María E. Pedreira
- Behavioral Neuroscience top 1%
- Stress Responses and Cortisol 5
- Cognitive Neuroscience top 1%
- Memory and Neural Mechanisms 37
- Memory Processes and Influences 16
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- Neuroscience and Neuropharmacology Research 18
- Neurobiology and Insect Physiology Research 16
- Neurology top 5%
- Social Psychology top 2%
- Neuroendocrine regulation and behavior 10
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- Zebrafish Biomedical Research Applications 7
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- Crustacean biology and ecology 5
- Co-authors
- Héctor MaldonadoCecilia ForcatoLuis Marı́a Pérez-CuestaRodrigo S. FernándezDaniel TomsicPablo ArgibayMariano M. BocciaArturo Romano
- Journals
- Neurobiology of Learning and Memory (11 papers)Scientific Reports (5 papers)Animal Cognition (4 papers)
- Partner nations
- ArgentinaUnited KingdomUnited States
In The Last Decade
María E. Pedreira
62 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 116
- Behavioral Neuroscience 372
- Cognitive Neuroscience 1.8k
- Cellular and Molecular Neuroscience 1.4k
- Neurology 223
- Social Psychology 443
Countries citing papers authored by María E. Pedreira
This map shows the geographic impact of María E. Pedreira'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 María E. Pedreira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites María E. Pedreira more than expected).
Fields of papers citing papers by María E. Pedreira
This network shows the impact of papers produced by María E. Pedreira. 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 María E. Pedreira. The network helps show where María E. Pedreira may publish in the future.
Co-authorship network
The 25 scholars most cited alongside María E. Pedreira, 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 | 2024 | 13 | |
| 2 | 2022 | 37 | |
| 3 | 2021 | 9 | |
| 4 | 2021 | 5 | |
| 5 | 2020 | 8 | |
| 6 | 2020 | 9 | |
| 7 | 2019 | 6 | |
| 8 | 2019 | 13 | |
| 9 | 2018 | 1 | |
| 10 | 2017 | 2 | |
| 11 | 2016 | 23 | |
| 12 | 2012 | 27 | |
| 13 | 2012 | 19 | |
| 14 | 2011 | 70 | |
| 15 | 2002 | 12 | |
| 16 | 2002 | 20 | |
| 17 | 1996 | 35 | |
| 18 | 1996 | 68 | |
| 19 | 1995 | 20 | |
| 20 | 1995 | 58 |
About María E. Pedreira
María E. Pedreira is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Behavioral Neuroscience, having authored 66 papers that have together received 2.7k indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (37 papers), Neuroscience and Neuropharmacology Research (18 papers), Memory Processes and Influences (16 papers), Neurobiology and Insect Physiology Research (16 papers), Neuroendocrine regulation and behavior (10 papers), Zebrafish Biomedical Research Applications (7 papers), Stress Responses and Cortisol (5 papers) and Crustacean biology and ecology (5 papers). The work is most often cited by research in Behavioral Neuroscience (372 citations), Cognitive Neuroscience (1.8k citations) and Cellular and Molecular Neuroscience (1.4k citations). María E. Pedreira has collaborated with scholars based in Argentina, United Kingdom and United States. Frequent co-authors include Héctor Maldonado, Cecilia Forcato, Luis Marı́a Pérez-Cuesta, Rodrigo S. Fernández, Daniel Tomsic, Pablo Argibay, Mariano M. Boccia, Arturo Romano, Vı́ctor A. Molina and Ricardo Allegri. Their work appears in journals such as Neurobiology of Learning and Memory, Scientific Reports, Animal Cognition, Learning & Memory and PLoS ONE.
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.