Aditya Gilra
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Memory and Neural Mechanisms
- EEG and Brain-Computer Interfaces
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- Neuroscience and Neuropharmacology Research
Papers in
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- Neural dynamics and brain function 7
- Visual perception and processing mechanisms 1
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- Neural Networks and Applications 4
- Neural Networks and Reservoir Computing 4
- Co-authors
- Michael M. Halassa (1 shared paper)Rajeev Rikhye (1 shared paper)Wulfram Gerstner (3 shared papers)Raoul-Martin Memmesheimer (1 shared paper)Upinder S. Bhalla (1 shared paper)Eleni Vasilaki (2 shared papers)S. K. Manhas (1 shared paper)Partha Pratim Roy (1 shared paper)
- Journals
- PLoS Computational Biology (1 paper)Nature Communications (1 paper)Nature Neuroscience (1 paper)eLife (1 paper)Physical Review Letters (1 paper)
- Partner nations
- United KingdomNetherlandsSwitzerland
In The Last Decade
Aditya Gilra
10 papers receiving 277 citations
Peers
Comparison fields: 5 of 58
- Cognitive Neuroscience 196
- Cellular and Molecular Neuroscience 69
- Sensory Systems 18
- Artificial Intelligence 79
- Behavioral Neuroscience 6
Countries citing papers authored by Aditya Gilra
This map shows the geographic impact of Aditya Gilra'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 Aditya Gilra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Gilra more than expected).
Fields of papers citing papers by Aditya Gilra
This network shows the impact of papers produced by Aditya Gilra. 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 Aditya Gilra. The network helps show where Aditya Gilra may publish in the future.
Co-authors
The 16 scholars most cited alongside Aditya Gilra, 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 | 2018 | 162 | |
| 2 | 2017 | 45 | |
| 3 | 2020 | 36 | |
| 4 | 2022 | 13 | |
| 5 | 2015 | 9 | |
| 6 | 2024 | 5 | |
| 7 | Predicting non-linear dynamics: a stable local learning scheme for recurrent spiking neural networks. | 2017 | 5 |
| 8 | 2023 | 2 | |
| 9 | Non-linear motor control by local learning in spiking neural networks | 2017 | 1 |
| 10 | 2007 | 1 |
About Aditya Gilra
Aditya Gilra is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Atomic and Molecular Physics, and Optics, having authored 10 papers that have together received 279 indexed citations. Recurring topics across this work include Neural dynamics and brain function (7 papers), Neural Networks and Applications (4 papers), Neural Networks and Reservoir Computing (4 papers), Advanced Memory and Neural Computing (4 papers), Advanced Chemical Sensor Technologies (1 paper), Visual perception and processing mechanisms (1 paper), Quantum Mechanics and Applications (1 paper) and Quantum optics and atomic interactions (1 paper). The work is most often cited by research in Cognitive Neuroscience (196 citations), Cellular and Molecular Neuroscience (69 citations), Sensory Systems (18 citations), Artificial Intelligence (79 citations) and Behavioral Neuroscience (6 citations). Aditya Gilra has collaborated with scholars based in United Kingdom, Netherlands and Switzerland. Frequent co-authors include Michael M. Halassa, Rajeev Rikhye, Wulfram Gerstner, Raoul-Martin Memmesheimer, Upinder S. Bhalla, Eleni Vasilaki, S. K. Manhas, Partha Pratim Roy, M.M. De Souza and Nicholas J. Cole. Their work appears in journals such as PLoS Computational Biology, Nature Communications, Nature Neuroscience, eLife and Physical Review Letters.
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.