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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Modeling statistical dependencies in multi-region spike train data
Stephen Keeley, David M. Zoltowski, Mikio C. Aoi, et al.
Current Opinion in Neurobiology (2020) Vol. 65, pp. 194-202
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Multiregion neuronal activity: the forest and the trees
Timothy A. Machado, Isaac Kauvar, Karl Deisseroth
Nature reviews. Neuroscience (2022) Vol. 23, Iss. 11, pp. 683-704
Open Access | Times Cited: 39
Modeling conditional distributions of neural and behavioral data with masked variational autoencoders
Auguste Schulz, Julius Vetter, Richard Gao, et al.
Cell Reports (2025) Vol. 44, Iss. 3, pp. 115338-115338
Open Access | Times Cited: 1
A multi-demand operating system underlying diverse cognitive tasks
Weidong Cai, Jalil Taghia, Vinod Menon
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Dynamic causal communication channels between neocortical areas
Mitra Javadzadeh, Sonja B. Hofer
Neuron (2022) Vol. 110, Iss. 15, pp. 2470-2483.e7
Open Access | Times Cited: 27
Disentangling the flow of signals between populations of neurons
Evren Gokcen, Anna I. Jasper, João D. Semedo, et al.
Nature Computational Science (2022) Vol. 2, Iss. 8, pp. 512-525
Open Access | Times Cited: 24
Functional interactions among neurons within single columns of macaque V1
Ethan B Trepka, Shude Zhu, Ruobing Xia, et al.
eLife (2022) Vol. 11
Open Access | Times Cited: 24
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
Felix Pei, Joel Ye, David L. Zoltowski, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 27
Thalamocortical interactions shape hierarchical neural variability during stimulus perception
Adrià Tauste Campo, Antonio Zainos, Yuriria Vázquez, et al.
iScience (2024) Vol. 27, Iss. 7, pp. 110065-110065
Open Access | Times Cited: 3
MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks
Olivier Codol, Jonathan A. Michaels, Mehrdad Kashefi, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 8
Modeling conditional distributions of neural and behavioral data with masked variational autoencoders
Auguste Schulz, Julius Vetter, Richard Gao, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
A multi-region recurrent circuit for evidence accumulation in rats
Diksha Gupta, Charles D. Kopec, Adrian Bondy, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks
Olivier Codol, Jonathan A. Michaels, Mehrdad Kashefi, et al.
eLife (2024) Vol. 12
Open Access | Times Cited: 2
The Hybrid Drive: a chronic implant device combining tetrode arrays with silicon probes for layer-resolved ensemble electrophysiology in freely moving mice
Matteo Guardamagna, Ronny Eichler, Rafael Pedrosa, et al.
Journal of Neural Engineering (2022) Vol. 19, Iss. 3, pp. 036030-036030
Open Access | Times Cited: 8
Computational Circuit Mechanisms Underlying Thalamic Control of Attention
Qinglong L. Gu, Norman H. Lam, Ralf Wimmer, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 12
MotorNet: a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks
Olivier Codol, Jonathan A. Michaels, Mehrdad Kashefi, et al.
(2023)
Open Access | Times Cited: 4
Time-varying generalized linear models: characterizing and decoding neuronal dynamics in higher visual areas
Geyu Weng, Kelsey Clark, Amir Akbarian, et al.
Frontiers in Computational Neuroscience (2024) Vol. 18
Open Access | Times Cited: 1
MotorNet: a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks
Olivier Codol, Jonathan A. Michaels, Mehrdad Kashefi, et al.
(2024)
Open Access | Times Cited: 1
Dynamic causal communication channels between neocortical areas
Mitra Javadzadeh, Sonja B. Hofer
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 10
Population burst propagation across interacting areas of the brain
Yu Chen, Hannah Douglas, Bryan Medina, et al.
Journal of Neurophysiology (2022) Vol. 128, Iss. 6, pp. 1578-1592
Open Access | Times Cited: 7
Modeling Neural Connectivity in a Point-Process Analogue of Kalman Filter
Mingdong Li, Shuhang Chen, Xi Liu, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022), pp. 768-771
Open Access | Times Cited: 6
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models
Kristopher T. Jensen, Ta-Chu Kao, Jasmine T. Stone, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 8
MotorNet: a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks
Olivier Codol, Jonathan A. Michaels, Mehrdad Kashefi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Identification of interacting neural populations: methods and statistical considerations
Robert E. Kass, Heejong Bong, Motolani Olarinre, et al.
Journal of Neurophysiology (2023) Vol. 130, Iss. 3, pp. 475-496
Open Access | Times Cited: 2
Dynamic organization of visual cortical networks revealed by machine learning applied to massive spiking datasets
Colin Graber, Yurii A. Vlasov, Alexander G. Schwing
(2024)
Open Access
Dynamic organization of visual cortical networks revealed by machine learning applied to massive spiking datasets
Colin Graber, Yurii A. Vlasov, Alexander G. Schwing
(2024)
Open Access
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