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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:

A distributional code for value in dopamine-based reinforcement learning
Will Dabney, Zeb Kurth‐Nelson, Naoshige Uchida, et al.
Nature (2020) Vol. 577, Iss. 7792, pp. 671-675
Open Access | Times Cited: 380

Showing 26-50 of 380 citing articles:

Distinct temporal difference error signals in dopamine axons in three regions of the striatum in a decision-making task
Iku Tsutsui‐Kimura, Hideyuki Matsumoto, Korleki Akiti, et al.
eLife (2020) Vol. 9
Open Access | Times Cited: 87
What do reinforcement learning models measure? Interpreting model parameters in cognition and neuroscience
Maria K. Eckstein, Linda Wilbrecht, Anne Collins
Current Opinion in Behavioral Sciences (2021) Vol. 41, pp. 128-137
Open Access | Times Cited: 84
Recurrent dynamics in the cerebral cortex: Integration of sensory evidence with stored knowledge
Wolf Singer
Proceedings of the National Academy of Sciences (2021) Vol. 118, Iss. 33
Open Access | Times Cited: 80
How Outcome Uncertainty Mediates Attention, Learning, and Decision-Making
Ilya E. Monosov
Trends in Neurosciences (2020) Vol. 43, Iss. 10, pp. 795-809
Open Access | Times Cited: 74
Interoception as modeling, allostasis as control
Eli Sennesh, Jordan E. Theriault, Dana H. Brooks, et al.
Biological Psychology (2021) Vol. 167, pp. 108242-108242
Open Access | Times Cited: 71
A gradual temporal shift of dopamine responses mirrors the progression of temporal difference error in machine learning
Ryunosuke Amo, Sara Matias, Akihiro Yamanaka, et al.
Nature Neuroscience (2022) Vol. 25, Iss. 8, pp. 1082-1092
Open Access | Times Cited: 67
Mesoaccumbal Dopamine Heterogeneity: What Do Dopamine Firing and Release Have to Do with It?
Johannes W. de Jong, Kurt M. Fraser, Stephan Lammel
Annual Review of Neuroscience (2022) Vol. 45, Iss. 1, pp. 109-129
Open Access | Times Cited: 64
Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction
Korleki Akiti, Iku Tsutsui‐Kimura, Yu Xie, et al.
Neuron (2022) Vol. 110, Iss. 22, pp. 3789-3804.e9
Open Access | Times Cited: 63
A primate temporal cortex–zona incerta pathway for novelty seeking
Takaya Ogasawara, Fatih Sogukpinar, Kaining Zhang, et al.
Nature Neuroscience (2021) Vol. 25, Iss. 1, pp. 50-60
Open Access | Times Cited: 60
Promises and Perils of Experimentation: The Mutual-Internal-Validity Problem
Hause Lin, Kaitlyn M. Werner, Michael Inzlicht
Perspectives on Psychological Science (2021) Vol. 16, Iss. 4, pp. 854-863
Open Access | Times Cited: 59
Valence biases in reinforcement learning shift across adolescence and modulate subsequent memory
Gail Rosenbaum, Hannah L. Grassie, Catherine A. Hartley
eLife (2022) Vol. 11
Open Access | Times Cited: 52
Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal
Maria K. Eckstein, Sarah L. Master, Ronald E. Dahl, et al.
Developmental Cognitive Neuroscience (2022) Vol. 55, pp. 101106-101106
Open Access | Times Cited: 52
The signature-testing approach to mapping biological and artificial intelligences
Alex H. Taylor, Amalia P. M. Bastos, Rachael L. Brown, et al.
Trends in Cognitive Sciences (2022) Vol. 26, Iss. 9, pp. 738-750
Closed Access | Times Cited: 40
Brain-wide representations of prior information in mouse decision-making
Charles Findling, Félix Hubert, Luigi Acerbi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 38
Continuous improvement of self-driving cars using dynamic confidence-aware reinforcement learning
Zhong Cao, Kun Jiang, Weitao Zhou, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 2, pp. 145-158
Closed Access | Times Cited: 33
Distributional Reinforcement Learning
Marc G. Bellemare, Will Dabney, Mark Rowland
The MIT Press eBooks (2023)
Open Access | Times Cited: 33
Overlapping representations of food and social stimuli in mouse VTA dopamine neurons
Lindsay Willmore, Adelaide R. Minerva, Ben Engelhard, et al.
Neuron (2023) Vol. 111, Iss. 22, pp. 3541-3553.e8
Closed Access | Times Cited: 29
Studying the neural representations of uncertainty
Edgar Y. Walker, Stephan Pohl, Rachel N. Denison, et al.
Nature Neuroscience (2023) Vol. 26, Iss. 11, pp. 1857-1867
Closed Access | Times Cited: 29
Deep reinforcement learning challenges and opportunities for urban water systems
Ahmed S. Negm, Xiandong Ma, George Aggidis
Water Research (2024) Vol. 253, pp. 121145-121145
Open Access | Times Cited: 15
Distributional reinforcement learning in prefrontal cortex
Timothy Müller, James L. Butler, Sebastijan Veselič, et al.
Nature Neuroscience (2024) Vol. 27, Iss. 3, pp. 403-408
Open Access | Times Cited: 13
Distributional coding of associative learning in discrete populations of midbrain dopamine neurons
Riccardo Avvisati, Anna-Kristin Kaufmann, Callum J. Young, et al.
Cell Reports (2024) Vol. 43, Iss. 4, pp. 114080-114080
Open Access | Times Cited: 13
Glutamate inputs send prediction error of reward, but not negative value of aversive stimuli, to dopamine neurons
Ryunosuke Amo, Naoshige Uchida, Mitsuko Watabe‐Uchida
Neuron (2024) Vol. 112, Iss. 6, pp. 1001-1019.e6
Open Access | Times Cited: 9
Understanding the heterogeneity of anxiety using a translational neuroscience approach
Carly M. Drzewiecki, Andrew S. Fox
Cognitive Affective & Behavioral Neuroscience (2024) Vol. 24, Iss. 2, pp. 228-245
Open Access | Times Cited: 9
The lateral habenula: A hub for value-guided behavior
Dominik Groos, Fritjof Helmchen
Cell Reports (2024) Vol. 43, Iss. 4, pp. 113968-113968
Open Access | Times Cited: 8
The curious case of dopaminergic prediction errors and learning associative information beyond value
Thorsten Kahnt, Geoffrey Schoenbaum
Nature reviews. Neuroscience (2025)
Closed Access | Times Cited: 1

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