2002
DOI: 10.1006/nimg.2001.0978
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Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain

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Cited by 14,549 publications
(10,857 citation statements)
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References 32 publications
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“…Rigid body affine coregistration of PET and MRI scans as well as MRI gray‐white matter segmentation, spatial normalization, and transformation of template ROIs to PET space were performed using the neuro tool. As a template, the Automatic Anatomic Labelling (AAL)13 template was used. Cortical ROIs were masked using a gray matter probability map with a threshold set at 0.75 and transformed to PET space using the affine transformation obtained from MR‐to‐PET coregistration.…”
Section: Methodsmentioning
confidence: 99%
“…Rigid body affine coregistration of PET and MRI scans as well as MRI gray‐white matter segmentation, spatial normalization, and transformation of template ROIs to PET space were performed using the neuro tool. As a template, the Automatic Anatomic Labelling (AAL)13 template was used. Cortical ROIs were masked using a gray matter probability map with a threshold set at 0.75 and transformed to PET space using the affine transformation obtained from MR‐to‐PET coregistration.…”
Section: Methodsmentioning
confidence: 99%
“…A frequency analysis was performed using the multitaper method based on Hanning tapers in order to identify the peak virtual channel in each of 84 Automated Anatomical Labeling (AAL; Tzourio‐Mazoyer et al, 2002) atlas‐based ROIs (excluding the cerebellum and some deep structures; see Figure 6a). The classifier input consisted of the raw time‐series for each of the 84 virtual sensors, baseline corrected and averaged in groups of 5 trials to improve SNR.…”
Section: Methodsmentioning
confidence: 99%
“…We extracted regional mean fMRI time series for 90 regions of interest (ROI) in the Anatomical Automatic Labeling template (Tzourio‐Mazoyer et al 2002) for each individual. Each regional mean time series was decomposed into wavelet coefficients at four scales using the maximum overlap discrete wavelet transform, a time‐frequency transformation.…”
Section: Methodsmentioning
confidence: 99%