skip to main content


Title: Phasic dopamine reinforces distinct striatal stimulus encoding in the olfactory tubercle driving dopaminergic reward prediction
Abstract The learning of stimulus-outcome associations allows for predictions about the environment. Ventral striatum and dopaminergic midbrain neurons form a larger network for generating reward prediction signals from sensory cues. Yet, the network plasticity mechanisms to generate predictive signals in these distributed circuits have not been entirely clarified. Also, direct evidence of the underlying interregional assembly formation and information transfer is still missing. Here we show that phasic dopamine is sufficient to reinforce the distinctness of stimulus representations in the ventral striatum even in the absence of reward. Upon such reinforcement, striatal stimulus encoding gives rise to interregional assemblies that drive dopaminergic neurons during stimulus-outcome learning. These assemblies dynamically encode the predicted reward value of conditioned stimuli. Together, our data reveal that ventral striatal and midbrain reward networks form a reinforcing loop to generate reward prediction coding.  more » « less
Award ID(s):
1724221
NSF-PAR ID:
10377907
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Nature Communications
Volume:
11
Issue:
1
ISSN:
2041-1723
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Motivation is a powerful driver of learning and memory. Functional MRI studies show that interactions among the dopaminergic midbrain substantia nigra/ventral tegmental area (SN/VTA), hippocampus, and nucleus accumbens (NAc) are critical for motivated memory encoding. However, it is not known whether these effects are transient and purely functional, or whether individual differences in the structure of this circuit underlie motivated memory encoding. To quantify individual differences in structure, diffusion-weighted MRI and probabilistic tractography were used to quantify SN/VTA–striatum and SN/VTA–hippocampus pathways associated with motivated memory encoding in humans. Male and female participants completed a motivated source memory paradigm. During encoding, words were randomly assigned to one of three conditions, reward ($1.00), control ($0.00), or punishment (−$1.00). During retrieval, participants were asked to retrieve item and source information of the previously studied words and were rewarded or penalized according to their performance. Source memory for words assigned to both reward and punishment conditions was greater than those for control words, but there were no differences in item memory based on value. Anatomically, probabilistic tractography results revealed a heterogeneous, topological arrangement of the SN/VTA. Tract density measures of SN/VTA–hippocampus pathways were positively correlated with individual differences in reward-and-punishment-modulated memory performance, whereas density of SN/VTA–striatum pathways showed no association. This novel finding suggests that pathways emerging from the human SV/VTA are anatomically separable and functionally heterogeneous. Individual differences in structural connectivity of the dopaminergic hippocampus–VTA loop are selectively associated with motivated memory encoding.

    SIGNIFICANCE STATEMENTFunctional MRI studies show that interactions among the SN/VTA, hippocampus, and NAc are critical for motivated memory encoding. This has led to competing theories that posit either SN/VTA–NAc reward prediction errors or SN/VTA–hippocampus signals underlie motivated memory encoding. Additionally, it is not known whether these effects are transient and purely functional or whether individual differences in the structure of these circuits underlie motivated memory encoding. Using diffusion-weighted MRI and probabilistic tractography, we show that tract density measures of SN/VTA–hippocampus pathways are positively correlated with motivated memory performance, whereas density of SN/VTA–striatum pathways show no association. This finding suggests that anatomic individual differences of the dopaminergic hippocampus–VTA loop are selectively associated with motivated memory encoding.

     
    more » « less
  2. Abstract Identifying the circuits responsible for cognition and understanding their embedded computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach, from behavioral modeling and fMRI in task-performing mice to cellular recordings, in order to disentangle local network contributions to olfactory reinforcement learning. At mesoscale, fMRI identifies a functional olfactory-striatal network interacting dynamically with higher-order cortices. While primary olfactory cortices respectively contribute only some value components, the downstream olfactory tubercle of the ventral striatum expresses comprehensively reward prediction, its dynamic updating, and prediction error components. In the tubercle, recordings reveal two underlying neuronal populations with non-redundant reward prediction coding schemes. One population collectively produces stabilized predictions as distributed activity across neurons; in the other, neurons encode value individually and dynamically integrate the recent history of uncertain outcomes. These findings validate a cross-scale approach to mechanistic investigations of higher cognitive functions in rodents. 
    more » « less
  3. Abstract

