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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:

Direct Fit to Nature: An Evolutionary Perspective on Biological and Artificial Neural Networks
Uri Hasson, Samuel A. Nastase, Ariel Goldstein
Neuron (2020) Vol. 105, Iss. 3, pp. 416-434
Open Access | Times Cited: 303

Showing 1-25 of 303 citing articles:

The neural architecture of language: Integrative modeling converges on predictive processing
Martin Schrimpf, Idan Blank, Greta Tuckute, et al.
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 45
Open Access | Times Cited: 360
If deep learning is the answer, what is the question?
Andrew Saxe, Stephanie Nelli, Christopher Summerfield
Nature reviews. Neuroscience (2020) Vol. 22, Iss. 1, pp. 55-67
Open Access | Times Cited: 340
A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection
Brad K. Hulse, Hannah Haberkern, Romain Franconville, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 298
Shared computational principles for language processing in humans and deep language models
Ariel Goldstein, Zaid Zada, Eliav Buchnik, et al.
Nature Neuroscience (2022) Vol. 25, Iss. 3, pp. 369-380
Open Access | Times Cited: 285
Keep it real: rethinking the primacy of experimental control in cognitive neuroscience
Samuel A. Nastase, Ariel Goldstein, Uri Hasson
NeuroImage (2020) Vol. 222, pp. 117254-117254
Open Access | Times Cited: 253
Deep Reinforcement Learning and Its Neuroscientific Implications
Matthew Botvinick, Jane X. Wang, Will Dabney, et al.
Neuron (2020) Vol. 107, Iss. 4, pp. 603-616
Open Access | Times Cited: 204
Descriptive, Predictive and Explanatory Personality Research: Different Goals, Different Approaches, but a Shared Need to Move beyond the Big Few Traits
René Mõttus, Dustin Wood, David Condon, et al.
European Journal of Personality (2020) Vol. 34, Iss. 6, pp. 1175-1201
Open Access | Times Cited: 185
Ecological Psychology
Miguel Segundo‐Ortin, Vicente Raja
(2024)
Closed Access | Times Cited: 180
Spine dynamics in the brain, mental disorders and artificial neural networks
Haruo Kasai, Noam Ziv, Hitoshi Okazaki, et al.
Nature reviews. Neuroscience (2021) Vol. 22, Iss. 7, pp. 407-422
Closed Access | Times Cited: 145
Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Mohamed Massaoudi, Haitham Abu‐Rub, Shady S. Refaat, et al.
IEEE Access (2021) Vol. 9, pp. 54558-54578
Open Access | Times Cited: 132
Meta-learning in natural and artificial intelligence
Jane X. Wang
Current Opinion in Behavioral Sciences (2021) Vol. 38, pp. 90-95
Open Access | Times Cited: 117
Biological constraints on neural network models of cognitive function
Friedemann Pulvermüller, Rosario Tomasello, Malte R. Henningsen‐Schomers, et al.
Nature reviews. Neuroscience (2021) Vol. 22, Iss. 8, pp. 488-502
Open Access | Times Cited: 113
The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension
Samuel A. Nastase, Yunfei Liu, Hanna Hillman, et al.
Scientific Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 103
A Review of Millimeter Wave Device-Based Localization and Device-Free Sensing Technologies and Applications
Anish Shastri, Neharika Valecha, Enver Bashirov, et al.
IEEE Communications Surveys & Tutorials (2022) Vol. 24, Iss. 3, pp. 1708-1749
Open Access | Times Cited: 70
Memristor-based neural networks: a bridge from device to artificial intelligence
Zelin Cao, Bai Sun, Guangdong Zhou, et al.
Nanoscale Horizons (2023) Vol. 8, Iss. 6, pp. 716-745
Closed Access | Times Cited: 70
Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications
Hefei Liu, Yuan Qin, Hung‐Yu Chen, et al.
Advanced Materials (2023) Vol. 35, Iss. 37
Open Access | Times Cited: 49
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics
Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, et al.
Journal of Computing and Information Science in Engineering (2024) Vol. 24, Iss. 4
Closed Access | Times Cited: 46
The nature and neurobiology of fear and anxiety: State of the science and opportunities for accelerating discovery
Shannon E. Grogans, Eliza Bliss‐Moreau, Kristin A. Buss, et al.
Neuroscience & Biobehavioral Reviews (2023) Vol. 151, pp. 105237-105237
Closed Access | Times Cited: 44
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Ariel Goldstein, Avigail Grinstein-Dabush, Mariano Schain, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 23
Evaluating large language models in theory of mind tasks
Michał Kosiński
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 45
Open Access | Times Cited: 19
A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations
Zaid Zada, Ariel Goldstein, Sebastian Michelmann, et al.
Neuron (2024) Vol. 112, Iss. 18, pp. 3211-3222.e5
Closed Access | Times Cited: 15
Incremental accumulation of linguistic context in artificial and biological neural networks
Refael Tikochinski, Ariel Goldstein, Yoav Meiri, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 2
Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research
Tom Macpherson, Anne K. Churchland, Terry Sejnowski, et al.
Neural Networks (2021) Vol. 144, pp. 603-613
Open Access | Times Cited: 102
The Treachery of Images: How Realism Influences Brain and Behavior
Jacqueline C. Snow, Jody C. Culham
Trends in Cognitive Sciences (2021) Vol. 25, Iss. 6, pp. 506-519
Open Access | Times Cited: 89
The neural architecture of language: Integrative modeling converges on predictive processing
Martin Schrimpf, Idan Blank, Greta Tuckute, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 77
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