Michael Hanke
- Cognitive Neuroscience top 1%
- Functional Brain Connectivity Studies 20
- Neural dynamics and brain function 15
- Visual perception and processing mechanisms 9
- Face Recognition and Perception 7
- Structural Biology top 5%
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- Scientific Computing and Data Management 9
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- Graphene research and applications 8
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- Chalcogenide Semiconductor Thin Films 8
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- Research Data Management Practices 7
- Co-authors
- Yaroslav O. HalchenkoJames V. HaxbyJ. Swaroop GuntupalliAndrew C. ConnollyStefan PollmannPeter J. RamadgeStephen José HansonPer B. Sederberg
- Partner nations
- GermanyUnited StatesFrance
In The Last Decade
Michael Hanke
82 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Cognitive Neuroscience 2.0k
- Experimental and Cognitive Psychology 312
- Structural Biology 31
- Radiology, Nuclear Medicine and Imaging 427
- Statistics, Probability and Uncertainty 126
Countries citing papers authored by Michael Hanke
This map shows the geographic impact of Michael Hanke'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 Hanke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hanke more than expected).
Fields of papers citing papers by Michael Hanke
This network shows the impact of papers produced by Michael Hanke. 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 Hanke. The network helps show where Michael Hanke may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Hanke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2023 | 5 | |
| 3 | 2023 | 12 | |
| 4 | 2022 | 8 | |
| 5 | 2022 | 10 | |
| 6 | 2021 | 9 | |
| 7 | 2020 | 3 | |
| 8 | 2020 | 27 | |
| 9 | 2017 | 63 | |
| 10 | Best practices in data analysis and sharing in neuroimaging using MRIbreakdown → | 2017 | 412 |
| 11 | PyMVPA: MultiVariate Pattern Analysis in Python | 2017 | 0 |
| 12 | 2017 | 11 | |
| 13 | Brains on Beats | 2016 | 7 |
| 14 | 2016 | 26 | |
| 15 | 2013 | 15 | |
| 16 | 2012 | 260 | |
| 17 | 2012 | 20 | |
| 18 | 2012 | 35 | |
| 19 | 2011 | 2 | |
| 20 | 2010 | 13 |
About Michael Hanke
Michael Hanke is a scholar working on Structural Biology, Cognitive Neuroscience, Information Systems and Management, Biophysics and Materials Chemistry, having authored 87 papers that have together received 3.3k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (20 papers), Neural dynamics and brain function (15 papers), Scientific Computing and Data Management (9 papers), Visual perception and processing mechanisms (9 papers), Graphene research and applications (8 papers), Chalcogenide Semiconductor Thin Films (8 papers), Face Recognition and Perception (7 papers) and Research Data Management Practices (7 papers). The work is most often cited by research in Cognitive Neuroscience (2.0k citations), Experimental and Cognitive Psychology (312 citations), Structural Biology (31 citations), Radiology, Nuclear Medicine and Imaging (427 citations) and Statistics, Probability and Uncertainty (126 citations). Michael Hanke has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Yaroslav O. Halchenko, James V. Haxby, J. Swaroop Guntupalli, Andrew C. Connolly, Stefan Pollmann, Peter J. Ramadge, Stephen José Hanson, Per B. Sederberg, Bryan Conroy and M. Ida Gobbini. Their work appears in journals such as NeuroImage, Scientific Data, Physical Review B, Frontiers in Neuroinformatics and Applied Physics Letters.
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.