Mark A. Straccia
Impact in
- General Decision Sciences top 5%
- Decision-Making and Behavioral Economics
- Cognitive Neuroscience top 5%
- Neural and Behavioral Psychology Studies
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Memory and Neural Mechanisms
Papers in
-
- Neural and Behavioral Psychology Studies 4
- Memory and Neural Mechanisms 2
- Neural dynamics and brain function 1
-
- Decision-Making and Behavioral Economics 2
- Co-authors
- Jonathan D. Cohen (4 shared papers)Amitai Shenhav (4 shared papers)Matthew Botvinick (3 shared papers)Matthew D. Lieberman (2 shared papers)Kevin M. Tan (2 shared papers)Meng Du (1 shared paper)Meghan L. Meyer (1 shared paper)Robert C. Wilson (1 shared paper)
- Journals
- Nature Communications (2 papers)Psychological Medicine (1 paper)Nature Neuroscience (1 paper)Neuroscience & Biobehavioral Reviews (1 paper)Cognitive Affective & Behavioral Neuroscience (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Mark A. Straccia
6 papers receiving 505 citations
Peers
Comparison fields: 5 of 85
- General Decision Sciences 62
- Cognitive Neuroscience 357
- Applied Psychology 37
- Experimental and Cognitive Psychology 81
- Social Psychology 95
Countries citing papers authored by Mark A. Straccia
This map shows the geographic impact of Mark A. Straccia'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 Mark A. Straccia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Straccia more than expected).
Fields of papers citing papers by Mark A. Straccia
This network shows the impact of papers produced by Mark A. Straccia. 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 Mark A. Straccia. The network helps show where Mark A. Straccia may publish in the future.
Co-authors
The 13 scholars most cited alongside Mark A. Straccia, 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 | 186 | |
| 2 | 2014 | 180 | |
| 3 | 2019 | 63 | |
| 4 | 2016 | 44 | |
| 5 | 2018 | 27 | |
| 6 | 2021 | 11 |
About Mark A. Straccia
Mark A. Straccia is a scholar working on Cognitive Neuroscience, General Decision Sciences, Social Psychology, Artificial Intelligence and Experimental and Cognitive Psychology, having authored 6 papers that have together received 511 indexed citations. Recurring topics across this work include Neural and Behavioral Psychology Studies (4 papers), Memory and Neural Mechanisms (2 papers), Decision-Making and Behavioral Economics (2 papers), Neural Networks and Applications (1 paper), Attachment and Relationship Dynamics (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Machine Learning and Algorithms (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in General Decision Sciences (62 citations), Cognitive Neuroscience (357 citations), Applied Psychology (37 citations), Experimental and Cognitive Psychology (81 citations) and Social Psychology (95 citations). Mark A. Straccia has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Jonathan D. Cohen, Amitai Shenhav, Matthew Botvinick, Matthew D. Lieberman, Kevin M. Tan, Meng Du, Meghan L. Meyer, Robert C. Wilson, Sebastian Musslick and Naomi I. Eisenberger. Their work appears in journals such as Nature Communications, Psychological Medicine, Nature Neuroscience, Neuroscience & Biobehavioral Reviews and Cognitive Affective & Behavioral Neuroscience.
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.