Literature DB >> 18026098

Dopamine neurons encode the better option in rats deciding between differently delayed or sized rewards.

Matthew R Roesch1, Donna J Calu, Geoffrey Schoenbaum.   

Abstract

The dopamine system is thought to be involved in making decisions about reward. Here we recorded from the ventral tegmental area in rats learning to choose between differently delayed and sized rewards. As expected, the activity of many putative dopamine neurons reflected reward prediction errors, changing when the value of the reward increased or decreased unexpectedly. During learning, neural responses to reward in these neurons waned and responses to cues that predicted reward emerged. Notably, this cue-evoked activity varied with size and delay. Moreover, when rats were given a choice between two differently valued outcomes, the activity of the neurons initially reflected the more valuable option, even when it was not subsequently selected.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18026098      PMCID: PMC2562672          DOI: 10.1038/nn2013

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  44 in total

Review 1.  Theory and method in the quantitative analysis of "impulsive choice" behaviour: implications for psychopharmacology.

Authors:  M Y Ho; S Mobini; T J Chiang; C M Bradshaw; E Szabadi
Journal:  Psychopharmacology (Berl)       Date:  1999-10       Impact factor: 4.530

2.  Adaptive coding of reward value by dopamine neurons.

Authors:  Philippe N Tobler; Christopher D Fiorillo; Wolfram Schultz
Journal:  Science       Date:  2005-03-11       Impact factor: 47.728

3.  Midbrain dopamine neurons encode a quantitative reward prediction error signal.

Authors:  Hannah M Bayer; Paul W Glimcher
Journal:  Neuron       Date:  2005-07-07       Impact factor: 17.173

4.  Choice values.

Authors:  Yael Niv; Nathaniel D Daw; Peter Dayan
Journal:  Nat Neurosci       Date:  2006-08       Impact factor: 24.884

5.  Encoding of time-discounted rewards in orbitofrontal cortex is independent of value representation.

Authors:  Matthew R Roesch; Adam R Taylor; Geoffrey Schoenbaum
Journal:  Neuron       Date:  2006-08-17       Impact factor: 17.173

6.  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

7.  Previous cocaine exposure makes rats hypersensitive to both delay and reward magnitude.

Authors:  Matthew R Roesch; Yuji Takahashi; Nishan Gugsa; Gregory B Bissonette; Geoffrey Schoenbaum
Journal:  J Neurosci       Date:  2007-01-03       Impact factor: 6.167

8.  Single units in the pigeon brain integrate reward amount and time-to-reward in an impulsive choice task.

Authors:  Tobias Kalenscher; Sabine Windmann; Bettina Diekamp; Jonas Rose; Onur Güntürkün; Michael Colombo
Journal:  Curr Biol       Date:  2005-04-12       Impact factor: 10.834

9.  Dopamine cells respond to predicted events during classical conditioning: evidence for eligibility traces in the reward-learning network.

Authors:  Wei-Xing Pan; Robert Schmidt; Jeffery R Wickens; Brian I Hyland
Journal:  J Neurosci       Date:  2005-06-29       Impact factor: 6.167

10.  Associative learning mediates dynamic shifts in dopamine signaling in the nucleus accumbens.

Authors:  Jeremy J Day; Mitchell F Roitman; R Mark Wightman; Regina M Carelli
Journal:  Nat Neurosci       Date:  2007-07-01       Impact factor: 24.884

View more
  267 in total

1.  Phasic nucleus accumbens dopamine release encodes effort- and delay-related costs.

Authors:  Jeremy J Day; Joshua L Jones; R Mark Wightman; Regina M Carelli
Journal:  Biol Psychiatry       Date:  2010-05-10       Impact factor: 13.382

2.  The prefrontal cortex and hybrid learning during iterative competitive games.

Authors:  Hiroshi Abe; Hyojung Seo; Daeyeol Lee
Journal:  Ann N Y Acad Sci       Date:  2011-12       Impact factor: 5.691

Review 3.  Does the orbitofrontal cortex signal value?

Authors:  Geoffrey Schoenbaum; Yuji Takahashi; Tzu-Lan Liu; Michael A McDannald
Journal:  Ann N Y Acad Sci       Date:  2011-12       Impact factor: 5.691

4.  Visual object categorization in birds and primates: integrating behavioral, neurobiological, and computational evidence within a "general process" framework.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Cogn Affect Behav Neurosci       Date:  2012-03       Impact factor: 3.282

Review 5.  The role of the basal ganglia in learning and memory: insight from Parkinson's disease.

Authors:  Karin Foerde; Daphna Shohamy
Journal:  Neurobiol Learn Mem       Date:  2011-09-16       Impact factor: 2.877

6.  A pallidus-habenula-dopamine pathway signals inferred stimulus values.

Authors:  Ethan S Bromberg-Martin; Masayuki Matsumoto; Simon Hong; Okihide Hikosaka
Journal:  J Neurophysiol       Date:  2010-06-10       Impact factor: 2.714

Review 7.  All that glitters ... dissociating attention and outcome expectancy from prediction errors signals.

Authors:  Matthew R Roesch; Donna J Calu; Guillem R Esber; Geoffrey Schoenbaum
Journal:  J Neurophysiol       Date:  2010-06-16       Impact factor: 2.714

Review 8.  Dopamine in motivational control: rewarding, aversive, and alerting.

Authors:  Ethan S Bromberg-Martin; Masayuki Matsumoto; Okihide Hikosaka
Journal:  Neuron       Date:  2010-12-09       Impact factor: 17.173

Review 9.  Opponency revisited: competition and cooperation between dopamine and serotonin.

Authors:  Y-Lan Boureau; Peter Dayan
Journal:  Neuropsychopharmacology       Date:  2010-09-29       Impact factor: 7.853

Review 10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.