Dissertations / Theses on the topic 'Excitation (physiologie) – Modèles mathématiques'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Excitation (physiologie) – Modèles mathématiques.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
Paragot, Paul. "Analyse numérique du système d'équations Poisson-Nernst Planck pour étudier la propagation d'un signal transitoire dans les neurones." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5020.
Full textNeuroscientific questions about dendrites include understanding their structural plasticityin response to learning and how they integrate signals. Researchers aim to unravel these aspects to enhance our understanding of neural function and its complexities. This thesis aims at offering numerical insights concerning voltage and ionic dynamics in dendrites. Our primary focus is on modeling neuronal excitation, particularly in dendritic small compartments. We address ionic dynamics following the influx of nerve signals from synapses, including dendritic spines. To accurately represent their small scale, we solve the well-known Poisson-Nernst-Planck (PNP) system of equations, within this real application. The PNP system is widely recognized as the standard model for characterizing the electrodiffusion phenomenon of ions in electrolytes, including dendritic structures. This non-linear system presents challenges in both modeling and computation due to the presence of stiff boundary layers (BL). We begin by proposing numerical schemes based on the Discrete Duality Finite Volumes method (DDFV) to solve the PNP system. This method enables local mesh refinement at the BL, using general meshes. This approach facilitates solving the system on a 2D domain that represents the geometry of dendritic arborization. Additionally, we employ numerical schemes that preserve the positivity of ionic concentrations. Chapters 1 and 2 present the PNP system and the DDFV method along with its discrete operators. Chapter 2 presents a "linear" coupling of equations and investigate its associated numerical scheme. This coupling poses convergence challenges, where we demonstrate its limitations through numerical results. Chapter 3 introduces a "nonlinear" coupling, which enables accurate numerical resolution of the PNP system. Both of couplings are performed using DDFV method. However, in Chapter 3, we demonstrate the accuracy of the DDFV scheme, achieving second-order accuracy in space. Furthermore, we simulate a test case involving the BL. Finally, we apply the DDFV scheme to the geometry of dendritic spines and discuss our numerical simulations by comparing them with 1D existing simulations in the literature. Our approach considers the complexities of 2D dendritic structures. We also introduce two original configurations of dendrites, providing insights into how dendritic spines influence each other, revealing the extent of their mutual influence. Our simulations show the propagation distance of ionic influx during synaptic connections. In Chapter 4, we solve the PNP system over a 2D multi-domain consisting of a membrane, an internal and external medium. This approach allows the modeling of voltage dynamics in a more realistic way, and further helps checking consistency of the results in Chapter 3. To achieve this, we employ the FreeFem++ software to solve the PNP system within this 2D context. We present simulations that correspond to the results obtained in Chapter 3, demonstrating linear summation in a dendrite bifurcation. Furthermore, we investigate signal summation by adding inputs to the membrane of a dendritic branch. We identify an excitability threshold where the voltage dynamics are significantly influenced by the number of inputs. Finally, we also offer numerical illustrations of the BL within the intracellular medium, observing small fluctuations. These results are preliminary, aiming to provide insights into understanding dendritic dynamics. Chapter 5 presents collaborative work conducted during the Cemracs 2022. We focus on a composite finite volume scheme where we aim to derive the Euler equations with source terms on unstructured meshes
Liautard, Camille. "Mécanismes physiopathologiques dans deux modèles murins d'épilepsie liée à la mutation des canaux sodiques 1. 1." Nice, 2012. http://www.theses.fr/2012NICE4080.
Full textDravet Syndrome (DS), a very severe pharmaco-resistant epilepsy of infancy, and Genetic Epilepsy with febrile Seizures Plus (GEFS+), presenting a moderate phenotype, are two epilepsies linked to an heterozygous mutation of SCN1A, the gene coding for voltage-dependent sodium channels 1. 1. To better understand the pathogenic mechanisms in these epilepsies, electrophysiological recordings in brain slices from two animal models with altered SCN1A were performed. Our data have shown a specific implication of the hippocampus in the generation of epileptic seizures in mice models of DS. This structure presents a hyperexcitability of the neuronal network due to an inhibitory transmission defect linked to the Nav1. 1 loss of function. In epileptogenic conditions, an activity specific to our model was identified. In GEFS+ mice models, the thalamo-cortical network, implied in the generation of absence seizures observed in patients, was studied. A spontaneous neuronal hyperexcitability in the circuit was detected. This hyperexcitability could be correlated to the specific alteration of the inhibitory neurons present in the different structures of the circuit. This alteration may be responsible for the inhibitory transmission dysfunction observed in the thalamo-cortical network. In conclusion, we have characterized the pathogenic mechanisms present in these neuronal networks. These mice models will be used in the future to develop new therapeutic strategies
Langlois, Cyril. "L'enregistrement isotopique des tissus minéralisés des vertébrés : apports de la modélisation numérique à l'estimation des influences de la physiologie, de l'écologie et du régime alimentaire." Lyon 1, 2005. http://www.theses.fr/2005LYO10061.
Full textPerez-Guevara, Fermin. "Production de schizosaccharomyces pombe. Physiologie et paramètres de culture." Toulouse, INPT, 1992. http://www.theses.fr/1992INPT053G.
Full textGuigon, Emmanuel. "Modélisation des propriétés du cortex cérébral : comparaison entre aires visuelles, motrices et préfrontales." Châtenay-Malabry, Ecole centrale de Paris, 1993. http://www.theses.fr/1993ECAP0305.
Full textDemont-Guignard, Sophie. "Interprétation des évènements inter critiques dans les signaux EEG intra cérébraux : apport des modèles détaillés de réseaux neuronaux." Rennes 1, 2009. http://www.theses.fr/2009REN1S068.
Full textThis work deals with the analysis of particular electrophysiological events of intracerebral signals recorded in the pre-surgical evaluation of patients with drug-resistant epilepsy. Our objective was to to explain specific mechanisms involved in the interictal transient events production (epileptic spikes). In order to meet this objective, we have developed a model, at the cellular level, of neuronal network including pyramidal cells and interneurons. This model was able to bridge between recorded signals with intracerebral electrodes and network activity, from the reconstruction of the local field potential (dipole theory). This work is focused on the CA1 subfield of the hippocampus, a structure often involved in temporal lobe epilepsy. At cellular level, a new pyramidal neuron model with two compartments was proposed and validated by comparison with real intracellular recordings, in normal and pathological conditions. At network level (including a large number of cells), the model was able to simulate events that closely resemble actual epileptic spikes
Lavigne, Jennifer. "Caractérisation de l'hyperexcitabilité cérébrale dans des modèles murins d'épilepsies génétiques et développement d'une nouvelle stratégie pour la réduire." Electronic Thesis or Diss., Université Côte d'Azur (ComUE), 2016. http://theses.unice.fr/2016AZUR4053.
