Literature DB >> 24431428

Phasic dopamine release in the rat nucleus accumbens symmetrically encodes a reward prediction error term.

Andrew S Hart1, Robb B Rutledge, Paul W Glimcher, Paul E M Phillips.   

Abstract

Making predictions about the rewards associated with environmental stimuli and updating those predictions through feedback is an essential aspect of adaptive behavior. Theorists have argued that dopamine encodes a reward prediction error (RPE) signal that is used in such a reinforcement learning process. Recent work with fMRI has demonstrated that the BOLD signal in dopaminergic target areas meets both necessary and sufficient conditions of an axiomatic model of the RPE hypothesis. However, there has been no direct evidence that dopamine release itself also meets necessary and sufficient criteria for encoding an RPE signal. Further, the fact that dopamine neurons have low tonic firing rates that yield a limited dynamic range for encoding negative RPEs has led to significant debate about whether positive and negative prediction errors are encoded on a similar scale. To address both of these issues, we used fast-scan cyclic voltammetry to measure reward-evoked dopamine release at carbon fiber electrodes chronically implanted in the nucleus accumbens core of rats trained on a probabilistic decision-making task. We demonstrate that dopamine concentrations transmit a bidirectional RPE signal with symmetrical encoding of positive and negative RPEs. Our findings strengthen the case that changes in dopamine concentration alone are sufficient to encode the full range of RPEs necessary for reinforcement learning.

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Year:  2014        PMID: 24431428      PMCID: PMC3891951          DOI: 10.1523/JNEUROSCI.2489-13.2014

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  25 in total

1.  Testing the reward prediction error hypothesis with an axiomatic model.

Authors:  Robb B Rutledge; Mark Dean; Andrew Caplin; Paul W Glimcher
Journal:  J Neurosci       Date:  2010-10-06       Impact factor: 6.167

2.  Influence of phasic and tonic dopamine release on receptor activation.

Authors:  Jakob K Dreyer; Kjartan F Herrik; Rune W Berg; Jørn D Hounsgaard
Journal:  J Neurosci       Date:  2010-10-20       Impact factor: 6.167

3.  Midbrain dopamine neurons encode decisions for future action.

Authors:  Genela Morris; Alon Nevet; David Arkadir; Eilon Vaadia; Hagai Bergman
Journal:  Nat Neurosci       Date:  2006-07-23       Impact factor: 24.884

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.  Dopamine responses comply with basic assumptions of formal learning theory.

Authors:  P Waelti; A Dickinson; W Schultz
Journal:  Nature       Date:  2001-07-05       Impact factor: 49.962

6.  Multivariate concentration determination using principal component regression with residual analysis.

Authors:  Richard B Keithley; Michael L Heien; R Mark Wightman
Journal:  Trends Analyt Chem       Date:  2009-10-01       Impact factor: 12.296

7.  Sub-second dopamine detection in human striatum.

Authors:  Kenneth T Kishida; Stefan G Sandberg; Terry Lohrenz; Youssef G Comair; Ignacio Sáez; Paul E M Phillips; P Read Montague
Journal:  PLoS One       Date:  2011-08-04       Impact factor: 3.240

8.  Chronic microsensors for longitudinal, subsecond dopamine detection in behaving animals.

Authors:  Jeremy J Clark; Stefan G Sandberg; Matthew J Wanat; Jerylin O Gan; Eric A Horne; Andrew S Hart; Christina A Akers; Jones G Parker; Ingo Willuhn; Vicente Martinez; Scott B Evans; Nephi Stella; Paul E M Phillips
Journal:  Nat Methods       Date:  2009-12-27       Impact factor: 28.547

9.  MEASURING BELIEFS AND REWARDS: A NEUROECONOMIC APPROACH.

Authors:  Andrew Caplin; Mark Dean; Paul W Glimcher; Robb B Rutledge
Journal:  Q J Econ       Date:  2010-12-31

10.  A causal link between prediction errors, dopamine neurons and learning.

Authors:  Elizabeth E Steinberg; Ronald Keiflin; Josiah R Boivin; Ilana B Witten; Karl Deisseroth; Patricia H Janak
Journal:  Nat Neurosci       Date:  2013-05-26       Impact factor: 24.884

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  122 in total

Review 1.  Motivational Processes Underlying Substance Abuse Disorder.

Authors:  Paul J Meyer; Christopher P King; Carrie R Ferrario
Journal:  Curr Top Behav Neurosci       Date:  2016

2.  Surprise! Dopamine signals mix action, value and error.

Authors:  Anne G E Collins; Michael J Frank
Journal:  Nat Neurosci       Date:  2016-01       Impact factor: 24.884

Review 3.  The Origins and Organization of Vertebrate Pavlovian Conditioning.

Authors:  Michael S Fanselow; Kate M Wassum
Journal:  Cold Spring Harb Perspect Biol       Date:  2015-11-09       Impact factor: 10.005

4.  Contributions of nucleus accumbens dopamine to cognitive flexibility.

Authors:  Anna K Radke; Adrina Kocharian; Dan P Covey; David M Lovinger; Joseph F Cheer; Yolanda Mateo; Andrew Holmes
Journal:  Eur J Neurosci       Date:  2018-10-10       Impact factor: 3.386

5.  Background Signal as an in Situ Predictor of Dopamine Oxidation Potential: Improving Interpretation of Fast-Scan Cyclic Voltammetry Data.

Authors:  Carl J Meunier; James G Roberts; Gregory S McCarty; Leslie A Sombers
Journal:  ACS Chem Neurosci       Date:  2017-01-24       Impact factor: 4.418

6.  Dopaminergic Modulation of Decision Making and Subjective Well-Being.

Authors:  Robb B Rutledge; Nikolina Skandali; Peter Dayan; Raymond J Dolan
Journal:  J Neurosci       Date:  2015-07-08       Impact factor: 6.167

7.  Cocaine Place Conditioning Strengthens Location-Specific Hippocampal Coupling to the Nucleus Accumbens.

Authors:  Lucas Sjulson; Adrien Peyrache; Andrea Cumpelik; Daniela Cassataro; György Buzsáki
Journal:  Neuron       Date:  2018-05-10       Impact factor: 17.173

8.  Dopamine-associated cached values are not sufficient as the basis for action selection.

Authors:  Nick G Hollon; Monica M Arnold; Jerylin O Gan; Mark E Walton; Paul E M Phillips
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-08       Impact factor: 11.205

9.  Taming the beast: extracting generalizable knowledge from computational models of cognition.

Authors:  Matthew R Nassar; Michael J Frank
Journal:  Curr Opin Behav Sci       Date:  2016-10

Review 10.  Dopamine Prediction Errors in Reward Learning and Addiction: From Theory to Neural Circuitry.

Authors:  Ronald Keiflin; Patricia H Janak
Journal:  Neuron       Date:  2015-10-21       Impact factor: 17.173

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