Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Causal evidence supporting the proposal that dopamine transients function as temporal difference prediction errors.

ABSTRACT: Reward-evoked dopamine transients are well established as prediction errors. However, the central tenet of temporal difference accounts-that similar transients evoked by reward-predictive cues also function as errors-remains untested. In the present communication we addressed this by showing that optogenetically shunting dopamine activity at the start of a reward-predicting cue prevents second-order conditioning without affecting blocking. These results indicate that cue-evoked transients function as temporal-difference prediction errors rather than reward predictions.

SUBMITTER: Maes EJP

PROVIDER: S-EPMC7007380 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Causal evidence supporting the proposal that dopamine transients function as temporal difference prediction errors.

Maes Etienne J P EJP Sharpe Melissa J MJ Usypchuk Alexandra A AA Lozzi Megan M Chang Chun Yun CY Gardner Matthew P H MPH Schoenbaum Geoffrey G Iordanova Mihaela D MD

Nature neuroscience 20200120 2

Reward-evoked dopamine transients are well established as prediction errors. However, the central tenet of temporal difference accounts-that similar transients evoked by reward-predictive cues also function as errors-remains untested. In the present communication we addressed this by showing that optogenetically shunting dopamine activity at the start of a reward-predicting cue prevents second-order conditioning without affecting blocking. These results indicate that cue-evoked transients functi ...[more]

PMID: 31959935

Similar Datasets

Dopamine transients do not act as model-free prediction errors during associative learning.

Project description:Dopamine neurons are proposed to signal the reward prediction error in model-free reinforcement learning algorithms. This term represents the unpredicted or 'excess' value of the rewarding event, value that is then added to the intrinsic value of any antecedent cues, contexts or events. To support this proposal, proponents cite evidence that artificially-induced dopamine transients cause lasting changes in behavior. Yet these studies do not generally assess learning under conditions where an endogenous prediction error would occur. Here, to address this, we conducted three experiments where we optogenetically activated dopamine neurons while rats were learning associative relationships, both with and without reward. In each experiment, the antecedent cues failed to acquire value and instead entered into associations with the later events, whether valueless cues or valued rewards. These results show that in learning situations appropriate for the appearance of a prediction error, dopamine transients support associative, rather than model-free, learning.

| S-EPMC6949299 | biostudies-literature

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

Project description:Situations in which rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.

| S-EPMC3705924 | biostudies-literature

Dopamine restores reward prediction errors in old age.

Project description:Senescence affects the ability to utilize information about the likelihood of rewards for optimal decision-making. Using functional magnetic resonance imaging in humans, we found that healthy older adults had an abnormal signature of expected value, resulting in an incomplete reward prediction error (RPE) signal in the nucleus accumbens, a brain region that receives rich input projections from substantia nigra/ventral tegmental area (SN/VTA) dopaminergic neurons. Structural connectivity between SN/VTA and striatum, measured by diffusion tensor imaging, was tightly coupled to inter-individual differences in the expression of this expected reward value signal. The dopamine precursor levodopa (L-DOPA) increased the task-based learning rate and task performance in some older adults to the level of young adults. This drug effect was linked to restoration of a canonical neural RPE. Our results identify a neurochemical signature underlying abnormal reward processing in older adults and indicate that this can be modulated by L-DOPA.

| S-EPMC3672991 | biostudies-literature

Arithmetic and local circuitry underlying dopamine prediction errors.

Project description:Dopamine neurons are thought to facilitate learning by comparing actual and expected reward. Despite two decades of investigation, little is known about how this comparison is made. To determine how dopamine neurons calculate prediction error, we combined optogenetic manipulations with extracellular recordings in the ventral tegmental area while mice engaged in classical conditioning. Here we demonstrate, by manipulating the temporal expectation of reward, that dopamine neurons perform subtraction, a computation that is ideal for reinforcement learning but rarely observed in the brain. Furthermore, selectively exciting and inhibiting neighbouring GABA (γ-aminobutyric acid) neurons in the ventral tegmental area reveals that these neurons are a source of subtraction: they inhibit dopamine neurons when reward is expected, causally contributing to prediction-error calculations. Finally, bilaterally stimulating ventral tegmental area GABA neurons dramatically reduces anticipatory licking to conditioned odours, consistent with an important role for these neurons in reinforcement learning. Together, our results uncover the arithmetic and local circuitry underlying dopamine prediction errors.

| S-EPMC4567485 | biostudies-literature

Temporal Specificity of Reward Prediction Errors Signaled by Putative Dopamine Neurons in Rat VTA Depends on Ventral Striatum.

Project description:Dopamine neurons signal reward prediction errors. This requires accurate reward predictions. It has been suggested that the ventral striatum provides these predictions. Here we tested this hypothesis by recording from putative dopamine neurons in the VTA of rats performing a task in which prediction errors were induced by shifting reward timing or number. In controls, the neurons exhibited error signals in response to both manipulations. However, dopamine neurons in rats with ipsilateral ventral striatal lesions exhibited errors only to changes in number and failed to respond to changes in timing of reward. These results, supported by computational modeling, indicate that predictions about the temporal specificity and the number of expected reward are dissociable and that dopaminergic prediction-error signals rely on the ventral striatum for the former but not the latter.

| S-EPMC4938771 | biostudies-literature

Nigrostriatal dopamine signals sequence-specific action-outcome prediction errors.

