Mangor Pedersen

Multilayer Network Modelling of the Human Reading System

The paper uses multilayer network modelling to analyze fMRI data and shows that reading ability correlates with specific dynamic interactions within the reading network, particularly involving the left fusiform gyrus and inferior frontal gyrus.

Exploring Directed Connectivity Patterns of OPM-MEG with Multivariate Transfer Entropy

This study uses multivariate transfer entropy to analyze directed connectivity in OPM-MEG data, finding that out-degree connectivity is stronger and more hub-like than in-degree connectivity.

Music Affects State Anxiety and Brain Connectivity

This study examines how different music genres affect state anxiety and brain connectivity using EEG, finding that pleasant, low-arousal music reduces anxiety but shows varied brain responses.

Connectome embedding in multidimensional graph-invariant spaces

The paper embeds brain networks into high-dimensional graph spaces using nodal invariants and shows improved classification accuracy in higher dimensions.

Intracranial brain stimulation modulates fMRI-based network switching

This study investigates how intracranial brain stimulation affects network switching in fMRI data, finding reduced switching rates and more consistent patterns after stimulation.

Temporal complexity of fMRI is reproducible and correlates with higher order cognition

The paper validates that rsfMRI temporal complexity is reproducible and correlates with fluid intelligence across multiple brain networks.

Reducing module size bias of participation coefficient

The paper introduces a normalized participation coefficient to reduce module size bias in network analysis, demonstrating improved identification of high-participation nodes in various networks.

Towards fast and reliable simultaneous EEG-fMRI analysis of epilepsy with automatic spike detection

This paper develops an automatic EEG spike detection method for epilepsy studies, showing it can detect more spikes, identify additional brain regions, and speed up analysis compared to manual methods.

Brain connectivity dynamics: Multilayer network switching rate predicts brain performance

The paper models brain network switching using multilayer networks and finds it correlates with cognitive performance and sleep.

On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis

This study compares instantaneous phase synchrony analysis and correlation-based sliding window analysis for time-resolved fMRI connectivity, finding they are comparable with optimal parameters.