Decision theory, reinforcement learning, and the brain

Cited by (583)

Items 201–300 of 583

1. The statistics of optimal decision making: Exploring the relationship between signal detection theory and sequential analysis
   Thom Griffith, Sophie-Anne Baker, Nathan F. Lepora · 2021 · Journal of Mathematical Psychology
2. Controlled variations in stimulus similarity during learning determine visual discrimination capacity in freely moving mice
   Mario Treviño, Tatiana Oviedo, Patrick Jendritza, Shi‐Bin Li, Georg Köhr, Rodrigo J. De Marco · 2013 · Scientific Reports
3. Scarce Means with Alternative Uses: Robbins’ Definition of Economics and Its Extension to the Behavioral and Neurobiological Study of Animal Decision Making
   Peter Shizgal · 2012 · Frontiers in Neuroscience
4. Integrating Media Selection and Media Effects Using Decision Theory
   Jacob Taylor Fisher, Kristy A. Hamilton · 2021 · Journal of Media Psychology Theories Methods and Applications
5. A neurally plausible model learns successor representations in partially observable environments
   Eszter Vértes, Maneesh Sahani · 2019 · arXiv (Cornell University)
6. Striatal BOLD and midfrontal theta power express motivation for action
   Johannes Algermissen, Jennifer C. Swart, René Scheeringa, Roshan Cools, Hanneke E.M. den Ouden · 2021 · Cerebral Cortex
7. Reinforcement learning establishes a minimal metacognitive process to monitor and control motor learning performance
   Taisei Sugiyama, Nicolas Schweighofer, Jun Izawa · 2023 · Nature Communications
8. Proactive Action Preparation: Seeing Action Preparation as a Continuous and Proactive Process
   Giovanni Pezzulo, Dimitri Ognibene · 2012 · Motor Control
9. An integrated utility-based model of conflict evaluation and resolution in the Stroop task.
   Adam Chuderski, Tomasz Smoleń · 2016 · Psychological Review
10. A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision Making
    Pouyan Rafiei Fard, Hame Park, Andrej Warkentin, Stefan J. Kiebel, Sebastian Bitzer · 2017 · Frontiers in Computational Neuroscience
11. Interpersonal dysfunction in borderline personality: a decision neuroscience perspective
    Michael N. Hallquist, Nathan T. Hall, Alison Schreiber, Alexandre Y. Dombrovski · 2017 · Current Opinion in Psychology
12. Visual fixation patterns during economic choice reflect covert valuation processes that emerge with learning
    Sean Edward Cavanagh, W. M. Nishantha Malalasekera, Bruno Miranda, Laurence Tudor Hunt, Steven Wayne Kennerley · 2019 · Proceedings of the National Academy of Sciences
13. Order Matters! Influences of Linear Order on Linguistic Category Learning
    Dorothée B. Hoppe, Jacolien van Rij, Petra Hendriks, Michael Ramscar · 2020 · Cognitive Science
14. A cognitive category-learning model of rule abstraction, attention learning, and contextual modulation.
    René Schlegelmilch, Andy J. Wills, Bettina von Helversen · 2021 · Psychological Review
15. Learning to maximize reward rate: a model based on semi-Markov decision processes
    Arash Khodadadi, Pegah Fakhari, Jerome R. Busemeyer · 2014 · Frontiers in Neuroscience
16. How Prior Probability Influences Decision Making: A Unifying Probabilistic Model
    Yanping Huang, Timothy D. Hanks, Michael Neil Shadlen, Abram L. Friesen, Rajesh P. N. Rao · 2012
17. Combination of Simultaneous Artificial Sensory Percepts to Identify Prosthetic Hand Postures: A Case Study
    Jacob L. Segil, Ivana Cuberovic, Emily L. Graczyk, Richard F ff Weir, Dustin James Tyler · 2020 · Scientific Reports
18. Reinforcement Learning during Adolescence in Rats
    Neema Moin Afshar, Alex J. Keip, Jane R. Taylor, Daeyeol Lee, Stephanie Mary Groman · 2020 · Journal of Neuroscience
