Ken Nakae

877 total citations
21 papers, 272 citations indexed

About

Ken Nakae is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ken Nakae has authored 21 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 5 papers in Cellular and Molecular Neuroscience and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ken Nakae's work include Functional Brain Connectivity Studies (9 papers), Neural dynamics and brain function (8 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Ken Nakae is often cited by papers focused on Functional Brain Connectivity Studies (9 papers), Neural dynamics and brain function (8 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). Ken Nakae collaborates with scholars based in Japan, Germany and Australia. Ken Nakae's co-authors include Shin Ishii, Masanori Koyama, Shin‐ichi Maeda, Takeru Miyato, Junichi Hata, Hideyuki Okano, Ryo Ito, Honda Naoki, Tetsuo Yamamori and Henrik Skibbe and has published in prestigious journals such as Nature Communications, Neuron and NeuroImage.

In The Last Decade

Ken Nakae

20 papers receiving 257 citations

Peers

Ken Nakae

CVPR

RNMI

NEURO

Junning Li United States

Roman Filipovych United States

Benjamin D. Haeffele United States

Daniel Haehn United States

Zhijiang Wan China

Qiankun Zuo China

Aklima Akter Lima Bangladesh

Hrishikesh Deshpande United States

Baocan Zhang China

J. Alexander Bae United States

Junning Li United States

Ken Nakae

40 ×0.4

48 ×0.6

CVPR

130 ×2.0

108 ×2.6

RNMI

44 ×1.3

NEURO

Citations per year, relative to Ken Nakae Ken Nakae (= 1×) peers Junning Li

Countries citing papers authored by Ken Nakae

Since Specialization

Citations

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

Fields of papers citing papers by Ken Nakae

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Nakae

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ishii, Shin, et al.. (2025). Integrated information theory reveals the potential role of the posterior parietal cortex in sustaining conditioning responses in classical conditioning tasks. Frontiers in Neuroscience. 19. 1512724–1512724. 1 indexed citations

Yoshida, Eriko, Masashi Kondo, Ken Nakae, et al.. (2025). Whether or not to act is determined by distinct signals from motor thalamus and orbitofrontal cortex to secondary motor cortex. Nature Communications. 16(1). 3106–3106. 2 indexed citations

Hata, Junichi, Takaaki Kaneko, Yuji Komaki, et al.. (2024). Commonality and variance of resting-state networks in common marmoset brains. Scientific Reports. 14(1). 3 indexed citations

Watakabe, Akiya, Henrik Skibbe, Ken Nakae, et al.. (2023). Local and long-distance organization of prefrontal cortex circuits in the marmoset brain. Neuron. 111(14). 2258–2273.e10. 21 indexed citations

Skibbe, Henrik, Muhammad Febrian Rachmadi, Ken Nakae, et al.. (2023). The Brain/MINDS Marmoset Connectivity Resource: An open-access platform for cellular-level tracing and tractography in the primate brain. PLoS Biology. 21(6). e3002158–e3002158. 9 indexed citations

Hata, Junichi, et al.. (2023). Group Surrogate Data Generating Models and similarity quantification of multivariate time-series: A resting-state fMRI study. NeuroImage. 279. 120329–120329. 1 indexed citations

Nakae, Ken, et al.. (2021). yasokochi/Perler: First release of Perler. Figshare. 1 indexed citations

Woodward, Alexander, Rui Gong, Hiroshi Abe, et al.. (2020). The NanoZoomer artificial intelligence connectomics pipeline for tracer injection studies of the marmoset brain. Brain Structure and Function. 225(4). 1225–1243. 5 indexed citations

Gutierrez, Carlos Enrique, Henrik Skibbe, Ken Nakae, et al.. (2020). Optimization and validation of diffusion MRI-based fiber tracking with neural tracer data as a reference. Scientific Reports. 10(1). 21285–21285. 14 indexed citations

10.

Taniguchi, Atsushi, Hiroshi Kohsaka, Ken Nakae, et al.. (2019). System level analysis of motor-related neural activities in larval Drosophila. Journal of Neurogenetics. 33(3). 179–189. 4 indexed citations

11.

Ito, Ryo, Ken Nakae, Junichi Hata, Hideyuki Okano, & Shin Ishii. (2019). Semi-supervised deep learning of brain tissue segmentation. Neural Networks. 116. 25–34. 58 indexed citations

12.

Nakae, Ken. (2019). Statistical Estimation of Phase Response Curves Using Data Transformation. Journal of the Physical Society of Japan. 88(8). 84003–84003.

13.

Nakae, Ken, et al.. (2018). Zero-shot fMRI decoding with three-dimensional registration based on diffusion tensor imaging. Scientific Reports. 8(1). 12342–12342. 2 indexed citations

14.

Skibbe, Henrik, Marco Reisert, Ken Nakae, et al.. (2018). PAT—Probabilistic Axon Tracking for Densely Labeled Neurons in Large 3-D Micrographs. IEEE Transactions on Medical Imaging. 38(1). 69–78. 11 indexed citations

15.

Miyato, Takeru, Shin‐ichi Maeda, Masanori Koyama, Ken Nakae, & Shin Ishii. (2016). Distributional Smoothing with Virtual Adversarial Training. arXiv (Cornell University). 97 indexed citations

16.

Oba, Shigeyuki, et al.. (2016). Empirical Bayesian significance measure of neuronal spike response. BMC Neuroscience. 17(1). 27–27. 1 indexed citations

17.

Nakae, Ken, et al.. (2016). Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model. PLoS Computational Biology. 12(9). e1005099–e1005099. 14 indexed citations

18.

Miyato, Takeru, Shin‐ichi Maeda, Masanori Koyama, Ken Nakae, & Shin Ishii. (2015). Distributional Smoothing by Virtual Adversarial Examples. arXiv (Cornell University). 2 indexed citations

19.

Nakae, Ken, Yuji Ikegaya, Tomoe Ishikawa, et al.. (2014). A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging. PLoS Computational Biology. 10(11). e1003949–e1003949. 6 indexed citations

20.

Nakae, Ken, Yukito Iba, Yasuhiro Tsubo, Tomoki Fukai, & Toshio Aoyagi. (2010). Bayesian estimation of phase response curves. Neural Networks. 23(6). 752–763. 11 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.

Explore authors with similar magnitude of impact