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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:

CORnet: Modeling the Neural Mechanisms of Core Object Recognition
Jonas Kubilius, Martin Schrimpf, Aran Nayebi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2018)
Open Access | Times Cited: 170

Showing 1-25 of 170 citing articles:

Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, et al.
Nature Neuroscience (2019) Vol. 22, Iss. 6, pp. 974-983
Open Access | Times Cited: 437
Neural population control via deep image synthesis
Pouya Bashivan, Kohitij Kar, James J. DiCarlo
Science (2019) Vol. 364, Iss. 6439
Open Access | Times Cited: 375
THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images
Martin N. Hebart, Adam H. Dickter, Alexis Kidder, et al.
PLoS ONE (2019) Vol. 14, Iss. 10, pp. e0223792-e0223792
Open Access | Times Cited: 183
Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision
Courtney J. Spoerer, Tim C. Kietzmann, Johannes Mehrer, et al.
PLoS Computational Biology (2020) Vol. 16, Iss. 10, pp. e1008215-e1008215
Open Access | Times Cited: 93
Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization
Priyadarshini Panda, Sai Aparna Aketi, Kaushik Roy
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 92
Computational models of category-selective brain regions enable high-throughput tests of selectivity
N. Apurva Ratan Murty, Pouya Bashivan, Alex Abate, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 83
Linking artificial and human neural representations of language
Jon Gauthier, Roger Lévy
(2019)
Open Access | Times Cited: 78
A connectivity-constrained computational account of topographic organization in primate high-level visual cortex
Nicholas M. Blauch, Marlene Behrmann, David C. Plaut
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 3
Open Access | Times Cited: 49
Texture-like representation of objects in human visual cortex
Akshay Jagadeesh, Justin L. Gardner
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 17
Open Access | Times Cited: 41
Does the visual word form area split in bilingual readers? A millimeter-scale 7-T fMRI study
Minye Zhan, Christophe Pallier, Aakash Agrawal, et al.
Science Advances (2023) Vol. 9, Iss. 14
Open Access | Times Cited: 27
Deep Neural Networks and Visuo-Semantic Models Explain Complementary Components of Human Ventral-Stream Representational Dynamics
Kamila M. Jozwik, Tim C. Kietzmann, Radoslaw M. Cichy, et al.
Journal of Neuroscience (2023) Vol. 43, Iss. 10, pp. 1731-1741
Open Access | Times Cited: 24
Improved modeling of human vision by incorporating robustness to blur in convolutional neural networks
Hojin Jang, Frank Tong
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 11
Brain hierarchy score: Which deep neural networks are hierarchically brain-like?
Soma Nonaka, Kei Majima, Shuntaro Aoki, et al.
iScience (2021) Vol. 24, Iss. 9, pp. 103013-103013
Open Access | Times Cited: 55
Untangling the Animacy Organization of Occipitotemporal Cortex
J. Brendan Ritchie, Astrid Zeman, Joyce Bosmans, et al.
Journal of Neuroscience (2021) Vol. 41, Iss. 33, pp. 7103-7119
Open Access | Times Cited: 52
Comparing memory capacity across stimuli requires maximally dissimilar foils: Using deep convolutional neural networks to understand visual working memory capacity for real-world objects
Timothy F. Brady, Viola S. Störmer
Memory & Cognition (2023) Vol. 52, Iss. 3, pp. 595-609
Closed Access | Times Cited: 20
Representational formats of human memory traces
Rebekka Heinen, Anne Bierbrauer, Oliver T. Wolf, et al.
Brain Structure and Function (2023) Vol. 229, Iss. 3, pp. 513-529
Open Access | Times Cited: 19
Diverse task-driven modeling of macaque V4 reveals functional specialization towards semantic tasks
Santiago A. Cadena, Konstantin F. Willeke, Kelli Restivo, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 5, pp. e1012056-e1012056
Open Access | Times Cited: 6
What do adversarial images tell us about human vision?
Marin Dujmović, Gaurav Malhotra, Jeffrey S. Bowers
eLife (2020) Vol. 9
Open Access | Times Cited: 48
Diverse deep neural networks all predict human IT well, after training and fitting
Katherine R. Storrs, Tim C. Kietzmann, Alexander Walther, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 44
Topographic deep artificial neural networks reproduce the hallmarks of the primate inferior temporal cortex face processing network
Hyodong Lee, Eshed Margalit, Kamila M. Jozwik, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 43
Explaining face representation in the primate brain using different computational models
Le Chang, Bernhard Egger, Thomas Vetter, et al.
Current Biology (2021) Vol. 31, Iss. 13, pp. 2785-2795.e4
Open Access | Times Cited: 38
Emergence of a compositional neural code for written words: Recycling of a convolutional neural network for reading
Thomas Hannagan, Aakash Agrawal, Laurent Cohen, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 46
Open Access | Times Cited: 36
Learning-induced reorganization of number neurons and emergence of numerical representations in a biologically inspired neural network
Percy K. Mistry, Anthony Strock, Ruizhe Liu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 15
Gain, not concomitant changes in spatial receptive field properties, improves task performance in a neural network attention model
Kai J Fox, Daniel Birman, Justin L. Gardner
eLife (2023) Vol. 12
Open Access | Times Cited: 13
The inferior temporal cortex is a potential cortical precursor of orthographic processing in untrained monkeys
Rishi Rajalingham, Kohitij Kar, Sachi Sanghavi, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 39
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