Effects of Action-Outcome Agency on Feedback Processing
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The current study investigated the effect of action-outcome agency, or one’s ability to guide behavior during reinforcement learning, on reward and loss processing in a gambling task. Thirty undergraduates (13 females; M age = 19.57, SD = 2.18) completed two computer gambling tasks, one designed to exhibit high levels of action-outcome agency and one with low, while attached to a 128-channel EEG system. Time-frequency event-related potential (TF- ERP) analysis was conducted on the acquired EEG data. ERP components associated with reward and loss processing were significantly dampened in the low action-outcome agency task relative to the high action-outcome agency task. Interestingly, TF-ERP analysis demonstrated a significant effect of action-outcome agency on gain-loss differences in theta but not delta frequencies, suggesting a more central role of loss processing in guidance of goal-directed behavior. These results challenge components of the well-established predicted response-outcome (PRO) model of reinforcement learning.