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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:

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory
Anne Collins, Michael J. Frank
Proceedings of the National Academy of Sciences (2018) Vol. 115, Iss. 10, pp. 2502-2507
Open Access | Times Cited: 139

Showing 1-25 of 139 citing articles:

Ten simple rules for the computational modeling of behavioral data
Robert C. Wilson, Anne Collins
eLife (2019) Vol. 8
Open Access | Times Cited: 541
Reinforcement learning across development: What insights can we draw from a decade of research?
Kate Nussenbaum, Catherine A. Hartley
Developmental Cognitive Neuroscience (2019) Vol. 40, pp. 100733-100733
Open Access | Times Cited: 198
The interpretation of computational model parameters depends on the context
Maria K. Eckstein, Sarah L. Master, Liyu Xia, et al.
eLife (2022) Vol. 11
Open Access | Times Cited: 72
Advances in the computational understanding of mental illness
Quentin J. M. Huys, Michael Browning, Martin P. Paulus, et al.
Neuropsychopharmacology (2020) Vol. 46, Iss. 1, pp. 3-19
Open Access | Times Cited: 137
Beyond dichotomies in reinforcement learning
Anne Collins, Jeffrey Cockburn
Nature reviews. Neuroscience (2020) Vol. 21, Iss. 10, pp. 576-586
Open Access | Times Cited: 105
Brain signatures of a multiscale process of sequence learning in humans
Maxime Maheu, Stanislas Dehaene, Florent Meyniel
eLife (2019) Vol. 8
Open Access | Times Cited: 104
Statistical context dictates the relationship between feedback-related EEG signals and learning
Matthew R. Nassar, Rasmus Bruckner, Michael J. Frank
eLife (2019) Vol. 8
Open Access | Times Cited: 99
Attention for action in visual working memory
Christian N. L. Olivers, Pieter R. Roelfsema
Cortex (2020) Vol. 131, pp. 179-194
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
Disentangling the systems contributing to changes in learning during adolescence
Sarah L. Master, Maria K. Eckstein, Neta Gotlieb, et al.
Developmental Cognitive Neuroscience (2019) Vol. 41, pp. 100732-100732
Open Access | Times Cited: 82
Ten simple rules for the computational modeling of behavioral data
Robert C. Wilson, Anne Collins
(2019)
Open Access | Times Cited: 76
Abstract representations of events arise from mental errors in learning and memory
Christopher W. Lynn, Ari E. Kahn, Nathaniel Nyema, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 72
Decision-making ability, psychopathology, and brain connectivity
Michael Moutoussis, Benjamín Garzón, Sharon Neufeld, et al.
Neuron (2021) Vol. 109, Iss. 12, pp. 2025-2040.e7
Open Access | Times Cited: 64
Advances in modeling learning and decision-making in neuroscience
Anne Collins, Amitai Shenhav
Neuropsychopharmacology (2021) Vol. 47, Iss. 1, pp. 104-118
Open Access | Times Cited: 62
“Don't [ruminate], be happy”: A cognitive perspective linking depression and anhedonia
Ashleigh Rutherford, Samuel D. McDougle, Jutta Joormann
Clinical Psychology Review (2023) Vol. 101, pp. 102255-102255
Closed Access | Times Cited: 27
Using multivariate pattern analysis to increase effect sizes for event‐related potential analyses
Carlos Daniel Carrasco, Brett Bahle, Aaron Matthew Simmons, et al.
Psychophysiology (2024) Vol. 61, Iss. 7
Open Access | Times Cited: 10
Toward a functional future for the cognitive neuroscience of human aging
Zoya Mooraj, Alireza Salami, Karen L. Campbell, et al.
Neuron (2025) Vol. 113, Iss. 1, pp. 154-183
Closed Access | Times Cited: 1
Decodability of Reward Learning Signals Predicts Mood Fluctuations
Eran Eldar, Charlotte Roth, Peter Dayan, et al.
Current Biology (2018) Vol. 28, Iss. 9, pp. 1433-1439.e7
Open Access | Times Cited: 82
The Tortoise and the Hare: Interactions between Reinforcement Learning and Working Memory
Anne Collins
Journal of Cognitive Neuroscience (2018) Vol. 30, Iss. 10, pp. 1422-1432
Open Access | Times Cited: 80
The Case for Adaptive Neuromodulation to Treat Severe Intractable Mental Disorders
Nicole R. Provenza, Evan Matteson, Anusha Allawala, et al.
Frontiers in Neuroscience (2019) Vol. 13
Open Access | Times Cited: 57
A new model of decision processing in instrumental learning tasks
Steven Miletić, Russell J. Boag, Anne C. Trutti, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 54
Modeling the influence of working memory, reinforcement, and action uncertainty on reaction time and choice during instrumental learning
Samuel D. McDougle, Anne Collins
Psychonomic Bulletin & Review (2020) Vol. 28, Iss. 1, pp. 20-39
Open Access | Times Cited: 53
Similarities and differences in spatial and non-spatial cognitive maps
Charley M. Wu, Eric Schulz, Mona M. Garvert, et al.
PLoS Computational Biology (2020) Vol. 16, Iss. 9, pp. e1008149-e1008149
Open Access | Times Cited: 53
How Working Memory and Reinforcement Learning Are Intertwined: A Cognitive, Neural, and Computational Perspective
Aspen H. Yoo, Anne Collins
Journal of Cognitive Neuroscience (2021) Vol. 34, Iss. 4, pp. 551-568
Open Access | Times Cited: 49
Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG
Colin W. Hoy, Sheila C. Steiner, Robert T. Knight
Communications Biology (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 43
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