Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts
Colas, Jaron T., O’Doherty, John P., Grafton, Scott T.·2024·PLOS Computational Biology
Cites (450)
Items 201–400 of 450
- When Does Model-Based Control Pay Off?Kool, Wouter, Cushman, Fiery A., Gershman, Samuel J. · 2016 · PLOS Computational Biology
- Activation of Dorsal Raphe Serotonergic Neurons Promotes Waiting but Is Not ReinforcingMadalena S. Fonseca, Masayoshi Murakami, Zachary F. Mainen · 2015 · Current Biology
- Computational Grounded Cognition: a new alliance between grounded cognition and computational modelingGiovanni Pezzulo, Lawrence W. Barsalou, Angelo Cangelosi, Martin H. Fischer, Ken McRae, Michael James Spivey · 2013 · Frontiers in Psychology
- Terrain-adaptive locomotion skills using deep reinforcement learningXue Bin Peng, Glen Berseth, Michiel van de Panne · 2016 · ACM Transactions on Graphics
- Serial Choice Reaction-time as a Function of Response versus Signal-and-Response RepetitionPaul Bertelson · 1965 · Nature
- LINEAR-NONLINEAR-POISSON MODELS OF PRIMATE CHOICE DYNAMICSCorrado, Greg S., Sugrue, Leo P., Seung, H. Sebastian, Newsome, William T. · 2005 · Journal of the Experimental Analysis of Behavior
- Perseveration in behavioral neurologyJennifer R. Sandson, Martin L. Albert · 1987 · Neurology
- Global perspectives on the ecology of human-machine systemsAlfred T. Lee · 1996 · Journal of the American Society for Information Science
- The Mechanics of Embodiment: A Dialog on Embodiment and Computational ModelingGiovanni Pezzulo, Lawrence W. Barsalou, Angelo Cangelosi, Martin H. Fischer, Ken McRae, Michael James Spivey · 2011 · Frontiers in Psychology
- Model-Based Cognitive Neuroscience Approaches to Computational PsychiatryThomas V. Wiecki, Jeffrey S. Poland, Michael J. Frank · 2015 · Clinical Psychological Science
- Conditional Computation in Neural Networks for faster modelsEmmanuel Bengio, Pierre‐Luc Bacon, Joëlle Pineau, Doina Precup · 2015 · arXiv (Cornell University)
- Autonomous Mechanism of Internal Choice Estimate Underlies Decision InertiaRei Akaishi, Kazumasa Umeda, Asako Mitsuto Nagase, Katsuyuki Sakai · 2013 · Neuron
- Exploring the consequences of the previous trialJillian H. Fecteau, Douglas P. Munoz · 2003 · Nature reviews. Neuroscience
- The algorithmic architecture of exploration in the human brainEric Schulz, Samuel Joseph Gershman · 2018 · Current Opinion in Neurobiology
- Adaptable history biases in human perceptual decisionsArman Abrahamyan, Laura Luz Silva, Steven C. Dakin, Matteo Carandini, Justin L. Gardner · 2016 · Proceedings of the National Academy of Sciences
- Modification of the Backlin-Kirk Combustion Chamber for Micro-Determination of Carbon and LipoidsWm. L. Doyle · 1933 · Science
- An adaptive optimal controller for discrete-time Markov environmentsWitten, Ian H. · 1977 · Information and Control
- Uncertainty and Exploration in a Restless Bandit ProblemMaarten Speekenbrink, Emmanouil Konstantinidis · 2015 · Topics in Cognitive Science
- The Anterior Cingulate Cortex Predicts Future States to Mediate Model-Based Action SelectionAkam, Thomas, Rodrigues-Vaz, Ines, Marcelo, Ivo, Zhang, Xiangyu, Pereira, Michael, Oliveira, Rodrigo Freire, Dayan, Peter, Costa, Rui M. · 2021 · Neuron
- TD(λ) Converges with Probability 1Peter Dayan, Terrence J. Sejnowski A B · 1994 · Machine Learning
- Dopamine and effort-based decision makingIrma Triasih Kurniawan · 2011 · Frontiers in Neuroscience
- Reward-based training of recurrent neural networks for cognitive and value-based tasksHui Song, Guangyu Robert Yang, Xiao‐Jing Wang · 2017 · eLife
- Resource-rational decision makingBhui, Rahul, Lai, Lucy, Gershman, Samuel J · 2021 · Current Opinion in Behavioral Sciences
- Computational neuroimaging strategies for single patient predictionsKlaas Enno Stephan, Florian Schlagenhauf, Quentin J. M. Huys, Sudhir Raman, Eduardo A. Aponte, Kay Henning Brodersen, Lionel Rigoux, Rosalyn Moran, Jean Daunizeau A, Raymond J. Dolan et al. · 2016 · NeuroImage
- Assessing inter individual differences with task related functional neuroimagingLebreton, Maël, Bavard, Sophie, Daunizeau, Jean, Palminteri, Stefano · 2019 · Nature Human Behaviour
- Neuronal Origins of Choice Variability in Economic DecisionsCamillo Padoa‐Schioppa · 2013 · Neuron
- Adaptive History Biases Result from Confidence-Weighted Accumulation of past ChoicesAnke Braun, Anne E Urai, Tobias H. Donner · 2018 · Journal of Neuroscience
