Abstract
We describe the use of non-parametric permutation tests to detect activation in cortically-constrained maps of current density computed from MEG data. The methods are applicable to any inverse imaging method that maps event-related MEG to a coregistered cortical surface. To determine an appropriate threshold to apply to statistics computed from these maps, it is important to control for the multiple testing problem associated with testing 10’s of thousands of hypotheses (one per surface element). By randomly permuting pre- and post-stimulus data from the collection of individual epochs in an event related study, we develop thresholds that control the familywise (type 1) error rate. These thresholds are based on the distribution of the maximum intensity, which implicitly accounts for spatial and temporal correlation in the cortical maps. We demonstrate the method in application to simulated data and experimental data from a somatosensory evoked response study.
This work was supported by grant R01 EB002010 from the National Institute of Biomedical Imaging and Bioengineering.
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References
Phillips, J.W., Leahy, R.M., Mosher, J.C.: MEG-Based Imaging of Focal Neuronal Current Sources. IEEE Transactions of Medical Imaging 163, 338–348 (1997)
Dale, A.M., Liu, A.K., Fischi, R.B., Buckner, R.L., Belliveau, J.W., Lewine, J.D., Halgren, E.: Dynamic Statistical Parametric Mapping: Combining fMRI and MEG for High- Resolution Imaging of Cortical Activity. Neuron 26, 55–67 (2000)
Worsley, K.J., Andermann, M., Koulis, T., MacDonald, D., Evans, A.C.: Detecting Changes in Nonisotropic Images. Human Brain Mapping 8, 98–101 (1999)
Barnes, G.R., Hillebrand, A.: Statistical Flattening of MEG Beamformer Images. Human Brain Mapping 18, 1–12 (2003)
Nichols, T.E., Holmes, A.P.: Nonparametric Permutation Tests For Functional Neuroimaging: A Primer with Examples. Human Brain Mapping 15, 1–25 (2001)
Blair, R.C., Karnisky, W.: Distribution-Free Statistical Analyses of Surface and Volumetric Maps. In: Thatcher, R.W., Hallett, M., Roy, J.E., Huerta, M. (eds.) Functional Neuroimaging: Technical Foundations, Academic Press, San Diego (1994)
Arndt, S., Cizadlo, T., Andreasen, N.C., Heckel, D., Gold, S., O’Leary, D.S.: Tests for comparing images based on randomization and permutation methods. Journal of Cerebral Blood Flow and Metabolism 16, 1271–1279 (1996)
Holmes, A.P., Blair, R.C., Watson, J.D.G., Ford, I.: Nonparametric analysis of statistic images from functional mapping experiements. Journal of Cerebral Blood Flow and Metabolism 16, 7–22 (1996)
Shattuck, D.W., Leahy, R.M.: BrainSuite: An Automated Cortical Surface Identification Tool. Medical Image Analysis 6(2), 129–142 (2002)
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© 2003 Springer-Verlag Berlin Heidelberg
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Pantazis, D., Nichols, T.E., Baillet, S., Leahy, R.M. (2003). Spatiotemporal Localization of Significant Activation in MEG Using Permutation Tests. In: Taylor, C., Noble, J.A. (eds) Information Processing in Medical Imaging. IPMI 2003. Lecture Notes in Computer Science, vol 2732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45087-0_43
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DOI: https://doi.org/10.1007/978-3-540-45087-0_43
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