Integrated Multiscale Modeling of the Nervous System: Predicting Changes in Hippocampal Network Activity by a Positive AMPA Receptor Modulator

One of the fundamental characteristics of the brain is its hierarchical organization. Scales in both space and time that must be considered when integrating across hierarchies of the nervous system are sufficiently great as to have impeded the development of routine multilevel modeling methodologies. Complex molecular interactions at the level of receptors and channels regulate activity at the level of neurons; interactions between multiple populations of neurons ultimately give rise to complex neural systems function and behavior. This spatial complexity takes place in the context of a composite temporal integration of multiple, different events unfolding at the millisecond, second, minute, hour, and longer time scales. In this study, we present a multiscale modeling methodology that integrates synaptic models into single neuron, and multineuron, network models. We have applied this approach to the specific problem of how changes at the level of kinetic parameters of a receptor-channel model are translated into changes in the temporal firing pattern of a single neuron, and ultimately, changes in the spatiotemporal activity of a network of neurons. These results demonstrate how this powerful methodology can be applied to understand the effects of a given local process within multiple hierarchical levels of the nervous system

Simulation of Postsynaptic Glutamate Receptors Reveals Critical Features of Glutamatergic Transmission

Activation of several subtypes of glutamate receptors contributes to changes in postsynaptic calcium concentration at hippocampal synapses, resulting in various types of changes in synaptic strength. Thus, while activation of NMDA receptors has been shown to be critical for long-term potentiation (LTP) and long term depression (LTD) of synaptic transmission, activation of metabotropic glutamate receptors (mGluRs) has been linked to either LTP or LTD. While it is generally admitted that dynamic changes in postsynaptic calcium concentration represent the critical elements to determine the direction and amplitude of the changes in synaptic strength, it has been difficult to quantitatively estimate the relative contribution of the different types of glutamate receptors to these changes under different experimental conditions. Here we present a detailed model of a postsynaptic glutamatergic synapse that incorporates ionotropic and mGluR type I receptors, and we use this model to determine the role of the different receptors to the dynamics of postsynaptic calcium with different patterns of presynaptic activation. Our modeling framework includes glutamate vesicular release and diffusion in the cleft and a glutamate transporter that modulates extracellular glutamate concentration. Our results indicate that the contribution of mGluRs to changes in postsynaptic calcium concentration is minimal under basal stimulation conditions and becomes apparent only at high frequency of stimulation. Furthermore, the location of mGluRs in the postsynaptic membrane is also a critical factor, as activation of distant receptors contributes significantly less to calcium dynamics than more centrally located ones. These results confirm the important role of glutamate transporters and of the localization of mGluRs in postsynaptic sites in their signaling properties, and further strengthen the notion that mGluR activation significantly contributes to postsynaptic calcium dynamics only following high-frequency stimulation. They also provide a new tool to analyze the interactions between metabotropic and ionotropic glutamate receptors

Modelisation and simulation of synaptic transmission

Au cours des dernières années, la biologie et plus généralement la recherche médicale, a connu des avancées majeures grâce aux nombreux progrès de la microscopie, de la génétique, de la biologie moléculaire, de la protéomique, et du séquençage à haut débit. Il s’agit maintenant d’identifier à partir de toutes ces données gigantesques, les grandes lois de la biologie. Le principe de la biologie intégrative ou systémique est de poser les bases d'une véritable théorie de l'organisation fonctionnelle du vivant à partir des différents mécanismes découverts expérimentalement. De la même manière que l'on décrit la matière par les théories des mathématiques, de la physique, et de la chimie, on veut pouvoir comprendre, formaliser et modéliser le fonctionnement des mécanismes du vivant. Cette thèse a consisté à réaliser une bibliothèque de modèles fonctionnels des réactions chimiques qui prennent place dans les cellules nerveuses aussi appelés modèles élémentaires et de les assembler afin d’obtenir un système mimant le plus finement possible les mécanismes de la propagation du signal électrique au sein d’une synapse. Les travaux réalisés jusqu'alors ont permis de modéliser les mécanismes essentiels et de reconstituer le comportement d’une synapse glutamatergique. En particulier, l’utilisation de cette nouvelle méthode de recherche et de développement de médicaments a pour objectif de proposer des molécules innovantes, en optimisant leurs propriétés biochimiques. Cette technique permettra, dans un futur proche, l'avènement d'une nouvelle génération de pharmaceutiques, dit multi-cibles, c'est-à-dire permettant d'intervenir sur les différents mécanismes d'une pathologie.In recent years, biology and medical research more generally, has seen major advances in microscopy, genetics, molecular biology, proteomics, and high-throughput sequencing. We now identify from these huge data, the great laws of biology. The principle of integrative biology or systemic is to defined the basis of the foundations for a theory of the functional organization of living from different mechanisms discovered experimentally. In the same way that matter is described by the theories of mathematics, physics, and chemistry, we want to understand, formalize and model the functioning of living mechanisms. This thesis has been to achieve a library of functional models of chemical reactions that take place in nerve cells also called elementary models and assemble them to obtain a system mimicking the finest possible mechanisms of electrical signal propagation within of a synapse. The work done so far allow us to model the essential mechanisms and reconstruct the behavior of a glutamatergic synapse. In particular, the use of this new method of research and drug development aims to offer innovative molecules by optimizing their biochemical properties. This technique will, in the near future, the advent of a new generation of pharmaceuticals, said multi-target, able to intervene on the different mechanisms of disease

