Prefrontal cortex and striatum are two major areas in the brain. Some research reports suggest that both areas are involved in many advanced cognitive processes, such as learning and memory, reward processing, and behavioral decision. Single-unit recording experiments have found that neurons in the prefrontal cortex and striatum can represent reward information, but it remains elusive whether and how local field potentials (LFPs) in the two areas encode reward information. To investigate these issues, we recorded LFPs simultaneously in the prefrontal cortex and striatum of two monkeys by performing a reward prediction task (a large amount reward vs a small amount reward). Recorded LFP signals were transformed from the time domain to the time and frequency domain using the method of short-time Fourier transform (STFT). We calculated the power in each frequency and time, and examined whether they were different in the two reward conditions. The results showed that power of LFPs in both the prefrontal cortex and striatum distinguished one reward condition from the other one. And the power in small reward trials was greater than that in large reward trials. Furthermore, it was found that the LFPs better encoded reward information in the beta band (14-30 Hz) rather than other frequency bands. Our results suggest that the LFPs in the prefrontal cortex and striatum effectively represent reward information, which would help to further understand functional roles of LFPs in reward processing.

It has been reported that single-unit activity in the prefrontal cortex (PFC) and striatum represented visual stimulus and reward information. But how to encode these pieces of information is quite complex from the view of single-neuron activity. Different neurons represented stimulus or reward information in different task epochs with increasing or decreasing their activities relative to their baseline firing rates. The present paper was aimed to study whether population neurons in the two brain areas could stably encode task-relevant parameters in a whole trial period. We recorded single-unit activities in the lateral PFC (LPFC) and striatum while the monkey was performing a stimulus- reward prediction task, and analyzed the neuronal activities by the method of a multi-variable regression model and the linear support vector machine. The results showed that, although proportions of task-related neurons in the two areas varied largely in the whole trial period, LPFC population neurons encoded reward and stimulus information stably and reliably. Population neurons in the striatum encoded only reward information, not stimulus information. A group of neurons in the two areas represented combined information of stimulus and reward. Further analysis showed that LPFC neurons encoded reward information for a group of relevant stimuli, while striatal neurons encoded reward information for a specific stimulus. These results suggest that both LPFC and striatal population neurons are able to stably represent task-relevant information, but from different aspects of the task. The different strategies to encode information in the LPFC and striatum suggest their different contributions in reward-based decision making.
Animals ; Corpus Striatum ; Neurons ; Prefrontal Cortex ; Primates ; Reward