- Empirical priors for reinforcement learning modelsSamuel J. Gershman · 2016 · Journal of Mathematical Psychology
- Reading habits and line bisection: a developmental approachSylvie Chokron A, Maria De Agostini · 1995 · Cognitive Brain Research
- History-based action selection bias in posterior parietal cortexEun Jung Hwang, Jeffrey E. Dahlen, Madan Mukundan, Takaki Komiyama · 2017 · Nature Communications
- What Is the Relationship between Dopamine and Effort?Mark E. Walton, Sébastien Bouret · 2018 · Trends in Neurosciences
- Value normalization in decision making: theory and evidenceAntonio Rangel, John A. Clithero · 2012 · Current Opinion in Neurobiology
- Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modelingNitzan Shahar, Tobias U. Hauser, Michael Moutoussis, Rani Moran, Mehdi Keramati, Raymond J. Dolan · 2019 · PLoS Computational Biology
- Confidence and speed in the two-category judgmentDonald M. Johnson · 1939 · University of Michigan Library Repository
- An information-theoretic perspective on the costs of cognitionAlexandre Zénon, Oleg Solopchuk, Giovanni Pezzulo · 2017 · Neuropsychologia
- Mechanisms underlying dependencies of performance on stimulus history in a two-alternative forced-choice taskR.Y. Cho, Leigh E. Nystrom, Eric Brown, Andrew D. Jones, Todd Samuel Braver, Philip J. Holmes, J. D. COHEN · 2002 · Cognitive Affective & Behavioral Neuroscience
- The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral EvidenceMatthew L. Dixon, Kalina Christoff A · 2012 · PLoS ONE
- On the Fallacy of Imputing the Correlations Found for Groups to the Individuals or Smaller Groups Composing ThemEdward Lee Thorndike · 1939 · The American Journal of Psychology
- Hierarchical Bayesian inference for concurrent model fitting and comparison for group studiesPayam Piray, Amir Dezfouli, Tom Heskes, Michael J. Frank, Nathaniel D. Daw · 2019 · PLoS Computational Biology
- Beyond reward prediction errors: the role of dopamine in movement kinematicsJoseph W. Barter, Suellen Li, Dongye Lu, Ryan A. Bartholomew, Mark A. Rossi, Charles T. Shoemaker, Daniel Salas-Meza, Erin Gaidis, Henry H. Yin · 2015 · Frontiers in Integrative Neuroscience
- Learning Factored Representations in a Deep Mixture of ExpertsDavid Eigen, Marc’Aurelio Ranzato, Ilya Sutskever · 2013 · arXiv (Cornell University)
- Neural and Psychological Maturation of Decision-making in Adolescence and Young AdulthoodAnastasia Christakou, Samuel Joseph Gershman, Yael Niv, Andrew Simmons, Mick J. Brammer, Katya Rubia · 2013 · Journal of Cognitive Neuroscience
- Inhibition of return in manual and saccadic response systemsKevin A. Briand, Abigail L. Larrison, Anne B. Sereno · 2000 · Perception & Psychophysics
- Empirical Bayes Methods for Combining LikelihoodsBradley Efron · 1996 · Journal of the American Statistical Association
- Between the Devil and the Deep Blue Sea: Tensions Between Scientific Judgement and Statistical Model SelectionDanielle Navarro · 2018 · Computational Brain & Behavior
- How hierarchical models improve point estimates of model parameters at the individual levelKentaro Katahira · 2016 · Journal of Mathematical Psychology
- Reinforcement-learning in fronto-striatal circuitsBruno B. Averbeck, John P. O’Doherty · 2021 · Neuropsychopharmacology
- The computational roots of positivity and confirmation biases in reinforcement learningStefano Palminteri, Maël P. Lebreton · 2022 · Trends in Cognitive Sciences
- Episodic Memory Encoding Interferes with Reward Learning and Decreases Striatal Prediction ErrorsG. Elliott Wimmer, Erin Kendall Braun, Nathaniel D. Daw, Daphna Shohamy A · 2014 · Journal of Neuroscience
- Spontaneous alternation behavior in animals: A reviewCharles L. Richman, William N. Dember, Paul Kim · 1986 · Current Psychology
- Brain-wide representations of prior information in mouse decision-makingCharles Findling, Félix Hubert, Luigi Acerbi, Brandon Benson, Julius Benson, Daniel Birman, Niccolò Bonacchi, E. Kelly Buchanan, Sebastian A. Bruijns, Matteo Carandini et al. · 2025 · Nature
- The Relative Influences of Priors and Sensory Evidence on an Oculomotor Decision Variable During Perceptual LearningJoshua I. Gold, Chi-Tat Law, Patrick M. Connolly, Sharath Bennur · 2008 · Journal of Neurophysiology
- Scanning direction and line bisection: a study of normal subjects and unilateral neglect patients with opposite reading habitsSylvie Chokron A, Paolo Bartolomeo, Marie-Thérèse Perenin, Gérard Helft, M. Imbert · 1998 · Cognitive Brain Research
- Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural NetworksRäuker, Tilman, Ho, Anson, Casper, Stephen, Hadfield-Menell, Dylan · 2023 · 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
- Dopaminergic modulation of the exploration/exploitation trade-off in human decision-makingKarima Chakroun, David Mathar, Antonius Wiehler, Florian Ganzer, Jan Peters · 2020 · eLife
- An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervalsIigaya, Kiyohito, Fonseca, Madalena S., Murakami, Masayoshi, Mainen, Zachary F., Dayan, Peter · 2018 · Nature Communications
- Human reinforcement learning subdivides structured action spaces by learning effector-specific valuesGershman, Samuel J., Pesaran, Bijan, Daw, Nathaniel D. · 2009 · The Journal of Neuroscience
- The interpretation of computational model parameters depends on the contextMaria Katharina Eckstein, Sarah L. Master, Liyu Xia, Ronald E. Dahl, Linda Wilbrecht, Anne Gabrielle Eva Collins · 2022 · eLife
- Choice-Induced Preference Change in the Free-Choice Paradigm: A Critical Methodological ReviewKeise Izuma, Kou Murayama · 2013 · Frontiers in Psychology
- Individual differences in computational psychiatry: A review of current challengesPovilas Karvelis, Martin P. Paulus, Andreea Oliviana Diaconescu · 2023 · Neuroscience & Biobehavioral Reviews
- Theoretically Informed Generative Models Can Advance the Psychological and Brain Sciences: Lessons from the Reliability ParadoxNathaniel Haines, Peter D. Kvam, Louis H. Irving, Colin Tucker Smith, Theodore P. Beauchaine, Mark A. Pitt, Woo‐Young Ahn, Brandon M. Turner · 2020
- What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and NeuroscienceMaria Katharina Eckstein, Linda Wilbrecht, Anne Gabrielle Eva Collins · 2021 · Current Opinion in Behavioral Sciences
- Generalization of value in reinforcement learning by humansWimmer, G. Elliott, Daw, Nathaniel D., Shohamy, Daphna · 2012 · European Journal of Neuroscience
- Extracting the dynamics of behavior in sensory decision-making experimentsNicholas A. Roy, Ji Hyun Bak, Athena Akrami, Carlos D. Brody, Jonathan W. Pillow · 2021 · Neuron
- Using Bayesian hierarchical parameter estimation to assess the generalizability of cognitive models of choiceBenjamin Scheibehenne, Thorsten Pachur · 2014 · Psychonomic Bulletin & Review
- Differential, but not opponent, effects of l-DOPA and citalopram on action learning with reward and punishmentMarc Guitart‐Masip, Marcos Economides, Quentin J. M. Huys, Michael J. Frank, Rumana Chowdhury, Emrah Düzel, Peter Dayan, Raymond J. Dolan · 2013 · Psychopharmacology
- From Google Gemini to OpenAI Q* (Q-Star): A Survey on Reshaping the Generative Artificial Intelligence (AI) Research LandscapeMcIntosh, Timothy R., Susnjak, Teo, Liu, Tong, Watters, Paul, Xu, Dan, Liu, Dongwei, Halgamuge, Malka N. · 2025 · Technologies
- Are computational models of any use to psychiatry?Quentin J. M. Huys, Michael Moutoussis, Jonathan H. Williams · 2011 · Neural Networks
- Anterior Prefrontal Cortex Contributes to Action Selection through Tracking of Recent Reward TrendsChristopher K. Kovach, Nathaniel D. Daw, David Rudrauf, Daniel Tranel, John P. O’Doherty, Ralph Adolphs · 2012 · Journal of Neuroscience
- Adaptive properties of differential learning rates for positive and negative outcomesRomain D. Cazé, Matthijs A. A. van der Meer · 2013 · Biological Cybernetics
- Competitive-Cooperative-Concurrent Reinforcement Learning with Importance SamplingEiji Uchibe, Kenji Doya · 2004 · The MIT Press eBooks
- Origin of perseveration in the trade-off between reward and complexitySamuel Joseph Gershman · 2020 · Cognition
- Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical ImplicationsTakashi Nakao, Hideki Ohira, Georg Northoff · 2012 · Frontiers in Neuroscience
- Information about action outcomes differentially affects learning from self-determined versus imposed choicesValérian Chambon, Héloïse Théro, Marie Vidal, Henri Vandendriessche, Patrick Haggard, Stefano Palminteri · 2020 · Nature Human Behaviour
- A neuro-computational model of economic decisionsAldo Rustichini, Camillo Padoa‐Schioppa · 2015 · Journal of Neurophysiology
- Brain Hemispheres Selectively Track the Expected Value of Contralateral OptionsStefano Palminteri, Thomas Boraud, Gilles Lafargue, Bruno Dubois, Mathias Pessiglione · 2009 · Journal of Neuroscience
