149 resultados para STOCHASTIC DYNAMICS
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Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a 'signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.
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Changes in intracellular Na(+) concentration underlie essential neurobiological processes, but few reliable tools exist for their measurement. Here we characterize a new synthetic Na(+)-sensitive fluorescent dye, Asante Natrium Green (ANG), with unique properties. This indicator was excitable in the visible spectrum and by two-photon illumination, suffered little photobleaching and located to the cytosol were it remained for long durations without noticeable unwanted effects on basic cell properties. When used in brain tissue, ANG yielded a bright fluorescent signal during physiological Na(+) responses both in neurons and astrocytes. Synchronous electrophysiological and fluorometric recordings showed that ANG produced accurate Na(+) measurement in situ. This new Na(+) indicator opens innovative ways of probing neuronal circuits.
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We study the dynamics of a water-oil meniscus moving from a smaller to a larger pore. The process is characterised by an abrupt change in the configuration, yielding a sudden energy release. A theoretic study for static conditions provides analytical solutions of the surface energy content of the system. Although the configuration after the sudden energy release is energetically more convenient, an energy barrier must be overcome before the process can happen spontaneously. The energy barrier depends on the system geometry and on the flow parameters. The analytical results are compared to numerical simulations that solve the full Navier-Stokes equation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. First, the numerical simulations of a quasi-static process are validated by comparison with the analytical solutions for a static meniscus, then numerical simulations with varying injection velocity are used to investigate dynamic effects on the configuration change. During the sudden energy jump the system exhibits an oscillatory behaviour. Extension to more complex geometries might elucidate the mechanisms leading to a dynamic capillary pressure and to bifurcations in final distributions of fluid phases in porous
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Despite accumulating evidence from in vitro studies that cellular senescence is linked to telomere dynamics, how this relates to whole-organism senescence and longevity is poorly understood and controversial. Using data on telomere length in red blood cells and long-term survival from wild Alpine swifts of a range of ages, we report that the telomere length and the rate of telomere loss are predictive of life expectancy, and that slow erosion of relatively long telomeres is associated with the highest survival probabilities. Importantly, because telomere dynamics, rather than chronological age, predict life expectancy, our study provides good evidence for a mechanistic link between telomere erosion and reduced organism longevity under natural conditions, chronological age itself possibly not becoming a significant predictor until very old ages beyond those in our sample.
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Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.
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Issue ownership theory argues that when a voter considers a party to be the most competent amongst others to deal with an issue (that is, the party "owns" the issue), chances are the voter will vote for that party. Recent work has shown that perceptions of issue ownership are dynamic: they are affected by the media coverage of party messages. However, based on the broad literature on partisan bias, we predict that parties' efforts to change issue ownership perceptions will have a difficult time breaching the perceptual screen created by a voter's party preference. Using two separate experiments with a similar design we show that the effect of partisan issue messages on issue competence is moderated by party preference. The effect of issue messages is reinforced when people already like a party, and blocked when people dislike a party.
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Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.
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Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.
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Public goods cooperation is common in microbes, and there is much interest in understanding how such traits evolve. Research in recent years has identified several important factors that shape the evolutionary dynamics of such systems, yet few studies have investigated scenarios involving interactions between multiple public goods. Here, we offer general predictions about the evolutionary trajectories of two public goods traits having positive, negative or neutral regulatory influence on one another's expression, and we report on a test of some of our predictions in the context of Pseudomonas aeruginosa's production of two interlinked iron-scavenging siderophores. First, we confirmed that both pyoverdine and pyochelin siderophores do operate as public goods under appropriate environmental conditions. We then tracked their production in lines experimentally evolved under different iron-limitation regimes known to favour different siderophore expression profiles. Under strong iron limitation, where pyoverdine represses pyochelin, we saw a decline in pyoverdine and a concomitant increase in pyochelin - consistent with expansion of pyoverdine-defective cheats derepressed for pyochelin. Under moderate iron limitation, pyochelin declined - again consistent with an expected cheat invasion scenario - but there was no concomitant shift in pyoverdine because cross-suppression between the traits is unidirectional only. Alternating exposure to strong and moderate iron limitation caused qualitatively similar though lesser shifts compared to the constant-environment regimes. Our results confirm that the regulatory interconnections between public goods traits can significantly modulate the course of evolution, yet also suggest how we can start to predict the impacts such complexities will have on phenotypic divergence and community stability.
