Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks Using Big Data Population Priors

Large brain imaging databases contain a wealth of information on brain organization in the populations they target, and on individual variability. While such databases have been used to study group-level features of populations directly, they are currently underutilized as a resource to inform singl...

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Vydané v:	Journal of the American Statistical Association Ročník 115; číslo 531; s. 1151 - 1177
Hlavní autori:	Mejia, Amanda F., Nebel, Mary Beth, Wang, Yikai, Caffo, Brian S., Guo, Ying
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Taylor & Francis 02.07.2020 Taylor & Francis Ltd
Predmet:	Algorithms Applications and case studies Bayesian analysis Bayesian methods Bayesian theory Big Data Brain Brain size Computationally intensive methods Computer simulation Empirical analysis Estimation Expectation-maximization Functional magnetic resonance imaging humans Independent component analysis Individual differences Magnetic resonance imaging magnetism Networks Neuroimaging Populations Regression analysis Reliability Reliability analysis Simulation Statistical methods Statistics Wealth
ISSN:	0162-1459, 1537-274X, 1537-274X
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