Neurotransmission operates on a millisecond timescale, but is changed by normal experience or neuropathology over days, weeks or even months. Despite the great importance of long-term neurotransmitter dynamics, no technique exists to track these changes within a subject from day to day over extended periods of time. Here we describe and characterize a microsensor that can detect the neurotransmitter dopamine with subsecond temporal resolution over months in vivo in rats and mice.
Making predictions about the rewards associated with environmental stimuli and updating those predictions through feedback is an essential aspect of adaptive behavior. Theorists have argued that dopamine encodes a reward prediction error (RPE) signal that is used in such a reinforcement learning process. Recent work with fMRI has demonstrated that the BOLD signal in dopaminergic target areas meets both necessary and sufficient conditions of an axiomatic model of the RPE hypothesis. However, there has been no direct evidence that dopamine release itself also meets necessary and sufficient criteria for encoding an RPE signal. Further, the fact that dopamine neurons have low tonic firing rates that yield a limited dynamic range for encoding negative RPEs has led to significant debate about whether positive and negative prediction errors are encoded on a similar scale. To address both of these issues, we used fast-scan cyclic voltammetry to measure reward-evoked dopamine release at carbon fiber electrodes chronically implanted in the nucleus accumbens core of rats trained on a probabilistic decision-making task. We demonstrate that dopamine concentrations transmit a bidirectional RPE signal with symmetrical encoding of positive and negative RPEs. Our findings strengthen the case that changes in dopamine concentration alone are sufficient to encode the full range of RPEs necessary for reinforcement learning.
Rats emit ultrasonic vocalizations (USVs) that are thought to serve as situation-dependent affective signals and accomplish important communicative functions. In appetitive situations, rats produce 50 kHz USVs, whereas 22 kHz USVs occur in aversive situations. Reception of 50 kHz USVs induces social approach behavior, while 22 kHz USVs lead to freezing behavior. These opposite behavioral responses are paralleled by distinct brain activation patterns, with 50 kHz USVs, but not 22 kHz USVs, activating neurons in the nucleus accumbens (NAcc). The NAcc mediates appetitive behavior and is critically modulated by dopaminergic afferents that are known to encode the value of reward. Therefore, we hypothesized that 50 kHz USVs, but not 22 kHz USVs, elicit NAcc dopamine release. While recording dopamine signaling with fast-scan cyclic voltammetry, freely moving rats were exposed to playback of four acoustic stimuli via an ultrasonic speaker in random order: (1) 50 kHz USVs, (2) 22 kHz USVs, (3) time-and amplitude-matched white noise, and (4) background noise. Only presentation of 50 kHz USVs induced phasic dopamine release and elicited approach behavior toward the speaker. Both of these effects, neurochemical and behavioral, were most pronounced during initial playback, but then declined rapidly with subsequent presentations, indicating a close temporal relationship between the two measures. Moreover, the magnitudes of these effects during initial playback were significantly correlated. Collectively, our findings show that NAcc dopamine release encodes pro-social 50 kHz USVs, but not alarming 22 kHz USVs. Thus, our results support the hypothesis that these call types are processed in distinct neuroanatomical regions and establish a functional link between pro-social communicative signals and reward-related neurotransmission.
Cue- and reward-evoked phasic dopamine activity during Pavlovian and operant conditioning paradigms is well correlated with reward-prediction errors from formal reinforcement learning models, which feature teaching signals in the form of discrepancies between actual and expected reward outcomes. Additionally, in learning tasks where conditioned cues probabilistically predict rewards, dopamine neurons show sustained cue-evoked responses that are correlated with the variance of reward and are maximal to cues predicting rewards with a probability of 0.5. Therefore, it has been suggested that sustained dopamine activity after cue presentation encodes the uncertainty of impending reward delivery. In the current study we examined the acquisition and maintenance of these neural correlates using fast-scan cyclic voltammetry in rats implanted with carbon fiber electrodes in the nucleus accumbens core during probabilistic Pavlovian conditioning. The advantage of this technique is that we can sample from the same animal and recording location throughout learning with single trial resolution. We report that dopamine release in the nucleus accumbens core contains correlates of both expected value and variance. A quantitative analysis of these signals throughout learning, and during the ongoing updating process after learning in probabilistic conditions, demonstrates that these correlates are dynamically encoded during these phases. Peak CS-evoked responses are correlated with expected value and predominate during early learning while a variance-correlated sustained CS signal develops during the post-asymptotic updating phase.
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