Theoretically, the Pearce-Hall model predicts that events will be better attended to, and hence learned about faster, when their consequences are surprising or unexpected Pearce and Hall, This is similar to empirical observations in the rat BLA, where responses to reward are also consistent with prediction error signals that follow the Pearce-Hall model, as the same neurons fired whether the reward unexpectedly increased or decreased in value Roesch et al. These neuronal responses in the BLA differ to those measured in the striatum, which more closely approximate the Rescorla-Wagner model Rescorla and Wagner, in that the activity of neurons was higher when reward was better than expected, but showed suppression when reward was worse than expected Delgado et al. Neurons within the CeN, however, have only been shown to fire specifically to the omission of an expected reward, and no more to the surprising delivery of a reward than to an expected reward Calu et al. This is consistent with lesion studies showing that the CeN is critical for allocating attention for increased processing of events after downshifts but not upshifts in reward value Holland and Gallagher, The contrasting responses of the BLA and the CeN support the parallel processing model of amygdala function, with neuronal activity in the CeN mirroring the time course and activity of midbrain dopamine neurons. It has been proposed that negative prediction errors signaled by midbrain dopamine neurons may be conveyed to the CeN, which might then activate basal forebrain cholinergic neurons and other attention-related systems for increases in attention after omission of expected events Calu et al. Further characterization of the firing of neurons fitted to prediction error learning models within the BLA and CeN, and in structures projecting to and from these amygdala nuclei, may reveal how these two subnuclei process different representations of a CS-US association.
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