Full textDuring my thesis, I studied two murine models of childhood genetic epilepsies, caused by mutations of Nav1.1 channels (involved in the excitability of inhibitory neurons): Dravet Syndrome (DS), a severe and drug resistant epilepsy, and Genetic Epilepsy with Febrile Seizures Plus (GEFS+), characterized by a milder phenotype.My work is divided into three parts:- The first one revealed a process of epileptogenesis in these murine models.- In the second, I identified experimental conditions to induce epileptiform activities which are specific of the DS model in brain slices, which could allow pharmacological screens ex-vivo.- The third one was aimed at developing a new strategy to reduce cerebral hyperexcitability
Bornancin, Plantier Audrey. "Conception de modèles de prévision des crues éclair par apprentissage artificiel." Paris 6, 2013. http://www.theses.fr/2013PA066015.
Full textThe South of France is often subject to dramatic floods, which cause casualties and damages. Very intense, localized rainfalls generate fast, complex flash floods that are very difficult to forecast. The FLASH project (Flood forecasting with machine Learning, data Assimilation and Semi-pHysical modeling) was created in this context. It brings together several laboratories from different scientific fields, whose purpose is to provide the French Flood Surveillance Service (SCHAPI), with a model of flood forecasting. These forecasts will feed the real-time flood vigilance map that is available on the Internet. The main watershed under investigation here is the Gardon d’Anduze. Two types of neural networks are designed and trained to forecast the water level at Anduze from the past water levels and rainfalls. The selection of the number of hidden neurons, of the number of inputs, of some parameters of the training algorithm, and of the initialization of the networks parameters, which is crucial for estimating the generalization capability of the models, is performed by cross validation. The forecasts on the test events are satisfactory for 2 to 3 hour-ahead predictions, depending on the test event. An attempt at on-line training for model adaptation was unconvincing. Encouraging preliminary results are obtained by using rainfall estimates from radar images instead of rain gauge measurements. Finally, the methodology is applied to design predictive models of the water level of the Gardon at Remoulins, a watershed that includes the Gardon d’Anduze catchment. The level forecasts at Remoulins are statisfactory up to a prediction horizon of seven to nine hours
Hamidi, Saad. "Analyse quantitative de l'ECG ambulatoire et étude de la dynamique spatio-temporelle de la repolarisation ventriculaire : méthodes, modèles et résultats." Lyon, INSA, 1995. http://www.theses.fr/1995ISAL0112.
Full textWe propose a quantitative investigation method to study the dynamic relationship between the ambulatory ECG parameters and to evaluate their interaction mechanisms. To overcome the limitations of the sampling frequency (128Hz), we have developed two interpolation methods based on a linear and a cubic spline approach. Our methodology based on CAVIAR serial analysis method to precisely measure the QT interval and to analyze the changes in the QRS and T morphology. First we have developed a set of methods for the precise quantification of the changes of the repolarization phase during tilt tests. Using FFT spectral analysis after oversampling the ECG data at 4 Hz allowed clearly identify spectral events in the QT interval around 0. 1 Hz and a significant increase of the QT low frequency components in upright tilt position that are clearly correlated to RR interval variations and correspond to an interaction between the sympathetic system and the ventricular action potentials. In a second step we have developed methods for the modelization and the identification of the "heart" system with RR as input and QT as output. Two approaches have been assessed, respectively based on parametric models and on Neural Nets. Because of the complexity and the non-linearity of the relationship QT(t)=f(RR,t), parametric models failed in modeling precisely its dynamic behavior. Neural Nets however have proven to be adequate for approximating the non linear characteristics. The results obtained by using the latter approach allowed to characterize the dynamic behavior of the repolarization phase of patients presenting a long QT syndrome
Ravaz, Nathalie. "Croissance de populations levuriennes mixtes : effet Killer : analyse et modélisation." Toulouse, INPT, 1992. http://www.theses.fr/1992INPT058G.
Full textDugué, Pierre. "Vers un modèle de la chaîne auditive humaine dans le traitement de l’enveloppe temporelle." Rennes 1, 2008. http://www.theses.fr/2008REN1S024.
Full textThis work is aimed at studying the auditory perception of sound temporal envelope, i. E. The amplitude fluctuations whose frequency is lower than about fifty Hertz, this envelope being closely related to speech intelligibility. A physiological model of the temporal envelope processing is proposed. It is composed of two parts : the first one, from the outer ear to the inferior colliculus, generates unitary responses and the second one, from the medial geniculate body to the primary auditory cortex, neural populations responses. In addition to indices frequently used in the literature, two new indices are proposed and validated. Responses to amplitude modulation measured in the main processing centres of the temporal envelope, particularly in the human primary auditory cortex, are effectively reproduced in terms of modulation transfer functions
Soria, Martínez Rubén. "Modeling of local excitation processes in molecular nanojunctions." Thesis, Strasbourg, 2020. http://www.theses.fr/2020STRAE017.
Full textOne of the most remarkable applications of the tunnel effect is the Scanning Tunneling Microscope (STM), allowing to get the spatially and energetically map distribution of electrons on the surface of materials with nanometric resolution. Recent advances make it possible to exploit the tip of the STM as a source of local excitation of materials. The work presented in this manuscript aims to describe and model the phenomena involved in such excitation process. We present a modeling of the absorption spectra of phthalocyanine molecules lying on surfaces within the framework of the time-dependent density functional theory (TD-DFT). We show that spectroscopic analysis of the transitions between the ground state and the excited states of the molecule allows to characterize the stress inside the molecule. We also highlight a variety of excitation spectra depending on the location of the excitation of the molecule. We discuss the possibility of exploiting this phenomenon to characterize inter-molecular energy transport
Weens, William. "Mathematical modeling of liver tumor." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00779177.
Full textTlapale, Olivier Émilien. "Modelling the dynamics of contextual motion integration in the primate." Nice, 2011. https://tel.archives-ouvertes.fr/tel-00850265.
Full textThis thesis addresses the study of motion integration in the primate. Based on anatomical and functional knowledge of two cortical areas involved in motion perception, namely VI and MT, we explain various perceptual and oculo-motor responses found in the literature. First, we build a recurrent model of motion integration where a minimal number of cortical interactions are assumed. Proposing a simple readout mechanism, we are able to reproduce not only motion perception but also the dynamics of smooth pursuit eye movements on various line figures and gratings viewed through different apertures. Second, following perceptual studies concerning motion integration and physiological studies of receptive fields, we construct another dynamical model where motion information is gated by form cues. To this end, we postulate that the visual cortex takes advantage of luminance smoothness in order to gate motion diffusion. Such an elementary diffusion mechanism allows to solve various contextual problems where extrinsic junctions should be eliminated, without relying on complex junction detectors or depth computation. Finally, we rewrite the initial dynamical model into the neural field formalism in order to mathematically analyse its properties. We incorporate the multiplicative feedback term into the formalism, and prove the existence and uniqueness of the solution. To generalise the comparison against visual performance, we propose a new evaluation methodology based on human visual performance and design a database of image sequences taken from biology and psychophysics literature. Offering proper evaluation methodology is essential to continue progress in modelling the neural mechanisms involved in motion processing. To conclude, we investigate the performances of our neural field model by comparison against state of the art computer vision approaches and sequences. We find that, despite its original objective, this model gives results comparable to recent computer vision approaches of motion estimation
Fin, Loïc. "Etude et modélisation de la circulation du liquide cérébro-spinal (LCS)." Compiègne, 2002. http://www.theses.fr/2002COMP1406.