    Learning about positive and negative outcomes of actions is crucial for survival and underpinned by conserved circuits including the striatum. How associations between actions and outcomes are formed is not fully understood, particularly when the outcomes have mixed positive and negative features. We developed a novel foraging (‘bandit’) task requiring mice to maximize rewards while minimizing punishments. By 2-photon Ca++imaging, we monitored activity of visually identified anterodorsal striatal striosomal and matrix neurons. We found that action-outcome associations for reward and punishment were encoded in parallel in partially overlapping populations. Single neurons could, for one action, encode outcomes of opposing valence. Striosome compartments consistently exhibited stronger representations of reinforcement outcomes than matrix, especially for high reward or punishment prediction errors. These findings demonstrate multiplexing of action-outcome contingencies by single identified striatal neurons and suggest that striosomal neurons are particularly important in action-outcome learning.

     
    more » « less
  4. Do dopaminergic reward structures represent the expected utility of information similarly to a reward? Optimal experimental design models from Bayesian decision theory and statistics have proposed a theoretical framework for quantifying the expected value of information that might result from a query. In particular, this formulation quantifies the value of information before the answer to that query is known, in situations where payoffs are unknown and the goal is purely epistemic: That is, to increase knowledge about the state of the world. Whether and how such a theoretical quantity is represented in the brain is unknown. Here we use an event-related functional MRI (fMRI) task design to disentangle information expectation, information revelation and categorization outcome anticipation, and response-contingent reward processing in a visual probabilistic categorization task. We identify a neural signature corresponding to the expectation of information, involving the left lateral ventral striatum. Moreover, we show a temporal dissociation in the activation of different reward-related regions, including the nucleus accumbens, medial prefrontal cortex, and orbitofrontal cortex, during information expectation versus reward-related processing.

     
    more » « less
  5. The estrous cycle is a potent modulator of neuron physiology. In rodents,in vivoventral tegmental area (VTA) dopamine (DA) activity has been shown to fluctuate across the estrous cycle. Although the behavioral effect of fluctuating sex steroids on the reward circuit is well studied in response to drugs of abuse, few studies have focused on the molecular adaptations in the context of stress and motivated social behaviors. We hypothesized that estradiol fluctuations across the estrous cycle acts on the dopaminergic activity of the VTA to alter excitability and stress response. We used whole-cell slice electrophysiology of VTA DA neurons in naturally cycling, adult female C57BL/6J mice to characterize the effects of the estrous cycle and the role of 17β-estradiol on neuronal activity. We show that the estrous phase alters the effect of 17β-estradiol on excitability in the VTA. Behaviorally, the estrous phase during a series of acute variable social stressors modulates subsequent reward-related behaviors. Pharmacological inhibition of estrogen receptors in the VTA before stress during diestrus mimics the stress susceptibility found during estrus, whereas increased potassium channel activity in the VTA before stress reverses stress susceptibility found during estrus as assessed by social interaction behavior. This study identifies one possible potassium channel mechanism underlying the increased DA activity during estrus and reveals estrogen-dependent changes in neuronal function. Our findings demonstrate that the estrous cycle and estrogen signaling changes the physiology of DA neurons resulting in behavioral differences when the reward circuit is challenged with stress.

    SIGNIFICANCE STATEMENTThe activity of the ventral tegmental area encodes signals of stress and reward. Dopaminergic activity has been found to be regulated by both local synaptic inputs as well as inputs from other brain regions. Here, we provide evidence that cycling sex steroids also play a role in modulating stress sensitivity of dopaminergic reward behavior. Specifically, we reveal a correlation of ionic activity with estrous phase, which influences the behavioral response to stress. These findings shed new light on how estrous cycle may influence dopaminergic activity primarily during times of stress perturbation.

     
    more » « less