Nina M. Hanning
- Cognitive Neuroscience top 5%
- Experimental and Cognitive Psychology
- Computer Vision and Pattern Recognition
- Social Psychology
- Cellular and Molecular Neuroscience
- Co-authors
- Heiner DeubelMarisa CarrascoMartin SzinteDonatas JonikaitisMarc M. HimmelbergHsin-Hung LiDavid Aagten‐MurphyMarian Sauter
- Topics
- Visual perception and processing mechanisms (23 papers)Neural and Behavioral Psychology Studies (16 papers)Neural dynamics and brain function (8 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsJournal of Neuroscience
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Nina M. Hanning
26 papers receiving 437 citations
Peers
Comparison fields: 5 of 55
- Cognitive Neuroscience 388
- Experimental and Cognitive Psychology 46
- Computer Vision and Pattern Recognition 44
- Social Psychology 37
- Cellular and Molecular Neuroscience 29
Countries citing papers authored by Nina M. Hanning
This map shows the geographic impact of Nina M. Hanning'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 Nina M. Hanning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina M. Hanning more than expected).
Fields of papers citing papers by Nina M. Hanning
This network shows the impact of papers produced by Nina M. Hanning. 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 Nina M. Hanning. The network helps show where Nina M. Hanning may publish in the future.
Co-authorship network of co-authors of Nina M. Hanning
This figure shows the co-authorship network connecting the top 25 collaborators of Nina M. Hanning. A scholar is included among the top collaborators of Nina M. Hanning 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 Nina M. Hanning. Nina M. Hanning is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 7 | |
| 4 | 12 | |
| 5 | 2 | |
| 6 | 11 | |
| 7 | 16 | |
| 8 | 19 | |
| 9 | 10 | |
| 10 | 7 | |
| 11 | 24 | |
| 12 | 3 | |
| 13 | 34 | |
| 14 | 15 | |
| 15 | 36 | |
| 16 | 16 | |
| 17 | 25 | |
| 18 | 33 | |
| 19 | 58 | |
| 20 | 45 |
About Nina M. Hanning
Nina M. Hanning is a scholar working on Cognitive Neuroscience, Human-Computer Interaction and Neurology, having authored 26 papers that have together received 439 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (23 papers), Neural and Behavioral Psychology Studies (16 papers) and Neural dynamics and brain function (8 papers). The work is most often cited by research in Cognitive Neuroscience (388 citations), Sensory Systems (25 citations) and Human-Computer Interaction (22 citations). Nina M. Hanning has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Heiner Deubel, Marisa Carrasco, Martin Szinte, Donatas Jonikaitis, Marc M. Himmelberg, Hsin-Hung Li, David Aagten‐Murphy, Marian Sauter, Heinrich R. Liesefeld and Hermann J. Müller. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.
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.