19. Inferring learning rules from animal decision-making.
    Zoe C. Ashwood, Nicholas A Roy, Ji Hyun Bak, Jonathan W. Pillow · 2020 · PubMed
20. Model-Based Reinforcement Learning as Cognitive Search: Neurocomputational Theories
    Peter Martin Todd, Thomas T. Hills, Trevor William Robbins · 2012
21. Dreams, reality and memory: confabulations in lucid dreamers implicate reality-monitoring dysfunction in dream consciousness
    Philip Robert Corlett, Sofija V. Canavan, L. Nahum, F. Appah, PETER T. MORGAN · 2014 · Cognitive Neuropsychiatry
22. Predictive coding for the actions and emotions of others and its deficits in autism spectrum disorders
    Christian Keysers, Giorgia Silani, Valeria Gazzola · 2024 · Neuroscience & Biobehavioral Reviews
23. Five theses on neuroeconomics
    Roberto Fumagalli · 2015 · Journal of Economic Methodology
24. Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula
    Lara Henco, Marie‐Luise Brandi, Juha M. Lahnakoski, Andreea Oliviana Diaconescu, Christoph D. Mathys, Leonhard Schilbach · 2020 · Cortex
25. Reasoning and choice in the Monty Hall Dilemma (MHD): implications for improving Bayesian reasoning
    Elisabet Tubau, David Aguilar‐Lleyda, Eric D. M. Johnson · 2015 · Frontiers in Psychology
26. Dopamine encodes deep network teaching signals for individual learning trajectories
    Samuel Liebana Garcia, Aeron Laffere, Chiara Toschi, Louisa Schilling, Jessica Moretti, Jacek Podlaski, Matthias Fritsche, Peter Zatka-Haas, Yulong Li, Rafał Bogacz et al. · 2025 · Cell
27. Tonic dopamine and biases in value learning linked through a biologically inspired reinforcement learning model
    Sandra Romero Pinto, Naoshige Uchida · 2025 · Nature Communications
28. Reinforcement regulates timing variability in thalamus
    Jing Wang, Eghbal A. Hosseini, Nicolas Meirhaeghe, Adam Akkad, Mehrdad Jazayeri · 2020 · eLife
29. Understanding learning through uncertainty and bias
    Rasmus Bruckner, Hauke R. Heekeren, Matthew R. Nassar · 2025 · Communications Psychology
30. Exploring the formation conditions and dynamic trends of rural residents’ clean heating behaviour in northern China based on reinforcement learning
    Na Li, Xi Luo, Menglin Xing, Jianghua Liu, Yaru Gao, Tingting Zhou, Min Zhang, Jin Li, Yanfeng Liu · 2022 · Journal of Cleaner Production
31. Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning
    George I. Christopoulos, Xiaoxiao Liu, Ying‐yi Hong · 2016 · Journal of Business Ethics
32. Temporal chunking as a mechanism for unsupervised learning of task-sets
    Flora Bouchacourt, Stefano Palminteri, Étienne Koechlin, Srdjan Ostojic · 2020 · eLife
33. Autonomous and informed decision-making: The case of colorectal cancer screening
    Linda N. Douma, Ellen Uiters, Marcel F. Verweij, Daniëlle R. M. Timmermans · 2020 · PLoS ONE
34. Timing along the cardiac cycle modulates neural signals of reward-based learning
    Elsa Florence Fouragnan, Billy Hosking, Yin Bun Cheung, Brooke A. Prakash, Matthew F. S. Rushworth, Alejandra Sel · 2024 · Nature Communications
35. Perceptual bias is reduced with longer reaction times during visual discrimination
    Ron Dekel, Dov Sagi · 2020 · Communications Biology
36. Slow or sudden: Re-interpreting the learning curve for modern systems neuroscience
    Sharlen Moore, Kishore V. Kuchibhotla · 2022 · IBRO Neuroscience Reports
37. Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior
    Yoav Ger, Eliya Nachmani, Lior Wolf, Nitzan Shahar · 2024 · PLoS Computational Biology
38. Functional Neurological Disorder and Autism Spectrum Disorder: A Complex and Potentially Significant Relationship
    Belén González‐Herrero, Francesca G. E. Happe, Timothy R. Nicholson, Francesca Morgante, Javier Pagonabarraga, Quinton Deeley, Mark John Edwards · 2024 · Brain and Behavior
39. Rodent Models of Adaptive Decision Making
    Alicia Izquierdo, Annabelle M. Belcher · 2011 · Methods in molecular biology
40. Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
