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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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Valerie Sydnor

Nature Neuroscience

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Characterizing the Spatiotemporal Sequence of Cortical Plasticity

Leveraging intrinsic activity amplitude as a functional marker of plasticity, we find evidence for a cortical gradient of neurodevelopmental plasticity in youth. Declines in the amplitude of intrinsic activity were initiated heterochronously across regions, coupled to the maturation of a plasticity breaking factor, impacted by children’s developmental environments, and temporally staggered along a sensorimotor-association axis from ages 8 to 18.

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Chenying Zhao

Neuroimage

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ModelArray

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/

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Hamsi Radhakrishnan

bioRxiv

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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.

News

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News
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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