Eric Hunsberger
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
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- Neuroscience and Neural Engineering
Papers in
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- Neural dynamics and brain function 4
- Face Recognition and Perception 1
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- Neural Networks and Reservoir Computing 1
- Neural Networks and Applications 1
- Co-authors
- Chris Eliasmith (4 shared papers)James Bergstra (2 shared papers)Travis DeWolf (1 shared paper)Daniel Rasmussen (1 shared paper)Aaron R. Voelker (1 shared paper)Trevor Bekolay (1 shared paper)Terrence C. Stewart (1 shared paper)Xuan Choo (1 shared paper)
- Journals
- Cognitive Science (1 paper)Neural Computation (1 paper)Frontiers in Neuroinformatics (1 paper)IEEE Access (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- Canada
In The Last Decade
Eric Hunsberger
5 papers receiving 369 citations
Peers
Comparison fields: 5 of 56
- Cognitive Neuroscience 238
- Cellular and Molecular Neuroscience 87
- Electrical and Electronic Engineering 272
- Artificial Intelligence 129
- Statistical and Nonlinear Physics 16
Countries citing papers authored by Eric Hunsberger
This map shows the geographic impact of Eric Hunsberger'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 Eric Hunsberger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Hunsberger more than expected).
Fields of papers citing papers by Eric Hunsberger
This network shows the impact of papers produced by Eric Hunsberger. 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 Eric Hunsberger. The network helps show where Eric Hunsberger may publish in the future.
Co-authors
The 11 scholars most cited alongside Eric Hunsberger, 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 | 2014 | 299 | |
| 2 | 2014 | 41 | |
| 3 | Training Spiking Deep Networks for Neuromorphic Hardware | 2016 | 34 |
| 4 | A Neural Model of Human Image Categorization | 2013 | 2 |
| 5 | 2017 | 1 |
About Eric Hunsberger
Eric Hunsberger is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 5 papers that have together received 377 indexed citations. Recurring topics across this work include Neural dynamics and brain function (4 papers), stochastic dynamics and bifurcation (1 paper), Neuroscience and Neural Engineering (1 paper), Face Recognition and Perception (1 paper), Neural Networks and Reservoir Computing (1 paper), Advanced Vision and Imaging (1 paper), Image Processing Techniques and Applications (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Cognitive Neuroscience (238 citations), Cellular and Molecular Neuroscience (87 citations), Electrical and Electronic Engineering (272 citations), Artificial Intelligence (129 citations) and Statistical and Nonlinear Physics (16 citations). Eric Hunsberger has collaborated with scholars based in Canada. Frequent co-authors include Chris Eliasmith, James Bergstra, Travis DeWolf, Daniel Rasmussen, Aaron R. Voelker, Trevor Bekolay, Terrence C. Stewart, Xuan Choo, Matthew P. Scott and Peter Blouw. Their work appears in journals such as Cognitive Science, Neural Computation, Frontiers in Neuroinformatics, IEEE Access and arXiv (Cornell University).
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.