Full textGindre, Cyrille. "Modélisation des relations entraînements – performances – adaptations physiologiques chez des athlètes spécialistes de demi-fond court et de fond." Reims, 2009. http://www.theses.fr/2009REIMS011.
Full textBanister's model has been used to correlate training with performance. The basic assumption is that a dose of training contributes to both fitness and fatigue. Performance is related to the difference between these two first-order transfer functions. In the present study we tested the validity of the Banister model. For this, we followed developments of performance and physical qualities (aerobic, anaerobic, strength, speed, muscle power) with training of two group of runners specialists of long (≥ 10 km) and short (800 m) distances. The consideration of joint performance, physical and biological parameters allowed us 1) to have an integrated view of organism adaptations with training 2) to assess the validity of antagonist functions of the Banister's model. We were thus able to show that physical qualities evolution of short distances specialists on a season is done according to principles that can bring changes to the organization from those of an ecosystem consisting of different "species". Although Banister's model could be used to estimate performances, we have shown that fitness and fatigue functions may not be so valid linked to the physiological parameters of actual performance and fatigue. We conclude that the Banister's model is more a model of data than a model of structure. These results are a preliminary step in developing a new kind of model – which we proposed the foundation-for – linking training, performance and physical adaptation
Muradore, Fabien. "Optimisation de la forme pour l'amélioration de la qualité d'essuyage des pare-brise." Toulouse 3, 2004. http://www.theses.fr/2004TOU30220.
Full textBlondel, Nicolas. "Modélisation de la relation temps limite de course versus intensité relative de l'exercice : applications à l'entraînement." Lille 2, 2002. http://www.theses.fr/2002LIL2MT15.
Full textTime versus velocity relationship for running exercises : applications to training. Calculation of the relationships between time limit (tlim) and velocity (tlim=f(V)) allows the determination of the critical velocity (Cv) and anaerobic distance capacity (ADC). The aims of this thesis were 1) to explain the variability of time limit when exercise intensity is expressed as a percentage of maximal oxygen uptake (VO2max), 2) to analyse the influence of the equation used to fit the tlim=f(V) relationship on the Cv and ADC parameters, 3) to determine the effects of a high intensity training program on the Cv and ADC parameters, with regard to changes in ventilatory threshold (Vtresh) and maximal accumulated oxygen deficit. The first study demonstrated that exercise intensity individualized according to Cv and maximal velocity allowed to reduce the interindividual tlim variability. The second study confirms the influence of the mathematical model on the Cv and ADC parameters determination. The Cv calculated with the 3 component hyperbolic model was not significantly different from Vtresh. In the last study, the training program allowed a significant improvement of Cv and ADC. However, the magnitude of the improvement depends on the mathematical model used. Significant relationships were found between changes in Cv (linear model) and changes in VO2max. In an in-the-field perspective, the linear model seems to be the most interesting for coaches or physical education teachers
Benmaamar, Ramla. "Role of neuropeptide Y and its receptors in the development of epileptogenesis in mice and rats." Université Louis Pasteur (Strasbourg) (1971-2008), 2003. http://www.theses.fr/2003STR13007.
Full textPaquier, Williams. "Apprentissage ouvert de représentations et de fonctionalités en robotique : analyse, modèles et implémentation." Toulouse 3, 2004. http://www.theses.fr/2004TOU30233.
Full textAutonomous acquisition of representations and functionalities by a machine address several theoretical questions. Today’s autonomous robots are developed around a set of functionalities. Their representations of the world are deduced from the analysis and modeling of a given problem, and are initially given by the developers. This limits the learning capabilities of robots. In this thesis, we propose an approach and a system able to build open-ended representation and functionalities. This system learns through its experimentations of the environment and aims to augment a value function. Its objective consists in acting to reactivate the representations it has already learnt to connote positively. An analysis of the generalization capabilities to produce appropriate actions enable define a minimal set of properties needed by such a system. The open-ended representation system is composed of a network of homogeneous processing units and is based on position coding. The meaning of a processing unit depends on its position in the global network. This representation system presents similarities with the principle of numeration by position. A representation is given by a set of active units. This system is implemented in a suite of software called NeuSter, which is able to simulate million unit networks with billions of connections on heterogeneous clusters of POSIX machines. .
Lavigne, Jennifer. "Caractérisation de l'hyperexcitabilité cérébrale dans des modèles murins d'épilepsies génétiques et développement d'une nouvelle stratégie pour la réduire." Thesis, Université Côte d'Azur (ComUE), 2016. http://www.theses.fr/2016AZUR4053/document.
Full textDuring my thesis, I studied two murine models of childhood genetic epilepsies, caused by mutations of Nav1.1 channels (involved in the excitability of inhibitory neurons): Dravet Syndrome (DS), a severe and drug resistant epilepsy, and Genetic Epilepsy with Febrile Seizures Plus (GEFS+), characterized by a milder phenotype.My work is divided into three parts:- The first one revealed a process of epileptogenesis in these murine models.- In the second, I identified experimental conditions to induce epileptiform activities which are specific of the DS model in brain slices, which could allow pharmacological screens ex-vivo.- The third one was aimed at developing a new strategy to reduce cerebral hyperexcitability
Boutkhil, Latifa. "Coopération entre les aires corticales pour l'acquisition des capacités de reconnaissance visuelle invariante : modélisation fonctionnelle." Paris, EHESS, 2002. http://www.theses.fr/2002EHES0121.
Full textWe can recognize objects despite changes of point of view, eye’s position, size, orientation, relative position or non rigid transformations of the object itself (for instance of a newspaper or a gymnast). How this cognitive ability can be learned? That’s the question we try to answer in that work, which slots in the Cognitive Science framework, coupling neuroscience, experimental psychology, and connectionist modelling in order to take into account the richness of the biological neural substrate and of the multiplicity of the infant’s learning. We try to describe a progressive use of different kinds of sensorial and motor information, from the maturation logic of the nervous system, in the same connectionist neural network, which’s combinatory resembles in the most closer way possible to the actual visual cortex system. Within the framework of this connectionist neural network, we focus on the problem of the acquisition of perceptive visual invariants, that we modularise in a series of different learning stages from the developmental data, and we are interested in the causal sequence generated by this network, linking for instance the development of ocular exploration and the development of infant’s perceptual abilities. The first chapter reminds the conceptual foundations of connectionism, pointing particularly on the relative invariance capacities and the limits of different “classical” neural networks models. In the first part of the second chapter, we propose a review of the data from neurobiology, experimental psychology relative to the architecture of the cortical visual system, analysed from the point of view of the objects coding for an invariant recognition. A foreword to this part will present a synthesis on the principal invariant recognition theories. The second part gives a review of the connectionist solutions to the invariant visual recognition problem, naming a classification of different kinds of neural networks models, biologically plausible or not, arranged in four big classes to get perceptive invariance: I) invariance through the input coding (local or global transformation), II) invariance thanks to changes of the neural network structure or correlation methods: III) invariance to perspective by interpolation between a collection of 2D views: a)memorization of prototypes by RBF connectionists networks and b) use of the information of the spatiotemporal continuity. With the concepts of the first, the third chapter focus on the neural processing, realized by the visual cortex, considered as an architecture of a network of “cortical column” networks. Within this connectionist paradigm, a functional benchmarking of the invariance capacities of such a model of the cortical visual system is proposed from two simulations on a network of transputers applied a task of characters recognition. The relative translation and scale invariance capacities obtained, result principally from the cooperation between two networks (the first one models the temporal way of the visual cerebral cortex, dedicated more particularly to the identification task, the second one models the parietal, dedicated to the perception of space and ocular exploration). In order to reach the goal of this thesis, which consists in finding the correspondences between the development stages of the infant’s visual system and the setting of functional relations that could allow perceptive invariance, the last chapter proposes a functional modelling, that posits at the different levels of the architecture of the visual system in maturation, the neural networks models detailed previously in the second part of the second chapter to solve the problem of invariant recognition. This functional modelling make reference to the mechanisms simulated in the second part of the third chapter
Ammar, Aymen. "Modélisation et Optimisation d'un Générateur Synchrone à Double Excitation de Forte Puissance." Phd thesis, Ecole Centrale de Lille, 2013. http://tel.archives-ouvertes.fr/tel-00907699.
