Stefan Haufe

This study evaluates how robust different BSI methods are to noise level misspecification using simulations and metrics like EMD.

This study quantifies non-uniform effects of remaining field spread on ROI activity and connectivity estimation in M/EEG using cross-talk functions.

This study quantifies how defacing MRI data affects EEG source localization accuracy using boundary and finite element modeling in ten subjects.

This study identifies how dopamine and deep brain stimulation affect cortex-basal ganglia networks at different scales, showing distinct mesoscale effects and shared macroscale suppression of network synchrony.

This study shows that prediction performance for brain-imaging-based phenotypes can improve significantly with larger sample sizes and multimodal data.

This study investigates how dopamine and deep brain stimulation (DBS) affect neural dynamics in Parkinson's disease by measuring motor intention latency and oscillatory communication patterns.

This paper introduces ASB-PAC, a method to distinguish between-site and within-site phase-amplitude coupling in EEG data, showing it outperforms existing methods in detecting genuine interactions.

This study evaluates methods for detecting inter-regional linear functional connectivity from EEG, finding that certain pipelines outperform others and recommends best practices.

The paper investigates age-related changes in EEG biomarkers and their association with cognitive performance in older adults.

The paper develops a hierarchical Bayesian model for EEG source reconstruction that jointly estimates full-structure noise covariance matrices, improving accuracy in real-world scenarios with non-diagonal noise.

The paper investigates the relationship between white matter hyperintensities and alpha oscillations in older adults, finding that WMHs are associated with elevated alpha power but not with peak frequency or long-range temporal correlations.

This paper unifies three sparse Bayesian learning algorithms for EEG/MEG brain source imaging under the majorization-minimization framework and introduces a new method for low SNR settings and noise variance estimation.

This study identifies sensorimotor functional connectivity as a neurophysiological factor correlated with BCI performance, showing its significance beyond oscillation amplitude.

The paper investigates cortical excitability variability in response to sensory stimuli and finds evidence of criticality through long-range temporal dependencies in neural activity.

This study evaluates how head volume conduction affects directional connectivity estimates from EEG source reconstruction using simulations and multiple connectivity measures.

The paper examines the reliability and correlation of fMRI, ECoG, and EEG responses to natural stimuli across different brain regions and cohorts.

This study assesses the consistency of EEG source localization and connectivity estimates across different models and software, finding variability in effective connectivity but stability in source localization.