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Matthew M. Botvinick

Affiliations: 
Princeton University, Princeton, NJ 
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"Matthew Botvinick"
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Parents

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Jonathan D. Cohen grad student 1994-2001 Carnegie Mellon
 (The regulation of control: Two computational studies.)
David C. Plaut grad student 1999-2001 Carnegie Mellon

Children

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Zev B. Rosen research assistant 2005-2007 Penn
Christopher R. Thompson research assistant 2008-2009 Princeton
Debbie M. Yee research assistant 2011-2013 Princeton
Jonathan Berliner grad student Princeton
Jin Hyun Cheong grad student
Joe McGuire grad student Princeton
Kevin J. Miller grad student Princeton
Joseph T. McGuire grad student 2011 Princeton
José J F Ribas-Fernandes grad student 2008-2012 Princeton
Anna C. Schapiro grad student 2009-2014 Princeton
Alec Solway grad student 2009-2014 Princeton
Wouter Kool grad student 2008-2015 Princeton
Pavlos Kollias grad student 2012-2015 Princeton
Kachina Allen post-doc Princeton
Francisco Pereira post-doc Princeton
Carlos G. Diuk Wasser post-doc 2009- Princeton
Amitai Shenhav post-doc 2012- Princeton
Ida Momennejad post-doc 2013- Princeton

Collaborators

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Laurel J. Buxbaum collaborator 2005-2010 Moss Rehabilitation Research Institute
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Publications

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Moskovitz T, Miller KJ, Sahani M, et al. (2024) Understanding dual process cognition via the minimum description length principle. Plos Computational Biology. 20: e1012383
Miller KJ, Botvinick MM, Brody CD. (2022) Value representations in the rodent orbitofrontal cortex drive learning, not choice. Elife. 11
Langdon A, Botvinick M, Nakahara H, et al. (2022) Meta-learning, social cognition and consciousness in brains and machines. Neural Networks : the Official Journal of the International Neural Network Society. 145: 80-89
Botvinick M, An J. (2021) Goal-directed decision making in prefrontal cortex: A computational framework. Advances in Neural Information Processing Systems. 21: 169-176
Botvinick M, Wang JX, Dabney W, et al. (2020) Deep Reinforcement Learning and Its Neuroscientific Implications. Neuron
Dabney W, Kurth-Nelson Z, Uchida N, et al. (2020) A distributional code for value in dopamine-based reinforcement learning. Nature. 577: 671-675
Merel J, Botvinick M, Wayne G. (2019) Hierarchical motor control in mammals and machines. Nature Communications. 10: 5489
Santoro A, Hill F, Barrett D, et al. (2019) Is coding a relevant metaphor for building AI? The Behavioral and Brain Sciences. 42: e240
Smith EH, Horga G, Yates MJ, et al. (2019) Widespread temporal coding of cognitive control in the human prefrontal cortex. Nature Neuroscience
Botvinick M, Ritter S, Wang JX, et al. (2019) Reinforcement Learning, Fast and Slow. Trends in Cognitive Sciences
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