Project description:Dopamine has been suggested to encode cue-reward prediction errors during Pavlovian conditioning, signaling discrepancies between actual versus expected reward predicted by the cues.1-5 While this theory has been widely applied to reinforcement learning concerning instrumental actions, whether dopamine represents action-outcome prediction errors and how it controls sequential behavior remain largely unknown. The vast majority of previous studies examining dopamine responses primarily have used discrete reward-predictive stimuli,1-15 whether Pavlovian conditioned stimuli for which no action is required to earn reward or explicit discriminative stimuli that essentially instruct an animal how and when to respond for reward. Here, by training mice to perform optogenetic intracranial self-stimulation, we examined how self-initiated goal-directed behavior influences nigrostriatal dopamine transmission during single and sequential instrumental actions, in behavioral contexts with minimal overt changes in the animal's external environment. We found that dopamine release evoked by direct optogenetic stimulation was dramatically reduced when delivered as the consequence of the animal's own action, relative to non-contingent passive stimulation. This dopamine suppression generalized to food rewards was specific to the reinforced action, was temporally restricted to counteract the expected outcome, and exhibited sequence-selectivity consistent with hierarchical control of sequential behavior. These findings demonstrate that nigrostriatal dopamine signals sequence-specific prediction errors in action-outcome associations, with fundamental implications for reinforcement learning and instrumental behavior in health and disease.

| S-EPMC8665080 | biostudies-literature

Habenula Lesions Reveal that Multiple Mechanisms Underlie Dopamine Prediction Errors.

Project description:Dopamine (DA) neurons are thought to facilitate learning by signaling reward prediction errors (RPEs), the discrepancy between actual and expected reward. However, how RPEs are calculated remains unknown. It has been hypothesized that DA neurons receive RPE signals from the lateral habenula. Here, we tested how lesions of the habenular complex affect the response of optogenetically identified DA neurons in mice. We found that lesions impaired specific aspects of RPE signaling in DA neurons. The inhibitory responses caused by reward omission were greatly diminished while inhibitory responses to aversive stimuli, such as air puff-predictive cues or air puff, remained unimpaired. Furthermore, we found that after habenula lesions, DA neurons' ability to signal graded levels of positive RPEs became unreliable, yet significant excitatory responses still remained. These results demonstrate that the habenula plays a critical role in DA RPE signaling but suggest that it is not the exclusive source of RPE signals.

| S-EPMC4583356 | biostudies-literature

Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans.

Project description:Theories of instrumental learning are centred on understanding how success and failure are used to improve future decisions. These theories highlight a central role for reward prediction errors in updating the values associated with available actions. In animals, substantial evidence indicates that the neurotransmitter dopamine might have a key function in this type of learning, through its ability to modulate cortico-striatal synaptic efficacy. However, no direct evidence links dopamine, striatal activity and behavioural choice in humans. Here we show that, during instrumental learning, the magnitude of reward prediction error expressed in the striatum is modulated by the administration of drugs enhancing (3,4-dihydroxy-L-phenylalanine; L-DOPA) or reducing (haloperidol) dopaminergic function. Accordingly, subjects treated with L-DOPA have a greater propensity to choose the most rewarding action relative to subjects treated with haloperidol. Furthermore, incorporating the magnitude of the prediction errors into a standard action-value learning algorithm accurately reproduced subjects' behavioural choices under the different drug conditions. We conclude that dopamine-dependent modulation of striatal activity can account for how the human brain uses reward prediction errors to improve future decisions.

| S-EPMC2636869 | biostudies-literature

Mesolimbic Dopamine Encodes Prediction Errors in a State-Dependent Manner.

Project description:Mesolimbic dopamine encodes the benefits of a course of action. However, the value of an appetitive reward depends strongly on an animal's current state. To investigate the relationship between dopamine, value, and physiological state, we monitored sub-second dopamine release in the nucleus accumbens core while rats made choices between food and sucrose solution following selective satiation on one of these reinforcers. Dopamine signals reflected preference for the reinforcers in the new state, decreasing to the devalued reward and, after satiation on food, increasing for the valued sucrose solution. These changes were rapid and selective, with dopamine release returning to pre-satiation patterns when the animals were re-tested in a standard food-restricted state. Such rapid and selective adaptation of dopamine-associated value signals could provide an important signal to promote efficient foraging for a varied diet.

| S-EPMC4835543 | biostudies-literature

Dopamine neuron ensembles signal the content of sensory prediction errors.

Project description:Dopamine neurons respond to errors in predicting value-neutral sensory information. These data, combined with causal evidence that dopamine transients support sensory-based associative learning, suggest that the dopamine system signals a multidimensional prediction error. Yet such complexity is not evident in the activity of individual neurons or population averages. How then do downstream areas know what to learn in response to these signals? One possibility is that information about content is contained in the pattern of firing across many dopamine neurons. Consistent with this, here we show that the pattern of firing across a small group of dopamine neurons recorded in rats signals the identity of a mis-predicted sensory event. Further, this same information is reflected in the BOLD response elicited by sensory prediction errors in human midbrain. These data provide evidence that ensembles of dopamine neurons provide highly specific teaching signals, opening new possibilities for how this system might contribute to learning.

| S-EPMC6839916 | 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