A detailed anatomical and mathematical model of the hippocampal formation for the generation of sharp-wave ripples and theta-nested gamma oscillations

Abstract

The mechanisms underlying the broad variety of oscillatory rhythms measured in the hippocampus during the sleep-wake cycle are not yet fully understood. In this article, we propose a computational model of the hippocampal formation based on a realistic topology and synaptic connectivity, and we analyze the effect of different changes on the network, namely the variation of synaptic conductances, the variations of the CAN channel conductance and the variation of inputs. By using a detailed simulation of intracerebral recordings, we show that this model is able to reproduce both the theta-nested gamma oscillations that are seen in awake brains and the sharp-wave ripple complexes measured during slow-wave sleep. The results of our simulations support the idea that the functional connectivity of the hippocampus, modulated by the sleep-wake variations in Acetylcholine concentration, is a key factor in controlling its rhythms.

Cell to network computational model of the epileptic human hippocampus suggests specific roles of network and channel dysfunctions in the ictal and interictal oscillations

“…In the following subsections, we will briefly present the main features of our model of the healthy hippocampus (developed in details in [Aussel et al, 2018] and whose parameters were explored in [Aussel et al, 2021]), before showing how it was modified to account for epileptic abnormalities. We will then explain thoroughly how we simulated and analyzed the behavior of this epileptic model.…”

“…The model proposed in this paper is directly inspired from our previous work ([Aussel et al, 2018]). We recall that this model covers multiple scales, from channel level mechanisms (Hodgkin-Huxley formalism, used to model classical K and Na channels, but also Calcium-Activated Nonselective cation channel -CAN) to realistic anatomy and modulated connectivity (intra and inter structures connection probabilities and gains on synaptic conductances).…”

“…The model includes more than thirty thousand neurons to represent the four main regions of the hippocampal formation: the Dentate Gyrus (DG), CA3, CA1, and the entorhinal cortex (EC). The number of neurons in each region and the proportion of excitatory and inhibitory cells were chosen in accordance with the literature ([Jinno and Kosaka, 2010], [West and Gundersen, 1990], [Patton and McNaughton, 1995], see [Aussel et al, 2018] for a detailed explanation). The neuron models we use are taken from [Giovannini et al, 2017], which themselves trace back to the work on hippocampal neurons by [Jochems and Yoshida, 2015] (and explains the role of the CAN channel in the persistent firing involved in memory).…”

“…More precisely, we extend a healthy hippocampus model of the sleep-wake cycle we previously presented in [Aussel et al, 2018] so as to include four typical pathological modifications of the hippocampus seen in medial temporal lobe epilepsies. In particular, we focus on hippocampal sclerosis ([Blümcke et al, 2013]), mossy fiber sprouting ( [Noebels et al, 2012]), impaired potassium dynamics ([Lerche et al, 2012], [Coulter and Steinhauser, 2015]), and impaired chloride dynamics in pyramidal neurons (and its influence on inhibition, [Huberfeld et al, 2007]).…”

Research on Network Model of Dentate Gyrus Based on Bionics

“…The dentate gyrus can separate the neural representation of similar memory through different neural circuits to optimize memory storage and subsequent retrieval [ 2 , 3 ]. The dentate gyrus can be separated by mode [ 4 , 5 ] to minimize the interference on specific memory storage and retrieval [ 6 ], and the function of precise regulation of memory can be achieved by establishing the synaptic connection between specific cells [ 7 ]. The existence of dentate gyrus makes the generation of memory organized and has important significance in the process of information coding [ 8 ] and processing and learning memory.…”