Author

Matthias Zunhammer

Essen University HospitalORCID 0000-0002-3680-9675Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:imaging· 3 Research Focus:benchmarking· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Bálint KincsesiD· 3 shared Tamás SpisákiD· 3 shared Ulrike BingeliD· 3 shared Frederik SchlittiD· 2 shared Tobias Schmidt‐WilckeiD· 2 shared Zsigmond Tamás KincsesiD· 2 shared Helena HartmanniD· 1 shared Katja WiechiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersNeuroscience

Bálint KincsesORCID

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3 papers

Recent·Most cited

Meta-analytic evidence for distinct neural correlates of conditioned vs. verbally induced placebo analgesia

Tamás Spisák, Helena Hartmann, Matthias Zunhammer, Bálint Kincses, Katja Wiech, Tor Dessart Wager, Ulrike Bingel

This study compares neural mechanisms of placebo analgesia induced by verbal suggestions and conditioning, finding distinct brain activity patterns and enhanced analgesia when combined.

bioRxiv · May 21, 2025 · PreprintNeuroscience

Gray matter cortical thickness predicts individual pain sensitivity: a multi-center machine learning approach

Raviteja Kotikalapudi, Bálint Kincses, Matthias Zunhammer, Frederik Schlitt, Tobias Schmidt‐Wilcke, Zsigmond Tamás Kincses, Livia Asan, Ulrike Bingel, Tamás Spisák

This study develops a multi-center machine learning model using gray matter cortical thickness to predict individual pain sensitivity, achieving a moderate predictive performance.

bioRxiv · Jun 14, 2022 · PreprintNeuroscience

Pain-free resting-state functional brain connectivity predicts individual pain sensitivity

Tamás Spisák, Bálint Kincses, Frederik Schlitt, Matthias Zunhammer, Tobias Schmidt‐Wilcke, Zsigmond Tamás Kincses, Ulrike Bingel

The paper identifies a resting-state brain connectivity pattern predictive of individual pain sensitivity without painful stimulation.

Nature Communications · Jan 10, 2020Peer-reviewedNeuroscience