Matteo di Volo
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 31
- Functional Brain Connectivity Studies 3
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- stochastic dynamics and bifurcation 19
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- Neuroscience and Neuropharmacology Research 6
- Photoreceptor and optogenetics research 4
- Neuroscience and Neural Engineering 3
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- Nonlinear Dynamics and Pattern Formation 12
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- Advanced Memory and Neural Computing 8
Matteo di Volo
31 papers receiving 481 citations
Peers
Comparison fields: 5 of 47
- Cognitive Neuroscience 428
- Statistical and Nonlinear Physics 211
- Cellular and Molecular Neuroscience 148
- Computer Networks and Communications 155
- Electrical and Electronic Engineering 73
Countries citing papers authored by Matteo di Volo
This map shows the geographic impact of Matteo di Volo'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 Matteo di Volo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo di Volo more than expected).
Fields of papers citing papers by Matteo di Volo
This network shows the impact of papers produced by Matteo di Volo. 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 Matteo di Volo. The network helps show where Matteo di Volo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matteo di Volo, 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 | 3 | |
| 2 | 2024 | 10 | |
| 3 | 2021 | 15 | |
| 4 | 2021 | 14 | |
| 5 | 2021 | 4 | |
| 6 | 2021 | 36 | |
| 7 | 2019 | 55 | |
| 8 | 2019 | 26 | |
| 9 | 2019 | 31 | |
| 10 | 2019 | 32 | |
| 11 | Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing | 2019 | 1 |
| 12 | 2019 | 30 | |
| 13 | 2019 | 11 | |
| 14 | 2018 | 12 | |
| 15 | 2018 | 47 | |
| 16 | 2017 | 13 | |
| 17 | 2017 | 12 | |
| 18 | 2016 | 6 | |
| 19 | 2014 | 9 | |
| 20 | 2014 | 6 |
About Matteo di Volo
Matteo di Volo is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Computer Networks and Communications, Cellular and Molecular Neuroscience and Biophysics, having authored 32 papers that have together received 486 indexed citations. Recurring topics across this work include Neural dynamics and brain function (31 papers), stochastic dynamics and bifurcation (19 papers), Nonlinear Dynamics and Pattern Formation (12 papers), Advanced Memory and Neural Computing (8 papers), Neuroscience and Neuropharmacology Research (6 papers), Photoreceptor and optogenetics research (4 papers), Functional Brain Connectivity Studies (3 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Cognitive Neuroscience (428 citations), Statistical and Nonlinear Physics (211 citations), Cellular and Molecular Neuroscience (148 citations), Computer Networks and Communications (155 citations) and Electrical and Electronic Engineering (73 citations). Matteo di Volo has collaborated with scholars based in France, Italy and Russia. Frequent co-authors include Alessandro Torcini, Alain Destexhe, Cristiano Capone, Denis S. Goldobin, Alberto Romagnoni, Raffaella Burioni, A. Vezzani, Roberto Livi, Antonio Politi and Yann Zerlaut. Their work appears in journals such as Physical Review Letters, Physical review. E, Scientific Reports, Chaos Solitons & Fractals and Journal of Neurophysiology.
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.