3.7k citations · 4.1k across the 26 of their papers we have counts for
11 papers · 1 filter
Bayesian Modeling of Effective and Functional Brain Connectivity using Hierarchical Vector Autoregressions
Bertil Wegmann, Anders Lundquist, Anders Eklund +1
Analysis of brain connectivity is important for understanding how information is processed by the brain. We propose a novel Bayesian vector autoregression (VAR) hierarchical model…
Reply to Chen et al.: Parametric methods for cluster inference perform worse for two-sided t-tests
Anders Eklund, Hans Knutsson, Thomas E. Nichols
One-sided t-tests are commonly used in the neuroimaging field, but two-sided tests should be the default unless a researcher has a strong reason for using a one-sided test. Here we…
Cluster Failure Revisited: Impact of First Level Design and Data Quality on Cluster False Positive Rates
Anders Eklund, Hans Knutsson, Thomas E Nichols
Methodological research rarely generates a broad interest, yet our work on the validity of cluster inference methods for functional magnetic resonance imaging (fMRI) created intens…
Bayesian uncertainty quantification in linear models for diffusion MRI
Jens Sjölund, Anders Eklund, Evren Özarslan +3
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Se…
Physiological Gaussian Process Priors for the Hemodynamics in fMRI Analysis
Josef Wilzén, Anders Eklund, Mattias Villani
Background: Inference from fMRI data faces the challenge that the hemodynamic system that relates neural activity to the observed BOLD fMRI signal is unknown. New Method: We propos…
Reply to Cox et al. and Kessler et al.: Data and code sharing is the way forward for fMRI
Anders Eklund, Thomas Nichols, Hans Knutsson
We are glad that our paper has generated intense discussions in the fMRI field, on how to analyze fMRI data and how to correct for multiple comparisons. The goal of the paper was n…
A defense of using resting state fMRI as null data for estimating false positive rates
Thomas E. Nichols, Anders Eklund, Hans Knutsson
A recent Editorial by Slotnick (2017) reconsiders the findings of our paper on the accuracy of false positive rate control with cluster inference in fMRI (Eklund et al, 2016), in p…
Bayesian Non-Central Chi Regression For Neuroimaging
Bertil Wegmann, Anders Eklund, Mattias Villani
We propose a regression model for non-central (NC-) distributed functional magnetic resonance imaging (fMRI) and diffusion weighted imaging (DWI) data, with the heteroscedas…
A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes
Anders Eklund, Martin A. Lindquist, Mattias Villani
We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data.…
Gaussian process regression can turn non-uniform and undersampled diffusion MRI data into diffusion spectrum imaging
Jens Sjölund, Anders Eklund, Evren Özarslan +1
We propose to use Gaussian process regression to accurately estimate the diffusion MRI signal at arbitrary locations in q-space. By estimating the signal on a grid, we can do synth…
Can parametric statistical methods be trusted for fMRI based group studies?
Anders Eklund, Thomas Nichols, Hans Knutsson
The most widely used task fMRI analyses use parametric methods that depend on a variety of assumptions. While individual aspects of these fMRI models have been evaluated, they have…