期刊
NEUROIMAGE
卷 53, 期 2, 页码 491-505出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2010.06.032
关键词
Amygdala; Spherical harmonics; Fourier analysis; Surface flattening; Multivariate linear model; SurfStat
资金
- National Center for Research Resources, National Institutes of Health [1UL1RR025011]
- Department of Brain and Cognitive Sciences at Seoul National University
Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations This paper presents a unified computational and statistical framework for modeling amygdala shape variations in a clinical population The weighted spherical harmonic representation is used to parameterize, smooth out, and normalize amygdala surfaces The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using the SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects (C) 2010 Elsevier Inc All rights reserved
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