The notion is that in area CA3, synapses forming the recurrent connection from other area CA3 pyramidal cells, and the perforant path input from the entorhinal cortex have their effective strengths reduced, but are rendered more labile. The ability (M) of neuromodulators to control the course of activity by regulating which of a number of gross pathways determines the activity of neurons is a common scheme. There are also other potential neuromodulatory routes for this influence: for instance, ACh helps regulate oscillations ([N], a critical dynamical effect of neuromodulators in many circumstances)

that simultaneously affect multiple sub-regions of the hippocampal formation (Buzsáki, 2002). It has been suggested that different pathways between these regions are Forskolin ic50 dominant at different selleck chemical phases of theta (Hasselmo et al., 2002),

providing a route for neuromodulatory effects. ACh is also capable of influencing shorter-term storage in working memory (Klink and Alonso, 1997; Hasselmo, 2006). The (O) effects of neuromodulators on various timescales of plasticity are among their most influential. Another obvious issue for memory is whether or not an input actually merits long term storage. One way to assess this is to consider its affective consequences, bearing in mind that they may only be evident after some time has passed. Given the evidence adduced above, it should come as no surprise to find that dopamine is implicated in the later phases of hippocampal storage (Lisman et al., 2011), although this is a rather different function from the plasticity engendered by dopaminergically coded prediction errors that we discussed above as underpinning the learning of appetitive predictions. The extended timescale over which such assessments might be relevant could result in findings such as that patterns that are only incidentally correlated with the delivery of unexpected Tryptophan synthase reward are also preferentially stored (Wittmann et al., 2005). Boosted storage can perhaps be seen as

an instance of internal, cognitive, “approach” to a stimulus based on the reward it predicts (Adcock et al., 2006), matching the internal action of storage in working memory to the externally directed engagement actions that we mentioned above. An informationally more complex case for neuromodulatory influences on plasticity comes in the context of animal conditioning experiments (Gallistel and Gibbon, 2000; Pearce and Hall, 1980), which have particularly centered on the model-free Pavlovian case. Psychological notions, such as that the associability of a stimulus varies with the degree of surprise with which it is endowed (Pearce and Hall, 1980), can be translated into computational terms as the relative learning rate of a stimulus being determined by its predictive uncertainty (Dayan et al.