Literature DB >> 21389268

Understanding dopamine and reinforcement learning: the dopamine reward prediction error hypothesis.

Paul W Glimcher1.   

Abstract

A number of recent advances have been achieved in the study of midbrain dopaminergic neurons. Understanding these advances and how they relate to one another requires a deep understanding of the computational models that serve as an explanatory framework and guide ongoing experimental inquiry. This intertwining of theory and experiment now suggests very clearly that the phasic activity of the midbrain dopamine neurons provides a global mechanism for synaptic modification. These synaptic modifications, in turn, provide the mechanistic underpinning for a specific class of reinforcement learning mechanisms that now seem to underlie much of human and animal behavior. This review describes both the critical empirical findings that are at the root of this conclusion and the fantastic theoretical advances from which this conclusion is drawn.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21389268      PMCID: PMC3176615          DOI: 10.1073/pnas.1014269108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   12.779


  50 in total

1.  Modifications of reward expectation-related neuronal activity during learning in primate orbitofrontal cortex.

Authors:  L Tremblay; W Schultz
Journal:  J Neurophysiol       Date:  2000-04       Impact factor: 2.714

2.  Basal-ganglia 'projections' to the prefrontal cortex of the primate.

Authors:  Frank A Middleton; Peter L Strick
Journal:  Cereb Cortex       Date:  2002-09       Impact factor: 5.357

3.  EVIDENCE FOR THE EXISTENCE OF MONOAMINE-CONTAINING NEURONS IN THE CENTRAL NERVOUS SYSTEM. I. DEMONSTRATION OF MONOAMINES IN THE CELL BODIES OF BRAIN STEM NEURONS.

Authors:  A DAHLSTROEM; K FUXE
Journal:  Acta Physiol Scand Suppl       Date:  1964

Review 4.  Effects of stress and aversion on dopamine neurons: implications for addiction.

Authors:  Mark A Ungless; Emanuela Argilli; Antonello Bonci
Journal:  Neurosci Biobehav Rev       Date:  2010-05-08       Impact factor: 8.989

5.  Representation of action-specific reward values in the striatum.

Authors:  Kazuyuki Samejima; Yasumasa Ueda; Kenji Doya; Minoru Kimura
Journal:  Science       Date:  2005-11-25       Impact factor: 47.728

6.  A mathematical model for simple learning.

Authors:  R R BUSH; F MOSTELLER
Journal:  Psychol Rev       Date:  1951-09       Impact factor: 8.934

7.  Value representations in the primate striatum during matching behavior.

Authors:  Brian Lau; Paul W Glimcher
Journal:  Neuron       Date:  2008-05-08       Impact factor: 17.173

8.  The ventral tegmental area revisited: is there an electrophysiological marker for dopaminergic neurons?

Authors:  Elyssa B Margolis; Hagar Lock; Gregory O Hjelmstad; Howard L Fields
Journal:  J Physiol       Date:  2006-09-07       Impact factor: 5.182

9.  Bee foraging in uncertain environments using predictive hebbian learning.

Authors:  P R Montague; P Dayan; C Person; T J Sejnowski
Journal:  Nature       Date:  1995-10-26       Impact factor: 49.962

10.  Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate.

Authors:  Roberta M Kelly; Peter L Strick
Journal:  J Neurosci       Date:  2003-09-10       Impact factor: 6.167

View more
  235 in total

1.  Changes in corticostriatal connectivity during reinforcement learning in humans.

Authors:  Guillermo Horga; Tiago V Maia; Rachel Marsh; Xuejun Hao; Dongrong Xu; Yunsuo Duan; Gregory Z Tau; Barbara Graniello; Zhishun Wang; Alayar Kangarlu; Diana Martinez; Mark G Packard; Bradley S Peterson
Journal:  Hum Brain Mapp       Date:  2014-11-12       Impact factor: 5.038

Review 2.  Motivational Deficits in Schizophrenia and the Representation of Expected Value.

Authors:  James A Waltz; James M Gold
Journal:  Curr Top Behav Neurosci       Date:  2016

3.  Expanding the role of striatal cholinergic interneurons and the midbrain dopamine system in appetitive instrumental conditioning.

Authors:  Matthew J Crossley; Jon C Horvitz; Peter D Balsam; F Gregory Ashby
Journal:  J Neurophysiol       Date:  2015-10-14       Impact factor: 2.714

4.  Dopamine: Context and counterfactuals.

Authors:  Michael L Platt; John M Pearson
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-23       Impact factor: 11.205

Review 5.  Establishing causality for dopamine in neural function and behavior with optogenetics.

Authors:  Elizabeth E Steinberg; Patricia H Janak
Journal:  Brain Res       Date:  2012-09-29       Impact factor: 3.252

6.  Incentives facilitate developmental improvement in inhibitory control by modulating control-related networks.

Authors:  Michael N Hallquist; Charles F Geier; Beatriz Luna
Journal:  Neuroimage       Date:  2018-01-31       Impact factor: 6.556

7.  A Basal Ganglia Circuit Sufficient to Guide Birdsong Learning.

Authors:  Lei Xiao; Gaurav Chattree; Francisco Garcia Oscos; Mou Cao; Matthew J Wanat; Todd F Roberts
Journal:  Neuron       Date:  2018-03-15       Impact factor: 17.173

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

Authors:  Andrew S Hart; Robb B Rutledge; Paul W Glimcher; Paul E M Phillips
Journal:  J Neurosci       Date:  2014-01-15       Impact factor: 6.167

9.  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

10.  Neural signatures of experience-based improvements in deterministic decision-making.

Authors:  Joshua J Tremel; Patryk A Laurent; David A Wolk; Mark E Wheeler; Julie A Fiez
Journal:  Behav Brain Res       Date:  2016-08-11       Impact factor: 3.332

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.