Author

Michael Burke

Leibniz Research Centre for Working Environment and Human FactorsORCID 0000-0002-8516-9889Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 4

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 3 Research Focus:benchmarking· 2 Assay:imaging· 2 Assay:multiome· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1

Frequent Co-Authors

Erhan GençiD· 4 shared Michael Andreas NitscheiD· 4 shared Harleen ChhabraiD· 2 shared Asad Khan· 1 shared Carsten WatzliD· 1 shared Christina Stammen· 1 shared Christoph FraenziD· 1 shared Daniel SchneideriD· 1 shared

Activity by Year

2025-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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4 shared papersNeuroscience

Erhan GençORCID

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Author profile →

4 papers

Recent·Most cited

Testing the reliability of novel Voxel Placement approaches for Magnetic Resonance Spectroscopy

Harleen Chhabra, Melina Hehl, Koen Cuypers, Ulrike Dydak, Michael Andreas Nitsche, Erhan Genç, Michael Burke

This study evaluates three voxel placement methods for MRS, finding that SSVR significantly improves reliability and reduces metabolite variability in challenging regions.

bioRxiv · Aug 21, 2026 · PreprintNeuroscience

Optimizing Network-Level TMS-fMRI: Benchmarking the TMS-Compatible Sushi MR Setup

Yiwu Xiong, Michael Burke, Lorena Melo, Kuri Takahashi, Maximilian Lueckel, Til Ole Bergmann, Michael Andreas Nitsche, Erhan Genç, Emilio Chiappini

The paper benchmarks a TMS-compatible Sushi MR setup for whole-brain fMRI, showing it matches a 64-channel reference in resting-state networks and improves task-fMRI with multi-echo combination.

bioRxiv · Jul 26, 2026 · PreprintNeuroscience

Determining Reliable Neural Targets for enhancing Motor Sequence Learning: A preparatory study for focal tDCS

Asad Khan, Michael Burke, Erhan Genç, Harleen Chhabra, Min-Fang Kuo, Michael Andreas Nitsche

This study characterizes an fMRI-based SRTT protocol and identifies consistent neural signatures for motor sequence learning, providing targets for tDCS interventions.

bioRxiv · Jun 29, 2026 · PreprintNeuroscience

Electrophysiological resting-state signatures link polygenic scores to general intelligence

Rebecca Engler, Christina Stammen, Stefan Arnau, Javier Schneider Penate, Dorothea Metzen, Jan Digutsch, Patrick Darius Gajewski, Stephan Getzmann, Christoph Fraenz, Jörg Reinders, Manuel C. Voelkle, Fabian Streit, Sebastian Ocklenburg, Daniel Schneider, Michael Burke, , Erhan Genç

This study links polygenic scores for intelligence to general intelligence using resting-state EEG graph metrics, showing parieto-frontal brain connectivity mediates the genetic association.

Scientific Reports · Nov 21, 2025Peer-reviewedNeuroscience