Recurrence-based time series analysis by means of complex network methods

Complex networks are an important paradigm of modern complex systems sciences which allows quantitatively assessing the structural properties of systems composed of different interacting entities. During the last years, intensive efforts have been spent on applying network-based concepts also for the analysis of dynamically relevant higher-order statistical properties of time series. Notably, many corresponding approaches are closely related with the concept of recurrence in phase space. In this paper, we review recent methodological advances in time series analysis based on complex networks, with a special emphasis on methods founded on recurrence plots. The potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series. Complex network measures are shown to provide information about structural features of dynamical systems that are complementary to those characterized by other methods of time series analysis and, hence, substantially enrich the knowledge gathered from other existing (linear as well as nonlinear) approaches.Comment: To be published in International Journal of Bifurcation and Chaos (2011

A unified and automated approach to attractor reconstruction

We present a fully automated method for the optimal state space reconstruction from univariate and multivariate time series. The proposed methodology generalizes the time delay embedding procedure by unifying two promising ideas in a symbiotic fashion. Using non-uniform delays allows the successful reconstruction of systems inheriting different time scales. In contrast to the established methods, the minimization of an appropriate cost function determines the embedding dimension without using a threshold parameter. Moreover, the method is capable of detecting stochastic time series and, thus, can handle noise contaminated input without adjusting parameters. The superiority of the proposed method is shown on some paradigmatic models and experimental data from chaotic chemical oscillators

Successful Internalization of a Chronic Biliary Cutaneous Fistula After Liver Transplantation: Deepithelializing the Fistula Tract

Biliary cutaneous fistulas are uncommon sequelae after biliary surgery and can be a source of significant morbidity. We describe a liver recipient who developed a biliary cutaneous fistula secondary to hepatic artery thrombosis; this subsequently drained for over 7 years. Through a novel approach, using the transabdominal fistula tract as a conduit, the fistula skin opening was deepithelialized and anastomosed to a jejunal loop, internally draining the tract. For over 7 years postoperatively, this internal drainage procedure has continued to function effectively. This approach may have value in internalizing longstanding biliary cutaneous fistulas in well-selected patients in whom there is no existing biliary ductal system or the existing system anatomically does not lend itself to restoration of functional internal drainage through conventional approaches

Subthalamic nucleus phase-amplitude coupling correlates with motor impairment in Parkinson's disease

Objective High-amplitude beta band oscillations within the subthalamic nucleus are frequently associated with Parkinson’s disease but it is unclear how they might lead to motor impairments. Here we investigate a likely pathological coupling between the phase of beta band oscillations and the amplitude of high-frequency oscillations around 300Hz. Methods We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magneto-encephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex. Results We analysed an extensive data set comprising resting-state recordings obtained from deep brain stimulation electrodes in 33 patients before and/or after taking dopaminergic medication. We correlated mean values of spectral power and phase-amplitude coupling with severity of hemibody bradykinesia/rigidity. In addition, we used simultaneously recorded magneto-encephalography to look at functional interactions between the subthalamic nucleus and ipsilateral motor cortex. Conclusions We speculate that the beta band might impede pro-kinetic high-frequency activity patterns when phase-amplitude coupling is prominent. Furthermore, results provide evidence for a functional subdivision of the beta band into low and high frequencies. Significance Our findings contribute to the interpretation of oscillatory activity within the cortico-basal ganglia circuit

EXACT2: the semantics of biomedical protocols

© 2014 Soldatova et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background: The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods: We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously ‘unseen’ (not used for the construction of EXACT2) protocols. Results: The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions: The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format.This work has been partially funded by the Brunel University BRIEF award and a grant from Occams Resources

Chemotactic response and adaptation dynamics in Escherichia coli

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.Comment: accepted for publication in PLoS Computational Biology; manuscript (19 pages, 5 figures) and supplementary information; added additional clarification on alternative adaptation models in supplementary informatio