Geometric effects of volume-to-surface mapping of fMRI data
In this work, we identify a problem with the process of volume-to-surface mapping of functional Magnetic Resonance Imaging (fMRI) data that emerges in local connectivity analysis. We show that neighborhood correlations on the surface of the brain vary spatially with the gyral structure, even when th...
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| Veröffentlicht in: | Brain Structure and Function 2022-09, Vol.227 (7), p.2457-2464 |
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| container_title | Brain Structure and Function |
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| creator | Ciantar, Keith George Farrugia, Christine Galdi, Paola Scerri, Kenneth Xu, Ting Bajada, Claude J. |
| description | In this work, we identify a problem with the process of volume-to-surface mapping of functional Magnetic Resonance Imaging (fMRI) data that emerges in local connectivity analysis. We show that neighborhood correlations on the surface of the brain vary spatially with the gyral structure, even when the underlying volumetric data are uncorrelated noise. This could potentially have impacted studies focusing upon local neighborhood connectivity. We explore the effects of this anomaly across varying data resolutions and surface mesh densities, and propose several measures to mitigate these unwanted effects. |
| doi_str_mv | 10.1007/s00429-022-02536-4 |
| format | Article |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Algorithms Biomedical and Life Sciences Biomedicine Brain mapping Cell Biology Functional magnetic resonance imaging Mapping Neighborhoods Neural networks Neuroimaging Neurology Neurosciences Original Original Article |
| title | Geometric effects of volume-to-surface mapping of fMRI data |
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