Full textTrichet, Rémy. "Modélisation de la résorption d'un œdème de la prostate : approche par éléments finis." Master's thesis, Université Laval, 2009. http://hdl.handle.net/20.500.11794/21067.
Full textDaya, Bassam. "Résolution numérique des équations du champ neural : étude de la coordination du mouvement par des modèles mathématiques du cervelet." Angers, 1996. http://www.theses.fr/1996ANGE0013.
Full textFerrari, Maxence. "Study of a biosonar based on the modeling of a complete chain of emission-propagation-reception with validation on sperm whales." Thesis, Amiens, 2020. http://www.theses.fr/2020AMIE0006.
Full textThe sperm whale, Physeter macrocephalus, posses the largest biosonar in nature. Made of multiple oil sac, the sperm whale sonar is tailored to function from the sea surface down to a depth of 2 kilometers, emitting click as loud as 236 dB, and is multipurpose, as it produces clicks for either echolocation or socializing. However, the liquid wax that composes is sonar, made the sperm whales the target of whaling until 1986, when the remaining population was far too small to remain commercially viable, especially with the arrival of similar products from the petrochemical industry. The sperm whale population still faces some human threats, with the ingestion of plastic and collision with boats continuing to take a toll on the sperm whale population. Studying sperm whales thus aport outcomes in multiple fields, in conservation, ethology, as well as in bioacoustics. Understanding the mechanism that rules the sperm whale sonar will help to study those other fields, as it is a key element in the sperm whale life. Aiming for that goal, this thesis analyzed three databases with distinct characteristics, obtaining the trajectory of sperm whale dives. Clicks were also linked with the sperm whale that emitted them over multiple years of recording for the same population. A simulation of propagation wave through the sperm whale head was also developed to better understand the complex mechanism of this sonar. Finally, a coupling method was developed to improve the parameters of the simulation using the recorded clicks from the aforementioned databases
Ripoll, Camille. "Modèles compartimentaux de cellules végétales : influence de la croissance sur les flux." Rouen, 1986. http://www.theses.fr/1986ROUES010.
Full textCottrell, Marie. "Modélisation de réseaux de neurones par des chaines de Markov et autres applications." Paris 11, 1988. http://www.theses.fr/1988PA112232.
Full textThe first part of the thesis consists of a paper published in IEEE Trans. Aut. Control (vol. AC-28, n°9, 1983), with J. C. Fort and G. Malgouyres. It gives two methods of calculating the exit time of a Markov chain from an attraction domain this time is extremely long, sa we use an exponential change of probability (that of large deviations theory), for a fast simulation and a non-standard approximation by diffusion. The second part includes two papers published with J. C. Fort in the Annales de l'IHP, Probabilités and Statistiques (vol. 23, n° 1, 1987}, and in Biological Cybernetics (n° 53, 1986). In the first one, we prove the convergence of Kohonen's self-organizing algorithm, in dimension 1. In the second one, we define another self-organizing algorithm, which is a simplified variant of Kohonen's, and we prove its convergence in dimensions 1 and 2. In the third part, published in Biological Cybernetics (n°58, 1988), we solve the problem of the connection matrix calculus for a Mac-Culloch or Hopfield neural network, so as to get the largest attractivity for the deterministic algorithm and non-orthogonal patterns. Then we calculate the attractivity of each memorized pattern, for a given connection matrix. The last part is devoted to the study of the role of inhibition in a nearest-neighbours-connected neural network. The model closely ressembles the biological reality of the young animal's cerebellar cortex. We prove that, when inhibition is smaller than a certain threshold, the network is ergodic and works in a stationary way. Conversely, when inhibition increases, striped or moiré responses appear, whose form and width depend on the considered neighbourhood size
El, Hajj Dib Imad. "Analyse et modélisation de l'EMG et de la fatigue musculaire lors de mouvements dynamiques cycliques." Compiègne, 2006. http://www.theses.fr/2006COMP1666.
Full textThe surface EMG is a non-invasive method which allows the diagnosis of the muscular function. Our study relates to fatigue in dynamic contraction. We achieved two parallel tasks: realization of experiments to collect real EMG, and model development to simulate synthetic EMG. The signal processing tools classically used to quantify fatigue are the Fourier transform, adapted to the isometric signals, and time-frequency, adapted to the dynamic signals. We were then interested in the cyclostationnarity. The results show that spectral coherence, cyclostationnarity tool, increases with muscular fatigue whereas the average traditional or instantaneous frequency, is mainly influenced by the action potential conduction velocity. Spectral coherence thus makes it possible to quantify fatigue under conditions where the traditional tools do not provide significant information
Van, Grieken Milagros. "Optimisation pour l'apprentissage et apprentissage pour l'optimisation." Phd thesis, Université Paul Sabatier - Toulouse III, 2004. http://tel.archives-ouvertes.fr/tel-00010106.
Full textZaffaroni, Marta. "Modélisation des interactions plant-puceron, en considérant explicitement le rôle des pratiques agricoles : Pêche (Prunus persica) - puceron vert (Myzus persicae) comme cas d'étude An ecophysiological model of plant–pest interactions: the role of nutrient and water availability Maximizing plant production and minimizing environmental impact: comparing agricultural management scenarios with multi criteria decision analysis The role of vectors interference in a shared host-multi vector system." Thesis, Avignon, 2020. http://www.theses.fr/2020AVIG0723.
Full textAphids alter plant development and can transmit viruses, thus representing a major threat for crops. Aphid pressure on plant can be reduced and crop production can be enhanced by facilitating some ecological processes in addition, or in substitution, to the use of pesticides. Mathematical models can help in predicting the direction and strength of these ecological processes and they can reveal the impact of alternative ways of managing crops. The proposed thesis aims to develop process based mathematical models coupling plant physiology and aphid demography to drive ecological intensification and reduce the use of pesticides. The models consider i) interactions between plant and aphid, while most crop models only consider the effect of the pest on the plant and not vice versa hence impairing insights upon bottom-up pest control via cultural practices; and ii) the effect of cultural practices and the outcome in terms of harvest, issues that are usually absent in ecological models. Therefore, I firstly couple a mechanistic plant growth model with a pest population model, I calibrate it for a peach-green aphid system and I use it to get insights on the mechanisms behind the response of aphids to fertilization and irrigation. Furthermore, I develop an epidemiological model explicitly accounting for the interference between two aphid vectors. I apply the model to explore the effect of inter-specific aphid interference in shaping the spread of plant viruses, considering the effect of agricultural practices
Albaradeyia, Issa. "Modélisation de l'érosion en zone montagneuse semi-aride." Lille 1, 2007. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2007/50376-2007-Albaradeyia.pdf.
