An ERPs Research Of Feedback Processing Mechanism In Gambling Task

In actual living world of human being, one of the indispensable skills of decision makers is evaluating and adjusting their behavior through feedback. However, gains and losses, magnitude of the value are key factors for individual decision making in the pursuit of profit maximization. By far, there are two different explanations about the neural mechanism of decision making feedback processing, which are the reinforcement learning theory and the motivational/affective theory. In order to discuss the feedback of individual decision making process is based on reinforcement learning theory or the motivational/affective theory, the paper will take gambling task paradigm and apply event-related brain potentials (ERPs) to discuss the active decision, force decision and supersede choice which fecdback to the processing of neural mechanism.In this research, we choose Fz, FCz and Cz electrodes to analyze FRN and P300. In active choice research, the amplitude of the FRN has no significant difference in gains and losses (p>0.05). Whereas, it shows great difference in magnitude of value (p<0.05). The amplitude of the P300 shows that there is no significant difference in gains and losses (p>0.05). However, it shows great difference in magnitude of value (p<0.05). The study indicates that in active decision situation, the FRN and P300 of frontocentral area are sensitive to the magnitude of value. In force decision making situation, the amplitude of the FRN has no significant difference in gains and losses (p>0.05). Also, it has no significant difference in magnitude of value (p>0.05). However, the amplitude of the P300 shows that there is great significant difference in gains and losses (p>0.05), but no significant difference in magnitude of value (p>0.05). The study indicates that in force decision situation, the P300 of frontocentral area are sensitive to gain and losses. In supersede choice study, the amplitude of the FRN has no significant difference in gains and losses (p>0.05). Also, it has no significant difference in magnitude of value (p>0.05). However, the amplitude of the P300 shows that there is great significant difference in magnitude of value (p>0.05). The study indicates that in supersede decision situation, the P300 of frontocentral area are sensitive to gain and losses.Through the three kind of decision condition types and the two indexes of ERPs, it may be concluded that active decision feedback result shows FRN and P300 is regulated by magnitude of value but not gains and losses, force decision feedback result shows that P300 is regulated by the gains and losses, the supersede decision feedback result shows that P300 is regulated by magnitude of value.The result of the study may provided evidence of neuroscience for reinforcement learning theory, and motivational/affective hypothesis.