Geometric effects of volume-to-surface mapping of fMRI data.
Keith George CiantarChristine FarrugiaPaola GaldiKenneth ScerriTing XuClaude J BajadaPublished in: Brain structure & function (2022)
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.
Keyphrases
- resting state
- functional connectivity
- electronic health record
- magnetic resonance imaging
- big data
- white matter
- high resolution
- computed tomography
- data analysis
- machine learning
- magnetic resonance
- air pollution
- artificial intelligence
- high density
- brain injury
- blood brain barrier
- deep learning
- diffusion weighted imaging