, 2010; Rich and Shapiro, 2009). Cells in mPFC

also respond robustly to events, both motoric and sensory. The activity of single mPFC cells is often related to specific behaviors such as turning, running one direction on a path, and lever pressing (Cowen and McNaughton, 2007; Hyman et al., 2012; Jung et al., 1998; Narayanan and Laubach, 2006). When learning is involved, cells in mPFC can develop responses to cues or actions which predict reward (Mulder et al., 2000; Peters et al., 2005) or punishment (Gilmartin and McEchron, 2005; Laviolette et al., PARP inhibitor 2005; Takehara-Nishiuchi and McNaughton, 2008). The mPFC can also respond to salient cues, such as a tone, that are not tied to reward or punishment (e.g., Takehara-Nishiuchi and McNaughton, 2008). In many cases, the response of mPFC to motivationally salient events may reflect the adaptive anticipatory response, such as autonomic

arousal in expectation of reward. However, the mPFC also exhibits robust responses to outcomes, both positive and negative. In fact, in both monkeys and rats, anticipated reward value and actual reward value have been shown to be encoded by separate groups of neurons (Amiez et al., 2006; Cowen et al., 2012; Pratt and Mizumori, 2001; Shidara and Richmond, 2002; Sul et al., 2010). A similar picture exists for negative outcomes, though it is not clear that anticipated and actual outcomes are encoded by separate pools of neurons Dabrafenib price (Baeg et al., 2001; Gilmartin and McEchron, 2005; Takehara-Nishiuchi and McNaughton, 2008). In the framework presented here, the outcome-anticipatory Adenosine signals are part of the mPFC output whereas outcome evaluative signals serve to drive learning and as such are part of the mPFC input. Outcome feedback signals, from areas such as ventral tegmental area, insular cortex, and hypothalamus, may drive synaptic changes

via some form of reinforcement learning ( Holroyd et al., 2002). Alternatively, it has been suggested that the mPFC compares actual and expected outcomes and computes the degree of expectancy violation (i.e., “surprise”) ( Alexander and Brown, 2011). These surprise signals then drive learning within mPFC and elsewhere. As previously mentioned, anatomical evidence suggests a dorsal-ventral gradient in which dorsal mPFC is action-related whereas ventral mPFC is more emotion-related. Consistent with this anatomical gradient, a recent rodent electrophysiology study showed that responses in dorsal mPFC were strongly driven by what the animal was doing (i.e., traveling down the left or right arm of a maze) while responses in ventral mPFC showed greater sensitivity to reward outcomes (Sul et al., 2010). The dorsal mPFC also supports sustained responses in motor cortex during a delay, demonstrating a direct functional link to motor systems (Narayanan and Laubach, 2006).