Modélisation et simulation informatique de la transmission nerveuse

Au cours des dernières années, la biologie et plus généralement la recherche médicale, a connu des avancées majeures grâce aux nombreux progrès de la microscopie, de la génétique, de la biologie moléculaire, de la protéomique, et du séquençage à haut débit. Il s agit maintenant d identifier à partir de toutes ces données gigantesques, les grandes lois de la biologie. Le principe de la biologie intégrative ou systémique est de poser les bases d'une véritable théorie de l'organisation fonctionnelle du vivant à partir des différents mécanismes découverts expérimentalement. De la même manière que l'on décrit la matière par les théories des mathématiques, de la physique, et de la chimie, on veut pouvoir comprendre, formaliser et modéliser le fonctionnement des mécanismes du vivant. Cette thèse a consisté à réaliser une bibliothèque de modèles fonctionnels des réactions chimiques qui prennent place dans les cellules nerveuses aussi appelés modèles élémentaires et de les assembler afin d obtenir un système mimant le plus finement possible les mécanismes de la propagation du signal électrique au sein d une synapse. Les travaux réalisés jusqu'alors ont permis de modéliser les mécanismes essentiels et de reconstituer le comportement d une synapse glutamatergique. En particulier, l utilisation de cette nouvelle méthode de recherche et de développement de médicaments a pour objectif de proposer des molécules innovantes, en optimisant leurs propriétés biochimiques. Cette technique permettra, dans un futur proche, l'avènement d'une nouvelle génération de pharmaceutiques, dit multi-cibles, c'est-à-dire permettant d'intervenir sur les différents mécanismes d'une pathologie.In recent years, biology and medical research more generally, has seen major advances in microscopy, genetics, molecular biology, proteomics, and high-throughput sequencing. We now identify from these huge data, the great laws of biology. The principle of integrative biology or systemic is to defined the basis of the foundations for a theory of the functional organization of living from different mechanisms discovered experimentally. In the same way that matter is described by the theories of mathematics, physics, and chemistry, we want to understand, formalize and model the functioning of living mechanisms. This thesis has been to achieve a library of functional models of chemical reactions that take place in nerve cells also called elementary models and assemble them to obtain a system mimicking the finest possible mechanisms of electrical signal propagation within of a synapse. The work done so far allow us to model the essential mechanisms and reconstruct the behavior of a glutamatergic synapse. In particular, the use of this new method of research and drug development aims to offer innovative molecules by optimizing their biochemical properties. This technique will, in the near future, the advent of a new generation of pharmaceuticals, said multi-target, able to intervene on the different mechanisms of disease.MULHOUSE-SCD Sciences (682242102) / SudocSudocFranceF

A fully parallel in time and space algorithm for simulating the electrical activity of a neural tissue

International audienceThe resolution of a model describing the electrical activity of neural tissue and itspropagation within this tissue is highly consuming in term of computing time and requires strongcomputing power to achieve good results.New method: In this study, we present a method to solve a model describing the electricalpropagation in neuronal tissue, using parareal algorithm, coupling with parallelization space usingCUDA in graphical processing unit (GPU).Results: We applied the method of resolution to different dimensions of the geometry of our model(1-D, 2-D and 3-D). The GPU results are compared with simulations from a multi-core processorcluster, using message-passing interface (MPI), where the spatial scale was parallelized in order toreach a comparable calculation time than that of the presented method using GPU. A gain of afactor 100 in term of computational time between sequential results and those obtained using theGPU has been obtained, in the case of 3-D geometry. Given the structure of the GPU, this factorincreases according to the fineness of the geometry used in the computation.Comparison with existing method(s): To the best of our knowledge, it is the first time such amethod is used, even in the case of neuroscience.Conclusion: Parallelization time coupled with GPU parallelization space allows for drasticallyreducing computational time with a fine resolution of the model describing the propagation of theelectrical signal in a neuronal tissue

