Literature DB >> 27408906

Reinforcement learning with Marr.

Yael Niv1, Angela Langdon1.   

Abstract

To many, the poster child for David Marr's famous three levels of scientific inquiry is reinforcement learning-a computational theory of reward optimization, which readily prescribes algorithmic solutions that evidence striking resemblance to signals found in the brain, suggesting a straightforward neural implementation. Here we review questions that remain open at each level of analysis, concluding that the path forward to their resolution calls for inspiration across levels, rather than a focus on mutual constraints.

Entities:  

Year:  2016        PMID: 27408906      PMCID: PMC4939081          DOI: 10.1016/j.cobeha.2016.04.005

Source DB:  PubMed          Journal:  Curr Opin Behav Sci        ISSN: 2352-1546


  76 in total

Review 1.  The basal ganglia: a vertebrate solution to the selection problem?

Authors:  P Redgrave; T J Prescott; K Gurney
Journal:  Neuroscience       Date:  1999       Impact factor: 3.590

2.  A spiking neural network model of an actor-critic learning agent.

Authors:  Wiebke Potjans; Abigail Morrison; Markus Diesmann
Journal:  Neural Comput       Date:  2009-02       Impact factor: 2.026

3.  The wick in the candle of learning: epistemic curiosity activates reward circuitry and enhances memory.

Authors:  Min Jeong Kang; Ming Hsu; Ian M Krajbich; George Loewenstein; Samuel M McClure; Joseph Tao-yi Wang; Colin F Camerer
Journal:  Psychol Sci       Date:  2009-07-08

Review 4.  A neural substrate of prediction and reward.

Authors:  W Schultz; P Dayan; P R Montague
Journal:  Science       Date:  1997-03-14       Impact factor: 47.728

5.  Working memory contributions to reinforcement learning impairments in schizophrenia.

Authors:  Anne G E Collins; Jaime K Brown; James M Gold; James A Waltz; Michael J Frank
Journal:  J Neurosci       Date:  2014-10-08       Impact factor: 6.167

Review 6.  The root of all value: a neural common currency for choice.

Authors:  Dino J Levy; Paul W Glimcher
Journal:  Curr Opin Neurobiol       Date:  2012-07-03       Impact factor: 6.627

7.  Opponent actor learning (OpAL): modeling interactive effects of striatal dopamine on reinforcement learning and choice incentive.

Authors:  Anne G E Collins; Michael J Frank
Journal:  Psychol Rev       Date:  2014-07       Impact factor: 8.934

8.  Short-latency activation of striatal spiny neurons via subcortical visual pathways.

Authors:  Jan M Schulz; Peter Redgrave; Carsten Mehring; Ad Aertsen; Koreen M Clements; Jeff R Wickens; John N J Reynolds
Journal:  J Neurosci       Date:  2009-05-13       Impact factor: 6.167

9.  Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value.

Authors:  Lung-Hao Tai; A Moses Lee; Nora Benavidez; Antonello Bonci; Linda Wilbrecht
Journal:  Nat Neurosci       Date:  2012-08-19       Impact factor: 24.884

10.  Striatal dynamics explain duration judgments.

Authors:  Thiago S Gouvêa; Tiago Monteiro; Asma Motiwala; Sofia Soares; Christian Machens; Joseph J Paton
Journal:  Elife       Date:  2015-12-07       Impact factor: 8.140

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  14 in total

Review 1.  Learning task-state representations.

Authors:  Yael Niv
Journal:  Nat Neurosci       Date:  2019-09-24       Impact factor: 24.884

Review 2.  Advances in modeling learning and decision-making in neuroscience.

Authors:  Anne G E Collins; Amitai Shenhav
Journal:  Neuropsychopharmacology       Date:  2021-08-27       Impact factor: 7.853

3.  Efficient coding of cognitive variables underlies dopamine response and choice behavior.

Authors:  Joseph J Paton; Christian K Machens; Asma Motiwala; Sofia Soares; Bassam V Atallah
Journal:  Nat Neurosci       Date:  2022-06-06       Impact factor: 28.771

Review 4.  Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges.

Authors:  Jeffrey B Dennison; Daniel Sazhin; David V Smith
Journal:  Wiley Interdiscip Rev Cogn Sci       Date:  2022-02-08

5.  Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments.

Authors:  Logan Cross; Jeff Cockburn; Yisong Yue; John P O'Doherty
Journal:  Neuron       Date:  2020-12-15       Impact factor: 17.173

6.  Learning from other minds: An optimistic critique of reinforcement learning models of social learning.

Authors:  Natalia Vélez; Hyowon Gweon
Journal:  Curr Opin Behav Sci       Date:  2021-03-23

7.  Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making.

Authors:  He A Xu; Alireza Modirshanechi; Marco P Lehmann; Wulfram Gerstner; Michael H Herzog
Journal:  PLoS Comput Biol       Date:  2021-06-03       Impact factor: 4.475

8.  Temporal and state abstractions for efficient learning, transfer, and composition in humans.

Authors:  Liyu Xia; Anne G E Collins
Journal:  Psychol Rev       Date:  2021-05-20       Impact factor: 8.247

Review 9.  [Negative valence systems in the system of research domain criteria : Empirical results and new developments].

Authors:  Christoph W Korn; Robert C Wolf
Journal:  Nervenarzt       Date:  2021-08-05       Impact factor: 1.214

Review 10.  Is There a 'Social' Brain? Implementations and Algorithms.

Authors:  Patricia L Lockwood; Matthew A J Apps; Steve W C Chang
Journal:  Trends Cogn Sci       Date:  2020-07-28       Impact factor: 20.229

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