Grace W. Lindsay
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Co-authors
- Kenneth D. MillerJonathan V. GillRachel E. FieldRobert C. FroemkeKishore V. KuchibhotlaEleni S. PapadoyannisTom Hindmarsh StenTim C. Kietzmann
- Topics
- Neural dynamics and brain function (8 papers)EEG and Brain-Computer Interfaces (3 papers)Visual perception and processing mechanisms (2 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Grace W. Lindsay
10 papers receiving 817 citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Cognitive Neuroscience 505
- Cellular and Molecular Neuroscience 159
- Artificial Intelligence 149
- Computer Vision and Pattern Recognition 135
- Electrical and Electronic Engineering 69
Countries citing papers authored by Grace W. Lindsay
This map shows the geographic impact of Grace W. Lindsay'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 Grace W. Lindsay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grace W. Lindsay more than expected).
Fields of papers citing papers by Grace W. Lindsay
This network shows the impact of papers produced by Grace W. Lindsay. 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 Grace W. Lindsay. The network helps show where Grace W. Lindsay may publish in the future.
Co-authorship network of co-authors of Grace W. Lindsay
This figure shows the co-authorship network connecting the top 25 collaborators of Grace W. Lindsay. A scholar is included among the top collaborators of Grace W. Lindsay 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 Grace W. Lindsay. Grace W. Lindsay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | The neuroconnectionist research programmebreakdown → | 88 |
| 4 | 6 | |
| 5 | 12 | |
| 6 | 151 | |
| 7 | Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Futurebreakdown → | 291 |
| 8 | 41 | |
| 9 | 30 | |
| 10 | 1 | |
| 11 | 214 |
About Grace W. Lindsay
Grace W. Lindsay is a scholar working on Cognitive Neuroscience, Biophysics and Cellular and Molecular Neuroscience, having authored 11 papers that have together received 838 indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), EEG and Brain-Computer Interfaces (3 papers) and Visual perception and processing mechanisms (2 papers). The work is most often cited by research in Cognitive Neuroscience (505 citations), Cellular and Molecular Neuroscience (159 citations) and Sensory Systems (38 citations). Grace W. Lindsay has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Kenneth D. Miller, Jonathan V. Gill, Rachel E. Field, Robert C. Froemke, Kishore V. Kuchibhotla, Eleni S. Papadoyannis, Tom Hindmarsh Sten, Tim C. Kietzmann, Jenann Ismael and Marcel van Gerven. Their work appears in journals such as Journal of Neuroscience, Nature Neuroscience and Nature reviews. 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.