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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

bioRxiv

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Two Axes of White Matter Development

Despite decades of neuroimaging research, how white matter develops along the length of major tracts in humans remains unknown. Here, we identify fundamental patterns of white matter maturation by examining developmental variation along major, long-range cortico-cortical tracts in youth ages 5-23 years using diffusion MRI from three large-scale, cross-sectional datasets (total N = 2,710). Across datasets, we delineate two replicable axes of human white matter development. First, we find a deep-to-superficial axis, in which superficial tract regions near the cortical surface exhibit greater age-related change than deep tract regions. Second, we demonstrate that the development of superficial tract regions aligns with the cortical hierarchy defined by the sensorimotor-association axis, with tract ends adjacent to sensorimotor cortices maturing earlier than those adjacent to association cortices.

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Parker Singleton

Nature Mental Health

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An initiative for living evidence synthesis in clinical psychedelic research

Renewed interest in psychedelics as treatments for mental disorders has recently emerged, but substantial challenges remain in obtaining evidence from available data to inform clinical decision-making. This Comment explores the current landscape of clinical psychedelic research, highlighting the need for a systematic approach to evidence synthesis.

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Kahini Mehta

Imaging Neuroscience

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Post-processing fMRI with XCP-D

Functional neuroimaging is an essential tool for neuroscience research. However, post-processing is not standardized. While several options for post-processing exist, they tend not to support output from disparate pre-processing pipelines, may have limited documentation, and may not follow BIDS best practices. Here we present XCP-D, which presents a solution to these issues.

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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.

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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