Mathematical Modelling of Neural Oscillations in Hippocampal Memory Networks during Waking and under General Anaesthesia

Abstract : Memory is commonly defined as the ability to encode, store, and recall information we perceived. As we experience the world, we sense stimuli, we witness events, we ascertain facts, we study concepts, and we acquire skills. Although memory is an innate and familiar human behaviour, the interior workings of the brain which provide us with such faculties are far from being fully unravelled. Experimental studies have shown that during memory tasks, certain brain structures exhibit synchronous activity which is thought to be correlated with the short-term maintenance of salient stimuli. The objective of this thesis is to use biologically-inspired mathematical modelling and simulations of neural activity to shed some light on the mechanisms enabling the emergence of these memory-related synchronous oscillations. We focus in particular on hippocampal mnemonic activity during the awake state, and the amnesia and paradoxical memory consolidation occurring under general anaesthesia. We begin by introducing a detailed model of a type of persistent-firing pyramidal neuron commonly found in the CA3 and CA1 areas of the hippocampus. Stimulated with a brief transient current pulse, the neuron displays persistent activity maintained solely by cholinergic calcium-activated non-specific (CAN) receptors, and outlasting the stimulus for long delay periods (> 30s). Our model neuron and its parameters are derived from experimental in-vitro recordings of persistent firing hippocampal neurons carried out by our collaborators Beate Knauer and Motoharu Yoshida at the Ruhr University in Bochum, Germany. Subsequently, we turn our attention to the dynamics of a population of such interconnected pyramidal-CAN neurons. We hypothesise that networks of persistent firing neurons could provide the neural mechanism for the maintenance of memory-related hippocampal oscillations. The firing patterns elicited by this network are in accord with both experimental recordings and modelling studies. In addition, the network displays self-sustained oscillatory activity in the theta frequency. When connecting the pyramidal-CAN network to fast-spiking inhibitory interneurons, the dynamics of the model reveal that feedback inhibition improves the robustness of fast theta oscillations, by tightening the synchronisation of the pyramidal CAN neurons. We demonstrate that, in the model, the frequency and spectral power of the oscillations are modulated solely by the cholinergic mechanisms mediating the intrinsic persistent firing, allowing for a wide range of oscillation rates within the theta band. This is a biologically plausible mechanism for the maintenance of synchronous theta oscillations in the hippocampus which aims at extending the traditional models of septum-driven hippocampal rhythmic activity. In addition, we study the disruptive effects of general anaesthesia on hippocampal gamma-frequency oscillations. We present an in-depth study of the action of anaesthesia on neural oscillations by introducing a new computational model which takes into account the four main effects of the anaesthetic agent propofol GABAergic hippocampal interneurons. Our results indicate that propofol-mediated tonic inhibition contributes to enhancing network synchronisation in a network of hippocampal interneurons. This enhanced synchronisation could provide a possible mechanism supporting the occurrence of intraoperative awareness, explicit memory formation, and even paradoxical excitation under general anaesthesia, by facilitating the communication between brain structures which should supposedly be not allowed to do so when anaesthetised. In conclusion, the findings described within this thesis provide new insights into the mechanisms underlying mnemonic neural activity, both during wake and anaesthesia, opening compelling avenues for future work on clinical applications tackling neurodegenerative memory diseases, and anaesthesia monitoring
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Submitted on : Tuesday, December 12, 2017 - 12:24:32 AM
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Francesco Giovannini. Mathematical Modelling of Neural Oscillations in Hippocampal Memory Networks during Waking and under General Anaesthesia. Modeling and Simulation. Université de Lorraine, 2017. English. ⟨NNT : 2017LORR0182⟩. ⟨tel-01661465⟩

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