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Introduction This dissertation consists of three essays in equilibrium asset pricing. The first chapter studies the asset pricing implications of a general equilibrium model in which real investment is reversible at a cost. Firms face higher costs in contracting than in expanding their capital stock and decide to invest when their productive capital is scarce relative to the overall capital of the economy. Positive shocks to the capital of the firm increase the size of the firm and reduce the value of growth options. As a result, the firm is burdened with more unproductive capital and its value lowers with respect to the accumulated capital. The optimal consumption policy alters the optimal allocation of resources and affects firm's value, generating mean-reverting dynamics for the M/B ratios. The model (1) captures convergence of price-to-book ratios -negative for growth stocks and positive for value stocks - (firm migration), (2) generates deviations from the classic CAPM in line with the cross-sectional variation in expected stock returns and (3) generates a non-monotone relationship between Tobin's q and conditional volatility consistent with the empirical evidence. The second chapter proposes a standard portfolio-choice problem with transaction costs and mean reversion in expected returns. In the presence of transactions costs, no matter how small, arbitrage activity does not necessarily render equal all riskless rates of return. When two such rates follow stochastic processes, it is not optimal immediately to arbitrage out any discrepancy that arises between them. The reason is that immediate arbitrage would induce a definite expenditure of transactions costs whereas, without arbitrage intervention, there exists some, perhaps sufficient, probability that these two interest rates will come back together without any costs having been incurred. Hence, one can surmise that at equilibrium the financial market will permit the coexistence of two riskless rates that are not equal to each other. For analogous reasons, randomly fluctuating expected rates of return on risky assets will be allowed to differ even after correction for risk, leading to important violations of the Capital Asset Pricing Model. The combination of randomness in expected rates of return and proportional transactions costs is a serious blow to existing frictionless pricing models. Finally, in the last chapter I propose a two-countries two-goods general equilibrium economy with uncertainty about the fundamentals' growth rates to study the joint behavior of equity volatilities and correlation at the business cycle frequency. I assume that dividend growth rates jump from one state to other, while countries' switches are possibly correlated. The model is solved in closed-form and the analytical expressions for stock prices are reported. When calibrated to the empirical data of United States and United Kingdom, the results show that, given the existing degree of synchronization across these business cycles, the model captures quite well the historical patterns of stock return volatilities. Moreover, I can explain the time behavior of the correlation, but exclusively under the assumption of a global business cycle.
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The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.
Resumo:
RESUME LARGE PUBLIC Le système nerveux central est principalement composé de deux types de cellules :les neurones et les cellules gliales. Ces dernières, bien que l'emportant en nombre sur les neurones, ont longtemps été considérées comme des cellules sans intérêts par les neuroscientifiques. Hors, les connaissances modernes à leurs sujets indiquent qu'elles participent à la plupart des tâches physiologiques du cerveau. Plus particulièrement, elles prennent part aux processus énergétiques cérébraux. Ceux-ci, en plus d'être vitaux, sont particulièrement intrigants puisque le cerveau représente seulement 2 % de la masse corporelle mais consomme environ 25 % du glucose (substrat énergétique) corporel. Les astrocytes, un type de cellules gliales, jouent un rôle primordial dans cette formidable utilisation de glucose par le cerveau. En effet, l'activité neuronale (transmission de l'influx nerveux) est accompagnée d'une augmentation de la capture de glucose, issu de la circulation sanguine, par les astrocytes. Ce phénomène est appelé le «couplage neurométabolique » entre neurones et astrocytes. L'ion sodium fait partie des mécanismes cellulaires entrant en fonction lors de ces processus. Ainsi, dans le cadre de cette thèse, les aspects dynamiques de la régulation du sodium astrocytaire et leurs implications dans le couplage neurométabolique ont été étudiés par des techniques d'imagerie cellulaires. Ces études ont démontré que les mitochondries, machineries cellulaires convertissant l'énergie contenue dans le glucose, participent à la régulation du sodium astrocytaire. De plus, ce travail de thèse a permis de découvrir que les astrocytes sont capables de se transmettre, sous