    Minhae Kwon, Saurabh Daptardar, Paul Schrater, Xaq Pitkow · 2020 · PubMed
41. Policies and Priors
    Karl John Friston · 2011 · Springer eBooks
42. Formation and recurrence mechanism of residents' waste separation behavior under the intervention of an information interaction
    Feiyu Chen, Hong Chen, Shuo Liu, Wenbo Li, Qianwen Li, Ruyin Long · 2020 · Resources Conservation and Recycling
43. Individuals with problem gambling and obsessive-compulsive disorder learn through distinct reinforcement mechanisms
    Shinsuke Suzuki, Xiaoliu Zhang, Amir Dezfouli, Leah Braganza, Ben Fulcher, Linden Parkes, Leonardo Franklin Fontenelle, Ben J. Harrison, Carsten Murawski, Murat Yücel et al. · 2023 · PLoS Biology
44. Optimal nudging for cognitively bounded agents: A framework for modeling, predicting, and controlling the effects of choice architectures.
    Frederick Callaway, Mathew Hardy, Thomas L. Griffiths · 2023 · Psychological Review
45. Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex
    Kotaro Ishizu, S. Nishimoto, Yutaro Ueoka, Akihiro Funamizu · 2024 · Nature Communications
46. Neurocognitive Modeling of Perceptual Decision Making
    Thomas J. Palmeri, Jeffrey D. Schall, Gordon D. Logan · 2015 · Oxford University Press eBooks
47. An effective approach for determining the class integration test order using reinforcement learning
    Gabriela Czibula, István Gergely Czibula, Zsuzsanna Marian · 2018 · Applied Soft Computing
48. Psychological and Neuroscientific Connections with Reinforcement Learning
    Ashvin Shah · 2012 · Adaptation, learning, and optimization
49. The Neurobiology of Impulsive Decision-Making and Reinforcement Learning in Nonhuman Animals
    Stephanie Mary Groman · 2020 · Current topics in behavioral neurosciences
50. Metacognitive Computations for Information Search: Confidence in Control
    Lion Schulz, Stephen M. Fleming, Peter Dayan · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
51. Computational Models of Hallucinations
    Jardri, Renaud, Denève, Sophie · 2013 · The Neuroscience of Hallucinations
52. An opponent process for alcohol addiction based on changes in endocrine gland mass
    Omer Karin, Moriya Raz, Uri S. Alon · 2021 · iScience
53. Temporal regularities shape perceptual decisions and striatal dopamine signals
    Matthias Fritsche, Antara Majumdar, Lauren Strickland, Samuel Liebana Garcia, Rafał Bogacz, Armin Lak · 2024 · Nature Communications
54. Prediction and Control in a Dynamic Environment
    Magda Osman, Maarten Speekenbrink · 2012 · Frontiers in Psychology
55. Individual differences in behavioural inhibition explain free riding in public good games when punishment is expected but not implemented
    Anya Skatova, Eamonn Ferguson · 2013 · Behavioral and Brain Functions
56. A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker
    Felix Leibfried, Daniel A. Braun · 2015 · Neural Computation
57. Learning to allocate limited time to decisions with different expected outcomes
    Arash Khodadadi, Pegah Fakhari, Jerome R. Busemeyer · 2017 · Cognitive Psychology
58. Selective maintenance of value information helps resolve the exploration/exploitation dilemma
    Michael N. Hallquist, Alexandre Y. Dombrovski · 2018 · Cognition
59. Understanding multivariate brain activity: Evaluating the effect of voxelwise noise correlations on population codes in functional magnetic resonance imaging
    Ru‐Yuan Zhang, Xue-Xin Wei, Kendrick Kay · 2020 · PLoS Computational Biology
60. Reward and decision processes in the brains of humans and nonhuman primates
    Angela Sirigu B, Jean‐René Duhamel · 2016 · Dialogues in Clinical Neuroscience
61. Choice Under Risk: How Occupation Influences Preferences
    Tetiana Hill, Petko Kusev, Paul van Schaik · 2019 · Frontiers in Psychology
62. Predicting Short‐Term Remembering as Boundedly Optimal Strategy Choice
    Andrew Howes, Geoffrey B. Duggan, Kiran Kalidindi, Yuan‐Chi Tseng, Richard L. Lewis · 2015 · Cognitive Science
