The documentation for CuBIDS is available at https://cubids.readthedocs.io/en/latest/, and our package is available for download on the Python Package Manager (pypi): https://pypi.org/project/cubids/
Sex Differences in Association Network Topography
We identified normative developmental sex differences in the functional topography of personalized association networks including the ventral attention network and default mode network. Furthermore, chromosomal enrichment analyses revealed that sex differences in multivariate patterns of functional topography were spatially coupled to the expression of X- linked genes as well as astrocytic and excitatory neuronal cell-type signatures. These results highlight the role of sex as a biological variable in shaping functional brain 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.