Mar 10, 2016

Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path

BioRxiv : the Preprint Server for Biology
Holger FingerPeter König

Abstract

Here we use computational modeling of fast neural dynamics to explore the relationship between structural and functional coupling in a population of healthy subjects. We use DTI data to estimate structural connectivity and subsequently model phase couplings from band-limited oscillatory signals derived from multichannel EEG data. Our results show that about 23.4% of the variance in empirical networks of resting-state fast oscillations is explained by the underlying white matter architecture. By simulating functional connectivity using a simple reference model, the match between simulated and empirical functional connectivity further increases to 45.4%. In a second step, we use our modeling framework to explore several technical alternatives along the modeling path. First, we find that an augmentation of homotopic connections in the structural connectivity matrix improves the link to functional connectivity while a correction for fiber distance slightly decreases the performance of the model. Second, a more complex computational model based on Kuramoto oscillators leads to a slight improvement of the model fit. Third, we show that the comparison of modeled and empirical functional connectivity at source level is much more specif...Continue Reading

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Mentioned in this Paper

Study
Biological Neural Networks
Electroencephalography
Connectome
Neuroma
Brain
Extracellular Matrix
Evaluation
Neural Stem Cells
Neural Network Simulation

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