- Taming the beast: extracting generalizable knowledge from computational models of cognitionMatthew R. Nassar, Michael J. Frank · 2016 · Current Opinion in Behavioral Sciences
- MCP: Learning Composable Hierarchical Control with Multiplicative Compositional PoliciesPeng, Xue Bin, Chang, Michael, Zhang, Grace, Pieter Abbeel, Sergey Levine · 2019 · arXiv (Cornell University)
- Improving the reliability of computational analyses: Model-based planning and its relationship with compulsivityVanessa M Brown, Jia-Zhou Chen, C. Gillan, R. Price · 2020 · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
- A Brief Survey of Variables That Influence Random-GenerationG. S. Tune · 1964 · Perceptual and Motor Skills
- Dopaminergic action prediction errors serve as a value-free teaching signalFrancesca Greenstreet, Hernando Martínez Vergara, Yvonne Johansson, Sthitapranjya Pati, Laura Schwarz, Stephen C. Lenzi, Jesse P. Geerts, Matthew Wisdom, Alina Gubanova, Lars B. Rollik et al. · 2025 · Nature
- Sequential Effects in Two-Choice Reaction Time Tasks: Decomposition and Synthesis of MechanismsJuan Gao, KongFatt Wong‐Lin, Philip J. Holmes, Patrick Simen, Jonathan D. Cohen · 2009 · Neural Computation
- The statistical structures of reinforcement learning with asymmetric value updatesKentaro Katahira · 2018 · Journal of Mathematical Psychology
- Computational evidence for hierarchically structured reinforcement learning in humansMaria Katharina Eckstein, Anne Gabrielle Eva Collins · 2020 · Proceedings of the National Academy of Sciences
- The relation between reinforcement learning parameters and the influence of reinforcement history on choice behaviorKentaro Katahira · 2015 · Journal of Mathematical Psychology
- Motor cortex activity predicts response alternation during sensorimotor decisionsAnna-Antonia Pape, Markus Siegel · 2016 · Nature Communications
- Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthoodMichael Moutoussis, Edward Thomas Bullmore, Ian Michael Goodyer, Peter Fonagy, Peter Brian Jones, Raymond J. Dolan, Peter Dayan · 2018 · PLoS Computational Biology
- Dopamine role in learning and action inferenceRafał Bogacz · 2020 · eLife
- Context-dependent outcome encoding in human reinforcement learningStefano Palminteri, Maël P. Lebreton · 2021 · Current Opinion in Behavioral Sciences
- Policy compression: An information bottleneck in action selectionLucy Lai, S. Gershman · 2021 · The psychology of learning and motivation
- Actor–Critic Models of Reinforcement Learning in the Basal Ganglia: From Natural to Artificial RatsMehdi Khamassi, Loïc Lachèze, Benoît Girard, Alain Berthoz, Agnès Guillot · 2005 · Adaptive Behavior
- Not that bad after all: Generation of random sequences.Yaakov Kareev · 1992 · Journal of Experimental Psychology Human Perception & Performance
- The effects of hand preference and gender on finger tapping performance asymmetry by the use of an infra-red light measurement deviceSergio L. Schmidt, Rosinda Martins Oliveira, Thomas Eichenberg Krahe, Cláudio Carneiro Filgueiras · 2000 · Neuropsychologia
- On the ability to inhibit simple thoughts and actions: II. Stop-signal studies of repetition priming.Gordon D. Logan · 1985 · Journal of Experimental Psychology Learning Memory and Cognition
- The Outcome‐Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling TaskNathaniel Haines, Jasmin Vassileva, Woo‐Young Ahn · 2018 · Cognitive Science
- Reinforcement Learning Interpretation Methods: A SurveyAlnour Alharin, Thanh-Nam Doan, Mina Sartipi · 2020 · IEEE Access
- Dynamic computational phenotyping of human cognitionRoey Schurr, Daniel Reznik, Hanna Hillman, Rahul Bhui, Samuel Joseph Gershman · 2024 · Nature Human Behaviour
- Computational Phenotyping: Using Models to Understand Individual Differences in Personality, Development, and Mental IllnessEdward H. Patzelt, Catherine A. Hartley, Samuel Joseph Gershman · 2018 · Personality Neuroscience
- Models that learn how humans learn: The case of decision-making and its disordersAmir Dezfouli, Kristi R. Griffiths, Fabio Tozeto Ramos, Peter Dayan, Bernard W. Balleine · 2019 · PLoS Computational Biology
- Predicting human decisions with behavioural theories and machine learningOri Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart Russell, Even C Carter et al. · 2025 · Nature Human Behaviour
- Sufficient reliability of the behavioral and computational readouts of a probabilistic reversal learning taskMaria Waltmann, Florian Schlagenhauf, Lorenz Deserno · 2022 · Behavior Research Methods
