Semiconductor laser for modelling and controlling spiking cells and networks

Abstract : Excitable systems are everywhere in Nature, and among them the neuron, which responds to an external stimulus with an all-or-none type of response, is often regarded as the most typical example. This excitability behaviour is clearly established as to be one of the underlying operating mechanisms of the nervous system and its analysis in model systems (being them mathematical of physical) can, from one hand, shed some light on the dynamics of neural networks, and from the other, open novel ways for a neuro-mimetic treatment of information. The work presented in this PhD thesis was realized in this perspective. In this dissertation we will consider systems based on semiconductor lasers both for modelling excitable systems or coupled neuromorphic networks and for controlling (in an optogenetic outlook) ionic channels that are involved in the emission of action potentials of neurons in mammals. During the first chapter, we will briefly present the dynamical concepts on which we will build our understanding for the rest of the manuscript. Thereafter, we will describe the context of this work from the point of view of synchronized systems, in particular excitable cells. Finally, we will discuss in this context the applications potential of this work, namely the possibility of using “neuromimetic” photonic systems as a was to treat information. In chapter 2 we will firstly analyse from a theoretical and bibliographical standpoint the excitable character of a laser with coherent injection. Later, we will firstly detail our results, firstly experimental and subsequently numerical and theoretical, on the response of this “neuromimetic” system to perturbations repeated in time. Whereas the simplified mathematical model envisions an integrator behaviour in response to repeated perturbations, we will show that the system often acts as a resonator, thus imparting the remarkable property of being able to emit a single pulse only if it receives two perturbations that are separated by a specific time interval. We will also illustrate how this system can convert perturbations of different intensity in a series of all identical pulses whose number depends on the intensity of the incoming perturbation. In the third chapter we will analyse, first experimentally and later numerically and theoretically, the dynamical behaviour of a network of coupled semiconductor lasers in a slow-fast chaotic regime. We will rely on a previous study documenting that a single such element can present a neuromimetic dynamics (in particular, the emission of chaotic pulses originating from a canard phenomenon). Surprisingly for a system having such a large number of degrees of freedom, we observe a dynamics which seems low dimensional chaotic. We will examine the impact of statistical properties of the selected population on the dynamics, and we will link our experimental and numerical observations to the existence of a slow manifold for the mean field, computable analytically, and towards whom the dynamics converges thanks to the slow-fact nature of the system. Finally, in chapter 4 we will present a short experimental study on the response of biological cells to light perturbations. Indeed, optogenetic techniques enables to render the cells (in particular neurons) sensitive to light due to the optical control of the opening and closing of ionic channels. Hence, after having studied in the previous chapters optical systems on the basis of observations derived from biological systems, we will physically transfer an optical system towards a biological one. Here we lay the groundwork of a photonic system which allows, with a moderate complexity, to realize cell measurements in response to spatially localized optical perturbations.
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Axel Dolcemascolo. Semiconductor laser for modelling and controlling spiking cells and networks. Physics [physics]. Université Côte d'Azur, 2018. English. ⟨NNT : 2018AZUR4208⟩. ⟨tel-02100034⟩

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