The same issue arises with Kennerley and colleagues' (2006) conclusion that the ACCs is important for encoding the value of actions based on the recent history of responses and their outcomes. Cells in dorsolateral prefrontal cortex also seem to represent these factors (Barraclough, Conroy and Lee, 2004; Genovesio, Brasted, Mitz and Wise, 2005), and activity in caudate neurons has been shown to vary as a function of the value of one of the available options (Samejima, Ueda, Doya and Kimura, 2005). Both of these regions share connections with parts of ACCs (Bates and Goldman-Rakic, 1993; Hatanaka, Tokuno, Hamada, Inase, Ito, et al., 2003; Kunishio and Haber, 1994; Takada, Nambu, Hatanaka, Tachibana, Miyachi, et al., 2004; Takada, Tokuno, Hamada, Inase, Ito, et al., 2001). Based on detailed neurophysiological studies and computational modelling, it has been shown that the firing of dopamine neurons is well predicted by theoretical descriptions of a reward prediction error signal used by reinforcement learning algorithms (Bayer and Glimcher, 2005; Doya, 2002; Montague, Dayan and Sejnowski, 1996; Schultz, 2002). These cells, which signal discrepancies between the current outcome
