Laurent Perrinet
- Cognitive Neuroscience top 2%
- Cellular and Molecular Neuroscience top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Co-authors
- Guillaume S. MassonKarl FristonRick A. AdamsMichael BreakspearSimon J. ThorpeManuel SamuelidesArnaud DelormeAnna Montagnini
- Topics
- Neural dynamics and brain function (52 papers)Visual perception and processing mechanisms (33 papers)Advanced Memory and Neural Computing (19 papers)
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceComputer Vision and Pattern Recognition
- Partner nations
- FranceUnited StatesUnited Kingdom
In The Last Decade
Laurent Perrinet
67 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 98
- Cognitive Neuroscience 992
- Cellular and Molecular Neuroscience 252
- Electrical and Electronic Engineering 251
- Computer Vision and Pattern Recognition 195
- Artificial Intelligence 102
Countries citing papers authored by Laurent Perrinet
This map shows the geographic impact of Laurent Perrinet'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 Laurent Perrinet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laurent Perrinet more than expected).
Fields of papers citing papers by Laurent Perrinet
This network shows the impact of papers produced by Laurent Perrinet. 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 Laurent Perrinet. The network helps show where Laurent Perrinet may publish in the future.
Co-authorship network of co-authors of Laurent Perrinet
This figure shows the co-authorship network connecting the top 25 collaborators of Laurent Perrinet. A scholar is included among the top collaborators of Laurent Perrinet 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 Laurent Perrinet. Laurent Perrinet 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 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | 12 | |
| 12 | 4 | |
| 13 | 31 | |
| 14 | 8 | |
| 15 | Meaningful representations emerge from Sparse Deep Predictive Coding | 1 |
| 16 | 36 | |
| 17 | 1 | |
| 18 | Edge statistics in natural images versus laboratory animal environments: Implications for understanding lateral connectivity in V1 | 1 |
| 19 | 15 | |
| 20 | 10 |
About Laurent Perrinet
Laurent Perrinet is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Cellular and Molecular Neuroscience, having authored 70 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (52 papers), Visual perception and processing mechanisms (33 papers) and Advanced Memory and Neural Computing (19 papers). The work is most often cited by research in Cognitive Neuroscience (992 citations), Cellular and Molecular Neuroscience (252 citations) and Computer Vision and Pattern Recognition (195 citations). Laurent Perrinet has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Guillaume S. Masson, Karl Friston, Rick A. Adams, Michael Breakspear, Simon J. Thorpe, Manuel Samuelides, Arnaud Delorme, Anna Montagnini, Gabriel Cristóbal and Rafael Redondo. Their work appears in journals such as Nature Communications, Journal of Neuroscience and Nature 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.