Experiment on control of decision-making abilities in prefrontal cortex

Abstract

In recent years, developments in functional neuroimaging technologies have helped facilitate a clearer understanding of the activation of sites in the brain. This technology is applied to brain-computer interfaces (BCIs). Previous BCIs have primarily used information on the brain activity related to the motor system. In this study, we examined the possibility of controlling the decision-making abilities in the prefrontal cortex and consequently developed a trial BCI. In this experiment, the subject is shown two images; the subject selects one of these images and then the BCI determines the image that the subject selects on the basis of his/her brain information. This system is used to measure brain activity using fNIRS and to acquire data in real time. It preprocesses these data with a low-pass filter; the support vector machine is used as a learning model. Results of the current experiment indicate that the trial BCI developed in this study is not very accurate; however, wireless and lightweight versions of fNIRS are being developed. Results of the current experiment indicate that effective performance of the BCI can be achieved by measurements at specific sites of the brain. These results show that it is possible to develop a BCI for controlling decision-making abilities with lightweight and wireless equipment.