Dual reward prediction components yield Pavlovian sign- and goal-tracking.

Reinforcement learning (RL) has become a dominant paradigm for understanding animal behaviors and neural correlates of decision-making, in part because of its ability to explain Pavlovian conditioned behaviors and the role of midbrain dopamine activity as reward prediction error (RPE). However, rece...

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Main Authors: Sivaramakrishnan Kaveri, Hiroyuki Nakahara
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4195585?pdf=render
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spelling doaj-f800d89a568a48c5b9e111a6272538ea2020-11-25T01:26:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01910e10814210.1371/journal.pone.0108142Dual reward prediction components yield Pavlovian sign- and goal-tracking.Sivaramakrishnan KaveriHiroyuki NakaharaReinforcement learning (RL) has become a dominant paradigm for understanding animal behaviors and neural correlates of decision-making, in part because of its ability to explain Pavlovian conditioned behaviors and the role of midbrain dopamine activity as reward prediction error (RPE). However, recent experimental findings indicate that dopamine activity, contrary to the RL hypothesis, may not signal RPE and differs based on the type of Pavlovian response (e.g. sign- and goal-tracking responses). In this study, we address this discrepancy by introducing a new neural correlate for learning reward predictions; the correlate is called "cue-evoked reward". It refers to a recall of reward evoked by the cue that is learned through simple cue-reward associations. We introduce a temporal difference learning model, in which neural correlates of the cue itself and cue-evoked reward underlie learning of reward predictions. The animal's reward prediction supported by these two correlates is divided into sign and goal components respectively. We relate the sign and goal components to approach responses towards the cue (i.e. sign-tracking) and the food-tray (i.e. goal-tracking) respectively. We found a number of correspondences between simulated models and the experimental findings (i.e. behavior and neural responses). First, the development of modeled responses is consistent with those observed in the experimental task. Second, the model's RPEs were similar to dopamine activity in respective response groups. Finally, goal-tracking, but not sign-tracking, responses rapidly emerged when RPE was restored in the simulated models, similar to experiments with recovery from dopamine-antagonist. These results suggest two complementary neural correlates, corresponding to the cue and its evoked reward, form the basis for learning reward predictions in the sign- and goal-tracking rats.http://europepmc.org/articles/PMC4195585?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Sivaramakrishnan Kaveri
Hiroyuki Nakahara
spellingShingle Sivaramakrishnan Kaveri
Hiroyuki Nakahara
Dual reward prediction components yield Pavlovian sign- and goal-tracking.
PLoS ONE
author_facet Sivaramakrishnan Kaveri
Hiroyuki Nakahara
author_sort Sivaramakrishnan Kaveri
title Dual reward prediction components yield Pavlovian sign- and goal-tracking.
title_short Dual reward prediction components yield Pavlovian sign- and goal-tracking.
title_full Dual reward prediction components yield Pavlovian sign- and goal-tracking.
title_fullStr Dual reward prediction components yield Pavlovian sign- and goal-tracking.
title_full_unstemmed Dual reward prediction components yield Pavlovian sign- and goal-tracking.
title_sort dual reward prediction components yield pavlovian sign- and goal-tracking.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description Reinforcement learning (RL) has become a dominant paradigm for understanding animal behaviors and neural correlates of decision-making, in part because of its ability to explain Pavlovian conditioned behaviors and the role of midbrain dopamine activity as reward prediction error (RPE). However, recent experimental findings indicate that dopamine activity, contrary to the RL hypothesis, may not signal RPE and differs based on the type of Pavlovian response (e.g. sign- and goal-tracking responses). In this study, we address this discrepancy by introducing a new neural correlate for learning reward predictions; the correlate is called "cue-evoked reward". It refers to a recall of reward evoked by the cue that is learned through simple cue-reward associations. We introduce a temporal difference learning model, in which neural correlates of the cue itself and cue-evoked reward underlie learning of reward predictions. The animal's reward prediction supported by these two correlates is divided into sign and goal components respectively. We relate the sign and goal components to approach responses towards the cue (i.e. sign-tracking) and the food-tray (i.e. goal-tracking) respectively. We found a number of correspondences between simulated models and the experimental findings (i.e. behavior and neural responses). First, the development of modeled responses is consistent with those observed in the experimental task. Second, the model's RPEs were similar to dopamine activity in respective response groups. Finally, goal-tracking, but not sign-tracking, responses rapidly emerged when RPE was restored in the simulated models, similar to experiments with recovery from dopamine-antagonist. These results suggest two complementary neural correlates, corresponding to the cue and its evoked reward, form the basis for learning reward predictions in the sign- and goal-tracking rats.
url http://europepmc.org/articles/PMC4195585?pdf=render
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