M. Pellicoro
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
Papers in
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- Quantum Chromodynamics and Particle Interactions 19
- Particle physics theoretical and experimental studies 19
- High-Energy Particle Collisions Research 17
-
- Neural dynamics and brain function 13
- Co-authors
- Sebastiano Stramaglia (37 shared papers)Daniele Marinazzo (27 shared papers)Leonardo Angelini (41 shared papers)L. Nitti (29 shared papers)Marina de Tommaso (9 shared papers)Guo‐Rong Wu (4 shared papers)G. Preparata (19 shared papers)Marco Guido (4 shared papers)
In The Last Decade
M. Pellicoro
72 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 104
- Cognitive Neuroscience 602
- Statistical and Nonlinear Physics 247
- Psychiatry and Mental health 159
- Nuclear and High Energy Physics 145
- Signal Processing 97
Countries citing papers authored by M. Pellicoro
This map shows the geographic impact of M. Pellicoro'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 M. Pellicoro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pellicoro more than expected).
Fields of papers citing papers by M. Pellicoro
This network shows the impact of papers produced by M. Pellicoro. 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 M. Pellicoro. The network helps show where M. Pellicoro may publish in the future.
Co-authors
The 25 scholars most cited alongside M. Pellicoro, 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 290 | |
| 2 | 2008 | 124 | |
| 3 | 2004 | 90 | |
| 4 | 2014 | 59 | |
| 5 | 2012 | 58 | |
| 6 | 2007 | 56 | |
| 7 | 2006 | 55 | |
| 8 | 2012 | 53 | |
| 9 | 2009 | 48 | |
| 10 | 2013 | 48 | |
| 11 | 2005 | 40 | |
| 12 | 2010 | 30 | |
| 13 | 2007 | 29 | |
| 14 | 2017 | 28 | |
| 15 | 2000 | 25 | |
| 16 | 2007 | 25 | |
| 17 | 2017 | 24 | |
| 18 | 2003 | 24 | |
| 19 | 2012 | 17 | |
| 20 | 2019 | 16 |
About M. Pellicoro
M. Pellicoro is a scholar working on Nuclear and High Energy Physics, Cognitive Neuroscience, Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics and Artificial Intelligence, having authored 73 papers that have together received 1.4k indexed citations. Recurring topics across this work include Quantum Chromodynamics and Particle Interactions (19 papers), Particle physics theoretical and experimental studies (19 papers), High-Energy Particle Collisions Research (17 papers), Neural dynamics and brain function (13 papers), Neural Networks and Applications (10 papers), Theoretical and Computational Physics (8 papers), Complex Systems and Time Series Analysis (8 papers) and Opinion Dynamics and Social Influence (7 papers). The work is most often cited by research in Cognitive Neuroscience (602 citations), Statistical and Nonlinear Physics (247 citations), Psychiatry and Mental health (159 citations), Nuclear and High Energy Physics (145 citations) and Signal Processing (97 citations). M. Pellicoro has collaborated with scholars based in Italy, Belgium and China. Frequent co-authors include Sebastiano Stramaglia, Daniele Marinazzo, Leonardo Angelini, L. Nitti, Marina de Tommaso, Guo‐Rong Wu, G. Preparata, Marco Guido, Jesús M. Cortés and G. Nardulli. Their work appears in journals such as Physics Letters B, Physica A Statistical Mechanics and its Applications, Physics Letters A, Physical Review Letters 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.