Papers

4

Total Citations

151

H-Index

4

About

Arno Villringer is a pioneering neuroscientist whose work sits at the intersection of multimodal neuroimaging, sensorimotor rehabilitation, and the fascinating interplay between perception and emotion. His research is defined by two major thrusts: developing advanced computational methods to fuse functional neuroimaging data, and applying brain stimulation techniques—particularly transcranial direct current stimulation (tDCS)—to understand and enhance sensorimotor function across the lifespan. His most cited work, a 2015 paper on multivariate machine learning for multimodal neuroimaging (95 citations), provides a foundational framework for integrating diverse neural signals, a critical tool for modern cognitive neuroscience. Villringer’s applied contributions are equally impactful; he has demonstrated that anodal tDCS over the primary somatosensory cortex can differentially modulate proprioceptive accuracy in young and older adults, and that dual tDCS setups yield distinct effects on sensorimotor recovery in chronic stroke patients. Beyond motor systems, his creative investigations into cross-modal perception—showing that music can transfer perceived sexiness to the sense of touch—reveal a deep curiosity about how our senses shape social experience. With a career spanning methodological innovation and translational rehabilitation, Villringer’s work continues to influence how we measure, modulate, and understand the human brain.

Research Focus

Key Achievements

4
H-Index
4
Papers
151
Total Citations
38
Avg Citations/Paper
🏆 Most Cited Paper
Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data
95 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Leipzig University, Max Planck Institute for Human Cognitive and Brain Sciences, Humboldt-Universität zu Berlin

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago