Michael Reimann

3.9k total citations
45 papers, 762 citations indexed

About

Michael Reimann is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Materials Chemistry. According to data from OpenAlex, Michael Reimann has authored 45 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 13 papers in Cellular and Molecular Neuroscience and 6 papers in Materials Chemistry. Recurrent topics in Michael Reimann's work include Neural dynamics and brain function (19 papers), Functional Brain Connectivity Studies (10 papers) and Neuroscience and Neural Engineering (8 papers). Michael Reimann is often cited by papers focused on Neural dynamics and brain function (19 papers), Functional Brain Connectivity Studies (10 papers) and Neuroscience and Neural Engineering (8 papers). Michael Reimann collaborates with scholars based in Switzerland, Germany and United Kingdom. Michael Reimann's co-authors include Henry Markram, Rodrigo Perin, Eilif Müller, Srikanth Ramaswamy, Max Nolte, Sean Hill, Christof Koch, Costas A. Anastassiou, Ran Levi and Kathryn Hess and has published in prestigious journals such as Nature Communications, Neuron and SHILAP Revista de lepidopterología.

In The Last Decade

Michael Reimann

30 papers receiving 727 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Reimann Switzerland 11 510 297 95 84 80 45 762
Rishidev Chaudhuri United States 8 955 1.9× 278 0.9× 90 0.9× 73 0.9× 19 0.2× 11 1.1k
Nicholas M. Timme United States 16 867 1.7× 385 1.3× 144 1.5× 236 2.8× 36 0.5× 23 1.2k
Sacha J. van Albada Germany 17 871 1.7× 395 1.3× 238 2.5× 58 0.7× 15 0.2× 46 1.2k
Daniel Chicharro Italy 17 596 1.2× 246 0.8× 62 0.7× 138 1.6× 14 0.2× 23 823
Sarah F. Muldoon United States 13 703 1.4× 272 0.9× 30 0.3× 156 1.9× 20 0.3× 40 1.1k
Robert A. McDougal United States 14 367 0.7× 276 0.9× 107 1.1× 24 0.3× 13 0.2× 40 702
Marja‐Leena Linne Finland 16 283 0.6× 361 1.2× 55 0.6× 91 1.1× 23 0.3× 63 789
Sharon Crook United States 16 609 1.2× 295 1.0× 136 1.4× 123 1.5× 11 0.1× 57 1.0k
Remus Oşan United States 14 353 0.7× 202 0.7× 56 0.6× 70 0.8× 11 0.1× 33 617
Michiel W. H. Remme Germany 14 484 0.9× 390 1.3× 63 0.7× 74 0.9× 9 0.1× 26 630

Countries citing papers authored by Michael Reimann

Since Specialization
Citations

This map shows the geographic impact of Michael Reimann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Reimann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Reimann more than expected).

Fields of papers citing papers by Michael Reimann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Reimann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Reimann. The network helps show where Michael Reimann may publish in the future.

Co-authorship network of co-authors of Michael Reimann

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Reimann. A scholar is included among the top collaborators of Michael Reimann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Reimann. Michael Reimann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Farcito, Silvia, Bryn Lloyd, Armando Romani, et al.. (2025). BlueRecording: A pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models. PLoS Computational Biology. 21(5). e1013023–e1013023. 1 indexed citations
2.
Agnesi, Filippo, Bryn Lloyd, Silvia Farcito, et al.. (2025). Simulation insights on the compound action potential in multifascicular nerves. PLoS Computational Biology. 21(9). e1013452–e1013452.
3.
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5.
Hernando, Juan, et al.. (2024). Enhancement of brain atlases with laminar coordinate systems: Flatmaps and barrel column annotations. Imaging Neuroscience. 2. 3 indexed citations
6.
Reimann, Michael, et al.. (2024). Specific inhibition and disinhibition in the higher-order structure of a cortical connectome. Cerebral Cortex. 34(11). 2 indexed citations
7.
Ecker, András, et al.. (2024). Cortical cell assemblies and their underlying connectivity: An in silico study. PLoS Computational Biology. 20(3). e1011891–e1011891. 3 indexed citations
8.
Pokorny, Christoph, et al.. (2024). Heterogeneous and higher-order cortical connectivity undergirds efficient, robust, and reliable neural codes. iScience. 28(1). 111585–111585. 2 indexed citations
9.
Reimann, Michael, et al.. (2023). A parcellation scheme of mouse isocortex based on reversals in connectivity gradients. Network Neuroscience. 7(3). 999–1021. 1 indexed citations
10.
Reimann, Michael, Judit Symmank, Markus H. Gräler, et al.. (2023). Immunometabolic capacities of nutritional fatty acids in regulation of inflammatory bone cell interaction and systemic impact of periodontal infection. Frontiers in Immunology. 14. 1213026–1213026. 5 indexed citations
11.
Verasztó, Csaba, et al.. (2023). Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons. PLoS Computational Biology. 19(1). e1010058–e1010058. 2 indexed citations
12.
Verasztó, Csaba, Michael Reimann, Daniel Keller, et al.. (2022). A method to estimate the cellular composition of the mouse brain from heterogeneous datasets. PLoS Computational Biology. 18(12). e1010739–e1010739. 14 indexed citations
13.
Newton, Taylor, et al.. (2021). In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations. Nature Communications. 12(1). 3630–3630. 8 indexed citations
14.
Nolte, Max, Eyal Gal, Henry Markram, & Michael Reimann. (2020). Impact of higher order network structure on emergent cortical activity. Network Neuroscience. 4(1). 292–314. 17 indexed citations
15.
Reimann, Michael. (2019). Peace journalism in marginally to moderately escalated conflicts: Conflict theoretical foundations, variables and reportage patterns. SHILAP Revista de lepidopterología.
16.
Reimann, Michael, Michael Gevaert, Ying Shi, et al.. (2019). A null model of the mouse whole-neocortex micro-connectome. Nature Communications. 10(1). 3903–3903. 23 indexed citations
17.
Gal, Eyal, Michael London, Amir Globerson, et al.. (2017). Rich cell-type-specific network topology in neocortical microcircuitry. Nature Neuroscience. 20(7). 1004–1013. 76 indexed citations
18.
Reimann, Michael, James King, Eilif Müller, Srikanth Ramaswamy, & Henry Markram. (2015). An algorithm to predict the connectome of neural microcircuits. Frontiers in Computational Neuroscience. 9. 120–120. 68 indexed citations
19.
Reimann, Michael, Costas A. Anastassiou, Rodrigo Perin, et al.. (2013). A Biophysically Detailed Model of Neocortical Local Field Potentials Predicts the Critical Role of Active Membrane Currents. Neuron. 79(2). 375–390. 174 indexed citations
20.
Reimann, Michael, et al.. (1979). Penetration of hot melts into concrete structures. Transactions of the American Nuclear Society. 31. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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