Massimo Mascaro
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Motor Control and Adaptation
- EEG and Brain-Computer Interfaces
- Visual perception and processing mechanisms
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
Papers in
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- Neural dynamics and brain function 5
- Visual perception and processing mechanisms 5
- Spatial Neglect and Hemispheric Dysfunction 2
- Motor Control and Adaptation 2
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- Neural Networks and Applications 2
- Co-authors
- Yali Amit (2 shared papers)Alexandra Battaglia‐Mayer (2 shared papers)Roberto Caminiti (2 shared papers)Daniel J. Amit (2 shared papers)David C. Bradley (2 shared papers)Martin Bak (1 shared paper)Conrad Kufta (1 shared paper)Robert K. Erickson (1 shared paper)
- Journals
- Cerebral Cortex (3 papers)Network Computation in Neural Systems (2 papers)Vision Research (1 paper)Journal of Neurophysiology (1 paper)Neural Computation (1 paper)
- Partner nations
- ItalyUnited States
In The Last Decade
Massimo Mascaro
10 papers receiving 312 citations
Peers
Comparison fields: 5 of 50
- Cognitive Neuroscience 262
- Cellular and Molecular Neuroscience 146
- Neurology 17
- Social Psychology 38
- Electrical and Electronic Engineering 88
Countries citing papers authored by Massimo Mascaro
This map shows the geographic impact of Massimo Mascaro'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 Massimo Mascaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Mascaro more than expected).
Fields of papers citing papers by Massimo Mascaro
This network shows the impact of papers produced by Massimo Mascaro. 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 Massimo Mascaro. The network helps show where Massimo Mascaro may publish in the future.
Co-authors
The 17 scholars most cited alongside Massimo Mascaro, 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 | 2004 | 118 | |
| 2 | 2004 | 41 | |
| 3 | 2006 | 35 | |
| 4 | 2003 | 32 | |
| 5 | 2003 | 30 | |
| 6 | 1999 | 27 | |
| 7 | 2001 | 17 | |
| 8 | 2004 | 11 | |
| 9 | 1999 | 8 | |
| 10 | 2024 | 5 |
About Massimo Mascaro
Massimo Mascaro is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computer Networks and Communications, Molecular Biology and Cellular and Molecular Neuroscience, having authored 10 papers that have together received 324 indexed citations. Recurring topics across this work include Neural dynamics and brain function (5 papers), Visual perception and processing mechanisms (5 papers), Neural Networks and Applications (2 papers), Spatial Neglect and Hemispheric Dysfunction (2 papers), Motor Control and Adaptation (2 papers), Advanced Chemical Sensor Technologies (1 paper), Protein Degradation and Inhibitors (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Cognitive Neuroscience (262 citations), Cellular and Molecular Neuroscience (146 citations), Neurology (17 citations), Social Psychology (38 citations) and Electrical and Electronic Engineering (88 citations). Massimo Mascaro has collaborated with scholars based in Italy and United States. Frequent co-authors include Yali Amit, Alexandra Battaglia‐Mayer, Roberto Caminiti, Daniel J. Amit, David C. Bradley, Martin Bak, Conrad Kufta, Robert K. Erickson, J. Berg and Hong Xu. Their work appears in journals such as Cerebral Cortex, Network Computation in Neural Systems, Vision Research, Journal of Neurophysiology and Neural Computation.
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.