Coordinated Activity of Ventral Tegmental Neurons Adapts to Appetitive and Aversive Learning

Our understanding of how value-related information is encoded in the ventral tegmental area (VTA) is based mainly on the responses of individual putative dopamine neurons. In contrast to cortical areas, the nature of coordinated interactions between groups of VTA neurons during motivated behavior is largely unknown. These interactions can strongly affect information processing, highlighting the importance of investigating network level activity. We recorded the activity of multiple single units and local field potentials (LFP) in the VTA during a task in which rats learned to associate novel stimuli with different outcomes. We found that coordinated activity of VTA units with either putative dopamine or GABA waveforms was influenced differently by rewarding versus aversive outcomes. Specifically, after learning, stimuli paired with a rewarding outcome increased the correlation in activity levels between unit pairs whereas stimuli paired with an aversive outcome decreased the correlation. Paired single unit responses also became more redundant after learning. These response patterns flexibly tracked the reversal of contingencies, suggesting that learning is associated with changing correlations and enhanced functional connectivity between VTA neurons. Analysis of LFP recorded simultaneously with unit activity showed an increase in the power of theta oscillations when stimuli predicted reward but not an aversive outcome. With learning, a higher proportion of putative GABA units were phase locked to the theta oscillations than putative dopamine units. These patterns also adapted when task contingencies were changed. Taken together, these data demonstrate that VTA neurons organize flexibly as functional networks to support appetitive and aversive learning

Reward Anticipation Is Encoded Differently by Adolescent Ventral Tegmental Area Neurons

Background Elucidating the neurobiology of the adolescent brain is fundamental to our understanding of the etiology of psychiatric disorders such as schizophrenia and addiction, the symptoms of which often manifest during this developmental period. Dopamine neurons in the ventral tegmental area (VTA) are strongly implicated in adolescent behavioral and psychiatric vulnerabilities, but little is known about how adolescent VTA neurons encode information during motivated behavior. Methods We recorded daily from VTA neurons in adolescent and adult rats during learning and maintenance of a cued, reward-motivated instrumental task and extinction from this task. Results During performance of the same motivated behavior, identical events were encoded differently by adult and adolescent VTA neurons. Adolescent VTA neurons with dopamine-like characteristics lacked a reward anticipation signal and showed a smaller response to reward delivery compared with adults. After extinction, however, these neurons maintained a strong phasic response to cues formerly predictive of reward opportunity. Conclusions Anticipatory neuronal activity in the VTA supports preparatory attention and is implicated in error prediction signaling. Absence of this activity, combined with persistent representations of previously rewarded experiences, may provide a mechanism for rash decision making in adolescents

Change in LFP power pooled across subjects.

<p>(<b>A–D</b>) Spectrograms aligned to CS_AP and CS_AV and data depict group average baseline (−1.5–0 sec before CS) normalized power per frequency bin according to the color scale at the right. Frequencies between 0.7 and 50 Hz are displayed with top row representing CS_AP and bottom row representing CS_AV. (<b>E</b>) Change in theta power (4–8 Hz) during a 4 second window aligned to each CS onset. Data are depicted as mean + SEM in each session. The initial associations (pre-reversal) were presented during sessions 1–8 and are depicted with the grey background. The reversed association was presented during session 9–16 and is depicted with the white background. The arrow marks the reversal and the color legend is depicted in the upper left corner. As the most prominent changes in LFP oscillations were in the theta range, we more closely examined the normalized power of theta band oscillations. (<b>F</b>) Changes in LFP power within the session 9. Data in each spectrogram are depicted as the average over the first 10 trials. Similar format and same color scale as (A–D). The CS_AP and CS_AV were reversed in session 9. Spectrograms of the first 10 trials of CS_AP and CS_AV delivery showed opposite patterns as the pre-reversal sessions, indicating that power modulations were not tracking the reversal in associations (left). In the last 10 trials, the new CS_AP evoked an increase in power while the new CS_AV modulated power in a similar fashion as pre-reversal sessions, indicating the power modulations were now tracking the reversal of associations.</p

Task, behavior, and single unit activity.

<p>(<b>A</b>) Schematic representing the two conditioned associations in the initial segment of the task (left: sessions 1–8) and following the reversal of the initially conditioned associations (right: sessions 9–16). A tone or light CS was randomly presented for 10 sec and, upon termination of the stimulus, an aversive (mild electrical shock; 180 ms, 0.2 mA) or appetitive (sugar pellet 45 mg) outcome was delivered to the animal. Following 8 consecutive sessions of conditioning, these initial associations were reversed. (<b>B</b>) Behavioral performance. Data presented as mean + SEM. The behavioral index (<i>R</i>) is the ratio of nose pokes in the food trough during either CS presentation (10 sec, 30 trials) relative to nose pokes in the food trough during the baseline period (10 sec, 60 trials). (<b>C</b>) Population activity of VTA units. Data presented as mean + SEM. Empty bars represent the pre-stimulus baseline window (0.5 sec: −1 to −0.5 sec), filled bars represent the stimulus delivery window (0.5 sec: 0 to 0.5 sec). Data are plotted separately for CS_AP and CS_AV (left and right, respectively). Note that in the first conditioning session (session 1), population responses during CS_AP and CS_AV presentation did not differ from baseline levels. In the final sessions of the initial association (session 8) and reversal sessions (session 16), VTA population responses increased during CS_AP presentation and decreased during CS_AV presentation. Note that there were no statistically significant differences of firing rates during baseline period across session.</p

Phase locking of spike discharge to the theta rhythm.

