Guido Nolte

This paper introduces a low-rank tensor decomposition framework for cross-bispectral EEG data, enabling structured and interpretable analysis of brain interactions.

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

The paper introduces a method to localize interacting sources from EEG and MEG data by maximizing source-to-sensor coupling, which is faster and more statistically powerful than conventional approaches.

The paper shows that dynamic changes in large-scale functional connectivity before a task predict performance in an audiovisual detection task in ferrets.

The paper investigates causal interactions between phase and amplitude coupling in cortical networks using ECoG and MEG data, finding bidirectional or unidirectional information transmission depending on frequency bands.

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.

The paper examines how noise affects neural tracking of acoustic and semantic speech features during naturalistic speech comprehension, finding that semantic processing leads and is linked to comprehension performance.

This study shows that neural coupling between speakers and listeners occurs before speech onset and correlates with comprehension, suggesting predictive attentional mechanisms.

Harmoni removes spurious neuronal interactions caused by harmonic components in EEG data, improving the detection of genuine cross-frequency synchronization.

The paper examines how preparatory delta phase responses correlate with speech comprehension performance using EEG data from naturalistic speech tasks.

The paper compares PAC and bicoherence measures for cross-frequency coupling, showing that a 1:1 bandwidth ratio avoids frequency smearing and improves accuracy.

This paper derives mathematical relations between brain connectivity measures from Gaussian data and tests their validity using simulations and empirical EEG data.

This paper introduces NID, a method to decompose cross-frequency coupled sources in EEG/MEG data, showing it reliably extracts nonlinear interactions even at low SNR and identifies alpha-beta phase-phase coupling in resting-state EEG.

The paper shows that working memory training with voices increases beta-band connectivity in the visual cortex of congenitally blind individuals during auditory tasks.

This paper introduces the frequency-adaptive broadband (FAB) beamformer for EEG/MEG data, which outperforms existing methods in reconstructing broadband source signals.

This study shows that catecholamines change the intrinsic variability of cortical activity and perception, increasing the net E/I ratio in visual and parietal cortex, while acetylcholine does not.

This study localizes the auditory evoked gamma band response (aeGBR) sources and examines their connectivity using MEG, finding increased dACC activity and connectivity during cognitively demanding tasks.