Jun
20
2023

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

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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.

1 min read
May
08
2023

QuNex—Quantitative Neuroimaging Environment & Toolbox

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

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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

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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

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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.

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Oct
01
2022

Lara Oblak joined MBLab

A new young researcher, Lara Oblak, has joined the Mind & Brain Lab.

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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

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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.

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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].

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