Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

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.

SUBMITTER: Roesch MR

PROVIDER: S-EPMC2562672 | biostudies-literature | 2007 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

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

Roesch Matthew R MR Calu Donna J DJ Schoenbaum Geoffrey G

Nature neuroscience 20071118 12

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. Notabl ...[more]

PMID: 18026098

Similar Datasets

Dopamine neurons learn to encode the long-term value of multiple future rewards.

Project description:Midbrain dopamine neurons signal reward value, their prediction error, and the salience of events. If they play a critical role in achieving specific distant goals, long-term future rewards should also be encoded as suggested in reinforcement learning theories. Here, we address this experimentally untested issue. We recorded 185 dopamine neurons in three monkeys that performed a multistep choice task in which they explored a reward target among alternatives and then exploited that knowledge to receive one or two additional rewards by choosing the same target in a set of subsequent trials. An analysis of anticipatory licking for reward water indicated that the monkeys did not anticipate an immediately expected reward in individual trials; rather, they anticipated the sum of immediate and multiple future rewards. In accordance with this behavioral observation, the dopamine responses to the start cues and reinforcer beeps reflected the expected values of the multiple future rewards and their errors, respectively. More specifically, when monkeys learned the multistep choice task over the course of several weeks, the responses of dopamine neurons encoded the sum of the immediate and expected multiple future rewards. The dopamine responses were quantitatively predicted by theoretical descriptions of the value function with time discounting in reinforcement learning. These findings demonstrate that dopamine neurons learn to encode the long-term value of multiple future rewards with distant rewards discounted.

| S-EPMC3174584 | biostudies-literature

Human substantia nigra neurons encode unexpected financial rewards.

Project description:The brain's sensitivity to unexpected outcomes plays a fundamental role in an organism's ability to adapt and learn new behaviors. Emerging research suggests that midbrain dopaminergic neurons encode these unexpected outcomes. We used microelectrode recordings during deep brain stimulation surgery to study neuronal activity in the human substantia nigra (SN) while patients with Parkinson's disease engaged in a probabilistic learning task motivated by virtual financial rewards. Based on a model of the participants' expected reward, we divided trial outcomes into expected and unexpected gains and losses. SN neurons exhibited significantly higher firing rates after unexpected gains than unexpected losses. No such differences were observed after expected gains and losses. This result provides critical support for the hypothesized role of the SN in human reinforcement learning.

| S-EPMC2839450 | biostudies-literature

Dopamine neurons learn relative chosen value from probabilistic rewards.

Project description:Economic theories posit reward probability as one of the factors defining reward value. Individuals learn the value of cues that predict probabilistic rewards from experienced reward frequencies. Building on the notion that responses of dopamine neurons increase with reward probability and expected value, we asked how dopamine neurons in monkeys acquire this value signal that may represent an economic decision variable. We found in a Pavlovian learning task that reward probability-dependent value signals arose from experienced reward frequencies. We then assessed neuronal response acquisition during choices among probabilistic rewards. Here, dopamine responses became sensitive to the value of both chosen and unchosen options. Both experiments showed also the novelty responses of dopamine neurones that decreased as learning advanced. These results show that dopamine neurons acquire predictive value signals from the frequency of experienced rewards. This flexible and fast signal reflects a specific decision variable and could update neuronal decision mechanisms.

| S-EPMC5116238 | biostudies-literature

Dopamine neurons encode performance error in singing birds.

Project description:Many behaviors are learned through trial and error by matching performance to internal goals. Yet neural mechanisms of performance evaluation remain poorly understood. We recorded basal ganglia-projecting dopamine neurons in singing zebra finches as we controlled perceived song quality with distorted auditory feedback. Dopamine activity was phasically suppressed after distorted syllables, consistent with a worse-than-predicted outcome, and was phasically activated at the precise moment of the song when a predicted distortion did not occur, consistent with a better-than-predicted outcome. Error response magnitude depended on distortion probability. Thus, dopaminergic error signals can evaluate behaviors that are not learned for reward and are instead learned by matching performance outcomes to internal goals.

| S-EPMC5464363 | biostudies-literature

Subpopulations of neurons in lOFC encode previous and current rewards at time of choice.

