Author

Rico Fischer

Universität GreifswaldORCID 0000-0002-7142-1756Unclaimed 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:benchmarking· 3 Approach:statistical model· 3 Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:electronic health records· 1 Assay:imaging· 1

Frequent Co-Authors

Marcus MeinzeriD· 3 shared Agnes FlöeliD· 2 shared Axel ThielscheriD· 2 shared Daria AntonenkoiD· 2 shared Dagmar TimmanniD· 1 shared Dayana HayekiD· 1 shared Devu MahesaniD· 1 shared Felix BlankenburgiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersNeuroscience

Marcus MeinzerORCID

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3 papers

Recent·Most cited

Inhibition in motion: Test-retest reliability of inhibitory kinematics in a go/no-go mouse tracking task

Devu Mahesan, Komal Sharma, Maike Katharina Weinerth, Suman Dhaka, Marcus Meinzer, Rico Fischer

This study evaluates the test-retest reliability of kinematic measures in a mouse-tracking go/no-go task, finding moderate-to-good reliability for inhibitory control metrics.

bioRxiv · May 9, 2026 · PreprintNeuroscience

Harmonizing the stimulation dose of focal tDCS across target sites

Axel Thielscher, Dayana Hayek, Oula Puonti, Ulrike Grittner, Felix Blankenburg, Rico Fischer, Gesa Hartwigsen, Shu-Chen Li, Marcus Meinzer, Michael Andreas Nitsche, Dagmar Timmann, Agnes Flöel, Daria Antonenko

This paper develops a computational framework to standardize tDCS stimulation doses across brain regions while preserving individual variability, validated in an independent sample.

bioRxiv · Jan 10, 2026 · PreprintNeuroscience

Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies

Filip Niemann, Steffen Riemann, Sophie Dabelstein, Kira Hering, Harun Kocataş, Mohamed Abdelmotaleb, Leonardo M. Caisachana Guevara, Rico Fischer, Axel Thielscher, Daria Antonenko, Agnes Flöel, Marcus Meinzer

The paper develops a deep learning model to automate electrode detection in tDCS-fMRI studies, outperforming manual and semi-automated methods in precision and reducing human bias.

bioRxiv · Dec 25, 2025 · PreprintNeuroscience