Open AccessLinear and curvilinear correlations of brain gray matter volume and density with age using voxel‐based morphometry with the Akaike information criterion in 291 healthy children
Author(s) -
Taki Yasuyuki,
Hashizume Hiroshi,
Thyreau Benjamin,
Sassa Yuko,
Takeuchi Hikaru,
Wu Kai,
Kotozaki Yuka,
Nouchi Rui,
Asano Michiko,
Asano Kohei,
Fukuda Hiroshi,
Kawashima Ryuta
Publication year - 2013
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.22033
Subject(s) - akaike information criterion , voxel , voxel based morphometry , psychology , gray (unit) , curvilinear coordinates , grey matter , magnetic resonance imaging , mathematics , neuroscience , nuclear medicine , artificial intelligence , statistics , computer science , medicine , white matter , geometry , radiology
Abstract We examined linear and curvilinear correlations of gray matter volume and density in cortical and subcortical gray matter with age using magnetic resonance images (MRI) in a large number of healthy children. We applied voxel‐based morphometry (VBM) and region‐of‐interest (ROI) analyses with the Akaike information criterion (AIC), which was used to determine the best‐fit model by selecting which predictor terms should be included. We collected data on brain structural MRI in 291 healthy children aged 5–18 years. Structural MRI data were segmented and normalized using a custom template by applying the diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL) procedure. Next, we analyzed the correlations of gray matter volume and density with age in VBM with AIC by estimating linear, quadratic, and cubic polynomial functions. Several regions such as the prefrontal cortex, the precentral gyrus, and cerebellum showed significant linear or curvilinear correlations between gray matter volume and age on an increasing trajectory, and between gray matter density and age on a decreasing trajectory in VBM and ROI analyses with AIC. Because the trajectory of gray matter volume and density with age suggests the progress of brain maturation, our results may contribute to clarifying brain maturation in healthy children from the viewpoint of brain structure. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.