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A 12-step user guide for analyzing voxel-wise gray matter asymmetries in statistical parametric mapping (SPM)

Nature Protocols volume 10, pages 293–304 (2015)Cite this article

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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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Figure 1: Spatial normalization.
Figure 2: The asymmetry index (AI).
Figure 3: The left image shows SPM's three windows.
Figure 4: Workflow of the protocol.
Figure 5: Statistical outcomes and follow-up (stages I–III).

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Acknowledgements

This work was supported by the German Ministry of Education and Research (BMBF grant no. 01EV0709 to C.G.).

Author information

Authors and Affiliations

  1. Department of Neurology, University of California, Los Angeles (UCLA) School of Medicine, Los Angeles, California, USA

    Florian Kurth & Eileen Luders

  2. Department of Psychiatry, Jena University Hospital, Jena, Germany

    Christian Gaser

  3. Department of Neurology, Jena University Hospital, Jena, Germany

    Christian Gaser

Authors
  1. Florian Kurth
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  2. Christian Gaser
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  3. Eileen Luders
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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.

Corresponding author

Correspondence to Florian Kurth.

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Competing interests

The authors declare no competing financial interests.

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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