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Lifespan Informatics & Neuroimaging Center

Innovation in data science and translational neuroscience to understand brain development and mental illness

RESEARCH

  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.

Research
RecentPubs

RECENT PUBLICATIONS

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Matt Cieslak

Human Brain Mapping

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Benchmarking dMRI Head Motion Correction

We report a comprehensive evaluation of both methods on realistic simulations of a software fiber phantom that provides known ground-truth head motion. We demonstrate that both FSL's Eddy and QSIPrep's SHOREline methods perform remarkably well. However, we show that performance can be impacted by sampling scheme, the pervasiveness of head motion, and the denoising strategy applied before head motion correction. Our study also provides an open and fully-reproducible workflow that could be used to accelerate evaluation studies of other dMRI processing methods in the future.

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Chenying Zhao

Imaging Neuroscience

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BABS: workflow software for reproducible analysis

BABS is a user-friendly and generalizable Python package for reproducible image processing at scale. Leveraging DataLad and the FAIRly big framework, BABS allows the reproducible application of BIDS Apps to large-scale datasets on HPC clusters (SGE and Slurm). Comprehensive documentation of BABS can be found at: https://pennlinc-babs.readthedocs.io/

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Joëlle Bagautdinova & Josiane Bourque

Cell Reports

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Development of white matter covariance networks supports cognition

We sought to delineate the relationship between white-matter maturation and executive function, a higher-order cognitive function that undergoes extensive changes during youth. Increasingly, the field of neuroimaging is shifting toward data-driven machine-learning methods, but there have been few applications to developing white matter. Here, we leveraged machine-learning to delineate how white-matter networks develop in a large sample of youth from the Philadelphia Neurodevelopmental Cohort. We find 14 different white-matter networks that each have distinct spatial organization and maturational trajectories. These data-driven patterns of white-matter development are also linked to developmental changes in executive function, confirming that white-matter networks play a critical role in the maturation of higher-order cognition.

Ted
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ted satterthwaite

Ted is the McLure Associate Professor of Psychiatry & Behavioral Sciences 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.

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