Integrated Multiscale Modeling of the Nervous System: Predicting Changes in Hippocampal Network Activity by a Positive AMPA Receptor Modulator

International audienceOne of the fundamental characteristics of the brain is its hierarchical organization. Scales in both space and time that must be considered when integrating across hierarchies of the nervous system are sufficiently great as to have impeded the development of routine multilevel modeling methodologies. Complex molecular interactions at the level of receptors and channels regulate activity at the level of neurons; interactions between multiple populations of neurons ultimately give rise to complex neural systems function and behavior. This spatial complexity takes place in the context of a composite temporal integration of multiple, different events unfolding at the millisecond, second, minute, hour, and longer time scales. In this study, we present a multiscale modeling methodology that integrates synaptic models into single neuron, and multineuron, network models. We have applied this approach to the specific problem of how changes at the level of kinetic parameters of a receptor-channel model are translated into changes in the temporal firing pattern of a single neuron, and ultimately, changes in the spatiotemporal activity of a network of neurons. These results demonstrate how this powerful methodology can be applied to understand the effects of a given local process within multiple hierarchical levels of the nervous system

Synaptic Efficacy as a Function of Ionotropic Receptor Distribution: A Computational Study

<div><p>Glutamatergic synapses are the most prevalent functional elements of information processing in the brain. Changes in pre-synaptic activity and in the function of various post-synaptic elements contribute to generate a large variety of synaptic responses. Previous studies have explored postsynaptic factors responsible for regulating synaptic strength variations, but have given far less importance to synaptic geometry, and more specifically to the subcellular distribution of ionotropic receptors. We analyzed the functional effects resulting from changing the subsynaptic localization of ionotropic receptors by using a hippocampal synaptic computational framework. The present study was performed using the EONS (Elementary Objects of the Nervous System) synaptic modeling platform, which was specifically developed to explore the roles of subsynaptic elements as well as their interactions, and that of synaptic geometry. More specifically, we determined the effects of changing the localization of ionotropic receptors relative to the presynaptic glutamate release site, on synaptic efficacy and its variations following single pulse and paired-pulse stimulation protocols. The results indicate that changes in synaptic geometry do have consequences on synaptic efficacy and its dynamics.</p></div

Integrated Multiscale Modeling of the Nervous System: Predicting Changes in Hippocampal Network Activity by a Positive AMPA Receptor Modulator

One of the fundamental characteristics of the brain is its hierarchical organization. Scales in both space and time that must be considered when integrating across hierarchies of the nervous system are sufficiently great as to have impeded the development of routine multilevel modeling methodologies. Complex molecular interactions at the level of receptors and channels regulate activity at the level of neurons; interactions between multiple populations of neurons ultimately give rise to complex neural systems function and behavior. This spatial complexity takes place i

Schematic representation of the PSD and the receptors located on the postsynaptic membrane.

<p><b>A</b>: Postsynaptic responses were elicited by a paired pulse stimulus with an inter pulse interval of 10 ms. The EPSC waveforms (shown in red and blue) are a result of ionic current flow through both AMPAR (located right opposite to the glutamate release site and at 200 nm. respectively) and NMDAR channels. The paired pulse ratio (PPR) as explained in Box B is the ratio of the maximum amplitude of the second response divided by the maximum amplitude of the first response. When AMPARs are closer to the release site, PPR is ~0.85 and when they are farther away, PPR is ~0.96. Paired pulse ratios (collected from 16x11 simulations—AMPARs located from 0 nm to 300 nm (16 data points along the x-axis) and for inter pulse intervals varying from 10 to 2000 ms (11 data points along the y-axis) simulations). <b>C: PPRs of synaptic EPSCs for [Mg</b>^<b>2+</b><b>] = 1mM</b>. Paired pulse ratios were plotted for AMPARs located from 0 nm to 300 nm (16 data points along the x-axis) and for inter pulse intervals varying from 10 to 2000 ms (11 data points along the y-axis) simulations). The paired pulse ratios vary between 0.8 and 1.18 (as indicated by the color bar). <b>D: PPRs of synaptic EPSCs for [Mg</b>^<b>2+</b><b>] = 0.5mM</b>. [Mg²⁺] was maintained at 0.5 mM to simulate the effect of partial unblocking of NMDA receptors by Mg²⁺. PPRs significantly varied with AMPAR locations between 1 to 1.7, more specifically for relatively small inter pulse intervals (10–100 ms).</p