A new paper on dynamic and static functional connectivity
We are pleased to announce that a new paper has been published in Network Neuroscience entitled Static and dynamic fMRI-derived functional connectomes represent largely similar information. The paper was co-authored with Alan Anticevic and John D. Murray from Yale University. The paper provides valuable insights into the comparison and interpretation
1 min read
May
18
2023
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
1 min read
Dec
06
2022
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
1 min read
Nov
28
2022
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.
The
1 min read
Nov
14
2022
A review paper on deep learning in neuroimaging data analysis
The paper entitled Deep learning in neuroimaging data analysis: Applications, challenges, and solutions by Lev Kiar Avberšek and Grega Repovš has been published in Frontiers in Neuroimaging. The paper provides an overview of the use of deep learning as a form of machine learning in the analysis of neuroimaging data.
1 min read
Oct
01
2022
Lara Oblak joined MBLab
A new young researcher, Lara Oblak, has joined the Mind & Brain Lab.
1 min read
Jul
18
2022
Publication of The Cambridge Handbook of Working Memory and Language
The Cambridge University Press has recently published the book The Cambridge Handbook of Working Memory and Language, which includes the chapter The Cognitive Neuroscience of Working Memory and Language written by Nina Purg, Anka Slana Ozimič and Grega Repovš. The book is a result of the collaboration of many established
1 min read
Jul
15
2022
MBLab has a new Ph.D. member
Nina Purg has successfully defended her doctoral thesis Representations of position in spatial working memory on Wednesday July 13, 2022.
1 min read
May
18
2022
New paper on the phenomenology of visuo-spatial working memory
Our paper "What Individuals Experience During Visuo-Spatial Working Memory Task
Performance: An Exploratory Phenomenological Study" has been published in
Frontiers in Psychology.
The paper is available online at the Frontiers in Psychology website
[https://doi.org/10.3389/fpsyg.2022.811712].
