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 (possibly only when better than expected – see Bayer and Glimcher, 2005) and a weighted average of previous rewards, project to both the ACC and OFC and could be used to guide reward seeking and choice (Berger, Trottier, Verney, Gaspar and Alvarez, 1988; Williams and Goldman-Rakic, 1998). The neuromodulator noradrenaline, which receives direct input from both the ACC and OFC, has also been implicated in helping animals either engage with a particular behaviour or to search for a new mode of response (Aston-Jones and Cohen, 2005; Yu and Dayan, 2005). Other regions, such as posterior cingulate cortex and parts of parietal cortex, are also sensitive to reward probability and value (McCoy and Platt, 2005; Sugrue, Corrado and Newsome, 2004).
