A Comparison of Reward Values Encoding Function Between the Prefrontal Cortex and Striatum in Monkey

Abstract

Reward prediction is essential for learning behavior and decision-making process in the brain. It is well known that neurons in both prefrontal cortex (PFC) and striatum are involved in encoding reward values. The difference in reward coding function between these two brain regions remains unclear. In this work, local field potentials (LFPs) were recorded in the lateral PFC and striatum of a male monkey while performing a reward prediction task. A pattern classification method was used to characterize the function of PFC and striatum for encoding reward values. We used two different feature extraction methods to extract input features to two different classifiers, including random forest (RF) and support vector machine (SVM). We optimized the SVM using the particle swarm optimization (PSO) algorithm. The results suggested that even in a model-based process, the neurons in striatum are capable of encoding more reward information than those in PFC.