Germán Mato
Impact in
- Cognitive Neuroscience top 1%
- Neural dynamics and brain function
- Statistical and Nonlinear Physics top 0.5%
- stochastic dynamics and bifurcation
Papers in
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- Neural dynamics and brain function 26
- Visual perception and processing mechanisms 5
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- stochastic dynamics and bifurcation 12
- Co-authors
- D. Hansel (7 shared papers)C. Meunier (4 shared papers)David Hansel (6 shared papers)David Golomb (2 shared papers)Benjamin Pfeuty (2 shared papers)Néstor Parga (5 shared papers)Antonio Turiel (2 shared papers)Jean‐Pierre Nadal (2 shared papers)
In The Last Decade
Germán Mato
46 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 96
- Cognitive Neuroscience 1.5k
- Statistical and Nonlinear Physics 945
- Cellular and Molecular Neuroscience 722
- Computer Networks and Communications 823
- Sensory Systems 29
Countries citing papers authored by Germán Mato
This map shows the geographic impact of Germán Mato'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 Germán Mato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Germán Mato more than expected).
Fields of papers citing papers by Germán Mato
This network shows the impact of papers produced by Germán Mato. 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 Germán Mato. The network helps show where Germán Mato may publish in the future.
Co-authors
The 25 scholars most cited alongside Germán Mato, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 454 | |
| 2 | 1993 | 228 | |
| 3 | 1993 | 208 | |
| 4 | 1998 | 140 | |
| 5 | 2003 | 133 | |
| 6 | 2003 | 117 | |
| 7 | 2001 | 91 | |
| 8 | 2013 | 87 | |
| 9 | 2005 | 86 | |
| 10 | 2000 | 71 | |
| 11 | 1998 | 61 | |
| 12 | 1999 | 35 | |
| 13 | 2014 | 34 | |
| 14 | 2018 | 26 | |
| 15 | 2018 | 25 | |
| 16 | 1998 | 25 | |
| 17 | 1992 | 18 | |
| 18 | 1993 | 16 | |
| 19 | Self-similarity Properties of Natural Images | 1997 | 15 |
| 20 | 2019 | 15 |
About Germán Mato
Germán Mato is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience, Computer Networks and Communications and Artificial Intelligence, having authored 47 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (26 papers), stochastic dynamics and bifurcation (12 papers), Nonlinear Dynamics and Pattern Formation (10 papers), Neuroscience and Neuropharmacology Research (7 papers), Photoreceptor and optogenetics research (7 papers), Neural Networks and Applications (6 papers), Visual perception and processing mechanisms (5 papers) and Medical Imaging Techniques and Applications (4 papers). The work is most often cited by research in Cognitive Neuroscience (1.5k citations), Statistical and Nonlinear Physics (945 citations), Cellular and Molecular Neuroscience (722 citations), Computer Networks and Communications (823 citations) and Sensory Systems (29 citations). Germán Mato has collaborated with scholars based in Argentina, France and Israel. Frequent co-authors include D. Hansel, C. Meunier, David Hansel, David Golomb, Benjamin Pfeuty, Néstor Parga, Antonio Turiel, Jean‐Pierre Nadal, Claude Meunier and Yimy Amarillo. Their work appears in journals such as Neural Computation, Journal of Neurophysiology, Journal of Neuroscience, Physica A Statistical Mechanics and its Applications and Europhysics Letters (EPL).
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.