IEEE International Symposium on Biomedical Imaging (ISBI)NeurosciencePeer-reviewed journal article
Anatomically informed Bayesian spatial priors for fMRI analysis
David AbramianiD, Per SidéniD, Hans E. KnutssoniD, Mattias VillaniiD, Anders EklundiD
Abstract
Existing Bayesian spatial priors for functional magnetic resonance imaging (fMRI) data correspond to stationary isotropic smoothing filters that may oversmooth at anatomical boundaries. We propose two anatomically informed Bayesian spatial models for fMRI data with local smoothing in each voxel based on a tensor field estimated from a T1-weighted anatomical image. We show that our anatomically informed Bayesian spatial models results in posterior probability maps that follow the anatomical structure.
- Citations
- 5
- FWCI
- 0.65
- Field percentile
- top 38%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Bayesian MEG time courses with fMRI priors
Yingying Wang, Scott K. Holland·Brain Imaging and BehaviorPeer-reviewed·Sep 24, 2021
- A method to adjust a prior distribution in Bayesian second-level fMRI analysis
Hyemin Han·PeerJPeer-reviewed·Feb 3, 2021
- Diffusion-Informed Spatial Smoothing of fMRI Data in White Matter Using Spectral Graph Filters
David Abramian, Martin Larsson, … Hamid Behjat·NeuroImagePeer-reviewed·May 14, 2021
- Slice-sampled Bayesian PRF mapping
Silvan C. Quax, Thomas C. van Koppen, … Marcel A. J. van Gerven·bioRxiv·Dec 13, 2016
- BayesFactorFMRI: Implementing Bayesian second-level fMRI analysis with multiple comparison correction and Bayesian meta-analysis of fMRI images with multiprocessing
Hyemin Han·Journal of Open Research SoftwarePeer-reviewed·Feb 2, 2021
- Brain kernel: a new spatial covariance function for fMRI data
Anqi Wu, Samuel A. Nastase, … Jonathan W. Pillow·NeuroImagePeer-reviewed·Nov 3, 2021