- Anatomical dissociation of intracerebral signals for reward and punishment prediction errors in humansMaëlle C. M. Gueguen, Alizée Lopez‐Persem, Pablo B. Billeke, J.-P. Lachaux, Sylvain Rheims, Philippe Kahane, Lorella Minotti, Olivier David A, Mathias Pessiglione, Julien Bastin · 2021 · Nature Communications
- Why and how the brain weights contributions from a mixture of expertsJohn P. O’Doherty, Sang Wan Lee, Reza Tadayonnejad, Jeffrey Cockburn, Kyo Iigaya, Caroline J. Charpentier · 2021 · Neuroscience & Biobehavioral Reviews
- Value representations in the rodent orbitofrontal cortex drive learning, not choiceKevin J. Miller, Matthew Botvinick, Carlos D. Brody · 2022 · eLife
- Credit assignment to state-independent task representations and its relationship with model-based decision makingNitzan Shahar, Rani Moran, Tobias U. Hauser, Rogier Kievit, Daniel McNamee, Michael Moutoussis, Raymond J. Dolan, Edward Thomas Bullmore, Raymond J. Dolan, Ian Michael Goodyer et al. · 2019 · Proceedings of the National Academy of Sciences
- Discovering cognitive strategies with tiny recurrent neural networksJi-An, Li, Benna, Marcus K., Mattar, Marcelo G. · 2025 · Nature
- Automatic aftereffects in two-choice reaction time: A mathematical representation of some concepts.Eric L. L. Soetens, Michel Deboeck, Johan Hueting · 1984 · Journal of Experimental Psychology Human Perception & Performance
- Dissociation between asymmetric value updating and perseverance in human reinforcement learningMichiyo Sugawara, Kentaro Katahira · 2021 · Scientific Reports
- Using deep learning to predict human decisions and using cognitive models to explain deep learning modelsMatan Fintz, Margarita Osadchy, Uri Hertz · 2022 · Scientific Reports
- Hand path priming in manual obstacle avoidance: Rapid decay of dorsal stream informationSteven A. Jax, David Α. Rosenbaum · 2008 · Neuropsychologia
- Mice exhibit stochastic and efficient action switching during probabilistic decision makingCelia C. Beron, Shay Q. Neufeld, Scott W. Linderman, Bernardo Luis Sabatini · 2022 · Proceedings of the National Academy of Sciences
- Pavlovian Control of Escape and AvoidanceAlexander J. Millner, Samuel Joseph Gershman, Matthew K. Nock, Hanneke E.M. den Ouden · 2017 · Journal of Cognitive Neuroscience
- Between the devil and the deep blue sea: Tensions between scientific judgement and statistical model selectionDanielle Navarro · 2018
- Automatic aftereffects in two-choice reaction time: A mathematical representation of some concepts.Eric L. L. Soetens, Michel Deboeck, Johan Hueting · 1984 · Journal of Experimental Psychology Human Perception & Performance
- Tonic exploration governs both flexibility and lapsesR. Becket Ebitz, Brianna J. Sleezer, Hank Peter Jedema, Charles W. Bradberry, Benjamin Y. Hayden · 2019 · PLoS Computational Biology
- A Normative Account of Confirmation Bias During Reinforcement LearningGermain Lefebvre, Christopher Summerfield, Rafał Bogacz · 2021 · Neural Computation
- Movement-Specific Repetition Suppression in Ventral and Dorsal Premotor Cortex during Action ObservationJasminka Majdandžić, Harold Bekkering A, Hein Thomas van Schie, Ivan Toni · 2009 · Cerebral Cortex
- A modular neural-network model of the basal ganglia’s role in learning and selecting motor behavioursGianluca Baldassarre · 2002 · Cognitive Systems Research
- Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to MotivationAyaka Kato, Kenji Morita · 2016 · PLoS Computational Biology
- Joint modeling of reaction times and choice improves parameter identifiability in reinforcement learning modelsIan C. Ballard, Samuel M. McClure · 2019 · Journal of Neuroscience Methods
- Metacontrol for Adaptive Imagination-Based OptimizationJessica B. Hamrick, Andrew J. Ballard, Razvan Pascanu, Oriol Vinyals, Nicolas Heess, Peter Battaglia · 2017 · arXiv (Cornell University)
- Opposite effects of choice history and evidence history resolve a paradox of sequential choice biasElla Bosch, Matthias Fritsche, Benedikt Ehinger, Floris P. de Lange · 2020 · Journal of Vision
- Repetition suppression for performed hand gestures revealed by fMRIAntonia F. de C. Hamilton, Scott T. Grafton · 2008 · Human Brain Mapping
- The Convergence of TD(λ) for General λPeter Dayan · 1992 · Machine Learning
- Separating response‐execution bias from decision bias: Arguments for an additional parameter in Ratcliff's diffusion modelAndreas Voß, Jochen Voß, Karl Christoph Klauer · 2009 · British Journal of Mathematical and Statistical Psychology
