Author

Dionysia Kaziki

University Medical Center Hamburg-EppendorfORCID 0000-0001-8826-5801Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Assay:imaging· 1

Frequent Co-Authors

Andreas Karl EngeliD· 2 shared Guido NolteiD· 2 shared Florian GöschliD· 1 shared Gregor LeichtiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersNeuroscience

Andreas Karl EngelORCID

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2 papers

Recent·Most cited

NeuroscienceJournal of Neuroscience MethodsPeer-reviewedMar 14, 2026

Low-Rank Tensor Decomposition for Cross-Bispectral Analysis of EEG Data

Dionysia Kaziki, Andreas Karl Engel, Guido Nolte

This paper introduces a low-rank tensor decomposition framework for cross-bispectral EEG data, enabling structured and interpretable analysis of brain interactions.

DOI 10.1016/j.jneumeth.2026.110739

imagingstatistical model

𝕏 PostBluesky

NeuroscienceJournal of Neuroscience MethodsPeer-reviewedJun 8, 2025

Source to sensor coupling (SoSeC) as an effective tool to localize interacting sources from EEG and MEG data

Florian Göschl, Dionysia Kaziki, Gregor Leicht…·Guido Nolte

The paper introduces a method to localize interacting sources from EEG and MEG data by maximizing source-to-sensor coupling, which is faster and more statistically powerful than conventional approaches.

1 citation

electronic health recordsstatistical model

𝕏 PostBluesky