forme de vagues de sodium se propageant de cellules en cellules, un message donnant l'ordre d'accroître leur consommation d'énergie. Cette voie de signalisation leur permettrait de fournir de l'énergie aux neurones suite à leur activation. RESUME Le glutamate libéré dans la fente synaptique pendant l'activité neuronale, est éliminé par les astrocytes environnants. Le glutamate est co-transporté avec des ions sodiques, induisant une augmentation intracellulaire de sodium (Na+i) dans les astrocytes. Cette élévation de Na+i déclenche une cascade de mécanismes moléculaires qui aboutissent à la production de substrats énergétiques pouvant être utilisés par les neurones. Durant cette thèse, la mesure simultanée du sodium mitochondrial (Na+mit) et cytosolique par des techniques d'imagerie utilisant des sondes fluorescentes spécifiques, a indiqué que les variations de Na+i induites par le transport du glutamate sont transmises aux mitochondries. De plus, les voies d'entrée et de sortie du sodium mitochondrial ont été identifiées. L'échangeur de Na+ et de Ca2+ mitochondrial semble jouer un rôle primordial dans l'influx de Na+mit, alors que l'efflux de Na+mit est pris en charge par l'échangeur de Na+ et de H+ mitochondrial. L'étude du Na+mit a nécessité l'utilisation d'un système de photoactivation. Les sources de lumière ultraviolette (UV) classiques utilisées à cet effet (lasers, lampes à flash) ayant plusieurs désavantages, une alternative efficace et peu coûteuse a été développée. Il s'agit d'un système compact utilisant une diode électroluminescente (LED) à haute puissance et de longueur d'onde de 365nm. En plus de leurs rôles dans le couplage neurométabolique, les astrocytes participent à la signalisation multicellulaire en transmettant des vagues intercellulaires de calcium. Ce travail de thèse démontre également que des vagues intercellulaires de sodium peuvent être évoquées en parallèle à ces vagues calciques. Le glutamate, suite à sa libération par un mécanisme dépendent du calcium, est réabsorbé par les transporteurs au glutamate. Ce mécanisme a pour conséquence la génération de vagues sodiques se propageant de cellules en cellules. De plus, ces vagues sodiques sont corrélées spatialement avec une consommation accrue de glucose par les astrocytes. En conclusion, ce travail de thèse a permis de montrer que le signal sodique astrocytaire, déclenché en réponse au glutamate, se propage à la fois de façon intracellulaire aux mitochondries et de façon intercellulaire. Ces résultats suggèrent que les astrocytes fonctionnent comme un réseau de cellules nécessaire au couplage énergétique concerté entre neurones et astrocytes et que le sodium est un élément clé dans les mécanismes de signalisations cellulaires sous-jacents. SUMMARY Glutamate, released in the synaptic cleft during neuronal activity, is removed by surrounding astrocytes. Glutamate is taken-up with Na+ ions by specific transporters, inducing an intracellular Na+ (Na+i) elevation in astrocytes which triggers a cascade of molecular mechanisms that provides metabolic substrates to neurons. Thus, astrocytic Na+i homeostasis represents a key component of the so-called neurometabolic coupling. In this context, the first part of this thesis work was aimed at investigating whether cytosolic Na+ changes are transmitted to mitochondria, which could therefore influence their function and contribute to the overall intracellular Na+ regulation. Simultaneous monitoring of both mitochondrial Na+ (Na+mit) and cytosolic Na+ changes with fluorescent dyes revealed that glutamate-evoked cytosolic Na+ elevations are indeed transmitted to mitochondria. The mitochondrial Na+/Ca2+ exchangers have a prominent role in the regulation of Na+mit influx pathway, and Na+mit extrusion appears to be mediated by Na+/H+ exchangers. To demonstrate the implication of Na+/Ca2+ exchangers, this study has required the technical development of an UV-flash photolysis system. Because light sources for flash photolysis have to be powerful and in the near UV range, the use of UV lasers or flash lamps is usually required. As an alternative to these UV sources that have several drawbaks, we developped a compact, efficient and lowcost flash photolysis system which employs a high power 365nm light emitting diode. In addition to their role in neurometabolic coupling, astrocytes participate in multicellular signaling by transmitting intercellular Ca2+ waves. The third part of this thesis show that intercellular Na+ waves can be evoked in parallel to Ca2+ waves. Glutamate released by a Ca2+ wave-dependent mechanism is taken up by glutamate transporters, resulting in a regenerative propagation of cytosolic Na+ increases. Na+ waves in turn lead to a spatially correlated increase in glucose uptake. In conclusion, the present thesis demonstrates that glutamate-induced Na+ changes occurring in the cytosol of astrocytes propagate to both the mitochondrial matrix and the astrocytic network. These results furthermore support the view that astrocytic Na+ is a signal coupled to the brain energy metabolism.