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Neuroimaging meta regression for coordinate based meta analysis data with a spatial model.
Yu, Yifan; Lobo, Rosario Pintos; Riedel, Michael Cody; Bottenhorn, Katherine; Laird, Angela R; Nichols, Thomas E.
Affiliation
  • Yu Y; Oxford Big Data Institute, University of Oxford, Old road campus, Oxford, OX3 7LF, United Kingdom.
  • Lobo RP; Department of Psychology, Florida International University, Miami, FL, 33199, United States.
  • Riedel MC; Department of Physics, Florida International University, Miami, FL, 33199, United States.
  • Bottenhorn K; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, United States.
  • Laird AR; Center for Imaging Science, Florida International University, Miami, FL, 33199, United States.
  • Nichols TE; Oxford Big Data Institute, University of Oxford, Old road campus, Oxford, OX3 7LF, United Kingdom.
Biostatistics ; 25(4): 1210-1232, 2024 Oct 01.
Article de En | MEDLINE | ID: mdl-39002146
ABSTRACT
Coordinate-based meta-analysis combines evidence from a collection of neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally efficient approach with good statistical interpretability to model the locations of activation foci. In this article, we propose a generative coordinate-based meta-regression (CBMR) framework to approximate a smooth activation intensity function and investigate the effect of study-level covariates (e.g. year of publication, sample size). We employ a spline parameterization to model the spatial structure of brain activation and consider four stochastic models for modeling the random variation in foci. To examine the validity of CBMR, we estimate brain activation on 20 meta-analytic datasets, conduct spatial homogeneity tests at the voxel level, and compare the results to those generated by existing kernel-based and model-based approaches. Keywords generalized linear models; meta-analysis; spatial statistics; statistical modeling.
Sujet(s)

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Méta-analyse comme sujet / Neuroimagerie Limites: Humans Langue: En Journal: Biostatistics Année: 2024 Type de document: Article Pays d'affiliation: Royaume-Uni Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Méta-analyse comme sujet / Neuroimagerie Limites: Humans Langue: En Journal: Biostatistics Année: 2024 Type de document: Article Pays d'affiliation: Royaume-Uni Pays de publication: Royaume-Uni