Synchrony versus causality in distributed systems

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Given a synchronous system, we study the question whether – or, under which conditions – the behaviour of that system can be realized by a (non-trivially) distributed and hence asynchronous implementation. In this paper, we partially answer this question by examining the role of causality for the implementation of synchrony in two fundamental different formalisms of concurrency, Petri nets and the π-calculus. For both formalisms it turns out that each ‘good’ encoding of synchronous interactions using just asynchronous interactions introduces causal dependencies in the translation

Synchrony versus causality in distributed systems

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Given a synchronous system, we study the question whether – or, under which conditions – the behaviour of that system can be realized by a (non-trivially) distributed and hence asynchronous implementation. In this paper, we partially answer this question by examining the role of causality for the implementation of synchrony in two fundamental different formalisms of concurrency, Petri nets and the π-calculus. For both formalisms it turns out that each ‘good’ encoding of synchronous interactions using just asynchronous interactions introduces causal dependencies in the translation

Graph analysis of functional brain networks: practical issues in translational neuroscience

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires a know-how of all the methodological steps of the processing pipeline that manipulates the input brain signals and extract the functional network properties. On the other hand, a knowledge of the neural phenomenon under study is required to perform physiological-relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes

State of the art of interpersonal physiology in psychotherapy: A systematic review

Introduction: The fast expanding field of Interpersonal Physiology (IP) focuses on the study of co-ordination or synchronization dynamics between the physiological activities of two, or more, individuals. IP has been associated with various relational features (e.g., empathy, attachment security, rapport, closeness…) that overlap with desirable characteristics of clinical relationships, suggesting that the relevant studies might provide objective, economical, and theory-free techniques to investigate the clinical process. The goal of the present work is to systematically retrieve and review the literature on IP in the field of psychotherapy and psychological intervention, in order to consolidate the knowledge of this research domain, highlight its critical issues, and delineate possible developments.Method: Following the guidelines by Okoli and Schabram (2010), a systematic literature search was performed in Scopus, Web of Science, PsycINFO, and PubMed databases by means of multiple keyword combinations; the results were integrated with references to the retrieved articles' bibliography as well as to other published reviews on IP.Results: All the retrieved documents reported clinical interactions that are characterized, at least partially, by IP phenomena. They appear to use fragmented and sometimes ambiguous terminology and show a lack of both specific theory-informed hypotheses and sound analytical procedures.Conclusion: Although the psychological nature of IP and its role in the clinical relationship are still mostly unknown, the potential value of a physiology-based measure of implicit exchanges in psychotherapy drives an acceleration in this research field. On the basis of the highlighted critical issues, possible future directions for clinical IP researchers are discussed

Brain rhythms of pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain

Decomposing Neural Synchrony: Toward an Explanation for Near-Zero Phase-Lag in Cortical Oscillatory Networks

Background: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles. Methodology/Principal Findings: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys. Conclusion/Significance: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at al

Synchrony vs Causality in the Asynchronous Pi-Calculus

We study the relation between process calculi that differ in their either synchronous or asynchronous interaction mechanism. Concretely, we are interested in the conditions under which synchronous interaction can be implemented using just asynchronous interactions in the pi-calculus. We assume a number of minimal conditions referring to the work of Gorla: a "good" encoding must be compositional and preserve and reflect computations, deadlocks, divergence, and success. Under these conditions, we show that it is not possible to encode synchronous interactions without introducing additional causal dependencies in the translation.Comment: In Proceedings EXPRESS 2011, arXiv:1108.407

Brain Dynamics across levels of Organization

After presenting evidence that the electrical activity recorded from the brain surface can reflect metastable state transitions of neuronal configurations at the mesoscopic level, I will suggest that their patterns may correspond to the distinctive spatio-temporal activity in the Dynamic Core (DC) and the Global Neuronal Workspace (GNW), respectively, in the models of the Edelman group on the one hand, and of Dehaene-Changeux, on the other. In both cases, the recursively reentrant activity flow in intra-cortical and cortical-subcortical neuron loops plays an essential and distinct role. Reasons will be given for viewing the temporal characteristics of this activity flow as signature of Self-Organized Criticality (SOC), notably in reference to the dynamics of neuronal avalanches. This point of view enables the use of statistical Physics approaches for exploring phase transitions, scaling and universality properties of DC and GNW, with relevance to the macroscopic electrical activity in EEG and EMG

Reconstructing phase dynamics of oscillator networks

We generalize our recent approach to reconstruction of phase dynamics of coupled oscillators from data [B. Kralemann et al., Phys. Rev. E, 77, 066205 (2008)] to cover the case of small networks of coupled periodic units. Starting from the multivariate time series, we first reconstruct genuine phases and then obtain the coupling functions in terms of these phases. The partial norms of these coupling functions quantify directed coupling between oscillators. We illustrate the method by different network motifs for three coupled oscillators and for random networks of five and nine units. We also discuss nonlinear effects in coupling.Comment: 6 pages, 5 figures, 27 reference