Sunil Wimalaratna
- Cognitive Neuroscience top 5%
- Neurology top 2%
- Rehabilitation top 2%
- Neurology top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Matthew F. S. RushworthUdo KischkaPaul M. MatthewsHeidi Johansen‐BergMarko BogdanovicBrendan McLeanEmmanuel IfeachorNigel Hudson
- Topics
- EEG and Brain-Computer Interfaces (5 papers)Genetic Neurodegenerative Diseases (3 papers)Fractal and DNA sequence analysis (3 papers)
- Journals
- Proceedings of the National Academy of SciencesBMJJournal of Neurology Neurosurgery & Psychiatry
- Partner nations
- United KingdomSingaporeItaly
In The Last Decade
Sunil Wimalaratna
24 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Cognitive Neuroscience 525
- Neurology 443
- Rehabilitation 228
- Neurology 156
- Radiology, Nuclear Medicine and Imaging 149
Countries citing papers authored by Sunil Wimalaratna
This map shows the geographic impact of Sunil Wimalaratna'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 Sunil Wimalaratna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunil Wimalaratna more than expected).
Fields of papers citing papers by Sunil Wimalaratna
This network shows the impact of papers produced by Sunil Wimalaratna. 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 Sunil Wimalaratna. The network helps show where Sunil Wimalaratna may publish in the future.
Co-authorship network of co-authors of Sunil Wimalaratna
This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Wimalaratna. A scholar is included among the top collaborators of Sunil Wimalaratna 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 Sunil Wimalaratna. Sunil Wimalaratna is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | SPARSE BUMP MODELING OF MILDAD PATIENTS - Modeling Transient Oscillations in the EEG of Patients with Mild Alzheimer’s Disease | 0 |
| 3 | 7 | |
| 4 | 22 | |
| 5 | 8 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 58 | |
| 10 | 11 | |
| 11 | 71 | |
| 12 | 23 | |
| 13 | Comparison of Methods for Early detection of Alzheimer's disease | 3 |
| 14 | 34 | |
| 15 | 98 | |
| 16 | 6 | |
| 17 | The role of ipsilateral premotor cortex in hand movement after strokebreakdown → | 617 |
| 18 | 1 | |
| 19 | 18 | |
| 20 | 1 |
About Sunil Wimalaratna
Sunil Wimalaratna is a scholar working on Neurology, Cognitive Neuroscience and Cellular and Molecular Neuroscience, having authored 27 papers that have together received 1.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (5 papers), Genetic Neurodegenerative Diseases (3 papers) and Fractal and DNA sequence analysis (3 papers). The work is most often cited by research in Neurology (443 citations), Computational Mathematics (24 citations) and Rehabilitation (228 citations). Sunil Wimalaratna has collaborated with scholars based in United Kingdom, Singapore and Italy. Frequent co-authors include Matthew F. S. Rushworth, Udo Kischka, Paul M. Matthews, Heidi Johansen‐Berg, Marko Bogdanovic, Brendan McLean, Emmanuel Ifeachor, Nigel Hudson, Nicholas Outram and Fabrizio Vecchio. Their work appears in journals such as Proceedings of the National Academy of Sciences, BMJ and Journal of Neurology Neurosurgery & Psychiatry.
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.