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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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Audrey Luo

Nature Communications

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Functional Connectivity Development along the Sensorimotor-Association Axis

We investigated the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-assocation axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3,355; ages 5-23 years). In each dataset, the development of functional connectivity systematically varied along the S-A axis. These robust and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

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Hamsi Radhakrishnan

Human Brain Mapping

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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.

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Arielle S. Keller

Developmental Cognitive Neuroscience

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Linking the "exposome" with functional topography and cognition

Despite the importance of the environment in shaping individual differences in cognitive neurodevelopment, it has been challenging to quantify the many interconnected features of a child's environment ('exposome'). Here, we leverage a large-scale dataset to investigate to demonstrate that the exposome is associated with individual differences in functional brain network organization and cognition. We find that models trained on a single variable capturing a child′s exposome can more accurately and parsimoniously predict future cognitive performance than models trained on a wealth of personalized neuroimaging data. This highlights the importance of childhood environments in shaping neurocognitive development.

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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