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:

Interrogating theoretical models of neural computation with emergent property inference
Sean R. Bittner, Agostina Palmigiano, Alex T. Piet, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 24

Showing 24 citing articles:

Training deep neural density estimators to identify mechanistic models of neural dynamics
Pedro J. Gonçalves, Jan-Matthis Lueckmann, Michael Deistler, et al.
eLife (2020) Vol. 9
Open Access | Times Cited: 201

A unifying perspective on neural manifolds and circuits for cognition
Christopher Langdon, Mikhail Genkin, Tatiana A. Engel
Nature reviews. Neuroscience (2023) Vol. 24, Iss. 6, pp. 363-377
Closed Access | Times Cited: 116

Neural learning rules for generating flexible predictions and computing the successor representation
Ching Fang, Dmitriy Aronov, LF Abbott, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 41

Interactions between circuit architecture and plasticity in a closed-loop cerebellar system
Hannah L. Payne, Jennifer L Raymond, Mark S. Goldman
eLife (2024) Vol. 13
Open Access | Times Cited: 7

Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis
Taiga Abe, Ian Kinsella, Shreya Saxena, et al.
Neuron (2022) Vol. 110, Iss. 17, pp. 2771-2789.e7
Open Access | Times Cited: 27

pyABC: Efficient and robust easy-to-use approximate Bayesian computation
Yannik Schälte, Emmanuel Klinger, Emad Alamoudi, et al.
The Journal of Open Source Software (2022) Vol. 7, Iss. 74, pp. 4304-4304
Open Access | Times Cited: 22

Maximum Entropy Framework for Predictive Inference of Cell Population Heterogeneity and Responses in Signaling Networks
Purushottam D. Dixit, Eugenia Lyashenko, Mario Niepel, et al.
Cell Systems (2019) Vol. 10, Iss. 2, pp. 204-212.e8
Open Access | Times Cited: 36

Bringing Anatomical Information into Neuronal Network Models
Sacha J. van Albada, Aitor Morales-Gregorio, Timo Dickscheid, et al.
Advances in experimental medicine and biology (2021), pp. 201-234
Open Access | Times Cited: 29

Geometric framework to predict structure from function in neural networks
Tirthabir Biswas, James E. Fitzgerald
Physical Review Research (2022) Vol. 4, Iss. 2
Open Access | Times Cited: 18

Efficient Inference on a Network of Spiking Neurons using Deep Learning
Nina Baldy, Martin Breyton, Marmaduke Woodman, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3

Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics
Jonathan Oesterle, Christian Behrens, Cornelius Schröder, et al.
eLife (2020) Vol. 9
Open Access | Times Cited: 25

A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
Jan Clemens, Stefan Schöneich, Konstantinos Kostarakos, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 18

Connecting Connectomes to Physiology
Alexander Borst, Christian Leibold
Journal of Neuroscience (2023) Vol. 43, Iss. 20, pp. 3599-3610
Open Access | Times Cited: 6

Simulation-Based Inference for Whole-Brain Network Modeling of Epilepsy using Deep Neural Density Estimators
Meysam Hashemi, Anirudh Nihalani Vattikonda, Jayant Jha, et al.
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 9

Deep inverse modeling reveals dynamic-dependent invariances in neural circuit mechanisms
Richard Gao, Michael Deistler, Auguste Schulz, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1

Multimodal parameter spaces of a complex multi-channel neuron model
Y. Curtis Wang, Johann Rudi, James Velasco, et al.
Frontiers in Systems Neuroscience (2022) Vol. 16
Open Access | Times Cited: 7

Neural learning rules for generating flexible predictions and computing the successor representation
Ching Fang, Dmitriy Aronov, L. F. Abbott, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 5

A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
Jan Clemens, Stefan Schöneich, Konstantinos Kostarakos, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 5

Constructing neural networks with pre-specified dynamics
Camilo J. Mininni, B. Silvano Zanutto
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access

Cell-mechanical parameter estimation from 1D cell trajectories using simulation-based inference
Johannes Heyn, Miguel Atienza Juanatey, Martin Falcke, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access

Automated customization of large-scale spiking network models to neuronal population activity
Shenghao Wu, Chengcheng Huang, A. C. Snyder, et al.
Nature Computational Science (2024) Vol. 4, Iss. 9, pp. 690-705
Closed Access

Theoretical principles for illuminating sensorimotor processing with brain-wide neuronal recordings
Tirthabir Biswas, William E. Bishop, James E. Fitzgerald
Current Opinion in Neurobiology (2020) Vol. 65, pp. 138-145
Open Access | Times Cited: 3

The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience
Michele Nardin, Jozsef Csicsvari, Gašper Tkačik, et al.
Journal of Neuroscience (2023) Vol. 43, Iss. 48, pp. 8140-8156
Open Access | Times Cited: 1

A familiar thought: Machines that replace us?
Basile Confavreux, Tim P. Vogels
Neuron (2022) Vol. 110, Iss. 3, pp. 361-362
Open Access

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