Paper in collaboration with MBLab among best at ULJ in 2020
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Paper in collaboration with MBLab among best at ULJ in 2020

Paper Acute Hyperglycemia and Spatial Working Memory in Adolescents With Type 1 Diabetes was identified as one of best papers published at University of Ljubljana in 2020.

In collaboration between the Faculty of Medicine and the Mind and Brain Laboratory at the Faculty of Arts at the University of Ljubljana we found a reduction in spatial working memory capacity in adolescents with type 1 diabetes (T1D) in comparison to healthy peers during acute hypoglycaemia, while there were no statistically significant differences between the two groups when blood sugar levels were normal. The paper Acute Hyperglycemia and Spatial Working Memory in Adolescents With Type 1 Diabetes was published in Journal Diabetes Care.

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

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 paper is

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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