In addition to being thoroughly characterized at a cellular and circuit level (Zhao et al., 2008), neurogenesis has been a target of numerous computational
and behavioral studies (Aimone and Gage, 2011, Deng et al., 2010 and Inokuchi, 2011). Increasingly, the functional theories of neurogenesis have coalesced around several aspects of new neuron maturation (Aimone et al., 2010a). First, immature granule cells (GCs) show an increased intrinsic excitability and plasticity that distinguishes them from the less plastic and relatively silent older GC population (Espósito et al., 2005 and Ge et al., 2007). Second, this immature state of GCs represents a critical developmental period in which they encode significant features of their environments (Kee et al., 2007 and Tashiro et al., 2007). Finally, the process selleck kinase inhibitor of neurogenesis is a key component of the pattern separation function of the dentate gyrus (DG) (Clelland et al., 2009 and Sahay et al., 2011). Nevertheless, in many respects, this broader understanding of the DG’s function and how it relates to the hippocampus (Treves et al., 2008) has become the limiting factor to our understanding of the function of adult neurogenesis (Aimone et al., 2010b and Alme et al., 2010). We believe that MEK inhibitor much of the uncertainty of how neurogenesis relates to DG function is in fact not due to a misunderstanding
of the experimental and theoretical findings; rather, it is a challenge of description. Increasingly, descriptions of neurogenesis function have relied on the loaded term “pattern separation,” originally a computational concept that has taken
on somewhat different meanings depending on its context. In this opinion piece, we hope to clarify our interpretation of the function of neurogenesis, and more generally the DG, by describing neurogenesis and DG function using a more consistent framework. To understand the rationale for the predicted separation role for the DG, it is useful to briefly review the history of the pattern separation hypothesis (Figure 1). Although the no early hippocampal modeling work of David Marr did not explicitly consider a separation role for the DG, he did predict that the recurrent axons within CA3 would be ideal for forming memory representations (Marr, 1971). Subsequent work on CA3-like recurrent networks demonstrated the value of uncorrelated inputs for attractor formation (Amit et al., 1987 and Hopfield, 1982). This requirement for a separation device upstream of the CA3 was complemented by the anatomy of the DG and its unique mossy fiber projection to the CA3 (Amaral et al., 2007; Figure 1A). Despite containing several times more neurons than either the CA3 or its entorhinal cortex (EC) inputs, the projection from DG to CA3 was extremely sparse by cortical standards, with each GC only terminating on roughly a dozen CA3 neurons.