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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:

Neural circuits as computational dynamical systems
David Sussillo
Current Opinion in Neurobiology (2014) Vol. 25, pp. 156-163
Closed Access | Times Cited: 230

Showing 1-25 of 230 citing articles:

Toward an Integration of Deep Learning and Neuroscience
Adam Marblestone, Greg Wayne, Konrad P. Körding
Frontiers in Computational Neuroscience (2016) Vol. 10
Open Access | Times Cited: 631
Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks
David Sussillo, Omri Barak
Neural Computation (2012) Vol. 25, Iss. 3, pp. 626-649
Closed Access | Times Cited: 516
Vowel recognition with four coupled spin-torque nano-oscillators
M. Romera, Philippe Talatchian, Sumito Tsunegi, et al.
Nature (2018) Vol. 563, Iss. 7730, pp. 230-234
Open Access | Times Cited: 479
Spintronic Nanodevices for Bioinspired Computing
Julie Grollier, Damien Querlioz, M. D. Stiles
Proceedings of the IEEE (2016) Vol. 104, Iss. 10, pp. 2024-2039
Open Access | Times Cited: 395
Recurrent Network Models of Sequence Generation and Memory
Kanaka Rajan, Christopher D. Harvey, David W. Tank
Neuron (2016) Vol. 90, Iss. 1, pp. 128-142
Open Access | Times Cited: 365
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules
Nicolas Frémaux, Wulfram Gerstner
Frontiers in Neural Circuits (2016) Vol. 9
Open Access | Times Cited: 355
Thirst regulates motivated behavior through modulation of brainwide neural population dynamics
William E. Allen, Michael Z. Chen, Nandini Pichamoorthy, et al.
Science (2019) Vol. 364, Iss. 6437
Open Access | Times Cited: 342
Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks
Francesca Mastrogiuseppe, Srdjan Ostojic
Neuron (2018) Vol. 99, Iss. 3, pp. 609-623.e29
Open Access | Times Cited: 327
Why fish do not feel pain
Brian Key
Animal Sentience (2016) Vol. 1, Iss. 3
Open Access | Times Cited: 297
Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis
Alex H. Williams, Tony Hyun Kim, Forea Wang, et al.
Neuron (2018) Vol. 98, Iss. 6, pp. 1099-1115.e8
Open Access | Times Cited: 293
Artificial Neural Networks for Neuroscientists: A Primer
Guangyu Robert Yang, Xiao‐Jing Wang
Neuron (2020) Vol. 107, Iss. 6, pp. 1048-1070
Open Access | Times Cited: 291
Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework
Hui Song, Guangyu Robert Yang, Xiao‐Jing Wang
PLoS Computational Biology (2016) Vol. 12, Iss. 2, pp. e1004792-e1004792
Open Access | Times Cited: 284
Bayesian Computation through Cortical Latent Dynamics
Hansem Sohn, Devika Narain, Nicolas Meirhaeghe, et al.
Neuron (2019) Vol. 103, Iss. 5, pp. 934-947.e5
Open Access | Times Cited: 224
Recurrent neural networks as versatile tools of neuroscience research
Omri Barak
Current Opinion in Neurobiology (2017) Vol. 46, pp. 1-6
Closed Access | Times Cited: 222
Building functional networks of spiking model neurons
L. F. Abbott, Brian DePasquale, Raoul-Martin Memmesheimer
Nature Neuroscience (2016) Vol. 19, Iss. 3, pp. 350-355
Open Access | Times Cited: 219
Insects have the capacity for subjective experience
Colin Klein, Andrew B. Barron
Animal Sentience (2016) Vol. 1, Iss. 9
Open Access | Times Cited: 210
Revealing hidden states in visual working memory using electroencephalography
Michael J. Wolff, Jacqueline Ding, Nicholas E. Myers, et al.
Frontiers in Systems Neuroscience (2015) Vol. 9
Open Access | Times Cited: 202
Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions
Warasinee Chaisangmongkon, Sruthi K. Swaminathan, David J. Freedman, et al.
Neuron (2017) Vol. 93, Iss. 6, pp. 1504-1517.e4
Open Access | Times Cited: 183
Fronto-parietal Cortical Circuits Encode Accumulated Evidence with a Diversity of Timescales
Benjamin B. Scott, Christine M. Constantinople, Athena Akrami, et al.
Neuron (2017) Vol. 95, Iss. 2, pp. 385-398.e5
Open Access | Times Cited: 180
The population doctrine in cognitive neuroscience
R. Becket Ebitz, Benjamin Y. Hayden
Neuron (2021) Vol. 109, Iss. 19, pp. 3055-3068
Open Access | Times Cited: 179
The role of population structure in computations through neural dynamics
Alexis Dubreuil, Adrian Valente, Manuel Beirán, et al.
Nature Neuroscience (2022) Vol. 25, Iss. 6, pp. 783-794
Open Access | Times Cited: 151
Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity
Mehrdad Jazayeri, Srdjan Ostojic
Current Opinion in Neurobiology (2021) Vol. 70, pp. 113-120
Open Access | Times Cited: 140
An approximate line attractor in the hypothalamus encodes an aggressive state
Aditya Nair, Tomomi Karigo, Bin Yang, et al.
Cell (2023) Vol. 186, Iss. 1, pp. 178-193.e15
Open Access | Times Cited: 76
The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks
Brian DePasquale, David Sussillo, L. F. Abbott, et al.
Neuron (2023) Vol. 111, Iss. 5, pp. 631-649.e10
Open Access | Times Cited: 45
Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics
Hanle Zheng, Zheng Zhong, Rui Hu, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 34
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