<p>(<b>A–D</b>) Phase locking between neural discharge and LFP oscillations. Circular plots depict the number of units that were significantly phase-locked and the mean preferred angle of each unit in units of radians (bin size = π/12). Color legend is depicted at left of top row. Inset bar graphs depict the percentage of the units phased locked to the LFP theta rhythm during each CS. In session 1 (<b>A</b>), outer edge of circle inset = 3 units. In session 8 (<b>B</b>), outer edge of circle inset = 5 units. In session 9 (<b>C</b>), outer edge of circle inset = 5 units. In session 16 (<b>D</b>), outer edge of circle inset = 8 units. (<b>E–H</b>) Theta phase locking of putative dopamine and non-dopamine VTA units. The percentage of units phase locked to the theta oscillation during CS_AP and CS_AV presentation. Units were classified as putative dopaminergic or non-dopaminergic units. Data are presented with same conventions as insets from A–D.</p

Correlated discharge between pairs of VTA units.

<p>(<b>A–C</b>) The normalized mean spike count correlation between pairs of simultaneously recorded units aligned to onset of either CS. Data are depicted as mean ± SEM (solid line = mean, shaded area = SEM). Color legend for A–C appears in upper left corner of A. (<b>D</b>) The percentage of unit pairs with statistically significant noise correlations. Data are presented as the percentage of simultaneously recorded pairs of units, which had a significant correlation in the mean subtracted spike count during each session. (<b>E</b>) Magnitude of noise correlations for significant pairs during sessions 1, 8, and 16. Data are presented as the mean noise correlation + SEM between pairs of VTA units in each session.</p

Baseline normalized information ratio (<i>IR</i>).

<p>(<b>A–D</b>) The change in <i>IR</i> aligned to CS onset. Data are depicted as mean <i>IR</i> in each time bin according to the color scale at the right. Each row represents one simultaneously recorded VTA unit pair. The data are sorted by post-stimulus normalized IR value. Each VTA unit pair is depicted in session 1 (<b>A</b>), 8 (<b>B</b>), 9 (<b>C</b>) and 16 (<b>D</b>). Note 1) the abrupt onset of the effect and 2) the uniformity of the effect, which increases dramatically from early to later sessions. <b>(E)</b> Mean information ratio of pairs of simultaneously recorded VTA units. Data are depicted as mean ± SEM and baseline normalized to 0 for sessions 1, 8, 9 and 16.</p

Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility

The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action-outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action-outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action. Copyright ©2017 the authors1

New insights into the specificity and plasticity of reward and aversion encoding in the mesolimbic system.

The mesocorticolimbic system, consisting, at its core, of the ventral tegmental area, the nucleus accumbens, and medial prefrontal cortex, has historically been investigated primarily for its role in positively motivated behaviors and reinforcement learning, and its dysfunction in addiction, schizophrenia, depression, and other mood disorders. Recently, researchers have undertaken a more comprehensive analysis of this system, including its role in not only reward but also punishment, as well as in both positive and negative reinforcement. This focus has been facilitated by new anatomical, physiological, and behavioral approaches to delineate functional circuits underlying behaviors and to determine how this system flexibly encodes and responds to positive and negative states and events, beyond simple associative learning. This review is a summary of topics covered in a mini-symposium at the 2013 Society for Neuroscience annual meeting

New insights into the specificity and plasticity of reward and aversion encoding in the mesolimbic system.

The mesocorticolimbic system, consisting, at its core, of the ventral tegmental area, the nucleus accumbens, and medial prefrontal cortex, has historically been investigated primarily for its role in positively motivated behaviors and reinforcement learning, and its dysfunction in addiction, schizophrenia, depression, and other mood disorders. Recently, researchers have undertaken a more comprehensive analysis of this system, including its role in not only reward but also punishment, as well as in both positive and negative reinforcement. This focus has been facilitated by new anatomical, physiological, and behavioral approaches to delineate functional circuits underlying behaviors and to determine how this system flexibly encodes and responds to positive and negative states and events, beyond simple associative learning. This review is a summary of topics covered in a mini-symposium at the 2013 Society for Neuroscience annual meeting