Learning theory suggests that animals attend to pertinent environmental cues when reward contingencies unexpectedly change so that learning can occur. We have previously shown that activity in basolateral nucleus of amygdala (ABL) responds to unexpected changes in reward value, consistent with unsigned prediction error signals theorized by Pearce and Hall. However, changes in activity were only present at the time of unexpected reward delivery, not during the time when the animal needed to attend to conditioned stimuli that would come to predict the reward. This suggested that a different brain area must be signaling the need for attention necessary for learning. One likely candidate to fulfill this role is the anterior cingulate cortex (ACC). To test this hypothesis, we recorded from single neurons in ACC as they performed the same behavioral task that we have used to dissociate signed from unsigned prediction errors in dopamine and ABL neurons. In this task rats chose between two fluid wells that produced varying magnitudes of and delays to reward. Consistent with previous work, we found that ACC detected errors of commission and reward prediction errors. We also found that activity during cue sampling encoded reward size, but not expected delay to reward. Finally, activity in ACC was elevated during trials in which attention was increased following unexpected up- and down-shifts in value. We conclude that ACC not only signals errors in reward prediction as previously reported, but also signals the need for enhanced neural resources during learning on trials subsequent to those errors.

Endogenous dynorphin signaling via the kappa-opioid receptor (KOR) in the nucleus accumbens (NAcc) powerfully mediates negative affective states and stress reactivity. Excitatory inputs from the hippocampus and amygdala play a fundamental role in shaping the activity of both NAcc D1 and D2 MSNs, which encode positive and negative motivational valences, respectively. However, a circuit-based mechanism by which KOR modulation of excitation-inhibition balance modifies D1 and D2 MSN activity is lacking. Here, we provide a comprehensive synaptic framework wherein presynaptic KOR inhibition decreases excitatory drive of D1 MSN activity by the amygdala, but not hippocampus. Conversely, presynaptic inhibition by KORs of inhibitory synapses on D2 MSNs enhances integration of excitatory drive by the amygdala and hippocampus. In conclusion, we describe a circuit-based mechanism showing differential gating of afferent control of D1 and D2 MSN activity by KORs in a pathway specific manner.

The ability to inhibit action is critical for everyday behavior and is affected by a variety of disorders. Behavioral control and response inhibition is thought to depend on a neural circuit that includes the dorsal striatum, yet the neural signals that lead to response inhibition and its failure are unclear. To address this issue, we recorded from neurons in rat dorsomedial striatum (mDS) in a novel task in which rats responded to a spatial cue that signaled that reward would be delivered either to the left or to the right. On 80% of trials rats were instructed to respond in the direction cued by the light (GO). On 20% of trials a second light illuminated instructing the rat to refrain from making the cued movement and move in the opposite direction (STOP). Many neurons in mDS encoded direction, firing more or less strongly for GO movements made ipsilateral or contralateral to the recording electrode. Neurons that fired more strongly for contralateral GO responses were more active when rats were faster, showed reduced activity on STOP trials, and miscoded direction on errors, suggesting that when these neurons were overly active, response inhibition failed. Neurons that decreased firing for contralateral movement were excited during trials in which the rat was required to stop the ipsilateral movement. For these neurons activity was reduced when errors were made and was negatively correlated with movement time suggesting that when these neurons were less active on STOP trials, response inhibition failed. Finally, the activity of a significant number of neurons represented a global inhibitory signal, firing more strongly during response inhibition regardless of response direction. Breakdown by cell type suggests that putative medium spiny neurons (MSNs) tended to fire more strongly under STOP trials, whereas putative interneurons exhibited both activity patterns.

Background The development of addiction is thought to reflect a transition from goal-directed to stimulus-response driven behavior, functions attributed to ventral (VS) and dorsal striatum (DS), respectively. In line with this theory, neuroadaptations that occur during prolonged drug use progress from VS to DS. Here, we ask if VS dysfunction alone, independent of drug use, can impact neural selectivity in DS. Methods To address this issue we recorded from single neurons in DS while rats performed an odor-guided choice task for differently valued rewards in rats with and without unilateral VS lesions. In a separate group of animals we used bilateral VS lesions to determine if VS was critical for performance on this task. Results We describe data showing that unilateral lesions of VS enhance neural representations in DS during performance of a task that is dependent on VS. Furthermore, we show VS is critical for reward-guided decision-making initially, but rats regain function after several days. Conclusion These results suggest that loss of VS function, independent of chronic drug use, can trigger stronger encoding in DS in a reward-guided decision-making task and that the transition from VS to DS governed behavior observed in addiction might be due, in part, to initial loss of VS function.

Neurons in the ventral striatum (VS) fire to cues that predict differently valued rewards. It is unclear whether this activity represents the value associated with the expected reward or the level of motivation induced by reward anticipation. To distinguish between the two, we trained rats on a task in which we varied value independently from motivation by manipulating the size of the reward expected on correct trials and the threat of punishment expected upon errors. We found that separate populations of neurons in VS encode expected value and motivation.