It is likely that changes in baseline DA levels are important for understanding the effects of dopaminergic agents on the ERN. This has been proposed in a new computational model, which builds upon the RL-ERN model, and states that basal DA levels can have a significant effect on reinforcement learning due to possible range restrictions on phasic DA bursts (Frank, 2005). For example, individuals with Parkinson’s disease who are being treated with DA agonists may have elevated tonic DA levels that prevent effective phasic dips, which could hinder negative reinforcement learning. Since these phasic dips characterize the ERN signal, the ERN amplitude would be diminished in Parkinson’s disease patients, which is consistent with the literature (Falkenstein, Hielscher et al., 2001; Ito & Kitagawa, 2006; Stemmer, Segalowitz, Dywan, Panisset, & Melmed, 2007).
