Literature DB >> 31056386

Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures.

Samuel D McDougle1, Peter A Butcher2, Darius E Parvin3, Fasial Mushtaq4, Yael Niv5, Richard B Ivry6, Jordan A Taylor5.   

Abstract

Decisions must be implemented through actions, and actions are prone to error. As such, when an expected outcome is not obtained, an individual should be sensitive to not only whether the choice itself was suboptimal but also whether the action required to indicate that choice was executed successfully. The intelligent assignment of credit to action execution versus action selection has clear ecological utility for the learner. To explore this, we used a modified version of a classic reinforcement learning task in which feedback indicated whether negative prediction errors were, or were not, associated with execution errors. Using fMRI, we asked if prediction error computations in the human striatum, a key substrate in reinforcement learning and decision making, are modulated when a failure in action execution results in the negative outcome. Participants were more tolerant of non-rewarded outcomes when these resulted from execution errors versus when execution was successful, but reward was withheld. Consistent with this behavior, a model-driven analysis of neural activity revealed an attenuation of the signal associated with negative reward prediction errors in the striatum following execution failures. These results converge with other lines of evidence suggesting that prediction errors in the mesostriatal dopamine system integrate high-level information during the evaluation of instantaneous reward outcomes.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  decision making; error; reaching; reinforcement learning; striatum

Mesh:

Year:  2019        PMID: 31056386      PMCID: PMC6535105          DOI: 10.1016/j.cub.2019.04.011

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  33 in total

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2.  Action selection and action value in frontal-striatal circuits.

Authors:  Moonsang Seo; Eunjeong Lee; Bruno B Averbeck
Journal:  Neuron       Date:  2012-06-07       Impact factor: 17.173

3.  Credit Assignment in a Motor Decision Making Task Is Influenced by Agency and Not Sensory Prediction Errors.

Authors:  Darius E Parvin; Samuel D McDougle; Jordan A Taylor; Richard B Ivry
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4.  Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI.

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5.  Cortical substrates for exploratory decisions in humans.

Authors:  Nathaniel D Daw; John P O'Doherty; Peter Dayan; Ben Seymour; Raymond J Dolan
Journal:  Nature       Date:  2006-06-15       Impact factor: 49.962

6.  A neural signature of hierarchical reinforcement learning.

Authors:  José J F Ribas-Fernandes; Alec Solway; Carlos Diuk; Joseph T McGuire; Andrew G Barto; Yael Niv; Matthew M Botvinick
Journal:  Neuron       Date:  2011-07-28       Impact factor: 17.173

7.  Working Memory Load Strengthens Reward Prediction Errors.

Authors:  Anne G E Collins; Brittany Ciullo; Michael J Frank; David Badre
Journal:  J Neurosci       Date:  2017-03-20       Impact factor: 6.167

8.  Changes in performance monitoring during sensorimotor adaptation.

Authors:  Joaquin A Anguera; Rachael D Seidler; William J Gehring
Journal:  J Neurophysiol       Date:  2009-07-15       Impact factor: 2.714

9.  Reminders of past choices bias decisions for reward in humans.

Authors:  Aaron M Bornstein; Mel W Khaw; Daphna Shohamy; Nathaniel D Daw
Journal:  Nat Commun       Date:  2017-06-27       Impact factor: 14.919

10.  A mixture of delta-rules approximation to bayesian inference in change-point problems.

Authors:  Robert C Wilson; Matthew R Nassar; Joshua I Gold
Journal:  PLoS Comput Biol       Date:  2013-07-25       Impact factor: 4.475

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  7 in total

1.  Response-based outcome predictions and confidence regulate feedback processing and learning.

Authors:  Romy Frömer; Matthew R Nassar; Rasmus Bruckner; Birgit Stürmer; Werner Sommer; Nick Yeung
Journal:  Elife       Date:  2021-04-30       Impact factor: 8.140

2.  The Role of Executive Function in Shaping Reinforcement Learning.

Authors:  Milena Rmus; Samuel D McDougle; Anne G E Collins
Journal:  Curr Opin Behav Sci       Date:  2020-11-14

Review 3.  Harnessing behavioral diversity to understand neural computations for cognition.

Authors:  Simon Musall; Anne E Urai; David Sussillo; Anne K Churchland
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4.  Distinct Neural Signatures of Outcome Monitoring After Selection and Execution Errors.

Authors:  Faisal Mushtaq; Samuel D McDougle; Matt P Craddock; Darius E Parvin; Jack Brookes; Alexandre Schaefer; Mark Mon-Williams; Jordan A Taylor; Richard B Ivry
Journal:  J Cogn Neurosci       Date:  2022-03-31       Impact factor: 3.225

5.  Motor Plans under Uncertainty Reflect a Trade-Off between Maximizing Reward and Success.

Authors:  Aaron L Wong; Audrey L Green; Mitchell W Isaacs
Journal:  eNeuro       Date:  2022-04-12

Review 6.  Dopamine, Updated: Reward Prediction Error and Beyond.

Authors:  Talia N Lerner; Ashley L Holloway; Jillian L Seiler
Journal:  Curr Opin Neurobiol       Date:  2020-11-14       Impact factor: 6.627

7.  Executive Function Assigns Value to Novel Goal-Congruent Outcomes.

Authors:  Samuel D McDougle; Ian C Ballard; Beth Baribault; Sonia J Bishop; Anne G E Collins
Journal:  Cereb Cortex       Date:  2021-11-23       Impact factor: 4.861

  7 in total

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