Conference paper
Joint Modelling of Structural and Functional Brain Networks
Department of Applied Mathematics and Computer Science, Technical University of Denmark1
Copenhagen University Hospital Herlev and Gentofte2
Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Visual Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
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.
Language: | English |
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Year: | 2012 |
Proceedings: | 2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI 2012) |
Types: | Conference paper |
ORCIDs: | Herlau, Tue , Mørup, Morten , Schmidt, Mikkel Nørgaard and Hansen, Lars Kai |