Full textNedjar, Boumedyen. "Modélisation basée sur la méthode des réseaux de perméances en vue de l’optimisation de machines synchrones à simple et à double excitation." Thesis, Cachan, Ecole normale supérieure, 2011. http://www.theses.fr/2011DENS0056/document.
Full textThe electric and / or hybrid driveis are an application area growing with a strong restriction in terms of congestion. This prompted the designers to create appropriate structures. Among these topologies, we find the double-excitation synchronous machine (MSDE). These machines can combine the advantages of permanent magnets machine and those of a coils excited machine.The choice of a model for these machines is an important step in the analysis, optimization and pre-sizing. This thesis presents a contribution to the modeling by magnetic equivalent circuit (MEC) of single and double excitation synchronous machines. Three parties are offered as well. The first part of the thesis presents two states of the art: one on the double-excitation synchronous machines and the other on the modeling of electrical machines, mainly in the modeling by magnetic equivalent circuit. In the second part, we discuss the 2D modeling of flux concentration permanent magnet synchronous machine taking into account the rotation and saturation. The purpose of this section is to find ways to combine both computational time and accuracy. We start by using the magnetic equivalent circuit modeling based on a mesh of the structure and each mesh is replaced by two-way reluctances, then a torque estimation are obtened by two methods flux-FMM and Maxwell stress Tensor. The second section presents a coupling between magnetic equivalent circuit and finite element method. The proposed method is to solve the two models (reluctant and finite elements) simultaneously with software EF. The coupling is performed by an equivalence between the geometric dimensions and magnetic properties of materials. The presentation of different models in terms of time-accurate calculation shows the effectiveness of the use of MEC and coupling method compared to FEM. The third part concerns the three-dimensional modeling of double excitation synchronous machines. At first, we present an adaptation of the MEC to the three-dimensional structures. Then we apply this model to the double excitation synchronous machines (DESM). The DESM with flux concentration configuration is presented. To better control the wund flux of excitation, a buried magnet homopolar machine is also studied with the same approach. Model validation is performed by finite element and experimental measurements. In the last part, a comparison between homopolar and bipolar configurations is made, then the rotor flux concentration is optimized in order to compare it to the machine magnets buried
Gille, Jean-Pierre. "Technologies des échanges respiratoires (O2 et Co2) : application à la réalisation d'appareils médicaux." Compiègne, 1991. http://www.theses.fr/1991COMPE092.
Full textAshadi, Fakhrul Rozi. "Respiratory Neural Network in Humans : Spatiotemporal Mapping of Neural Oscillations and Mathematical Modelling." Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCC229.
Full textBreathing involves a complex interplay between the automatic brainstem network and the cortical command. Both networks interact harmoniously to control respiratory muscles contraction, thereby ensuring normal blood gas levels either during speech, volitional breathing or a ventilatory load increase. Understanding the respiratory neural network is crucial for many reasons in medicine, physiology and physics: (1) increased respiratory loading is a major feature of several respiratory diseases (chronic obstructive pulmonary disease, emphysema, pulmonary fibrosis), (2) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precedes acute respiratory failure. In addition some of the cerebral structures involved in responding to inspiratory loading also participate in the perception of breathlessness, a common and often distressing symptom in many diseases, (3) This neural network vital for life would benefit from the building of a mathematical model able to simulate and analyze its dynamics in disease conditions and may serve as a paradigm of physiological and physical synchronization. Therapeutic interventions could also be tested on the network model, for instance with a magnetic field, to alter connectivity. It will be then possible to test such approach in patients with chronic obstructive pulmonary disease (COPD) using cerebral neuro-modulating techniques with the goal to increase respiratory muscle performance. Using high density electroencephalography, we built the spatiotemporal map of the respiratory neural network during inspiratory loading in 20 healthy control subjects, and compared its dynamics to another motor network (hand motion). Time-frequency analyzes revealed the specific neural frequency patterns. To understand the brain communication, we reproduced mathematically the neural frequency code. There are three main components in the model: the neuronal scheme, the connectivity map and the synaptic model. Altogether, they are responsible of the dynamics of the neural networks. For the neuronal scheme, we use the Hodgkin Huxley (conductance-based) model, a set of nonlinear differential equations that approximates the electrical characteristics of excitable cells such as neurons. We consider the tonic-spiking regime of the model. For the connectivity map, the way neurons are connected into one another, we consider neurons that are placed in a two dimensional Cartesian grids. Connectivity between two neurons is governed probabilistically based on their Euclidean distance. For the synaptic model, neurons are either excitatory or inhibitory and are chemically connected. In the network, whether a neuron is excitatory or inhibitory is decided probabilistically. The type of connection depends on the type of the neurons. Finally, we are now able to replicate the dynamics of a specific region of interest (ROI) of the network and the complex interactions between two ROIs
Petrolli, Vanni. "Confinement induced transition between wave-like cellular migration modes." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAY056.
Full textThe ability of organisms to spontaneously generate order relies on the intricate interplay of mechanical and bio-chemical signals. If the general consensus is that chemical signaling governs the behavior of cells, an increasing amount of evidence points towards the impact of mechanical factors into differentiation, proliferation, motility and cancer progression. In this context, several studies recently highlighted the existence of long-range mechanical excitations (i.e. waves) at the supra-cellular level.Here, we investigate the origins of those velocity waves in tissues and their correlation with the presence of boundaries. Practically, we confine epithelial cell mono-layers to quasi-one dimensional geometries, to force the almost ubiquitous establishment of tissue-level waves. By tuning the length of the tissues, we uncover the existence of a phase transition between global and multi-nodal oscillations, and prove that in the latter regime, wavelength and period are independent of the confinement length. Together, these results demonstrate the intrinsic origin of tissue oscillations, which could provide cells with a mechanism to accurately measure distances at the supra-cellular level and ultimately lead to spatial patterning. Numerical simulations based on a Self-propelled Voronoi model reproduce the phase transition we measured experimentally and help in guiding our preliminary investigations on the origin of these wave-like phenomena, and their potential role for the spontaneous appearance of hair follicles in mouse skin explants
Beaudoin-Gagnon, Nicolas. "Entraînement d'un modèle supervisé pour la détection du plaisir en contexte de jeu vidéo à partir de signaux physiologiques et d'indices comportementaux." Master's thesis, Université Laval, 2020. http://hdl.handle.net/20.500.11794/66324.
