Arno Villringer

The paper shows that individual heartbeats reflect distinct prediction processes during human probabilistic learning, with specific cardiac responses linked to anticipation, orienting, and feedback-based updating.

This paper introduces a canonical correlation approach for multi-channel cardiac artefact removal in EEG data and shows it outperforms traditional methods in reducing artefacts while preserving neural signals.

The paper investigates how expectations about AI-generated images affect neural preparation, finding lower alpha power when expecting fake faces compared to real ones.

This study examines how acute stress reconfigures macroscale cortical organization and its relation to peripheral stress measures using functional cortical gradients.

This paper reviews 132 HER studies using M/EEG, identifies methodological inconsistencies, and provides a checklist and dataset to improve standardization and reproducibility.

The paper examines how structural brain features relate to functional activity across individuals and brain regions, finding distinct mechanisms for intra- and inter-individual variability in alpha power.

The paper investigates associations between retinal nerve fibre layer thickness and brain grey/white matter structure, finding some links but not supporting cardiovascular risk factor associations.

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 shows that aperiodic broadband power, not just beta oscillations, is linked to Parkinson's disease severity and is increased in the more affected hemisphere.

This study uses EEG and immersive VR to show that facial expressions can be decoded reliably in 3D space, with depth cues having a distinct neural signature but not affecting expression decoding.

The paper investigates how pre-stimulus beta power in different cortical areas predicts explicit and implicit perceptual biases in somatosensory detection tasks.

This study investigates how cardiac signals influence the perception of motor intention during Libet's task, finding that movement initiation aligns with the diastolic phase of the cardiac cycle.

This study identifies white matter disconnection patterns linked to proprioceptive deficits after stroke using CLSM and kinematic assessments in chronic stroke survivors.

This study investigates how spatial and feature attention interact in the frontoparietal cortex to selectively code task-relevant information during a visual discrimination task.

This study shows motor imagery enhances learning of both imagined and linked overt movements, supported by neural evidence of event-related synchronization.

The paper investigates whether somatosensory perception excitability depends on feedforward neuronal spikes, finding no evidence for such a link using HFO metrics and Bayesian analysis.

This study validates surrogate procedures for controlling heartbeat-independent confounding in HEP analysis using simulations and real EEG data, showing that uncontrolled analyses can falsely link HEPs to task-related measures.

The paper examines macro-scale brain activity patterns during wakeful rest, linking them to personality traits and ongoing thoughts by analyzing interactions between brain networks.

The paper shows that personality traits are more strongly associated with brain activity in specific tasks than in others, highlighting the need for context-specific analyses.

This paper develops a multi-channel electrophysiology method to non-invasively record human spinal cord activity with high temporal resolution and demonstrates its application in studying somatosensation and nociception.

This study investigates how obesity affects working memory gating and finds that dopaminergic gene variants and amino acid ratios influence cognitive flexibility in high-BMI individuals.

This study investigates brain-heart interactions during emotional arousal in immersive VR, finding reduced HEP amplitudes and altered information flow in temporo-occipital regions.

This study uses explainable AI to link brain-age prediction models with neuroimaging features of aging, revealing correlations between voxel relevance and structural brain markers.

This study investigates BCI performance using longitudinal data and finds that signal-to-noise ratio, not mu rhythm connectivity, predicts performance across multiple analysis pipelines.

The paper analyzes neural responses to extrasystoles using EEG and ECG data, finding reduced HEP for ventricular extrasystoles and increased HEP in postextrasystolic beats.

This study uses transcranial stimulation to show that frontal delta oscillations causally affect heartbeat perception, with enhanced synchrony reducing detection accuracy.

This study identifies 25 genetic loci associated with brain age gap and links them to mental and physical health traits using genome-wide data from UK Biobank.

This study investigates structural brain connectivity differences in children with developmental dyscalculia using diffusion tensor imaging and finds reduced white matter coherence and shorter tract lengths in specific brain regions associated with math ability.

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.

The paper investigates how visual memory array eccentricity affects EEG markers of visual short-term memory in a virtual reality setup, finding that CDA amplitude varies with memory load at certain eccentricities while alpha lateralization does not.