Jay Buckingham
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Memory and Neural Mechanisms
- Motor Control and Adaptation
- Neurology top 10%
- Vestibular and auditory disorders
Papers in ⓘ
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- Memory and Neural Mechanisms 3
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- Neural Networks and Applications 2
- Speech and dialogue systems 2
- Fuzzy Logic and Control Systems 2
- Co-authors
- David Willshaw (5 shared papers)Andrew G. Barto (2 shared papers)D.C. Barton (1 shared paper)D.A. Crolla (1 shared paper)
- Journals
- Network Computation in Neural Systems (4 papers)Philosophical Transactions of the Royal Society B Biological Sciences (1 paper)Behavioral and Brain Sciences (1 paper)Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (1 paper)Medical Entomology and Zoology (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Jay Buckingham
9 papers receiving 336 citations
Peers
Comparison fields: 5 of 60
- Cognitive Neuroscience 243
- Neurology 101
- Cellular and Molecular Neuroscience 110
- Sensory Systems 21
- Developmental Neuroscience 14
Countries citing papers authored by Jay Buckingham
This map shows the geographic impact of Jay Buckingham'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 Jay Buckingham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Buckingham more than expected).
Fields of papers citing papers by Jay Buckingham
This network shows the impact of papers produced by Jay Buckingham. 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 Jay Buckingham. The network helps show where Jay Buckingham may publish in the future.
Co-authors
The 4 scholars most cited alongside Jay Buckingham, 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 | 1996 | 148 | |
| 2 | 1990 | 83 | |
| 3 | 1993 | 43 | |
| 4 | 1998 | 35 | |
| 5 | 1992 | 31 | |
| 6 | 1993 | 14 | |
| 7 | 1992 | 12 | |
| 8 | Controlling a Nonlinear Spring-Mass System with a Cerebellar Model | 1994 | 2 |
| 9 | Chasing the molecule : discovering the building blocks of life | 2005 | 1 |
About Jay Buckingham
Jay Buckingham is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Neurology, Philosophy and Control and Systems Engineering, having authored 9 papers that have together received 369 indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (3 papers), Robotics and Automated Systems (2 papers), Neural Networks and Applications (2 papers), Speech and dialogue systems (2 papers), Fuzzy Logic and Control Systems (2 papers), Advanced Memory and Neural Computing (2 papers), Hermeneutics and Narrative Identity (1 paper) and Powder Metallurgy Techniques and Materials (1 paper). The work is most often cited by research in Cognitive Neuroscience (243 citations), Neurology (101 citations), Cellular and Molecular Neuroscience (110 citations), Sensory Systems (21 citations) and Developmental Neuroscience (14 citations). Jay Buckingham has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include David Willshaw, Andrew G. Barto, D.C. Barton and D.A. Crolla. Their work appears in journals such as Network Computation in Neural Systems, Philosophical Transactions of the Royal Society B Biological Sciences, Behavioral and Brain Sciences, Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering and Medical Entomology and Zoology.
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.