Rasmus Røge
Technical University of Denmark
9 Papers
24 Citations
Rasmus Røge is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Computer science & Bayesian probability. The author has an hindex of 5, co-authored 7 publications.
Chat about Author
Papers
Archetypal Analysis for Modeling Multisubject fMRI Data
Jesper Løve Hinrich,Sophia Elizabeth Bardenfleth,Rasmus Røge,Nathan W. Churchill,Kristoffer Hougaard Madsen,Morten Mørup +5 more
TL;DR: Multi-subject AA (MS-AA), which accounts for group-level data by assuming that archetypal temporal profiles have a common latent generator across subjects, ensuring that the temporal components are derived from a consistent set of brain regions, is developed.
33
Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data.
TL;DR: The results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of f MRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.
•Posted Content
Nonparametric Modeling of Dynamic Functional Connectivity in fMRI Data
Søren Føns Vind Nielsen,Kristoffer Hougaard Madsen,Rasmus Røge,Mikkel N. Schmidt,Morten Mørup +4 more
TL;DR: In this paper, a non-parametric generative model for dynamic functional connectivity in fMRI was proposed, which does not rely on specifying window lengths and number of dynamic states.
12
Whole brain functional connectivity predicted by indirect structural connections
Rasmus Røge,Karen Sando Ambrosen,Kristoffer Jon Albers,Casper T. Eriksen,Matthew George Liptrot,Mikkel N. Schmidt,Kristoffer Hougaard Madsen,Morten Mørup +7 more
- 01 Jun 2017
TL;DR: In this paper, the authors assess the structure-function relationship by evaluating how well functional connectivity can be predicted from structural graphs using high-resolution whole brain networks generated with varying density, and contrast the performance of several non-parametric link predictors that measure structural communication flow.
10
Unsupervised segmentation of task activated regions in fMRI
Rasmus Røge,Kristoffer Hougaard Madsen,MikkelN. Schmidt,Morten Mørup +3 more
- 12 Nov 2015
TL;DR: Demonstrating that a fully unsupervised manner are able to extract the task-induced activations forms a promising framework for the analysis of task fMRI and resting-state data in general where strong knowledge of how the task induces a BOLD response is missing.
8