- Striatal dopamine ramping may indicate flexible reinforcement learning with forgetting in the cortico-basal ganglia circuitsKenji Morita, Ayaka Kato · 2014 · Frontiers in Neural Circuits
- Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor modelsJames John Bonaiuto, Archy O. de Berker, Sven Bestmann · 2016 · eLife
- Not that bad after all: Generation of random sequences.Yaakov Kareev · 1992 · Journal of Experimental Psychology Human Perception & Performance
- The role of response bias in perceptual learning.Pete R. Jones, David Richard Moore, Daniel E. Shub · 2015 · Journal of Experimental Psychology Learning Memory and Cognition
- Perseveration. Part I: A reviewGillian Hotz, Nancy Helm‐Estabrooks · 1995 · Brain Injury
- Process dynamics in delay discounting decisions: An attractor dynamics approachStefan Scherbaum, Simon Frisch, Susanne Leiberg, Steven J. Lade, Thomas Goschke, Maja Dshemuchadse · 2016 · Judgment and Decision Making
- Frequency of Perseveration in Normal SubjectsAmy E. Ramage, Kathryn A. Bayles, Nancy Helm‐Estabrooks · 1999 · Brain and Language
- Inhibition of Return Arises from Inhibition of Response Processes: An Analysis of Oscillatory Beta ActivityBernhard Pastötter, Simon Hanslmayr, Karl‐Heinz T. Bäuml · 2007 · Journal of Cognitive Neuroscience
- Reliability of Decision-Making and Reinforcement Learning Computational ParametersAnahit Mkrtchian, Vincent Valton, Jonathan Paul Roiser · 2023 · Computational Psychiatry
- Test–retest reliability of reinforcement learning parametersJessica Vera Schaaf, Laura Weidinger, Lucas Molleman, Wouter van den Bos · 2023 · Behavior Research Methods
- Mixtures of strategies underlie rodent behavior during reversal learningNhat Minh Le, Murat Yıldırım, Yizhi Wang, 弘記 杉原, Mehrdad Jazayeri, Mriganka Sur · 2023 · PLoS Computational Biology
- A Healthy Fear of the Unknown: Perspectives on the Interpretation of Parameter Fits from Computational Models in NeuroscienceMatthew R. Nassar, Joshua I. Gold · 2013 · PLoS Computational Biology
- How the Level of Reward Awareness Changes the Computational and Electrophysiological Signatures of Reinforcement LearningCamile Maria Costa Corrêa, Samuel Noorman, Jun Jiang, Stefano Palminteri, Michael X Cohen, Maël P. Lebreton, Simon van Gaal · 2018 · Journal of Neuroscience
- Choice-confirmation bias and gradual perseveration in human reinforcement learning.Stefano Palminteri · 2022 · Behavioral Neuroscience
- Neural signatures of arbitration between Pavlovian and instrumental action selectionSamuel Joseph Gershman, Marc Guitart‐Masip, James F. Cavanagh · 2021 · PLoS Computational Biology
- The Dorsomedial Striatum Reflects Response Bias during LearningEyal Yaacov Kimchi, Mark Laubach · 2009 · Journal of Neuroscience
- The relative merit of empirical priors in non-identifiable and sloppy models: Applications to models of learning and decision-makingMikhail S. Spektor, David Kellen · 2018 · Psychonomic Bulletin & Review
- A neural network walks into a lab: towards using deep nets as models for human behaviorWei Ji Ma, Benjamin Peters · 2020 · arXiv (Cornell University)
- A Proof of the Law of EffectEdward Lee Thorndike · 1933 · Science
- The limits and potentials of deep learning for roboticsSünderhauf, Niko, Brock, Oliver, Scheirer, Walter, Hadsell, Raia, Fox, Dieter, Leitner, Jürgen, Upcroft, Ben, Abbeel, Pieter, Burgard, Wolfram, Milford, Michael et al. · 2018 · The International Journal of Robotics Research
- Dopaminergic Balance between Reward Maximization and Policy ComplexityNaama Parush, Naftali Tishby, Hagai Bergman · 2011 · Frontiers in Systems Neuroscience
- Enhancing the psychometric properties of the Iowa gambling task using full generative modelingSullivan-Toole, Holly, Haines, Nathaniel, Dale, Kristina, Olino, Thomas M. · 2022 · Computational Psychiatry
- Linking confidence biases to reinforcement-learning processes.Nahuel Salem-Garcia, Stefano Palminteri, Maël P. Lebreton · 2023 · Psychological Review
- How Predictable are “Spontaneous Decisions” and “Hidden Intentions”? Comparing Classification Results Based on Previous Responses with Multivariate Pattern Analysis of fMRI BOLD SignalsMartin Lages, Katarzyna Jaworska · 2012 · Frontiers in Psychology
- Cost-benefit trade-offs in decision-making and learningNura Sidarus, Stefano Palminteri, V. Chambon · 2019 · PLoS Comput. Biol.
