Maria Del Vecchio
- Cellular and Molecular Neuroscience top 1%
- Molecular Biology top 10%
- Cognitive Neuroscience top 5%
- Genetics top 5%
- Immunology top 10%
- Co-authors
- Tim TullyJie YinThomas PréatHong ZhouTimothy TullyElizabeth L. WilderWilliam G. QuinnKlara Velinzon
- Topics
- EEG and Brain-Computer Interfaces (10 papers)Neurobiology and Insect Physiology Research (6 papers)Functional Brain Connectivity Studies (6 papers)
- Journals
- CellNeuronJournal of Neuroscience
- Partner nations
- ItalyUnited StatesBelgium
In The Last Decade
Maria Del Vecchio
28 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Cellular and Molecular Neuroscience 1.7k
- Molecular Biology 822
- Cognitive Neuroscience 654
- Genetics 390
- Immunology 247
Countries citing papers authored by Maria Del Vecchio
This map shows the geographic impact of Maria Del Vecchio'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 Del Vecchio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Del Vecchio more than expected).
Fields of papers citing papers by Maria Del Vecchio
This network shows the impact of papers produced by Maria Del Vecchio. 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 Del Vecchio. The network helps show where Maria Del Vecchio may publish in the future.
Co-authorship network of co-authors of Maria Del Vecchio
This figure shows the co-authorship network connecting the top 25 collaborators of Maria Del Vecchio. A scholar is included among the top collaborators of Maria Del Vecchio 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 Maria Del Vecchio. Maria Del Vecchio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 16 | |
| 10 | 1 | |
| 11 | 15 | |
| 12 | 14 | |
| 13 | 22 | |
| 14 | 20 | |
| 15 | 17 | |
| 16 | 26 | |
| 17 | 37 | |
| 18 | 35 | |
| 19 | Genetic dissection of consolidated memory in Drosophilabreakdown → | 739 |
| 20 | Induction of a dominant negative CREB transgene specifically blocks long-term memory in Drosophilabreakdown → | 793 |
About Maria Del Vecchio
Maria Del Vecchio is a scholar working on Cognitive Neuroscience, Human-Computer Interaction and Cellular and Molecular Neuroscience, having authored 29 papers that have together received 2.5k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (10 papers), Neurobiology and Insect Physiology Research (6 papers) and Functional Brain Connectivity Studies (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.7k citations), Aging (151 citations) and Cognitive Neuroscience (654 citations). Maria Del Vecchio has collaborated with scholars based in Italy, United States and Belgium. Frequent co-authors include Tim Tully, Jie Yin, Thomas Préat, Hong Zhou, Timothy Tully, Elizabeth L. Wilder, Hong Zhou, William G. Quinn, Klara Velinzon and Stephen F. Goodwin. Their work appears in journals such as Cell, Neuron and Journal of Neuroscience.
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.