Full textModeling the gaming experience is of considerable interest for designing adaptive video games. Adaptive video games use the emotional information contained in physiological signals and behavioral cues to personalize the video game experience,in order to generate an optimal gaming experience. With the purpose of modeling the gaming experience, this research project has focused on the detection of a player’s fun using physiological signals (electrocardiogram, electrodermal activity, respiratory activity and electromyogram) and behavioral cues (facial expressions,head movements and facial expressions and inputs from an Xbox controller). In this work, supervised machine learning models (SVM, Random Forest and kNN) were trained on a dataset built from the FUNii database, which contains the physiobehavioral data of 219 players spread over 362 game sessions of the Assassin’s Creed franchise. A method for creating fun classes from the fun factor, a tool for continuous annotation of fun, has also been proposed. The best model trained allowed to distinguish three classes of pleasure with an accuracy of 53, 5% on a test dataset, an improvement of 12, 5% compared to the best result obtained in previous works.
Strock, Anthony. "Mémoire de travail dans les réseaux de neurones récurrents aléatoires." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0195.
Full textWorking memory can be defined as the ability to temporarily store and manipulate information of any kind.For example, imagine that you are asked to mentally add a series of numbers.In order to accomplish this task, you need to keep track of the partial sum that needs to be updated every time a new number is given.The working memory is precisely what would make it possible to maintain (i.e. temporarily store) the partial sum and to update it (i.e. manipulate).In this thesis, we propose to explore the neuronal implementations of this working memory using a limited number of hypotheses.To do this, we place ourselves in the general context of recurrent neural networks and we propose to use in particular the reservoir computing paradigm.This type of very simple model nevertheless makes it possible to produce dynamics that learning can take advantage of to solve a given task.In this job, the task to be performed is a gated working memory task.The model receives as input a signal which controls the update of the memory.When the door is closed, the model should maintain its current memory state, while when open, it should update it based on an input.In our approach, this additional input is present at all times, even when there is no update to do.In other words, we require our model to be an open system, i.e. a system which is always disturbed by its inputs but which must nevertheless learn to keep a stable memory.In the first part of this work, we present the architecture of the model and its properties, then we show its robustness through a parameter sensitivity study.This shows that the model is extremely robust for a wide range of parameters.More or less, any random population of neurons can be used to perform gating.Furthermore, after learning, we highlight an interesting property of the model, namely that information can be maintained in a fully distributed manner, i.e. without being correlated to any of the neurons but only to the dynamics of the group.More precisely, working memory is not correlated with the sustained activity of neurons, which has nevertheless been observed for a long time in the literature and recently questioned experimentally.This model confirms these results at the theoretical level.In the second part of this work, we show how these models obtained by learning can be extended in order to manipulate the information which is in the latent space.We therefore propose to consider conceptors which can be conceptualized as a set of synaptic weights which constrain the dynamics of the reservoir and direct it towards particular subspaces; for example subspaces corresponding to the maintenance of a particular value.More generally, we show that these conceptors can not only maintain information, they can also maintain functions.In the case of mental arithmetic mentioned previously, these conceptors then make it possible to remember and apply the operation to be carried out on the various inputs given to the system.These conceptors therefore make it possible to instantiate a procedural working memory in addition to the declarative working memory.We conclude this work by putting this theoretical model into perspective with respect to biology and neurosciences
Gimeno, Anthony. "Contribution à l'étude d'alternateurs automobiles : caractérisation des pertes en vue d'un dimensionnement optimal." Compiègne, 2011. http://www.theses.fr/2011COMP1923.
Full textThe advent of more stringent anti-pollution standards and the rising of oil price, lead car manufacturers and automotive suppliers to find efficient solutions for our future. This thesis is a contribution to improving the performance of the electrical generating function in a thermal powertrain. Two approaches are considered in this work. In the first approach, a study is done on the current machine (called Lundell structure or claw pole machine). In a second approach, we design a structure abble to replace the claw pole alternator. To identify and understand the evolution of the different losses, a characterization of losses is made and a study on VDA cycle is completed. We stress the importance of iron losses in claw pole structure and thereby study the influence of various factors on its evolution. The interest of a delta conexion in terms of stator iron losses is emphasized and the impact of this current in terms of copper losses is quantified. A study is conducted over the complementarity of experimental and finite element approach on the repartition of iron losses between the stator and the rotor of this structure. Finally, the impact of the rectifier on the evolution of iron losses is studied. During this first approach, we also propose an analytical modeling of the machine and his efficiency. The second approach leads to design an hybrid structure based on a wound rotor synchronous machine with interpolar magnets. In this study, we propose a coupling between an analytical design and a finite element one through the establishment of experimental designs. This study leads to an efficiency map of the hybrid structure, highlighting its value in terms of performance relative to a claw pole machine
Zohou, Thomas. "Rôle des facteurs cinématiques dans la technique du tir arrêté au football." Grenoble 1, 1988. http://www.theses.fr/1988GRE10142.
Full textIsberie, Carole. "Contribution du sol à l'alimentation hydrique d'un verger de cerisiers micro-irrigué selon un pilotage tensiométrique." Montpellier 2, 1992. http://www.theses.fr/1992MON20127.
Full textChraibi, Kaadoud Ikram. "apprentissage de séquences et extraction de règles de réseaux récurrents : application au traçage de schémas techniques." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0032/document.
Full textThere are two important aspects of the knowledge that an individual acquires through experience. One corresponds to the semantic memory (explicit knowledge, such as the learning of concepts and categories describing the objects of the world) and the other, the procedural or syntactic memory (knowledge relating to the learning of rules or syntax). This "syntactic memory" is built from experience and particularly from the observation of sequences of objects whose organization obeys syntactic rules.It must have the capability to aid recognizing as well as generating valid sequences in the future, i.e., sequences respecting the learnt rules. This production of valid sequences can be done either in an explicit way, that is, by evoking the underlying rules, or implicitly, when the learning phase has made it possible to capture the principle of organization of the sequences without explicit recourse to the rules. Although the latter is faster, more robust and less expensive in terms of cognitive load as compared to explicit reasoning, the implicit process has the disadvantage of not giving access to the rules and thus becoming less flexible and less explicable. These mnemonic mechanisms can also be applied to business expertise. The capitalization of information and knowledge in general, for any company is a major issue and concerns both the explicit and implicit knowledge. At first, the expert makes a choice to explicitly follow the rules of the trade. But then, by dint of repetition, the choice is made automatically, without explicit evocation of the underlying rules. This change in encoding rules in an individual in general and particularly in a business expert can be problematic when it is necessary to explain or transmit his or her knowledge. Indeed, if the business concepts can be formalized, it is usually in any other way for the expertise which is more difficult to extract and transmit.In our work, we endeavor to observe sequences of electrical components and in particular the problem of extracting rules hidden in these sequences, which are an important aspect of the extraction of business expertise from technical drawings. We place ourselves in the connectionist domain, and we have particularly considered neuronal models capable of processing sequences. We implemented two recurrent neural networks: the Elman model and a model with LSTM (Long Short Term Memory) units. We have evaluated these two models on different artificial grammars (Reber's grammar and its variations) in terms of learning, their generalization abilities and their management of sequential dependencies. Finally, we have also shown that it is possible to extract the encoded rules (from the sequences) in the recurrent network with LSTM units, in the form of an automaton. The electrical domain is particularly relevant for this problem. It is more constrained with a limited combinatorics than the planning of tasks in general cases like navigation for example, which could constitute a perspective of this work
Buhry, Laure. "Estimation de paramètres de modèles de neurones biologiques sur une plate-forme de SNN (Spiking Neural Network) implantés "insilico"." Thesis, Bordeaux 1, 2010. http://www.theses.fr/2010BOR14057/document.
