Author

Daniel Sharoh

Radboud University NijmegenORCID 0000-0002-6941-5680Unclaimed 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 Approach:experimental assay· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Assay:electronic health records· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1

Frequent Co-Authors

Peter Hagoort AiD· 2 shared David Gordon NorrisiD· 1 shared Fanhua GuoiD· 1 shared Jakob Udby BlicheriD· 1 shared Jiepin HuangiD· 1 shared Katrien SegaertiD· 1 shared Kirsten WeberiD· 1 shared Lasse KnudseniD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersNeuroscience

Peter Hagoort AORCID

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3 papers

Recent·Most cited

The laminar pattern of proprioceptive activation in human primary motor cortex

Lasse Knudsen, Fanhua Guo, Daniel Sharoh, Jiepin Huang, Jakob Udby Blicher, Torben E. Lund, Yan Zhou, Peng Zhang, Yan Tong Yang

This study uses laminar fMRI to show that deep layers of human primary motor cortex are activated during proprioceptive stimulation, suggesting their role in proprioceptive circuits.

Cerebral Cortex · Mar 20, 2025Peer-reviewedNeuroscience

Diverging Neural Dynamics for Syntactic Structure Building in Naturalistic Speaking and Listening

Laura Giglio, Markus Ostarek, Daniel Sharoh, Peter Hagoort A

This study compares syntactic processing in speaking and listening by analyzing neural dynamics during naturalistic tasks, finding divergent patterns in structure building.

Proceedings of the National Academy of Sciences · Mar 5, 2024Peer-reviewedNeuroscience

Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing

Daniel Sharoh, Tim van Mourik, Lauren J. Bains, Katrien Segaert, Kirsten Weber, Peter Hagoort A, David Gordon Norris

This study demonstrates that laminar fMRI can reveal directed connectivity in whole-brain networks during language processing by identifying top-down signal contributions in language-critical regions.

Proceedings of the National Academy of Sciences · Sep 30, 2019Peer-reviewedNeuroscience