The contribution of relative activation levels between populations of cells to network activity in a large-scale biologically realistic model of the hippocampus

Abstract

In previously published work, we showed the progress we’ve made towards creating a large-scale, biologically realistic model of the rat hippocampus, starting with the projection from entorhinal cortex (EC) to the dentate gyrus (DG). We created the model to help us study how the common components of neurobiological systems in mammals – large numbers of neurons with intricate, branching morphologies; active, non-linear membrane properties; non-uniform distributions throughout membrane surface of these non-linear conductances; non-uniform and topographic connectivity between pre- and post-synaptic neurons; and activity-dependent changes in synaptic function – combine and contribute to give a particular brain region its “neural processing” properties. In this work, we report on the results of a series of simulations we ran to test the role of feed-forward and feedback inhibition in the dentate gyrus. We find that a) the system shows rhythmic bands of activity only in the presence of feedback inhibition, b) that the frequency of rhythmicity increases with increasing amounts of feed-forward inhibition, c) that it decreases with increasing amounts of feedback inhibition, and d) that strong excitatory inputs appear to enhance and prolong the amount of rhythmicity in the system.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

“…Computational multi-scale and large-scale modeling are increasingly used to gain insights on brain functions and dysfunctions (Dyhrfjeld-Johnsen et al, 2007 ; Bouteiller et al, 2011 ; Hendrickson et al, 2013 ; Mattioni and Le Novère, 2013 ; Dougherty et al, 2014 ; Yu et al, 2014 ). At the synaptic level, a large number of receptors, mechanisms, and pathways modulate synaptic strength, function, and plasticity.…”