63. Does Amount of Information Support Aesthetic Values?
    Norberto Mauricio Grzywacz, Hassan Aleem · 2022 · Frontiers in Neuroscience
64. Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
    Sven Banisch, Felix Gaisbauer, Eckehard Olbrich · 2022 · Entropy
65. Sex-dependent effects of early life stress on reinforcement learning and limbic cortico-striatal functional connectivity
    Katharina Zühlsdorff, Laura López‐Cruz, Ethan G. Dutcher, Jolyon A. Jones, Claudia Pama, Stephen J. Sawiak, Shahid Ahmed Khan, Amy L. Milton, Trevor William Robbins, Edward Thomas Bullmore et al. · 2022 · Neurobiology of Stress
66. Food reinforcement architecture: A framework for impulsive and compulsive overeating and food abuse
    Kyle Stanley Burger · 2023 · Obesity
67. Towards machines that understand people
    Andrew Howes, Jussi Jokinen, Antti Oulasvirta · 2023 · AI Magazine
68. Optimal metacognitive control of memory recall.
    Frederick Callaway, Thomas L. Griffiths, Kenneth A. Norman, Qiong Zhang · 2023 · Psychological Review
69. Dorsolateral Striatal Task-initiation Bursts Represent Past Experiences More than Future Action Plans
    Paul J. Cunningham, Paul S. Regier, A. David Redish · 2021 · Journal of Neuroscience
70. Lapses in perceptual decisions reflect exploration
    Sashank Pisupati, Lital Chartarifsky-Lynn, Anup Khanal, Anne K. Churchland · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
71. Fast rule switching and slow rule updating in a perceptual categorization task
    Flora Bouchacourt, Sina Tafazoli, Marcelo Gomes Mattar, Timothy J. Buschman, Nathaniel D. Daw · 2022 · eLife
72. Neural representation of decision confidence
    Jing Chen, Tingyong Feng, Jinfu Shi, Lei Liu, Hong Li · 2013 · Behavioural Brain Research
73. A corticostriatal deficit promotes temporal distortion of automatic action in ageing
    Miriam Matamales, Zala Skrbis, Matthew R Bailey, Peter D. Balsam, Bernard W. Balleine, Jürgen Götz, Jesus Bertran‐Gonzalez · 2017 · eLife
74. Prediction errors drive dynamic changes in neural patterns that guide behavior
    Léon Möhring, Jan P. Gläscher · 2023 · Cell Reports
75. Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations
    Paul Richmond, Lars Buesing, Michèle Giugliano, Eleni Vasilaki · 2011 · PLoS ONE
76. Quantity versus quality: Convergent findings in effort-based choice tasks
    Evan E. Hart, Alicia Izquierdo · 2019 · Behavioural Processes
77. Representing the consequences of our actions trial by trial: Complex and flexible encoding of feedback valence and magnitude
    Isabel Padrón, José Fernández Rey, Carlos Acuña, José L. Pardo‐Vázquez · 2016 · Neuroscience
78. What to Choose Next? A Paradigm for Testing Human Sequential Decision Making
    Elisa M. Tartaglia, Aaron Clarke, Michael H. Herzog · 2017 · Frontiers in Psychology
79. A Computational Neuroscience Perspective on the Change Process in Psychotherapy
    Ryan P. Smith, Richard D. Lane, Lynn Nadel, Michael Moutoussis · 2020 · Oxford University Press eBooks
80. Belief states and categorical-choice biases determine reward-based learning under perceptual uncertainty
    Rasmus Bruckner, Hauke R. Heekeren, Dirk Ostwald · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
