T. Preece
Impact in
- Cognitive Neuroscience top 5%
- Memory Processes and Influences
- Neural and Behavioral Psychology Studies
- Neurobiology of Language and Bilingualism
- Memory and Neural Mechanisms
- Neuroscience and Music Perception
- Neural dynamics and brain function
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- Reading and Literacy Development
- Child and Animal Learning Development
Papers in
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- Evolutionary Algorithms and Applications 1
- Intelligent Tutoring Systems and Adaptive Learning 1
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- Evolutionary Game Theory and Cooperation 2
- Co-authors
- Charles Hulme (2 shared papers)Gordon D. A. Brown (1 shared paper)Angus Davison (1 shared paper)Yong Mao (3 shared papers)Juan P. Garrahan (1 shared paper)
- Journals
- Psychological Review (2 papers)Journal of Theoretical Biology (1 paper)The American Naturalist (1 paper)Physical Review E (1 paper)
- Partner nations
- United Kingdom
In The Last Decade
T. Preece
3 papers receiving 576 citations
T. Preece's Hit Papers
Peers
Comparison fields: 5 of 55
- Cognitive Neuroscience 521
- Developmental and Educational Psychology 233
- Experimental and Cognitive Psychology 153
- Statistics and Probability 42
- Artificial Intelligence 107
Countries citing papers authored by T. Preece
This map shows the geographic impact of T. Preece'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 T. Preece with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Preece more than expected).
Fields of papers citing papers by T. Preece
This network shows the impact of papers produced by T. Preece. 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 T. Preece. The network helps show where T. Preece may publish in the future.
Co-authors
The 6 scholars most cited alongside T. Preece, 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 | Oscillator-based memory for serial order. Hit paper breakdown → | 2000 | 546 |
| 2 | 2000 | 50 | |
| 3 | 2009 | 7 | |
| 4 | 2009 | 1 | |
| 5 | 2006 | 0 |
About T. Preece
T. Preece is a scholar working on Artificial Intelligence, Sociology and Political Science, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation and Information Systems, having authored 5 papers that have together received 604 indexed citations. Recurring topics across this work include Plant and animal studies (2 papers), Evolutionary Game Theory and Cooperation (2 papers), Cellular Automata and Applications (1 paper), Evolutionary Algorithms and Applications (1 paper), Intelligent Tutoring Systems and Adaptive Learning (1 paper), Evolution and Genetic Dynamics (1 paper), Species Distribution and Climate Change (1 paper) and Memory Processes and Influences (1 paper). The work is most often cited by research in Cognitive Neuroscience (521 citations), Developmental and Educational Psychology (233 citations), Experimental and Cognitive Psychology (153 citations), Statistics and Probability (42 citations) and Artificial Intelligence (107 citations). T. Preece has collaborated with scholars based in United Kingdom. Frequent co-authors include Charles Hulme, Gordon D. A. Brown, Gordon D. A. Brown, Angus Davison, Yong Mao and Juan P. Garrahan. Their work appears in journals such as Psychological Review, Journal of Theoretical Biology, The American Naturalist and Physical Review E.
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.