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fMRI activation mapping using wavelet-based SPM (WSPM) integrated with gray-matter graphs

Behjat, Hamid LU ; Leonardi, Nora; Sörnmo, Leif LU and Van De Ville, Dimitri (2014) 20th Annual Meeting of the Organization for Human Brain Mapping (OHBM)
Abstract
In many fMRI task-evoked studies, localized brain activity can be detected by GLM fitting and statistical hypothesis testing. Statistical parametric mapping (SPM) is the classical method that requires Gaussian pre-smoothing of the data. Instead, the wavelet transform provides a compact representation of activation patterns. Wavelet based SPM (WSPM) is an extension of SPM that combines wavelet processing with voxel-wise statistical testing. However, classical wavelets used in WSPM are designed for regular Euclidean grids and thus not adapted to the convoluted nature of the cerebral cortex. We recently showed how WSPM using graph wavelets tailored to the gray-matter structure of the cortex can improve detection of brain activity in... (More)
In many fMRI task-evoked studies, localized brain activity can be detected by GLM fitting and statistical hypothesis testing. Statistical parametric mapping (SPM) is the classical method that requires Gaussian pre-smoothing of the data. Instead, the wavelet transform provides a compact representation of activation patterns. Wavelet based SPM (WSPM) is an extension of SPM that combines wavelet processing with voxel-wise statistical testing. However, classical wavelets used in WSPM are designed for regular Euclidean grids and thus not adapted to the convoluted nature of the cerebral cortex. We recently showed how WSPM using graph wavelets tailored to the gray-matter structure of the cortex can improve detection of brain activity in single-subject studies. Here we extend this approach to group-level analysis by modifying the design of the brain graph. (Less)
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Contribution to conference
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published
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conference name
20th Annual Meeting of the Organization for Human Brain Mapping (OHBM)
language
English
LU publication?
yes
id
89487675-4399-4f64-bd30-ff97a0a8f5b8 (old id 4643576)
alternative location
http://f1000research.com/posters/1096083
date added to LUP
2014-10-16 11:58:42
date last changed
2016-05-10 11:50:11
@misc{89487675-4399-4f64-bd30-ff97a0a8f5b8,
  abstract     = {In many fMRI task-evoked studies, localized brain activity can be detected by GLM fitting and statistical hypothesis testing. Statistical parametric mapping (SPM) is the classical method that requires Gaussian pre-smoothing of the data. Instead, the wavelet transform provides a compact representation of activation patterns. Wavelet based SPM (WSPM) is an extension of SPM that combines wavelet processing with voxel-wise statistical testing. However, classical wavelets used in WSPM are designed for regular Euclidean grids and thus not adapted to the convoluted nature of the cerebral cortex. We recently showed how WSPM using graph wavelets tailored to the gray-matter structure of the cortex can improve detection of brain activity in single-subject studies. Here we extend this approach to group-level analysis by modifying the design of the brain graph.},
  author       = {Behjat, Hamid and Leonardi, Nora and Sörnmo, Leif and Van De Ville, Dimitri},
  language     = {eng},
  title        = {fMRI activation mapping using wavelet-based SPM (WSPM) integrated with gray-matter graphs},
  year         = {2014},
}