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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.

 
 

RECENT PUBLICATIONS

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Valerie Sydnor

Neuron

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Review: Neurodevelopment of the Association Cortices

We review how human brain maturation progresses along an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This spatiotemporal developmental program endows association cortices with a protracted period of plasticity, unique neurobiological properties, and heightened maturational variability linked to psychopathology.

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Adam Pines

bioRxiv

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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.

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Matt Cieslak

Nature Methods

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QSIPrep

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

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ted satterthwaite

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.