Abstract
Voxel-based morphometry (VBM) has been proven capable of capturing cerebral gray matter asymmetries with a high (voxel-wise) regional specificity. However, a standardized reference on how to conduct voxel-wise asymmetry analyses is missing. This protocol provides the scientific community with a carefully developed guide describing, in 12 distinct steps, how to take structural images from data pre-processing, via statistical analysis, to the final interpretation of the significance maps. Key adaptations compared with the standard VBM workflow involve establishing a voxel-wise hemispheric correspondence, capturing the direction and degree of asymmetry and preventing a blurring of information across hemispheres. The workflow incorporates the most recent methodological developments, including high-dimensional spatial normalization and partial volume estimations. Although the protocol is primarily designed to enable relatively inexperienced users to conduct a voxel-based asymmetry analysis on their own, it may also be useful to experienced users who wish to efficiently adapt their existing scripts or pipelines.
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Acknowledgements
This work was supported by the German Ministry of Education and Research (BMBF grant no. 01EV0709 to C.G.).
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Contributions
F.K. and E.L. developed and designed the protocol and experiments and drafted the manuscript; C.G. developed and wrote the VBM8 tool and provided methodological guidance and feedback; F.K., E.L. and C.G. finalized the manuscript.
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Integrated supplementary information
Supplementary Figure 1 Tissue segmentation.
Shown are examples for successful as well as failed tissue segmentations. The top left displays a successful segmentation of an original T1-weighted image and the two main tissue compartments resulting from the segmentation step: gray matter and white matter. The failed tissue segmentation #1 (top right) revealed a severely distorted gray matter segment and an almost non-existing white matter segment. The problem might be correctable by adjusting the origin of the image (see Troubleshooting Table, Step 1 - Problem 1). The failed tissue segmentation #2 (bottom left) – probably the most likely encountered situation – revealed segments that do not fully comprise the tissue segments (e.g., gray matter is missing in the occipital cortex). The failed tissue segmentation #3 (bottom right) represent a case of severe misclassification of gray and white matter (compare with the segments resulting from the successful tissue segmentation). The cases #2 and #3 might be correctable by adjusting the bias correction (see Troubleshooting Table, Step 1 - Problem 3).
Supplementary information
Supplementary Text and Figures
Supplementary Figure 1 and Supplementary Data 1 (PDF 1564 kb)
Supplementary Software 1
MATLAB script called extract.m. (ZIP 2 kb)
Supplementary Software 2
MATLAB script called calculate.m. (ZIP 2 kb)
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Kurth, F., Gaser, C. & Luders, E. A 12-step user guide for analyzing voxel-wise gray matter asymmetries in statistical parametric mapping (SPM). Nat Protoc 10, 293–304 (2015). https://doi.org/10.1038/nprot.2015.014
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DOI: https://doi.org/10.1038/nprot.2015.014
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