A citation-based method for searching scientific literature


List of co-cited articles
1106 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


A neural substrate of prediction and reward.
W Schultz, P Dayan, P R Montague. Science 1997
28

Model-based influences on humans' choices and striatal prediction errors.
Nathaniel D Daw, Samuel J Gershman, Ben Seymour, Peter Dayan, Raymond J Dolan. Neuron 2011
741
28


Learning the value of information in an uncertain world.
Timothy E J Behrens, Mark W Woolrich, Mark E Walton, Matthew F S Rushworth. Nat Neurosci 2007
984
22

Working memory contributions to reinforcement learning impairments in schizophrenia.
Anne G E Collins, Jaime K Brown, James M Gold, James A Waltz, Michael J Frank. J Neurosci 2014
95
22

By carrot or by stick: cognitive reinforcement learning in parkinsonism.
Michael J Frank, Lauren C Seeberger, Randall C O'reilly. Science 2004
20

Working Memory Load Strengthens Reward Prediction Errors.
Anne G E Collins, Brittany Ciullo, Michael J Frank, David Badre. J Neurosci 2017
37
51



Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning.
Michael J Frank, Ahmed A Moustafa, Heather M Haughey, Tim Curran, Kent E Hutchison. Proc Natl Acad Sci U S A 2007
408
14

Working-memory capacity protects model-based learning from stress.
A Ross Otto, Candace M Raio, Alice Chiang, Elizabeth A Phelps, Nathaniel D Daw. Proc Natl Acad Sci U S A 2013
227
14

Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans.
Mathias Pessiglione, Ben Seymour, Guillaume Flandin, Raymond J Dolan, Chris D Frith. Nature 2006
881
14


Reinforcement learning in multidimensional environments relies on attention mechanisms.
Yael Niv, Reka Daniel, Andra Geana, Samuel J Gershman, Yuan Chang Leong, Angela Radulescu, Robert C Wilson. J Neurosci 2015
138
14

Cortical substrates for exploratory decisions in humans.
Nathaniel D Daw, John P O'Doherty, Peter Dayan, Ben Seymour, Raymond J Dolan. Nature 2006
14

Interactions Among Working Memory, Reinforcement Learning, and Effort in Value-Based Choice: A New Paradigm and Selective Deficits in Schizophrenia.
Anne G E Collins, Matthew A Albrecht, James A Waltz, James M Gold, Michael J Frank. Biol Psychiatry 2017
42
33





An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment.
Matthew R Nassar, Robert C Wilson, Benjamin Heasly, Joshua I Gold. J Neurosci 2010
222
12

Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments.
Yuan Chang Leong, Angela Radulescu, Reka Daniel, Vivian DeWoskin, Yael Niv. Neuron 2017
107
12

Computational psychiatry as a bridge from neuroscience to clinical applications.
Quentin J M Huys, Tiago V Maia, Michael J Frank. Nat Neurosci 2016
333
12

Reinstated episodic context guides sampling-based decisions for reward.
Aaron M Bornstein, Kenneth A Norman. Nat Neurosci 2017
66
18


Interactive memory systems in the human brain.
R A Poldrack, J Clark, E J Paré-Blagoev, D Shohamy, J Creso Moyano, C Myers, M A Gluck. Nature 2001
684
10

Model-based choices involve prospective neural activity.
Bradley B Doll, Katherine D Duncan, Dylan A Simon, Daphna Shohamy, Nathaniel D Daw. Nat Neurosci 2015
129
10


Reminders of past choices bias decisions for reward in humans.
Aaron M Bornstein, Mel W Khaw, Daphna Shohamy, Nathaniel D Daw. Nat Commun 2017
80
12


The Importance of Falsification in Computational Cognitive Modeling.
Stefano Palminteri, Valentin Wyart, Etienne Koechlin. Trends Cogn Sci 2017
128
10

Orbitofrontal cortex as a cognitive map of task space.
Robert C Wilson, Yuji K Takahashi, G Schoenbaum, Yael Niv. Neuron 2014
399
10

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.
Nicolas W Schuck, Ming Bo Cai, Robert C Wilson, Yael Niv. Neuron 2016
192
10


Prefrontal cortex as a meta-reinforcement learning system.
Jane X Wang, Zeb Kurth-Nelson, Dharshan Kumaran, Dhruva Tirumala, Hubert Soyer, Joel Z Leibo, Demis Hassabis, Matthew Botvinick. Nat Neurosci 2018
129
10

The curse of planning: dissecting multiple reinforcement-learning systems by taxing the central executive.
A Ross Otto, Samuel J Gershman, Arthur B Markman, Nathaniel D Daw. Psychol Sci 2013
163
9

Episodic memory encoding interferes with reward learning and decreases striatal prediction errors.
G Elliott Wimmer, Erin Kendall Braun, Nathaniel D Daw, Daphna Shohamy. J Neurosci 2014
63
14

Characterizing a psychiatric symptom dimension related to deficits in goal-directed control.
Claire M Gillan, Michal Kosinski, Robert Whelan, Elizabeth A Phelps, Nathaniel D Daw. Elife 2016
201
9

Goals and habits in the brain.
Ray J Dolan, Peter Dayan. Neuron 2013
432
9

The ubiquity of model-based reinforcement learning.
Bradley B Doll, Dylan A Simon, Nathaniel D Daw. Curr Opin Neurobiol 2012
165
9


Dissociable roles of ventral and dorsal striatum in instrumental conditioning.
John O'Doherty, Peter Dayan, Johannes Schultz, Ralf Deichmann, Karl Friston, Raymond J Dolan. Science 2004
9

Humans use directed and random exploration to solve the explore-exploit dilemma.
Robert C Wilson, Andra Geana, John M White, Elliot A Ludvig, Jonathan D Cohen. J Exp Psychol Gen 2014
139
9

Inferring relevance in a changing world.
Robert C Wilson, Yael Niv. Front Hum Neurosci 2012
75
12


Feature-based learning improves adaptability without compromising precision.
Shiva Farashahi, Katherine Rowe, Zohra Aslami, Daeyeol Lee, Alireza Soltani. Nat Commun 2017
34
26


Human-level control through deep reinforcement learning.
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski,[...]. Nature 2015
959
8

Neural computations underlying arbitration between model-based and model-free learning.
Sang Wan Lee, Shinsuke Shimojo, John P O'Doherty. Neuron 2014
256
8

Computational psychiatry.
P Read Montague, Raymond J Dolan, Karl J Friston, Peter Dayan. Trends Cogn Sci 2012
374
8


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.