New paper on the MR-induced EEG artifact reduction
A new paper from our lab was recently published in Frontiers in Neuroimaging titled "Evaluation and comparison of most prevalent artifact reduction methods for EEG acquired simultaneously with fMRI". An in-depth evaluation of the most common approaches to MR-induced EEG artifact reduction utilizing Bayesian hierarchical probabilistic modeling.
Grega Repovš on the therapeutic effects of psychedelics
In an article in N1 Slovenia, you can read about research on the therapeutic effects of psychedelics in the treatment of mental disorders. One of the interviewees in the article is the head of our lab, Prof. Dr. Grega Repovš.
In collaboration with the Anticevic Lab at Yale School of Medicine, we have developed the Quantitative Neuroimaging Environment & Toolbox (QuNex). This toolbox integrates several packages to support a flexible and extensible framework for data organization, preprocessing, quality assurance, and various analyses across neuroimaging modalities. A detailed description of the toolbox
R package for the construction and evaluation of linear models for the analysis of task-related fMRI data
We published a paper in Frontiers in Neuroimaging with a title autohrf-an R package for generating data-informed event models for general linear modeling of task-based fMRI data.
The paper presents an original package for the R programming language that allows the evaluation of linear models and the automatic calculation of