Marcelo G. Mattar
- Cognitive Neuroscience top 2%
- Experimental and Cognitive Psychology top 5%
- Cellular and Molecular Neuroscience top 10%
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence top 10%
- Co-authors
- Nathaniel D. DawDanielle S. BassettSharon L. Thompson‐SchillGeoffrey K. AguirreMichael W. ColeScott T. GraftonMáté LengyelEvelina Fedorenko
- Topics
- Neural dynamics and brain function (15 papers)Functional Brain Connectivity Studies (8 papers)Visual perception and processing mechanisms (6 papers)
- Journals
- NatureScienceNature Communications
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Marcelo G. Mattar
26 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 94
- Cognitive Neuroscience 952
- Experimental and Cognitive Psychology 227
- Cellular and Molecular Neuroscience 169
- Radiology, Nuclear Medicine and Imaging 101
- Artificial Intelligence 99
Countries citing papers authored by Marcelo G. Mattar
This map shows the geographic impact of Marcelo G. Mattar'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 Marcelo G. Mattar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcelo G. Mattar more than expected).
Fields of papers citing papers by Marcelo G. Mattar
This network shows the impact of papers produced by Marcelo G. Mattar. 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 Marcelo G. Mattar. The network helps show where Marcelo G. Mattar may publish in the future.
Co-authorship network of co-authors of Marcelo G. Mattar
This figure shows the co-authorship network connecting the top 25 collaborators of Marcelo G. Mattar. A scholar is included among the top collaborators of Marcelo G. Mattar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcelo G. Mattar. Marcelo G. Mattar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 12 | |
| 6 | 19 | |
| 7 | 4 | |
| 8 | 90 | |
| 9 | 41 | |
| 10 | 195 | |
| 11 | 8 | |
| 12 | 37 | |
| 13 | 65 | |
| 14 | 15 | |
| 15 | 113 | |
| 16 | 18 | |
| 17 | 46 | |
| 18 | 129 | |
| 19 | 2 | |
| 20 | 60 |
About Marcelo G. Mattar
Marcelo G. Mattar is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Experimental and Cognitive Psychology, having authored 29 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (15 papers), Functional Brain Connectivity Studies (8 papers) and Visual perception and processing mechanisms (6 papers). The work is most often cited by research in Cognitive Neuroscience (952 citations), Experimental and Cognitive Psychology (227 citations) and General Decision Sciences (20 citations). Marcelo G. Mattar has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Nathaniel D. Daw, Danielle S. Bassett, Sharon L. Thompson‐Schill, Geoffrey K. Aguirre, Michael W. Cole, Scott T. Grafton, Máté Lengyel, Evelina Fedorenko, Idan Blank and Lucía Magis‐Weinberg. Their work appears in journals such as Nature, Science and Nature Communications.
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.