Joint Modelling of Structural and Functional Brain Networks

Kasper Winther Andersen, Tue Herlau, Morten Mørup, Mikkel Nørgaard Schmidt, Kristoffer H. Madsen, Mark Lyksborg, Tim B. Dyrby, Hartwig R. Siebner, Lars Kai Hansen

Research output: Contribution to conferencePaperResearchpeer-review

285 Downloads (Pure)


Functional and structural magnetic resonance imaging have become the most important noninvasive windows to the human brain. A major challenge in the analysis of brain networks is to establish the similarities and dissimilarities between functional and structural connectivity. We formulate a non-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish significant structures that are consistently shared across subjects and data splits. This provides an unsupervised approach for modeling of structure-function relations in the brain and provides a general framework for multimodal integration.
Original languageEnglish
Publication date2012
Number of pages7
Publication statusPublished - 2012
Event2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI 2012) - Lake Tahoe, Nevada, United States
Duration: 7 Dec 20128 Dec 2012


Conference2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI 2012)
Country/TerritoryUnited States
CityLake Tahoe, Nevada
Internet address


Dive into the research topics of 'Joint Modelling of Structural and Functional Brain Networks'. Together they form a unique fingerprint.

Cite this