Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.Comment: Final version published in Physics Reports. More information available at http://synchronets.googlepages.com

The Kuramoto model in complex networks

181 pages, 48 figures. In Press, Accepted Manuscript, Physics Reports 2015 Acknowledgments We are indebted with B. Sonnenschein, E. R. dos Santos, P. Schultz, C. Grabow, M. Ha and C. Choi for insightful and helpful discussions. T.P. acknowledges FAPESP (No. 2012/22160-7 and No. 2015/02486-3) and IRTG 1740. P.J. thanks founding from the China Scholarship Council (CSC). F.A.R. acknowledges CNPq (Grant No. 305940/2010-4) and FAPESP (Grants No. 2011/50761-2 and No. 2013/26416-9) for financial support. J.K. would like to acknowledge IRTG 1740 (DFG and FAPESP).Peer reviewedPreprin

Adaptive dynamical networks

It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields, in particular, for the models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In this review, we provide a detailed description of adaptive dynamical networks, show their applications in various areas of research, highlight their dynamical features and describe the arising dynamical phenomena, and give an overview of the available mathematical methods developed for understanding adaptive dynamical networks

Perspectives on adaptive dynamical systems

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches

Intracellular transport driven by cytoskeletal motors: General mechanisms and defects

Cells are strongly out-of-equilibrium systems driven by continuous energy supply. They carry out many vital functions requiring active transport of various ingredients and organelles, some being small, others being large. The cytoskeleton, composed of three types of filaments, determines the shape of the cell and plays a role in cell motion. It also serves as a road network for the so-called cytoskeletal motors. These molecules can attach to a cytoskeletal filament, perform directed motion, possibly carrying along some cargo, and then detach. It is a central issue to understand how intracellular transport driven by molecular motors is regulated, in particular because its breakdown is one of the signatures of some neuronal diseases like the Alzheimer. We give a survey of the current knowledge on microtubule based intracellular transport. We first review some biological facts obtained from experiments, and present some modeling attempts based on cellular automata. We start with background knowledge on the original and variants of the TASEP (Totally Asymmetric Simple Exclusion Process), before turning to more application oriented models. After addressing microtubule based transport in general, with a focus on in vitro experiments, and on cooperative effects in the transportation of large cargos by multiple motors, we concentrate on axonal transport, because of its relevance for neuronal diseases. It is a challenge to understand how this transport is organized, given that it takes place in a confined environment and that several types of motors moving in opposite directions are involved. We review several features that could contribute to the efficiency of this transport, including the role of motor-motor interactions and of the dynamics of the underlying microtubule network. Finally, we discuss some still open questions.Comment: 74 pages, 43 figure

Stratégies de contrôle laser de la dynamique moléculaire

Cette thèse étudie de façon phénoménologique la dynamique moléculaire en champ laser intense et plus précisément la mise en place des mécanismes de base pour stabiliser une molécule face à la dissociation. La ligne directrice dans ces travaux repose sur la dynamique des résonances Floquet en champ laser intense. Les stratégies simples et génériques proposées sont appliquées sur le modèle unidimensionnel de H₂⁺ pour lequel des calculs de paquets d'ondes dépendants du temps ont été effectués. En partant du mécanisme de synchronisation entre les mouvements du paquet d'ondes et celles des courbes d'énergie potentielle, à l'origine établi dans le domaine spectral de l'infrarouge où l'image quasi-statique prévaut, nous proposons un scénario pour étendre son champ d'application dans le domaine spectral de l'ultraviolet-visible où c'est plutôt l'image multiphotonique qui devient justifiée. Dans la représentation Floquet, on observe alors la respiration des courbes d'énergie potentielle habillées au croisement à un photon suivant non pas les oscillations de l'onde porteuse, mais celles de l'enveloppe dont la fréquence de répétition se trouve dans l'infrarouge. Nous nous intéressons particulièrement à la dépendance de la dynamique moléculaire sur la phase de l'enveloppe et nous faisons appel à une reformulation récente de la théorie de Floquet pour cerner l'origine du rôle dynamique de la phase absolue. Par une optimisation simple des paramètres optiques, nous prenons avantage sur les différent s mécanismes de base dans les images multiphotonique et quasi-statique pour stabiliser la molécule face à la dissociation par un transfer tadiabatique d'un état vibrationnel initial sur un état métastable, un état de résonance. De façon encore plus efficace, ce transfert adiabatique est ensuite effectué sur une résonance à largeur nulle. Tous ces processus multiphotoniques sont par la suite appliqués dans le problème d'ionisation dissociative de H₂ pour lequel on étudie la dynamique de l'ion moléculaire H₂⁺ sous une impulsion laser femtoseconde dans le proche infrarouge, préalablement préparé à partir de la molécule mère par une impulsion attoseconde ultaviolette extrême. L'étude du caractère adiabatique ou non-adiabatique de la préparation de l'ion et de son évolution subséquente sous l'impulsion infrarouge permet de retracer à la fois une signature de la dynamique parmi les résonances Floquet et une image indirecte du paquet d'ondes vibrationnel initial. Ce type d'imagerie de la dynamique moléculaire apporte un support théorique d'interprétation à des résultats expérimentaux portant sur les spectres d'énergie cinétique des photofragments. Puis, avec l'aide de la même reformulation de la théorie de Floquet, nous démontrons l'existence d'une interférométrie de paquets d'ondes, qui sont préparés successivement par chacune des impulsions attosecondes d'un train. Ce nouveau schéma impulsion pompe attoseconde ultraviolette extrême combinée à une impulsion sonde femtoseconde infrarouge offre en principe une stratégie pour la caractérisation des trains d 'impulsions attosecondes

Force Distribution in Macromolecules

All living organisms utilize thousands of molecular building blocks to perform mechanical tasks. These building blocks are mostly proteins, and their mechanical properties define the way they can be utilized by the cell. The spectrum ranges from rope like structures that give hold and stability to our bodies to microscopic engines helping us to perform or sense mechanical work. An increasing number of biological processes are revealed to be driven by force and well-directed distribution of strain is the very base of many of these mechanisms. We need to be able to observe the distribution of strain within bio-molecules if we want to gain detailed insight into the function of these highly complex nano-machines. Only by theoretical understanding and prediction of mechanical processes on the molecular level will we be able to rationally tailor proteins to mimic specific biological functions. This thesis aims at understanding the molecular mechanics of a wide range of biological molecules, such as the muscle protein titin or silk fibers. We introduce Force Distribution Analysis (FDA), a new approach to directly study the forces driving molecular processes, instead of indirectly observing them by means of coordinate changes

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201