- Combined model-free and model-sensitive reinforcement learning in non-human primatesBruno Miranda, W. M. Nishantha Malalasekera, Timothy E.J. Behrens, Peter Dayan, Steven Wayne Kennerley · 2020 · PLoS Computational Biology
- Dopamine release in human associative striatum during reversal learningFilip Grill, Marc Guitart‐Masip, Jarkko J. Johansson, Lars Stiernman Jonasson, Jan Axelsson, Lars H Nyberg, Anna Rieckmann · 2024 · Nature Communications
- Empirical Bayes Methods for Combining LikelihoodsBradley Efron · 1996 · Journal of the American Statistical Association
- Decision Making, Affect, and LearningMauricio R. Delgado, Elizabeth A. Phelps, Trevor William Robbins · 2011 · Oxford University Press eBooks
- Stimulus similarity determines the prevalence of behavioral laterality in a visual discrimination task for miceMario Treviño · 2014 · Scientific Reports
- From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health ResearchNathaniel Haines, Holly Sullivan‐Toole, Thomas M. Olino · 2023 · Biological Psychiatry Cognitive Neuroscience and Neuroimaging
- Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRIJaron T. Colas, Wolfgang M. Pauli, Tobias Larsen, J. Michael Tyszka, John P. O’Doherty · 2017 · PLoS Computational Biology
- A Survey of Explainable Reinforcement LearningMilani, Stephanie, Topin, Nicholay, Veloso, Manuela, Fang, Fei · 2022 · arXiv
- Biases in estimating the balance between model-free and model-based learning systems due to model misspecificationAsako Toyama, Kentaro Katahira, Hideki Ohira · 2019 · Journal of Mathematical Psychology
- Troubleshooting Bayesian cognitive models.Beth Baribault, Anne Gabrielle Eva Collins · 2023 · Psychological Methods
- Post-response βγ power predicts the degree of choice-based learning in internally guided decision-makingTakashi Nakao, Noriaki Kanayama, Kentaro Katahira, Misaki Odani, Yosuke Ito, Yuki Hirata, Reika Nasuno, 尾崎 繁, Ryosuke Hiramoto, Makoto Miyatani et al. · 2016 · Scientific Reports
- Multi-Task Reinforcement Learning With Attention-Based Mixture of ExpertsGuangran Cheng, Lu Dong, Wenzhe Cai, Changyin Sun · 2023 · IEEE Robotics and Automation Letters
- Repetition effects in grasping.Peter Dixon, Scott McAnsh, Lenore E. Read · 2011 · Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale
- Cognitive Model Discovery via Disentangled RNNsKevin J. Miller, Maria Katharina Eckstein, Matthew Botvinick · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
- The DalHouses: 100 new photographs of houses with ratings of typicality, familiarity, and degree of similarity to facesJillian Filliter, Jacqueline M. Glover, Patricia A. McMullen · 2015 · Behavior Research Methods
- Now and then: Hand choice is influenced by recent action historyKenneth F. Valyear, Aoife M. Fitzpatrick, Neil M. Dundon · 2018 · Psychonomic Bulletin & Review
- MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learningMarko Vasić, Andrija Petrović, Kaiyuan Wang, Mladen Nikolić, Rishabh Singh, Sarfraz Khurshid D · 2022 · Neural Networks
- Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent StickinessMatthew Balcarras, Salva Ardid, Daniel Kaping, Stefan Everling, Thilo Womelsdorf · 2015 · Journal of Cognitive Neuroscience
- Sequential response bias in randomized response sequences: A computer simulationSjoerd Wiegersma · 1982 · Acta Psychologica
- Discovering Cognitive Strategies with Tiny Recurrent Neural NetworksJian Li, Marcus K. Benna, Marcelo Gomes Mattar · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
- From predictive models to cognitive models: Separable behavioral processes underlying reward learning in the ratKevin J. Miller, Matthew Botvinick, Carlos D. Brody · 2018 · bioRxiv (Cold Spring Harbor Laboratory)
- A simple computational algorithm of model-based choice preferenceAsako Toyama, Kentaro Katahira, Hideki Ohira · 2017 · Cognitive Affective & Behavioral Neuroscience
- Model-based estimation of subjective values using choice tasks with probabilistic feedbackKentaro Katahira, Shoko Yuki, Kazuo Okanoya · 2017 · Journal of Mathematical Psychology
- Reinforcement Learning With Parsimonious Computation and a Forgetting ProcessAsako Toyama, Kentaro Katahira, Hideki Ohira · 2019 · Frontiers in Human Neuroscience
- Adaptive Choice Biases in Mice and HumansMario Treviño, Ricardo Medina‐Coss y León, Belén Haro · 2020 · Frontiers in Behavioral Neuroscience