Project description:Studies of neural dynamics in lateral orbitofrontal cortex (lOFC) have shown that subsets of neurons that encode distinct aspects of behavior, such as value, may project to common downstream targets. However, it is unclear whether reward history, which may subserve lOFC's well-documented role in learning, is represented by functional subpopulations in lOFC. Previously, we analyzed neural recordings from rats performing a value-based decision-making task, and we documented trial-by-trial learning that required lOFC (Constantinople et al., 2019). Here, we characterize functional subpopulations of lOFC neurons during behavior, including their encoding of task variables. We found five distinct clusters of lOFC neurons, either based on clustering of their trial-averaged peristimulus time histograms (PSTHs), or a feature space defined by their average conditional firing rates aligned to different task variables. We observed weak encoding of reward attributes, but stronger encoding of reward history, the animal's left or right choice, and reward receipt across all clusters. Only one cluster, however, encoded the animal's reward history at the time shortly preceding the choice, suggesting a possible role in integrating previous and current trial outcomes at the time of choice. This cluster also exhibits qualitatively similar responses to identified corticostriatal projection neurons in a recent study (Hirokawa et al., 2019), and suggests a possible role for subpopulations of lOFC neurons in mediating trial-by-trial learning.

| S-EPMC8616578 | biostudies-literature

Midbrain dopamine neurons signal preference for advance information about upcoming rewards.

Project description:The desire to know what the future holds is a powerful motivator in everyday life, but it is unknown how this desire is created by neurons in the brain. Here we show that when macaque monkeys are offered a water reward of variable magnitude, they seek advance information about its size. Furthermore, the same midbrain dopamine neurons that signal the expected amount of water also signal the expectation of information, in a manner that is correlated with the strength of the animal's preference. Our data show that single dopamine neurons process both primitive and cognitive rewards, and suggest that current theories of reward-seeking must be revised to include information-seeking.

| S-EPMC2723053 | biostudies-literature

Zona incerta dopamine neurons encode motivational vigor in food seeking

Project description: Not available

| S-EPMC10656063 | biostudies-literature

Dopamine Neurons Respond to Errors in the Prediction of Sensory Features of Expected Rewards.

Project description:Midbrain dopamine neurons have been proposed to signal prediction errors as defined in model-free reinforcement learning algorithms. While these algorithms have been extremely powerful in interpreting dopamine activity, these models do not register any error unless there is a difference between the value of what is predicted and what is received. Yet learning often occurs in response to changes in the unique features that characterize what is received, sometimes with no change in its value at all. Here, we show that classic error-signaling dopamine neurons also respond to changes in value-neutral sensory features of an expected reward. This suggests that dopamine neurons have access to a wider variety of information than contemplated by the models currently used to interpret their activity and that, while their firing may conform to predictions of these models in some cases, they are not restricted to signaling errors in the prediction of value.

| S-EPMC5658021 | biostudies-literature

The cost of obtaining rewards enhances the reward prediction error signal of midbrain dopamine neurons.

Project description:Midbrain dopamine neurons are known to encode reward prediction errors (RPE) used to update value predictions. Here, we examine whether RPE signals coded by midbrain dopamine neurons are modulated by the cost paid to obtain rewards, by recording from dopamine neurons in awake behaving monkeys during performance of an effortful saccade task. Dopamine neuron responses to cues predicting reward and to the delivery of rewards were increased after the performance of a costly action compared to a less costly action, suggesting that RPEs are enhanced following the performance of a costly action. At the behavioral level, stimulus-reward associations are learned faster after performing a costly action compared to a less costly action. Thus, information about action cost is processed in the dopamine reward system in a manner that amplifies the following dopamine RPE signal, which in turn promotes more rapid learning under situations of high cost.

| S-EPMC6695452 | biostudies-literature

Behavioral and neural evidence of incentive bias for immediate rewards relative to preference-matched delayed rewards.

Project description:Several theories of self-control [including intertemporal bargaining (Ainslie, 1992) and self-signaling (Bodner and Prelec, 2001)] imply that intertemporal decisions can be more farsighted than would be predicted by the incentive associated with rewards outside a decision context. We examined this hypothesis using behavior and functional neuroimaging. First, subjects expressed preferences between amounts of money delayed by 4 months and smaller amounts available that day. This allowed us to establish "indifference pairs" individualized to each participant: immediate and delayed amounts that were equally preferred. Participants subsequently performed a reaction time functional magnetic resonance imaging task (Knutson et al., 2001a) that provided them with distinct opportunities to win each of the rewards that comprised the indifference pairs. Anatomical region of interest analysis as well as whole-brain analysis indicated greater response recruited by the immediate rewards (relative to the preference-matched delayed rewards) in regions previously implicated as sensitive to incentive value using the same task (including bilateral putamen, bilateral anterior insula, and midbrain). Reaction time to the target was also faster during the immediate relative to delayed reward trials (p < 0.01), and individual differences in reaction time between immediate versus delayed reward trials correlated with variance in magnetic resonance signal in those clusters that responded preferentially to immediate rewards (r = 0.33, p < 0.05). These findings indicate a discrepancy in incentive associated with the immediate versus the preference-matched delayed rewards. This discrepancy may mark the contribution of self-control processes that are recruited during decision-making but that are absent when rewards are individually anticipated.

| S-EPMC2821568 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data