Document Detail


Reducing inter-subject anatomical variation: effect of normalization method on sensitivity of functional magnetic resonance imaging data analysis in auditory cortex and the superior temporal region.
MedLine Citation:
PMID:  19481162     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Conventional group analysis of functional MRI (fMRI) data usually involves spatial alignment of anatomy across participants by registering every brain image to an anatomical reference image. Due to the high degree of inter-subject anatomical variability, a low-resolution average anatomical model is typically used as the target template, and/or smoothing kernels are applied to the fMRI data to increase the overlap among subjects' image data. However, such smoothing can make it difficult to resolve small regions such as subregions of auditory cortex when anatomical morphology varies among subjects. Here, we use data from an auditory fMRI study to show that using a high-dimensional registration technique (HAMMER) results in an enhanced functional signal-to-noise ratio (fSNR) for functional data analysis within auditory regions, with more localized activation patterns. The technique is validated against DARTEL, a high-dimensional diffeomorphic registration, as well as against commonly used low-dimensional normalization techniques such as the techniques provided with SPM2 (cosine basis functions) and SPM5 (unified segmentation) software packages. We also systematically examine how spatial resolution of the template image and spatial smoothing of the functional data affect the results. Only the high-dimensional technique (HAMMER) appears to be able to capitalize on the excellent anatomical resolution of a single-subject reference template, and, as expected, smoothing increased fSNR, but at the cost of spatial resolution. In general, results demonstrate significant improvement in fSNR using HAMMER compared to analysis after normalization using DARTEL, or conventional normalization such as cosine basis function and unified segmentation in SPM, with more precisely localized activation foci, at least for activation in the region of auditory cortex.
Authors:
Amir M Tahmasebi; Purang Abolmaesumi; Zane Z Zheng; Kevin G Munhall; Ingrid S Johnsrude
Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-05-27
Journal Detail:
Title:  NeuroImage     Volume:  47     ISSN:  1095-9572     ISO Abbreviation:  Neuroimage     Publication Date:  2009 Oct 
Date Detail:
Created Date:  2009-07-31     Completed Date:  2009-10-15     Revised Date:  2010-12-03    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1522-31     Citation Subset:  IM    
Affiliation:
School of Computing, Queen's University, Kingston, ON, Canada. tahmaseb@cs.queensu.ca
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Auditory Cortex / anatomy & histology*,  physiology*
Brain Mapping / methods
Evoked Potentials, Auditory / physiology*
Female
Humans
Image Enhancement / methods*
Magnetic Resonance Imaging / methods*
Male
Reproducibility of Results
Sensitivity and Specificity
Temporal Lobe / anatomy & histology*,  physiology*
Young Adult
Grant Support
ID/Acronym/Agency:
R01 DC008092-03/DC/NIDCD NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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