Angelo Di Garbo
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 10%
- Statistical and Nonlinear Physics top 2%
- Computer Networks and Communications top 5%
- Neurology top 5%
- Co-authors
- Matteo CaleoMarco MainardiLamberto MaffeiAlessandro SaleNicoletta BerardiSanti ChillemiR. MeucciF. T. Arecchi
- Topics
- Neural dynamics and brain function (29 papers)stochastic dynamics and bifurcation (19 papers)Nonlinear Dynamics and Pattern Formation (17 papers)
In The Last Decade
Angelo Di Garbo
59 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Cognitive Neuroscience 458
- Cellular and Molecular Neuroscience 261
- Statistical and Nonlinear Physics 253
- Computer Networks and Communications 219
- Neurology 177
Countries citing papers authored by Angelo Di Garbo
This map shows the geographic impact of Angelo Di Garbo'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 Angelo Di Garbo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angelo Di Garbo more than expected).
Fields of papers citing papers by Angelo Di Garbo
This network shows the impact of papers produced by Angelo Di Garbo. 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 Angelo Di Garbo. The network helps show where Angelo Di Garbo may publish in the future.
Co-authorship network of co-authors of Angelo Di Garbo
This figure shows the co-authorship network connecting the top 25 collaborators of Angelo Di Garbo. A scholar is included among the top collaborators of Angelo Di Garbo 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 Angelo Di Garbo. Angelo Di Garbo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 19 | |
| 7 | 8 | |
| 8 | 168 | |
| 9 | 17 | |
| 10 | Environmental enrichment strengthens corticocortical interactions and reduces amyloid-β oligomers in aged micebreakdown → | 494 |
| 11 | 24 | |
| 12 | 14 | |
| 13 | 0 | |
| 14 | 48 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 12 | |
| 18 | 13 | |
| 19 | 90 | |
| 20 | 5 |
About Angelo Di Garbo
Angelo Di Garbo is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Cellular and Molecular Neuroscience, having authored 63 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural dynamics and brain function (29 papers), stochastic dynamics and bifurcation (19 papers) and Nonlinear Dynamics and Pattern Formation (17 papers). The work is most often cited by research in Cognitive Neuroscience (458 citations), Neurology (177 citations) and Statistical and Nonlinear Physics (253 citations). Angelo Di Garbo has collaborated with scholars based in Spain, Italy and France. Frequent co-authors include Matteo Caleo, Marco Mainardi, Lamberto Maffei, Alessandro Sale, Nicoletta Berardi, Santi Chillemi, R. Meucci, F. T. Arecchi, E. Allaria and Michele Barbi. Their work appears in journals such as Physical Review Letters, PLoS ONE and Scientific Reports.
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.