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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 51-75 of 380 citing articles:

Dopamine neuron ensembles signal the content of sensory prediction errors
Thomas A. Stalnaker, James D. Howard, Yuji K. Takahashi, et al.
eLife (2019) Vol. 8
Open Access | Times Cited: 61
Reinforcement Learning through Active Inference
Alexander Tschantz, Beren Millidge, Anil C. Seth, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 59
Distributional Reinforcement Learning in the Brain
Adam S. Lowet, Zheng Qiao, Sara Matias, et al.
Trends in Neurosciences (2020) Vol. 43, Iss. 12, pp. 980-997
Open Access | Times Cited: 59
Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments
Logan Cross, Jeff Cockburn, Yisong Yue, et al.
Neuron (2020) Vol. 109, Iss. 4, pp. 724-738.e7
Open Access | Times Cited: 54
An Improved Dyna-Q Algorithm for Mobile Robot Path Planning in Unknown Dynamic Environment
Muleilan Pei, Hao An, Bo Liu, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2021) Vol. 52, Iss. 7, pp. 4415-4425
Closed Access | Times Cited: 54
Dopamine, endocannabinoids and their interaction in fear extinction and negative affect in PTSD
Luke J. Ney, Jane Akhurst, Raimondo Bruno, et al.
Progress in Neuro-Psychopharmacology and Biological Psychiatry (2020) Vol. 105, pp. 110118-110118
Closed Access | Times Cited: 52
The Role of Dopamine in Associative Learning in Drosophila: An Updated Unified Model
Mohamed Adel, Leslie C. Griffith
Neuroscience Bulletin (2021) Vol. 37, Iss. 6, pp. 831-852
Open Access | Times Cited: 52
Context-Dependent Multiplexing by Individual VTA Dopamine Neurons
Yves Kremer, Jérôme Flakowski, Clément Rohner, et al.
Journal of Neuroscience (2020) Vol. 40, Iss. 39, pp. 7489-7509
Open Access | Times Cited: 51
Response-based outcome predictions and confidence regulate feedback processing and learning
Romy Frömer, Matthew R. Nassar, Rasmus Bruckner, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 46
Rare rewards amplify dopamine responses
Kathryn M. Rothenhoefer, Tao Hong, Aydin Alikaya, et al.
Nature Neuroscience (2021) Vol. 24, Iss. 4, pp. 465-469
Open Access | Times Cited: 44
The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again
Adam Safron
Entropy (2021) Vol. 23, Iss. 6, pp. 783-783
Open Access | Times Cited: 42
A feature-specific prediction error model explains dopaminergic heterogeneity
Rachel S. Lee, Yotam Sagiv, Ben Engelhard, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 33
Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents
Raphael Köster, Dylan Hadfield-Menell, Richard Everett, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 3
Open Access | Times Cited: 31
Informing deep neural networks by multiscale principles of neuromodulatory systems
Jie Mei, Eilif Müller, Srikanth Ramaswamy
Trends in Neurosciences (2022) Vol. 45, Iss. 3, pp. 237-250
Closed Access | Times Cited: 28
Brain-Inspired Deep Meta-Reinforcement Learning for Active Coordinated Fault-Tolerant Load Frequency Control of Multi-Area Grids
Jiawen Li, Tao Zhou, Haoyang Cui
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 3, pp. 2518-2530
Closed Access | Times Cited: 19
Intelligent service placement algorithm based on DDQN and prioritized experience replay in IoT-Fog computing environment
Ankur Sharma, Veni Thangaraj
Internet of Things (2024) Vol. 25, pp. 101112-101112
Closed Access | Times Cited: 7
Rationality, preferences, and emotions with biological constraints: it all starts from our senses
Rafael Polanía, Denis Burdakov, Todd A. Hare
Trends in Cognitive Sciences (2024) Vol. 28, Iss. 3, pp. 264-277
Open Access | Times Cited: 7
Learning to express reward prediction error-like dopaminergic activity requires plastic representations of time
Ian Cone, Claudia Clopath, Harel Z. Shouval
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
An opponent striatal circuit for distributional reinforcement learning
Adam S. Lowet, Zheng Qiao, Melissa Meng, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 6
Coordinating brain-distributed network activities in memory resistant to extinction
Charlie J. Clarke-Williams, Vítor Lopes‐dos‐Santos, Laura Lefèvre, et al.
Cell (2024) Vol. 187, Iss. 2, pp. 409-427.e19
Open Access | Times Cited: 6
Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies
Bing Yuan, Jiang Zhang, Aobo Lyu, et al.
Entropy (2024) Vol. 26, Iss. 2, pp. 108-108
Open Access | Times Cited: 6
A dopamine mechanism for reward maximization
Wolfram Schultz
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 20
Open Access | Times Cited: 6
The role of executive function in shaping reinforcement learning
Milena Rmus, Samuel D. McDougle, Anne Collins
Current Opinion in Behavioral Sciences (2020) Vol. 38, pp. 66-73
Open Access | Times Cited: 45
Big data, machine learning and artificial intelligence: a neurologist’s guide
Stephen D. Auger, Benjamin Meir Jacobs, Ruth Dobson, et al.
Practical Neurology (2020), pp. practneurol-002688
Open Access | Times Cited: 43
A Normative Account of Confirmation Bias During Reinforcement Learning
Germain Lefebvre, Christopher Summerfield, Rafał Bogacz
Neural Computation (2021) Vol. 34, Iss. 2, pp. 307-337
Open Access | Times Cited: 37

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