Disynaptic Effect of Hilar Cells on Pattern Separation in A Spiking Neural Network of Hippocampal Dentate Gyrus

Abstract

We investigate disynaptic effect of the hilar cells on pattern separation in a spiking neural network of the hippocampal dentate gyrus (DG). The principal granule cells (GCs) in the DG perform pattern separation, transforming similar input patterns into less-similar output patterns. The hilus consists of excitatory mossy cells (MCs) and inhibitory HIPP (hilar perforant path-associated) cells. Here, we consider the disynaptic effects of the MCs and the HIPP cells on the GCs, mediated by the inhibitory basket cells (BCs); MC BC GC and HIPP BC GC. By changing synaptic strength K^ (BC, X) ( X = MC or HIPP) from the default value K^ (BC, X)^*, we study the change in the pattern separation degree S_d. When decreasing K^ (BC, MC) or independently increasing K^ (BC, HIPP) from their default values, S_d is found to decrease (i.e., pattern separation is reduced). On the other hand, as K^ (BC, MC) is increased or independently K^ (BC, HIPP) is decreased from their default values, pattern separation becomes enhanced (i.e., S_d increases). In this way, the disynaptic effects of the MCs and the HIPP cells on the pattern separation are opposite ones. Thus, when simultaneously varying both K^ (BC, MC) and K^ (BC, HIPP), as a result of balance between the two competing disynaptic effects of the MCs and the HIPP cells, S_d forms a bell-shaped curve with an optimal maximum at their default values. Moreover, the population and individual behaviors of the sparsely synchronized rhythm of the GCs are found to be strongly correlated with the pattern separation degree S_d. Consequently, the larger the synchronization and the random phase-locking degrees of the sparsely synchronized rhythm is, the more the pattern separation becomes enhanced.

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