Kanaka Rajan

3.0k total citations
28 papers, 1.6k citations indexed

About

Kanaka Rajan is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kanaka Rajan has authored 28 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 10 papers in Artificial Intelligence and 7 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kanaka Rajan's work include Neural dynamics and brain function (17 papers), Neural Networks and Applications (9 papers) and Functional Brain Connectivity Studies (6 papers). Kanaka Rajan is often cited by papers focused on Neural dynamics and brain function (17 papers), Neural Networks and Applications (9 papers) and Functional Brain Connectivity Studies (6 papers). Kanaka Rajan collaborates with scholars based in United States, Israel and France. Kanaka Rajan's co-authors include L. F. Abbott, Tim P. Vogels, L. F. Abbott, David W. Tank, Christopher D. Harvey, Haim Sompolinsky, L. F. Abbott, Brian DePasquale, Carlos D. Brody and Lucas Pinto and has published in prestigious journals such as Nature, Cell and Physical Review Letters.

In The Last Decade

Kanaka Rajan

27 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kanaka Rajan United States 14 1.2k 515 354 325 246 28 1.6k
Taro Toyoizumi Japan 21 1.2k 1.0× 727 1.4× 297 0.8× 513 1.6× 194 0.8× 60 1.7k
Martin Stemmler Germany 22 1.4k 1.2× 868 1.7× 178 0.5× 271 0.8× 425 1.7× 41 2.0k
Yonatan Loewenstein Israel 24 1.3k 1.1× 749 1.5× 194 0.5× 215 0.7× 96 0.4× 65 2.0k
Artur Luczak Canada 21 1.7k 1.4× 1.1k 2.0× 171 0.5× 252 0.8× 152 0.6× 51 2.0k
Ştefan Mihalaş United States 27 1.7k 1.4× 978 1.9× 171 0.5× 440 1.4× 200 0.8× 72 2.4k
Yasser Roudi Norway 21 1.5k 1.3× 949 1.8× 225 0.6× 125 0.4× 324 1.3× 48 2.0k
Srdjan Ostojic France 21 1.4k 1.2× 562 1.1× 293 0.8× 372 1.1× 455 1.8× 48 1.7k
Marc-Oliver Gewaltig Germany 13 1.6k 1.4× 861 1.7× 283 0.8× 732 2.3× 331 1.3× 34 2.0k
Henning Sprekeler Germany 23 1.4k 1.2× 905 1.8× 292 0.8× 632 1.9× 89 0.4× 56 1.9k
Kamal Sen United States 19 2.4k 2.0× 1.4k 2.8× 201 0.6× 503 1.5× 218 0.9× 40 3.2k

Countries citing papers authored by Kanaka Rajan

Since Specialization
Citations

This map shows the geographic impact of Kanaka Rajan'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 Kanaka Rajan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanaka Rajan more than expected).

Fields of papers citing papers by Kanaka Rajan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanaka Rajan. 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 Kanaka Rajan. The network helps show where Kanaka Rajan may publish in the future.

Co-authorship network of co-authors of Kanaka Rajan

This figure shows the co-authorship network connecting the top 25 collaborators of Kanaka Rajan. A scholar is included among the top collaborators of Kanaka Rajan 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 Kanaka Rajan. Kanaka Rajan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lacagnina, Anthony F., H.S. Seo, Li Fang, et al.. (2025). Stress History Modulates Corticotropin-Releasing Factor Neurons to Establish Resilience. Biological Psychiatry Global Open Science. 6(2). 100656–100656.
2.
Zaki, Yosif, Zachary T. Pennington, Zhe Dong, et al.. (2024). Offline ensemble co-reactivation links memories across days. Nature. 637(8044). 145–155. 8 indexed citations
3.
Brynildsen, Julia K., Kanaka Rajan, Michael X. Henderson, & Dani S. Bassett. (2023). Network models to enhance the translational impact of cross-species studies. Nature reviews. Neuroscience. 24(9). 575–588. 13 indexed citations
4.
Young, Megan E., et al.. (2023). Temporally specific patterns of neural activity in interconnected corticolimbic structures during reward anticipation. Neuron. 111(22). 3668–3682.e5. 5 indexed citations
5.
Akitake, Bradley, Manuel Beirán, Ciana Deveau, et al.. (2023). Amplified cortical neural responses as animals learn to use novel activity patterns. Current Biology. 33(11). 2163–2174.e4. 9 indexed citations
6.
Dong, Zhe, William Mau, Yu Feng, et al.. (2022). Minian, an open-source miniscope analysis pipeline. eLife. 11. 35 indexed citations
7.
Momennejad, Ida, et al.. (2021). The Learning Salon: Toward a new participatory science. Neuron. 109(19). 3036–3040. 1 indexed citations
8.
Martini, Michael L., Aly Valliani, Anthony Costa, et al.. (2021). Deep anomaly detection of seizures with paired stereoelectroencephalography and video recordings. Scientific Reports. 11(1). 7482–7482. 11 indexed citations
9.
Perich, Matthew G. & Kanaka Rajan. (2020). Rethinking brain-wide interactions through multi-region ‘network of networks’ models. Current Opinion in Neurobiology. 65. 146–151. 35 indexed citations
10.
Pinto, Lucas, Kanaka Rajan, Brian DePasquale, et al.. (2019). Task-Dependent Changes in the Large-Scale Dynamics and Necessity of Cortical Regions. Neuron. 104(4). 810–824.e9. 144 indexed citations
11.
Yang, Guangyu Robert, Michael W. Cole, & Kanaka Rajan. (2019). How to study the neural mechanisms of multiple tasks. Current Opinion in Behavioral Sciences. 29. 134–143. 29 indexed citations
12.
Andalman, Aaron S., Matthew Lovett-Barron, Michael Broxton, et al.. (2019). Neuronal Dynamics Regulating Brain and Behavioral State Transitions. Cell. 177(4). 970–985.e20. 158 indexed citations
13.
DePasquale, Brian, Christopher J. Cueva, Kanaka Rajan, G. Sean Escola, & L. F. Abbott. (2018). full-FORCE: A target-based method for training recurrent networks. PLoS ONE. 13(2). e0191527–e0191527. 73 indexed citations
14.
Rajan, Kanaka, Christopher D. Harvey, & David W. Tank. (2016). Recurrent Network Models of Sequence Generation and Memory. Neuron. 90(1). 128–142. 213 indexed citations
15.
Rajan, Kanaka & William Bialek. (2013). Maximally Informative “Stimulus Energies” in the Analysis of Neural Responses to Natural Signals. PLoS ONE. 8(11). e71959–e71959. 18 indexed citations
16.
Rajan, Kanaka, et al.. (2012). Learning quadratic receptive fields from neural responses to natural stimuli. arXiv (Cornell University). 21 indexed citations
17.
Rajan, Kanaka, L. F. Abbott, & Haim Sompolinsky. (2010). Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics. Neural Information Processing Systems. 23. 1975–1983. 7 indexed citations
18.
Rajan, Kanaka, L. F. Abbott, & Haim Sompolinsky. (2010). Stimulus-dependent suppression of chaos in recurrent neural networks. Physical Review E. 82(1). 11903–11903. 171 indexed citations
19.
Rajan, Kanaka & L. F. Abbott. (2006). Eigenvalue Spectra of Random Matrices for Neural Networks. Physical Review Letters. 97(18). 188104–188104. 179 indexed citations
20.
Vogels, Tim P., Kanaka Rajan, & L. F. Abbott. (2005). NEURAL NETWORK DYNAMICS. Annual Review of Neuroscience. 28(1). 357–376. 340 indexed citations

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.

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