81. Understanding Learning Through Uncertainty and Bias
    Rasmus Bruckner, Hauke R. Heekeren, Matthew R. Nassar · 2022
82. The effects of mental fatigue on effort allocation: Modeling and estimation.
    Zhide Wang, Yanling Chang, Brandon J. Schmeichel, Alfredo García · 2022 · Psychological Review
83. Disentangling sources of variability in decision-making
    Jade S. Duffy, Mark A. Bellgrove, Peter R. Murphy, Redmond G O’Connell · 2025 · Nature reviews. Neuroscience
84. Advances in Artificial Intelligence-Based Medical Devices for Healthcare Applications
    Felix Tettey, Santosh Kumar Parupelli, Steven R. Bauer, Narayan Bhattarai, Salil S. Desai · 2025 · Biomedical Materials & Devices
85. How Does the Brain Solve the Computational Problems of Spatial Navigation?
    John Widloski, Ila Fiete · 2014 · Springer eBooks
86. Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task
    Lilla Horváth, Stanley J. Colcombe, Michael Peter Milham, Shruti Ray, Philipp Schwartenbeck, Dirk Ostwald · 2021 · Computational Brain & Behavior
87. Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task
    Guillaume D Viejo, Benoît Girard, Emmanuel Procyk, Mehdi Khamassi · 2017 · Behavioural Brain Research
88. Dual Reward Prediction Components Yield Pavlovian Sign- and Goal-Tracking
    Sivaramakrishnan Kaveri, Hiroyuki Nakahara · 2014 · PLoS ONE
89. Dark Control: Towards a Unified Account of Default Mode Function by Markov Decision Processes
    Elvis Dohmatob, Guillaume Dumas, Danilo Bzdok · 2017 · bioRxiv (Cold Spring Harbor Laboratory)
90. Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning
    Yamada, Jun, Shawe-Taylor, John, Fountas, Zafeirios · 2020 · 2020 International Joint Conference on Neural Networks (IJCNN)
91. Apparently Irrational Choice as Optimal Sequential Decision Making
    Haiyang Chen, Hyung Jin Chang, Andrew Howes · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
92. Redefining Affordance via Computational Rationality
    Yi-Chi Liao, Christian Holz · 2025 · ACM International Conference on Intelligent User Interfaces (IUI)
93. Integration of sensory evidence and reward expectation in mouse perceptual decision-making task with various sensory uncertainties
    Akihiro Funamizu · 2021 · iScience
94. Dichotomous dopaminergic and noradrenergic neural states mediate distinct aspects of exploitative behavioral states
    Aaron C. Koralek, Rui M. Costa · 2021 · Science Advances
95. Models of Value and Choice
    Peter Dayan · 2011 · Elsevier eBooks
96. An efficiency framework for valence processing systems inspired by soft cross-wiring
    P. Read Montague, Kenneth T. Kishida, Rosalyn Moran, Terry M. Lohrenz · 2016 · Current Opinion in Behavioral Sciences
97. Reward foraging task and model-based analysis reveal how fruit flies learn value of available options
    Sophie E Seidenbecher, Joshua I. Sanders, Anne C. von Philipsborn, Duda Kvitsiani · 2020 · PLoS ONE
98. Human Visual Search as a Deep Reinforcement Learning Solution to a POMDP.
    Aditya Acharya, Xiuli Chen, Christopher W. Myers, Richard L. Lewis, Andrew Howes · 2017 · eScholarship (California Digital Library)
99. Articulatory Variability is Reduced by Repetition and Predictability
    Fabian Tomaschek, Denis Arnold, Konstantin Florian Sering, Benjamin V. Tucker, Jacolien van Rij, Michael Ramscar · 2020 · Language and Speech
100. Endogenous Learning with Bounded Memory
     Yilmaz Kocer · 2011 · SSRN Electronic Journal