Full textThese works, which were conducted in a research group designing neuromimetic integrated circuits based on the Hodgkin-Huxley model, deal with the parameter estimation of biological neuron models. The first part of the manuscript tries to bridge the gap between neuron modeling and optimization. We focus our interest on the Hodgkin-Huxley model because it is used in the group. There already existed an estimation method associated to the voltage-clamp technique. Nevertheless, this classical estimation method does not allow to extract precisely all parameters of the model, so in the second part, we propose an alternative method to jointly estimate all parameters of one ionic channel avoiding the usual approximations. This method is based on the differential evolution algorithm. The third chaper is divided into three sections : the first two sections present the application of our new estimation method to two different problems, model fitting from biological data and development of an automated tuning of neuromimetic chips. In the third section, we propose an estimation technique using only membrane voltage recordings – easier to mesure than ionic currents. Finally, the fourth and last chapter is a theoretical study preparing the implementation of small neural networks on neuromimetic chips. More specifically, we try to study the influence of cellular intrinsic properties on the global behavior of a neural network in the context of gamma oscillations
Ployard, Maxime. "Efficacité énergétique des machines de production d'électricité." Thesis, Ecole centrale de Lille, 2017. http://www.theses.fr/2017ECLI0010/document.
Full textDuring the design phase of an electrical generator, the topology is generally imposed by preliminary criteria. This thesis aims at providing a decision support for the choice of high power generator structures. The interest for high efficiency machines is driven by strong environmental objectives. Consequently, understanding the origin of losses in power generation machines is a major issue. Thus, a methodology for iron loss calculation is developed for high power generators.In the energy production and conversion sectors, Hybrid Excitation Synchronous Machines have a great potential to respond to the challenges of energy transition. It is important to quantify the impact of these new structures compared with existing solutions. This thesis proposes analytical and lumped models to design a set of generator structures. The modeling approach is also compared with two high power generators, including one for a direct drive wind turbine. Then, this modeling is used in an optimization design process. The optimal Pareto structures are compared according to different specifications. These optimized designs show significant gains compared to the existing solutions, especially on wind profile from a Weibull probability density function
Doyennette, Marion. "La bouche, un réacteur complexe à l'origine de la libération des stimuli sensoriels : modélisation des transferts de composés d'arôme lors de la déstructuration d'aliments solides." Thesis, Paris, AgroParisTech, 2011. http://www.theses.fr/2011AGPT0047/document.
Full textDelivery of aroma compounds to olfactory receptors determines the aromatic quality of food products and contributes to consumer choices and preferences. Therefore, understanding and modelling the release kinetic is a scientific challenge and a health issue in order to formulate products of both high nutritional and sensory quality. This thesis studied in-mouth mechanisms responsible of the dynamics of olfactory stimuli release during food consumption. • First, a mechanistic model describing the aroma compounds release during consumption of a liquid or semi-liquid food has been developed. These products have a very short in-mouth residence time and do not require complex intra-oral manipulation. The model takes into account mass balances, transfer mechanisms occurring between some sub-compartments of the system, and the specific conditions at the different stages of consumption. A comparison of the model predictions with in vivo release data during the consumption of Newtnonien fluids flavored with diacetyl and ethyl hexanoate was performed. This study highlighted the role of post-pharyngeal residue and viscosity on the aroma compounds release: • the thickness of bolus covering the mucous membranes has been estimated at about 15μm; • it was found that the relevant properties to be considered for the release of aroma compounds from a Newtonian fluid are those of a mixture highly diluted by saliva. • Second, the model previously developed was adapted for products requiring chewing. It takes into account the phenomena of mass transfer and dissolution of the product in the saliva during chewing. The generation of a product/liquid contact surface as well as the velopharyngial opening that occurs during the mastication of the product were also integrated into the model. The model was then confronted with in vivo release data for ethyl propanoate during consumption of four cheese matrices. All simulations have been satisfactorily fitted to experimental data and the two unknown parameters of our model (the average rate of saliva incorporation into the bolus and the frequency of velopharyngial opening) could be estimated. This study has enabled us to understand the role of mastication on the release of aroma compounds during consumption of solid food: • the opening of velopharynx during intra-oral manipulation of the product produces a continuous supply of aroma compounds in the nose; • the residence time of solid product in the mouth are much longer than for the consumption of liquid and semi-liquid foods, allowing the secretion of significant volumes of saliva. In addition, the study of the release of 2-nonanone highlighted an adsorption phenomenon on the mucous membranes for this molecule. • Finally, sensitivity analysis of the two release models indicates that: • when eating a liquid or semi-liquid food, the mass transfer coefficient in the bolus, the breath rate and the thickness of post-pharyngeal residue are the three key factors governing the release of aroma compounds; • however, when eating a solid food product, it is the average rate of saliva incorporation into the bolus during consumption, the frequency and duration of velopharyngeal opening, and the mastication time which are the three parameters that have major effects on the kinetics of release. The modeling approach allowed us to better understand the relative effects of the product, the individual, and individual-product interaction on the release of aroma compounds during food consumption. The results of this work indicated that the most important parameters depend on the category of product (liquid or solid) under consideration
Rio, Maxime. "Modèles bayésiens pour la détection de synchronisations au sein de signaux électro-corticaux." Electronic Thesis or Diss., Université de Lorraine, 2013. http://www.theses.fr/2013LORR0090.
Full textThis thesis promotes new methods to analyze intracranial cerebral signals (local field potentials), which overcome limitations of the standard time-frequency method of event-related spectral perturbations analysis: averaging over the trials and relying on the activity in the pre-stimulus period. The first proposed method is based on the detection of sub-networks of electrodes whose activity presents cooccurring synchronisations at a same point of the time-frequency plan, using bayesian gaussian mixture models. The relevant sub-networks are validated with a stability measure computed over the results obtained from different trials. For the second proposed method, the fact that a white noise in the temporal domain is transformed into a rician noise in the amplitude domain of a time-frequency transform made possible the development of a segmentation of the signal in each frequency band of each trial into two possible levels, a high one and a low one, using bayesian rician mixture models with two components. From these two levels, a statistical analysis can detect time-frequency regions more or less active. To develop the bayesian rician mixture model, new algorithms of variational bayesian inference have been created for the Rice distribution and the rician mixture distribution. Performances of the new methods have been evaluated on artificial data and experimental data recorded on monkeys. It appears that the new methods generate less false positive results and are more robust to a lack of data in the pre-stimulus period
Pagliarini, Silvia. "Modeling the neural network responsible for song learning." Thesis, Bordeaux, 2021. http://www.theses.fr/2021BORD0107.