- Confirmation bias optimizes reward learningTor Tarantola, Tomas Folke, Annika Boldt, Omar David Perez, Benedetto De Martino · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
- Neural and computational underpinnings of biased confidence in human reinforcement learningChih-Chung Ting, Nahuel Salem-Garcia, Stefano Palminteri, Jan Benjamin Engelmann, Maël P. Lebreton · 2023 · Nature Communications
- Adaptive optimal training of animal behaviorJi Hyun Bak, Jung Yoon Choi, Athena Akrami · 2017 · Bulletin of the American Physical Society
- Artificial neural networks for model identification and parameter estimation in computational cognitive modelsMilena Rmus, Ti-Fen Pan, Liyu Xia, Anne Gabrielle Eva Collins · 2024 · PLoS Computational Biology
- Efficient inference for time-varying behavior during learning.Nicholas A Roy, Ji Hyun Bak, Athena Akrami · 2018 · PubMed
- Temporal chunking as a mechanism for unsupervised learning of task-setsFlora Bouchacourt, Stefano Palminteri, Étienne Koechlin, Srdjan Ostojic · 2020 · eLife
- Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy EnsembleZhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li · 2022 · International Joint Conference on Artificial Intelligence
- Tracking subjects’ strategies in behavioural choice experiments at trial resolutionSilvia Maggi, Rebecca M Hock, Martin J. O’Neill, Mark J. Buckley, Paula M. Moran, Tobias Bast, Musa Basseer Sami, Mark D. Humphries · 2024 · eLife
- Value-based decision making via sequential sampling with hierarchical competition and attentional modulationJaron T. Colas · 2017 · PLoS ONE
- Decision-making in brains and robots — the case for an interdisciplinary approachSang Wan Lee, Ben Seymour · 2019 · Current Opinion in Behavioral Sciences
- Continuous Action Reinforcement Learning From a Mixture of Interpretable ExpertsRiad Akrour, Davide Tateo, Jan Peters · 2021 · IEEE Transactions on Pattern Analysis and Machine Intelligence
- Hierarchical Bayesian models of reinforcement learning: Introduction and comparison to alternative methodsCamilla van Geen, Raphael T. Gerraty · 2021 · Journal of Mathematical Psychology
- Using deep neural networks as a guide for modeling human planningIonatan Kuperwajs, Heiko H. Schütt, Wei Ji Ma · 2023 · Scientific Reports
- Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behaviorYoav Ger, Eliya Nachmani, Lior Wolf, Nitzan Shahar · 2024 · PLoS Computational Biology
- Cognitive Choice ModelingZheng Joyce Wang, Jerome R. Busemeyer · 2021 · The MIT Press eBooks
- Predictive and Interpretable: Combining Artificial Neural Networks and Classic Cognitive Models to Understand Human Learning and Decision MakingEckstein, Maria K., Summerfield, Christopher, Daw, Nathaniel D., Miller, Kevin J. · 2023
- Examinations of Biases by Model Misspecification and Parameter Reliability of Reinforcement Learning ModelsAsako Toyama, Kentaro Katahira, Yoshihiko Kunisato · 2023 · Computational Brain & Behavior
- Undermatching Is a Consequence of Policy CompressionBilal A. Bari, Samuel Joseph Gershman · 2022 · Journal of Neuroscience
- Isomorphic decisional biases across perceptual tasksMario Treviño, Santiago Castiello, Óscar Arias-Carrión, Braniff de la Torre-Valdovinos, Ricardo Leon · 2021 · PLoS ONE
- Revisiting the importance of model fitting for model-based fMRI: It does matter in computational psychiatryKentaro Katahira, Asako Toyama · 2021 · PLoS Computational Biology
- Force tuning explains changes in phasic dopamine signaling during stimulus-reward learningKonstantin I. Bakhurin, Ryan N. Hughes, Qiaochu Jiang, M Afzal Hossain, Boris S Gutkin, Isabella P. Fallon, Henry H. Yin · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
- Comparing the test-retest reliability of behavioral, computational and self-reported individual measures of reward and punishment sensitivity in relation to mental health symptomsStefano Vrizzi, Anis Najar, Cédric Lemogne · 2023
- Undesirable Choice Biases with Small Differences in the Spatial Structure of Chance Stimulus SequencesDavid Herrera, Mario Treviño · 2015 · PLoS ONE
- Choice perseveration in value-based decision making: The impact of inter-trial interval and moodUlrike Senftleben, Martin Schoemann, Diana Schwenke, Sarah Richter, Maja Dshemuchadse, Stefan Scherbaum · 2019 · Acta Psychologica
- To stay or not to stay: The stability of choice perseveration in value-based decision makingUlrike Senftleben, Martin Schoemann, Matthias Rudolf, Stefan Scherbaum · 2020 · Quarterly Journal of Experimental Psychology