Psychological and microeconomic studies have shown that outcome values are discounted by imposed delays. The effect, called temporal discounting, is demonstrated typically by choice preferences for sooner smaller rewards over later larger rewards. However, it is unclear whether temporal discounting occurs during the decision process when differently delayed reward outcomes are compared or during predictions of reward delays by pavlovian conditioned stimuli without choice. To address this issue, we investigated the temporal discounting behavior in a choice situation and studied the effects of reward delay on the value signals of dopamine neurons. The choice behavior confirmed hyperbolic discounting of reward value by delays on the order of seconds. Reward delay reduced the responses of dopamine neurons to pavlovian conditioned stimuli according to a hyperbolic decay function similar to that observed in choice behavior. Moreover, the stimulus responses increased with larger reward magnitudes, suggesting that both delay and magnitude constituted viable components of dopamine value signals. In contrast, dopamine responses to the reward itself increased with longer delays, possibly reflecting temporal uncertainty and partial learning. These dopamine reward value signals might serve as useful inputs for brain mechanisms involved in economic choices between delayed rewards.

Animals depend on a large variety of rewards but their brains have a limited dynamic coding range. When rewards are uncertain, neuronal coding needs to cover a wide range of possible rewards. However, when reward is likely to occur within a specific range, focusing the sensitivity on the predicted range would optimize the discrimination of small reward differences. One way to overcome the trade-off between wide coverage and optimal discrimination is to adapt reward sensitivity dynamically to the available rewards. We investigated how changes in reward distribution influenced the coding of reward in the orbitofrontal cortex. Animals performed an oculomotor task in which a fixation cue predicted the SD of the probability distribution of juice volumes, while the expected mean volume was kept constant. A subsequent cue specified the exact juice volume obtained for a correct saccade response. Population responses of orbitofrontal neurons that reflected the predicted juice volume showed adaptation to the reward distribution. Statistical tests on individual responses revealed that a quarter of value-coding neurons shifted the reward sensitivity slope significantly between two reward distributions, whereas the remaining neurons showed insignificant change or lack of adaptation. Adaptations became more prominent when reward distributions changed less frequently, indicating time constraints for assessing reward distributions and adjusting neuronal sensitivity. The observed neuronal adaptation would optimize discrimination and contribute to the efficient coding of a large variety of potential rewards by neurons with limited dynamic range.

The lateral prefrontal cortex (LPFC) has been implicated in visuospatial processing, especially when it is required to hold spatial information during a delay period. It has also been reported that the LPFC receives information about expected reward outcome. However, the interaction between visuospatial processing and reward processing is still unclear because the two types of processing could not be dissociated in conventional delayed response tasks. To examine this, we used a memory-guided saccade task with an asymmetric reward schedule and recorded 228 LPFC neurons. The position of the target cue indicated the spatial location for the following saccade and the color of the target cue indicated the reward outcome for a correct saccade. Activity of LPFC was classified into three main types: S-type activity carried only spatial signals, R-type activity carried only reward signals, and SR-type activity carried both. Therefore only SR-type cells were potentially involved in both visuospatial processing and reward processing. SR-type activity was enhanced (SR+) or depressed (SR-) by the reward expectation. The spatial discriminability as expressed by the transmitted information was improved by reward expectation in SR+ type. In contrast, when reward information was coded by an increase of activity in the reward-absent condition (SR- type), it did not improve the spatial representation. This activity appeared to be involved in gaze fixation. These results extend previous findings suggesting that the LPFC exerts dual influences based on predicted reward outcome: improvement of memory-guided saccades (when reward is expected) and suppression of inappropriate behavior (when reward is not expected).

Neuronal reward valuations provide the physiological basis for economic behaviour. Yet, how such valuations are converted to economic decisions remains unclear. Here we show that the dorsolateral prefrontal cortex (DLPFC) implements a flexible value code based on object-specific valuations by single neurons. As monkeys perform a reward-based foraging task, individual DLPFC neurons signal the value of specific choice objects derived from recent experience. These neuronal object values satisfy principles of competitive choice mechanisms, track performance fluctuations and follow predictions of a classical behavioural model (Herrnstein’s matching law). Individual neurons dynamically encode both, the updating of object values from recently experienced rewards, and their subsequent conversion to object choices during decision-making. Decoding from unselected populations enables a read-out of motivational and decision variables not emphasized by individual neurons. These findings suggest a dynamic single-neuron and population value code in DLPFC that advances from reward experiences to economic object values and future choices.