Author

Maximilian Hommelsen

Forschungszentrum JülichORCID 0000-0003-1972-0465Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Assay:electronic health records· 2 Organism:human· 2 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Silvia DauniD· 2 shared Gereon R. FinkiD· 1 shared Nils RosjatiD· 1 shared Shivakumar ViswanathaniD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersNeuroscience

Silvia DaunORCID

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2 papers

Recent·Most cited

NeuroscienceImaging NeurosciencePeer-reviewedFeb 28, 2024

Previous motor task performance impacts phase-based EEG resting-state connectivity states

Nils Rosjat, Maximilian Hommelsen, Gereon R. Fink, Silvia Daun

The paper analyzes resting-state EEG data using phase-based connectivity states and shows that motor task performance affects these states but not classical microstates.

4 citations

humanelectronic health records

𝕏 PostBluesky

NeuroscienceEuropean Journal of NeurosciencePeer-reviewedApr 20, 2022

Robustness of individualized inferences from longitudinal resting state dynamics

Maximilian Hommelsen, Shivakumar Viswanathan, Silvia Daun

The paper assesses whether longitudinal resting state EEG data can reliably distinguish neurophysiological changes from cognitive state confounding, finding that multi-frequency, multi-channel classifiers achieve high cross-day accuracy.

8 citations

humanelectronic health records

𝕏 PostBluesky