Maria Mannone
Impact in
-
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Neuroscience and Music Perception
Papers in
-
- Music Technology and Sound Studies 15
-
- Functional Brain Connectivity Studies 5
- Neural dynamics and brain function 5
- Neuroscience and Music Perception 4
- Co-authors
- Valeria Seidita (8 shared papers)Antonio Chella (8 shared papers)Guerino Mazzola (7 shared papers)Rosario Lo Franco (1 shared paper)Giuseppe Compagno (2 shared papers)Norbert Marwan (7 shared papers)Peppino Fazio (9 shared papers)Yan Pang (3 shared papers)
- Journals
- Journal of Mathematics and Music (4 papers)Robotics and Autonomous Systems (1 paper)Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (1 paper)BioData Mining (1 paper)Journal of Medical Systems (1 paper)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Maria Mannone
37 papers receiving 156 citations
Peers
Comparison fields: 5 of 54
- Music 8
- Cognitive Neuroscience 50
- Computer Vision and Pattern Recognition 43
- Visual Arts and Performing Arts 9
- Artificial Intelligence 54
Countries citing papers authored by Maria Mannone
This map shows the geographic impact of Maria Mannone'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 Maria Mannone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Mannone more than expected).
Fields of papers citing papers by Maria Mannone
This network shows the impact of papers produced by Maria Mannone. 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 Maria Mannone. The network helps show where Maria Mannone may publish in the future.
Co-authors
The 25 scholars most cited alongside Maria Mannone, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 25 | |
| 2 | 2013 | 17 | |
| 3 | 2023 | 16 | |
| 4 | 2022 | 12 | |
| 5 | 2016 | 10 | |
| 6 | 2020 | 8 | |
| 7 | 2024 | 7 | |
| 8 | 2024 | 6 | |
| 9 | 2018 | 6 | |
| 10 | 2017 | 5 | |
| 11 | 2020 | 4 | |
| 12 | 2016 | 4 | |
| 13 | Networks of Music and Images | 2017 | 4 |
| 14 | 2022 | 4 | |
| 15 | 2023 | 3 | |
| 16 | 2019 | 3 | |
| 17 | 2018 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2025 | 2 |
About Maria Mannone
Maria Mannone is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence, Molecular Biology and Signal Processing, having authored 46 papers that have together received 163 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (15 papers), Functional Brain Connectivity Studies (5 papers), Neural dynamics and brain function (5 papers), Neuroscience and Music Perception (4 papers), Music and Audio Processing (4 papers), Modular Robots and Swarm Intelligence (4 papers), Neural Networks and Reservoir Computing (3 papers) and Quantum Computing Algorithms and Architecture (3 papers). The work is most often cited by research in Music (8 citations), Cognitive Neuroscience (50 citations), Computer Vision and Pattern Recognition (43 citations), Visual Arts and Performing Arts (9 citations) and Artificial Intelligence (54 citations). Maria Mannone has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Valeria Seidita, Antonio Chella, Guerino Mazzola, Rosario Lo Franco, Giuseppe Compagno, Norbert Marwan, Peppino Fazio, Yan Pang, Peter beim Graben and Salvatore Gaglio. Their work appears in journals such as Journal of Mathematics and Music, Robotics and Autonomous Systems, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, BioData Mining and Journal of Medical Systems.
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.