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Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.
Weinstein, Sarah M; Tu, Danni; Hu, Fengling; Pan, Ruyi; Zhang, Rongqian; Vandekar, Simon N; Baller, Erica B; Gur, Ruben C; Gur, Raquel E; Alexander-Bloch, Aaron F; Satterthwaite, Theodore D; Park, Jun Young.
Afiliación
  • Weinstein SM; Department of Epidemiology and Biostatistics, Temple University College of Public Health, Philadelphia, PA, USA.
  • Tu D; Regeneron Pharmaceuticals, Tarrytown, NY, USA.
  • Hu F; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Pan R; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Zhang R; Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada.
  • Vandekar SN; Centre for Addiction and Mental Health, Toronto, ON, Canada.
  • Baller EB; Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada.
  • Gur RC; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Gur RE; Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
  • Alexander-Bloch AF; Penn Lifespan Informatics and Neuroimaging Center, Philadelphia, PA, USA.
  • Satterthwaite TD; Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
  • Park JY; Penn-CHOP Lifespan Brain Institute (LiBI), Philadelphia, PA, USA.
bioRxiv ; 2024 Jun 28.
Article en En | MEDLINE | ID: mdl-38979274
ABSTRACT
Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos