Joachim Groß

This paper identifies cross-species EEG biomarkers of sleep deprivation using multi-methodological analysis in humans and mice, finding theta power and spectral offset/slope as key features.

The paper uses MEG and cortical maps to predict neural activity patterns across age, linking them to anatomical and molecular features.

The paper shows that beta responses to naturalistic speech can be explained by a simple acoustic model, suggesting a domain-general temporal forecasting function rather than a linguistic one.

This study applies personalized tDCS targeting V5 to modulate sensorimotor integration during pursuit eye movements, showing specific effects on pursuit initiation.

This paper reports on respiration-modulated changes in excitation-inhibition balance and interictal spike timing in a focal epilepsy patient using MEG.

This study investigates whether peak alpha frequency predicts sensitivity to brief experimental pain and finds no consistent evidence for such a relationship.

This study investigates whether the aperiodic component of EEG in the medial prefrontal cortex can differentiate between individuals with chronic pain and healthy controls, finding no significant differences.

This paper investigates the relationship between respiratory patterns and arousal, finding stronger coupling during rest and a role for respiratory rate in modulating arousal dynamics.

The paper re-analyzes MEG data to show cerebellar activity aligns with rhythmic speech and persists as 'entrainment echoes' after the stimulus stops, coupling with the left inferior frontal gyrus.

This study examines intrinsic brain network function in chronic pain using EEG data from 537 individuals, finding some replicable associations but highlighting the need for collaborative research.

The paper identifies neurophysiological markers of cortical hierarchy and shows how these markers change with age using MEG data from 350 participants.

This study uses MEG time-series analysis to identify neural markers predictive of age, finding that temporal autocorrelation in specific brain regions is the most robust predictor.

This paper introduces new features for characterizing brain states using MEG data and shows they outperform traditional frequency-based features in classification across participants.

This study uses MEG to examine cortico-cortical and cortico-subcortical connectivity during speech production and listening, finding frequency-specific interactions.

This paper introduces a new analysis scheme to improve the robustness of non-invasive functional connectivity assessment by addressing signal leakage and baseline assumptions.

This study dissociates neural tracking of prosodic pauses from multi-word chunk processing using MEG, showing distinct low-frequency brain activity patterns for each.

DISCOVER-EEG is an open, automated EEG pipeline that preprocesses, analyzes, and visualizes resting state EEG data to extract brain function features, tested on two large datasets.

This study investigates how respiration modulates both periodic and aperiodic brain activity using MEG and EEG data, finding phase-locking of aperiodic activity to the respiratory cycle.

This study maps brain connectivity during continuous speaking and listening using MEG, revealing shared and dissociated neural substrates in different frequency bands.

This study investigates how sensory and expectation effects on pain are mediated by distinct brain mechanisms through local oscillations and inter-regional connectivity.

This study uses MEG to examine the timing and neural correlates of associator grapheme-colour synaesthesia, finding evoked activity at ~190 ms localized to occipito-parietal regions, supporting the Disinhibited Feedback model.

The paper investigates breathing coordination during speaking and listening, finding inhalation depth correlates with speech envelope power and inhalation alignment during listening to one's own speech.

The paper investigates how delta and theta brain oscillations contribute to semantic processing during audiovisual speech perception, finding distinct roles for each band in integrating auditory and visual inputs.

This study creates a voxel-based atlas of resting human brain natural frequencies using MEG data from 128 volunteers, revealing region-specific oscillatory patterns.

This study investigates how the brain processes topic keywords in multi-speaker speech using MEG and probabilistic topic modeling, showing differences in neural representation for attended and unattended speech.

The paper examines how arousal influences cortical processing by analyzing pupil and neuronal population dynamics across the human brain.

This study investigates how respiration modulates neural excitability and perceptual performance during a spatial detection task, finding that respiration phase lags align sensory sampling with cortical excitability cycles.

This study investigates how respiration modulates brain oscillations at rest using MEG data and phase-amplitude coupling analysis, revealing widespread neural network activity modulations.

This paper compares frequency-domain connectivity measures for cerebro-peripheral analysis using simulated and real MEG data, finding that wppc and gcmi perform best overall.

This paper develops an artifact rejection method for MEG data during speech production, showing it effectively removes speech-related distortions.