Neuroimaging of the Philadelphia Neurodevelopmental Cohort

By Theodore D. Satterthwaite, Mark A. Elliott, Kosha Ruparel, James Loughead, K. Prabhakaran, Monica E. Calkins, Ryan Hopson, Chad Jackson, Jack Keefe, M. Riley and 7 more. NeuroImage, 2013

512 citations recorded by the source corpus.

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1,445 adolescents ages 8–21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development.

Subfields: Cognitive Neuroscience, Health, Toxicology and Mutagenesis, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/08e2beb9fc1b77e3d42efb7708f2649da533d93b

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Citations in the corpus

The Philadelphia Neurodevelopmental Cohort: A Publicly Available Resource for the Study of Normal and Abnormal Brain Development in Youth (2015, unknown): “While we have previously described the design of the PNC in detail (1), here we focus on the publicly available PNC datasets in dbGaP and associated data access procedures.”
Benchmarking of participant‐level confound regression strategies for the control of motion artifact in studies of functional connectivity (2017, methodology): “The task-free BOLD data used in this study (N=393) were drawn from the Philadelphia Neurodevelopmental Cohort (PNC) (Satterthwaite et al., 2014, 2016) on the basis of age, health, and data quality.”
MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection (2015, unknown): “In order to evaluate the multi-site segmentation performance of our method we created a large multi-study dataset of clinically normal subjects by pooling data from studies including BLSA (Resnick et al., 2000, 2003), ADNI-1 (Jack et al., 2008), PNC (Satterthwaite et al., 2014), BBL-NC 7 , and NiCK ”
Harmonization of multi-site diffusion tensor imaging data (2017, methodology): “Independent Dataset 2: The dataset contains 105 additional healthy participants from the PNC with a slightly older age distribution than that of Dataset 1.”