  We are concerned about the main encoding granule cells (GCs) in the
hippocampal dentate gyrus (DG). Young immature GCs (imGCs) appear through adult
neurogenesis. In comparison to the mature GCs (mGCs) (born during development),
the imGCs show high activation due to lower firing threshold. On the other
hand, they receive low excitatory drive from the entorhinal cortex via
perforant paths and from the hilar mossy cells with lower connection
probability $p_c~(=20~x~\%)$ ($x:$ synaptic connectivity fraction; $ 0 \leq x
\leq 1$) than the mGCs with the connection probability $p_c~(=20~\%)$. Thus,
the effect of low excitatory innervation (reducing activation degree) for the
imGCs counteracts the effect of their high excitability. We consider a spiking
neural network for the DG, incorporating both the mGCs and the imGCs. With
decreasing $x$ from 1 to 0, we investigate the effect of young adult-born imGCs
on the sparsely synchronized rhythms (SSRs) of the GCs (mGCs, imGC, and whole
GCs). For each $x$, population and individual firing behaviors in the SSRs are
characterized in terms of the amplitude measure ${\cal M}_a^{(X)}$
($X=m,~im,~w$ for the mGCs, the imGCs, and the whole GCs, respectively)
(representing the population synchronization degree) and the random
phase-locking degree ${\cal L}_d^{(X)}$ (characterizing the regularity of
individual single-cell discharges), respectively. We also note that, for $0
\leq x \leq 1,$ the mGCs and the imGCs exhibit pattern separation (i.e., a
process of transforming similar input patterns into less similar output
patterns) and pattern integration (making association between patterns),
respectively. Quantitative relationship between SSRs and pattern separation and
integration is also discussed.
