Georg Northoff

The paper examines if resting-state neural temporal organization persists during sentence processing and links it to semantic anomaly responses.

This paper shows that task engagement in fMRI reorganizes infra-slow BOLD dynamics by redistributing power across frequencies rather than just adding to ongoing activity.

This study identifies a reproducible neurodynamic core of meditation in experienced meditators using EEG, distinguishing it from rest and task states with reliable and consistent features.

The paper investigates how intrinsic neural timescales relate to event-related activity using computational modeling and MEG data, finding that intracolumnar connections are critical for both resting state and task-related responses.

The paper analyzes EEG data from meditators and controls to identify neurodynamic features distinguishing meditation techniques from non-meditative states, finding shared yet distinct signatures across traditions.

This study examines non-duality in advanced meditators using EEG-based intrinsic neural timescales and psychological scales, finding that advanced meditators show reduced distinction between internal and external attention.

This study examines the time-to-onset and temporal dynamics of EEG changes during breath-watching meditation across three groups, finding significant differences in power changes between groups.

This study shows that GABA levels in hMT+ and frontal-hMT+ connectivity correlate with visuo-spatial intelligence, with frontal connectivity mediating the effect of hMT+ GABA.

This study investigates the neural correlates of equanimity in advanced meditators using EEG data and finds shorter intrinsic neural timescales correlate with higher equanimity.

The paper identifies that co-activation of the ventral posterolateral nucleus and global brain activity correlates with physiological arousal but not perceptual awareness.

The paper shows that the brain's timescale hierarchy reduces information transfer in associative regions compared to sensory areas, with human MEG data supporting the findings.

The paper shows that the intrinsic topographic hierarchy of self, consisting of internal, external, and mental layers, exists during rest and tasks, and converges with dynamic measures.

The paper investigates how intrinsic neural activity, particularly frontal power and delta oscillations, correlates with susceptibility to the rubber hand illusion.

The paper identifies cortical hubs associated with consciousness recovery in UWS patients and finds the anterior precuneus is a key region.

The paper investigates how intrinsic neural timescales in the human cortex align with spatial core-periphery organization using MEG data and shows ACW-0 better predicts core vs. periphery regions.

The paper identifies higher-order sensorimotor brain hubs that correlate with consciousness levels across different unconscious states using resting-state fMRI data.

This paper investigates the hybrid nature of task-evoked neural activity using intracranial EEG and Deep Learning LSTM models, showing that poststimulus activity is influenced more by prestimulus dynamics than the external stimulus itself.

The paper investigates intrinsic neural timescales in different behavioural states and finds that sensory deficits are associated with prolonged neural timescales, while motor deficits do not show such changes.

The paper shows that spontaneous neural activity influences stimulus-evoked spectral power through positive and negative interactions in cortical oscillations.

The paper examines how rest-task modulation affects global signal topography in fMRI data, showing it is linked to dynamic co-activation patterns and not fully explained by respiration effects.

This study investigates how infraslow frequencies process information through their temporal dynamics using resting and task state fMRI data.

This paper introduces a category theory framework to analyze the relationship between consciousness and its neural correlates, applying it to integrated information theory and temporo-spatial theory.

This paper investigates the role of the parietal memory network in auditory hallucinations using longitudinal data from schizophrenia patients and finds decreased connectivity in this network correlates with hallucination severity and predicts treatment response.