Lee Averell
Impact in
- General Decision Sciences top 5%
- Decision-Making and Behavioral Economics
- Cognitive Neuroscience top 10%
- Neural and Behavioral Psychology Studies
- Neural dynamics and brain function
- Memory Processes and Influences
- Visual perception and processing mechanisms
Papers in
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- Memory Processes and Influences 3
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- Neuroendocrine regulation and behavior 2
- Deception detection and forensic psychology 1
- Co-authors
- Andrew Heathcote (5 shared papers)Chris Donkin (2 shared papers)Scott Brown (2 shared papers)Peter R. Dunkley (1 shared paper)Phillip W. Dickson (1 shared paper)Deborah M. Hodgson (2 shared papers)Luba Sominsky (1 shared paper)Eugene Nalivaiko (2 shared papers)
- Journals
- Autonomic Neuroscience (1 paper)Journal of Experimental Psychology Learning Memory and Cognition (1 paper)Journal of Mathematical Psychology (1 paper)Behavior Research Methods (1 paper)Journal of Memory and Language (1 paper)
- Partner nations
- Australia
In The Last Decade
Lee Averell
7 papers receiving 470 citations
Peers
Comparison fields: 5 of 107
- General Decision Sciences 67
- Cognitive Neuroscience 220
- Biological Psychiatry 23
- Behavioral Neuroscience 32
- Experimental and Cognitive Psychology 73
Countries citing papers authored by Lee Averell
This map shows the geographic impact of Lee Averell'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 Lee Averell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lee Averell more than expected).
Fields of papers citing papers by Lee Averell
This network shows the impact of papers produced by Lee Averell. 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 Lee Averell. The network helps show where Lee Averell may publish in the future.
Co-authors
The 10 scholars most cited alongside Lee Averell, 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 | 2010 | 172 | |
| 2 | 2014 | 160 | |
| 3 | 2013 | 83 | |
| 4 | 2009 | 68 | |
| 5 | 2016 | 7 | |
| 6 | Long term implicit and explicit memory for briefly studied words | 2009 | 2 |
| 7 | 2013 | 1 |
About Lee Averell
Lee Averell is a scholar working on Cognitive Neuroscience, Social Psychology, General Decision Sciences, Artificial Intelligence and Management Science and Operations Research, having authored 7 papers that have together received 493 indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (3 papers), Memory Processes and Influences (3 papers), Forecasting Techniques and Applications (2 papers), Neuroendocrine regulation and behavior (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Deception detection and forensic psychology (1 paper), Tryptophan and brain disorders (1 paper) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in General Decision Sciences (67 citations), Cognitive Neuroscience (220 citations), Biological Psychiatry (23 citations), Behavioral Neuroscience (32 citations) and Experimental and Cognitive Psychology (73 citations). Lee Averell has collaborated with scholars based in Australia. Frequent co-authors include Andrew Heathcote, Chris Donkin, Scott Brown, Peter R. Dunkley, Phillip W. Dickson, Deborah M. Hodgson, Luba Sominsky, Eugene Nalivaiko, Lin Kooi Ong and Melissa Prince. Their work appears in journals such as Autonomic Neuroscience, Journal of Experimental Psychology Learning Memory and Cognition, Journal of Mathematical Psychology, Behavior Research Methods and Journal of Memory and Language.
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.