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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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Steven L. Meisler

bioRxiv

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ABCC Diffusion MRI Data Release

The Adolescent Brain Cognitive Development (ABCD) Study is the largest U.S. effort to track brain development in adolescence. Diffusion MRI (dMRI) offers a powerful window into white matter, but large, multi-site datasets are difficult to process and analyze. We address this with the ABCD-BIDS Community Collection (ABCC, release 3.1.0): an open resource of 24,000+ fully processed dMRI scans. ABCC includes analysis-ready data, detailed quality metrics, advanced microstructural measures, and individualized white matter tractography. Using these data, we show that newer dMRI metrics outperform traditional measures in detecting developmental change—and are more robust to differences in image quality. We also demonstrate that harmonizing data across scanners improves the consistency of findings across sites. ABCC lowers barriers to large-scale neuroimaging and provides a powerful, open foundation for studying adolescent brain development.

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Golia Shafiei

bioRxiv

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Developmental patterns of intrinsic timescale

Intrinsic timescale is a commonly used measure of spontaneous neural dynamics that quantifies the temporal window of processing in neuronal populations. It displays a hierarchical cortical organization across species and imaging modalities, with shorter timescales in sensorimotor cortex and longer timescales in association cortex. However, less is known about how intrinsic timescale evolves during human brain development. Here, we estimate intrinsic timescale in two independent youth datasets (HCPD: n=565; HBN: n=729; ages 8–22) and examine its developmental patterns. We find that changes in intrinsic timescale follow a hierarchical gradient along the sensorimotor-to-association (S–A) axis. Analysis of an independent adult dataset (HCPYA: n=973; ages 22–37) suggests this pattern stabilizes in adulthood. Together, these findings highlight intrinsic timescale as a marker of hierarchical brain maturation during development.

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Parker Singleton, Brooke Sevchik

Nature Mental Health

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Psilocybin treatment for symptoms of depression

Here, we present the results of a fully pre-registered, living systematic review on psilocybin treatment for depressive symptoms. The original studies included in our primary meta-analysis suggest promise: compared to control conditions, psilocybin showed a greater reduction in depression scores, greater treatment response, and higher remission rates. Notably, our living review will be regularly updated, with all data, code, and results openly available on our public website for the SYPRES initiative (Synthesis of Psychedelic Research Studies; sypres.io). Our continuously maintained database already includes over 200 total effect sizes, encompassing all depression timepoints and outcomes reported by arm in each of the 15 randomized controlled clinical trials included.

Ted
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ted satterthwaite

Ted is the McLure II Professor of Psychiatry & Behavioral Research 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.

Lifespan Informatics and Neuroimaging Center

Richards Research Labs, 5th Floor

3700 Hamilton Walk

Philadelphia, PA 19104

Email: sattertt@pennmedicine.upenn.edu

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