Full textDuring the first period of their life, babies and juvenile birds show comparable phases of vocal development: first, they listen to their parents/tutors in order to build a neural representation of the experienced auditory stimulus, then they start to produce sound and progressively get closer to reproducing their tutor song. This phase of learning is called the sensorimotor phase and is characterized by the presence of babbling, in babies, and subsong, in birds. It ends when the song crystallizes and becomes similar to the one produced by the adults.It is possible to find analogies between brain pathways responsible for sensorimotor learning in humans and birds: a vocal production pathway involves direct projections from auditory areas to motor neurons, and a vocal learning pathway is responsible for imitation and plasticity. The behavioral studies and the neuroanatomical structure of the vocal control circuit in humans and birds provide the basis for bio-inspired models of vocal learning.In particular, birds have brain circuits exclusively dedicated to song learning, making them an ideal model for exploring the representation of vocal learning by imitation of tutors.This thesis aims to build a vocal learning model underlying song learning in birds. An extensive review of the existing literature is discussed in the thesis: many previous studies have attempted to implement imitative learning in computational models and share a common structure. These learning architectures include the learning mechanisms and, eventually, exploration and evaluation strategies. A motor control function enables sound production and sensory response models either how sound is perceived or how it shapes the reward. The inputs and outputs of these functions lie (1)~in the motor space (motor parameters’ space), (2)~in the sensory space (real sounds) and (3)~either in the perceptual space (a low dimensional representation of the sound) or in the internal representation of goals (a non-perceptual representation of the target sound).The first model proposed in this thesis is a theoretical inverse model based on a simplified vocal learning model where the sensory space coincides with the motor space (i.e., there is no sound production). Such a simplification allows us to investigate how to introduce biological assumptions (e.g. non-linearity response) into a vocal learning model and which parameters influence the computational power of the model the most. The influence of the sharpness of auditory selectivity and the motor dimension are discussed.To have a complete model (which is able to perceive and produce sound), we needed a motor control function capable of reproducing sounds similar to real data (e.g. recordings of adult canaries). We analyzed the capability of WaveGAN (a Generative Adversarial Network) to provide a generator model able to produce realistic canary songs. In this generator model, the input space becomes the latent space after training and allows the representation of a high-dimensional dataset in a lower-dimensional manifold. We obtained realistic canary sounds using only three dimensions for the latent space. Among other results, quantitative and qualitative analyses demonstrate the interpolation abilities of the model, which suggests that the generator model we studied can be used as a motor function in a vocal learning model.The second version of the sensorimotor model is a complete vocal learning model with a full action-perception loop (i.e., it includes motor space, sensory space, and perceptual space). The sound production is performed by the GAN generator previously obtained. A recurrent neural network classifying syllables serves as the perceptual sensory response. Similar to the first model, the mapping between the perceptual space and the motor space is learned via an inverse model. Preliminary results show the influence of the learning rate when different sensory response functions are implemented
Azevedo, Carvalho Nathalie. "Un modèle informatique biologiquement réaliste des oscillations neuronales pathologiques observées dans la maladie de Parkinson." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0077.
Full textMy thesis is based on three axes: to develop a biophysical model, to propose a simulation tool, and exploit the model in simulation.We develop a biophysical model of the neuronal structure involved in Parkinson's disease, the basal ganglia. We simulate physiologically realistic neurons using the Hodgkin-Huxley formalism to incorporate specific ion channels present in different populations of GB neurons, including arkipallidal and proptotypic GPe, as well as dopaminergic D1 and D2 neurons in the striatum, whose cellular properties and connectivity appear to be prominent factors in the oscillatory behavior of the network. Our model is validated by experimental data in healthy conditions of the rat, collected by our biologist collaborators.We propose a simulation tool for impulse neural networks allowing realistic simulations on a large scale, > 1 million neurons, on a parallel machine i.e. Grid'5000, Explor, etc... SiReNe is a neural network simulator developed in the C language. This software is based on a hybrid simulation approach. It combines a numerical integration, Runge-Kutta 2, of the neuronal dynamics and an event-driven generation of the network connectivity during action potentials emissions. This approach, developed during the thesis, allows the simulation of large and very detailedneural networks of the Hodgkin-Huxley type.In the future, our model could be used in simulation to test some hypotheses on the pathological synchronization observed in Parkinson's disease. Like the role of GABAergic synaptic connections and the intrinsic neuronal properties of SK channels which control the precision of neuronal discharge. The simulation of large-scale models could be used to limit pathological synchronization and motor disorders through new neurostimulation methods, such as deep brain stimulation
Kubler, Samuel. "Statistical methods for the robust extraction of objects’ spatio-temporal relations in bioimaging – Application to the functional analysis of neuronal networks in vivo." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS455.
Full textThe neural code, i.e. how interconnected neurons can perform complex operations, allowing the quick adaptation of animals to their environment, remains an open question and an intensive field of research both in experimental and computational neurosciences. Advances in molecular biology and microscopy have recently made it possible to monitor the activity of individual neurons in living animals and, in the case of small animals containing only a few thousands of neurons, to measure the activity of the entire nervous system. However, the mathematical framework that would bridge the gap between single neuron activity and the emergent computational properties of neuronal ensembles is missing.In the thesis manuscript, we introduce a sequential statistical processing pipeline that efficiently and robustly extracts neuronal ensembles from calcium imagery of neuronal activity. In particular, we develop a Bayesian inference framework based on a biologically interpretable model to extract neuronal ensembles characterized by noise, asynchrony and overlapping. The provided tool demonstrates that a Gibbs sampling routine can efficiently estimate statistical parameters and hidden variables to uncover neuronal ensembles based on synchronization patterns both on synthetic data and on various experimental datasets from mice and zebrafish visual cortex to Hydra Vulgaris. The thesis equally develops a point process statistical framework to quantify how neuronal ensembles encode evoked stimuli or spontaneous behaviors in living animals. This versatile tool is also used for the inference of the functional connectivity of neuronal activity or the automatically calibration procedure of the spike inference algorithms applied to calcium recordings. For the providing algorithms to be largely spread in the neurobiologist community, results are supported by interpretable biological estimates, statistical evidence, rigorous mathematical proofs, and free-available software. Our contributive implementation, that goes from pixel intensity to estimated neuronal ensembles, equally identify from the synchronous firing patterns of neuronal ensembles, neurons with specific roles that can be used to predict, improve, or alter the behaviors of living animals. The provided framework unravels the emergence of collective properties from the recording of extremely varying individual signals that make the neural code still elusive
Weng, Qilong. "Stabilité pour des modèles de réseaux de neurones et de chimiotaxie." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLED026/document.
Full textThis thesis is aimed to study some biological models in neuronal network and chemotaxis with the spectral analysis method. In order to deal with the main concerning problems, such as the existence and uniqueness of the solutions and steady states as well as the asymptotic behaviors, the associated linear or linearized model is considered from the aspect of spectrum and semigroups in appropriate spaces then the nonlinear stability follows. More precisely, we start with a linear runs-and-tumbles equation in dimension d≥1 to establish the existence of a unique positive and normalized steady state and the exponential asymptotic stability in weighted L¹ space based on the Krein-Rutman theory together with some moment estimates from kinetic theory. Then, we consider time elapsed model under general assumptions on the firing rate and prove the uniqueness of the steady state and its nonlinear exponential stability in case without or with delay in the weak connectivity regime from the spectral analysis theory for semigroups. Finally, we study the model under weaker regularity assumption on the firing rate and the existence of the solution as well as the same exponential stability are established generally no matter taking delay into account or not and no matter in weak or strong connectivity regime