Cooper Smout
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Visual perception and processing mechanisms
- Neuroscience and Music Perception
- Face Recognition and Perception
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- Scientific Computing and Data Management
Papers in
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- Visual perception and processing mechanisms 4
- Neural dynamics and brain function 3
- Neural and Behavioral Psychology Studies 3
- Face Recognition and Perception 1
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- Research Data Management Practices 1
- Co-authors
- Jason B. Mattingley (4 shared papers)Matthew F. Tang (2 shared papers)Marta I. Garrido (2 shared papers)Ehsan Arabzadeh (1 shared paper)Paula Andrea Martinez (1 shared paper)Dylan Gomes (1 shared paper)Kaitlyn M. Gaynor (1 shared paper)Patrice Pottier (1 shared paper)
- Journals
- Journal of Cognitive Neuroscience (1 paper)PLoS Biology (1 paper)Proceedings of the Royal Society B Biological Sciences (1 paper)NeuroImage (1 paper)eLife (1 paper)
- Partner nations
- AustraliaCanadaUnited States
In The Last Decade
Cooper Smout
5 papers receiving 182 citations
Peers
Comparison fields: 5 of 48
- Cognitive Neuroscience 110
- Information Systems and Management 25
- Health Informatics 3
- Ecological Modeling 8
- Experimental and Cognitive Psychology 22
Countries citing papers authored by Cooper Smout
This map shows the geographic impact of Cooper Smout'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 Cooper Smout with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cooper Smout more than expected).
Fields of papers citing papers by Cooper Smout
This network shows the impact of papers produced by Cooper Smout. 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 Cooper Smout. The network helps show where Cooper Smout may publish in the future.
Co-authors
The 19 scholars most cited alongside Cooper Smout, 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 | 2019 | 72 | |
| 2 | 2022 | 56 | |
| 3 | 2018 | 43 | |
| 4 | 2020 | 7 | |
| 5 | 2018 | 5 | |
| 6 | 2019 | 0 |
About Cooper Smout
Cooper Smout is a scholar working on Cognitive Neuroscience, Information Systems, Information Systems and Management, Public Health, Environmental and Occupational Health and Experimental and Cognitive Psychology, having authored 6 papers that have together received 183 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (4 papers), Neural dynamics and brain function (3 papers), Neural and Behavioral Psychology Studies (3 papers), Research Data Management Practices (1 paper), Scientific Computing and Data Management (1 paper), Face Recognition and Perception (1 paper), Ethics in Clinical Research (1 paper) and Multisensory perception and integration (1 paper). The work is most often cited by research in Cognitive Neuroscience (110 citations), Information Systems and Management (25 citations), Health Informatics (3 citations), Ecological Modeling (8 citations) and Experimental and Cognitive Psychology (22 citations). Cooper Smout has collaborated with scholars based in Australia, Canada and United States. Frequent co-authors include Jason B. Mattingley, Matthew F. Tang, Marta I. Garrido, Ehsan Arabzadeh, Paula Andrea Martinez, Dylan Gomes, Kaitlyn M. Gaynor, Patrice Pottier, Vivienne Foroughirad and David Moreau. Their work appears in journals such as Journal of Cognitive Neuroscience, PLoS Biology, Proceedings of the Royal Society B Biological Sciences, NeuroImage and eLife.
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.