Stankovski Tomislav

Preferred name

Stankovski Tomislav

Official Name

Stankovski Tomislav

Translated Name

Станковски Томислав

Main Affiliation

t.stankovski@ukim.edu.mk

t.stankovski@lancaster.ac.uk

t.stankovski@medf.ukim.edu.mk

Researcher ID

J-9992-2014

Now showing 1 - 10 of 41

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Dynamical Bayesian inference of time-evolving interactions: from a pair of coupled oscillators to networks of oscillators
(2012-12)
Duggento, Andrea
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McClintock, Peter V E
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Stefanovska, Aneta
Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski et al. [Phys. Rev. Lett. 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.
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Detecting Chronotaxic Systems from Single-Variable Time Series with Separable Amplitude and Phase
(MDPI AG, 2015-06-23)
Lancaster, Gemma
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Clemson, Philip
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Suprunenko, Yevhen
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Stefanovska, Aneta
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Cardiorespiratory interactions during three different temperatures – a case report
(IEEE, 2020-07)
Lin, Aihua
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Zilakos, Ilias
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Ugland, Nora
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Andersen, Marian Berge
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Bergersen, Tone Kristin
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Time-frequency methods and voluntary ramped-frequency breathing: a powerful combination for exploration of human neurophysiological mechanisms
(American Physiological Society, 2013-12)
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Cooke, William H
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Rudas, László
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Stefanovska, Aneta
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Eckberg, Dwain L
We experimentally altered the timing of respiratory motoneuron activity as a means to modulate and better understand otherwise hidden human central neural and hemodynamic oscillatory mechanisms. We recorded the electrocardiogram, finger photoplethysmographic arterial pressure, tidal carbon dioxide concentrations, and muscle sympathetic nerve activity in 13 healthy supine young men who gradually increased or decreased their breathing frequencies between 0.05 and 0.25 Hz over 9-min periods. We analyzed results with traditional time- and frequency-domain methods, and also with time-frequency methods (wavelet transform, wavelet phase coherence, and directional coupling). We determined statistical significance and identified frequency boundaries by comparing measurements with randomly generated surrogates. Our results support several major conclusions. First, respiration causally modulates both sympathetic (weakly) and vagal motoneuron (strongly) oscillations over a wide frequency range-one that extends well below the frequency of actual breaths. Second, breathing frequency broadly modulates vagal baroreflex gain, with peak gains registered in the low frequency range. Third, breathing frequency does not influence median levels of sympathetic or vagal activity over time. Fourth, phase relations between arterial pressure and sympathetic and vagal motoneurons are unaffected by breathing, and are therefore likely secondary to intrinsic responsiveness of these motoneurons to other synaptic inputs. Finally, breathing frequency does not affect phase coherence between diastolic pressure and muscle sympathetic oscillations, but it augments phase coherence between systolic pressure and R-R interval oscillations over a limited portion of the usual breathing frequency range. These results refine understanding of autonomic oscillatory processes and those physiological mechanisms known as the human respiratory gate.
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Cardiorespiratory coupling functions, synchronization and ageing
(IEEE, 2014-05)
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McClintock, Peter V. E.
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Stefanovska, Aneta
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Evolution of cardiorespiratory interactions with age
(The Royal Society, 2013-08-28)
Iatsenko, D
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Bernjak, A
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Shiogai, Y
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Owen-Lynch, P J
We describe an analysis of cardiac and respiratory time series recorded from 189 subjects of both genders aged 16-90. By application of the synchrosqueezed wavelet transform, we extract the respiratory and cardiac frequencies and phases with better time resolution than is possible with the marked events procedure. By treating the heart and respiration as coupled oscillators, we then apply a method based on Bayesian inference to find the underlying coupling parameters and their time dependence, deriving from them measures such as synchronization, coupling directionality and the relative contributions of different mechanisms. We report a detailed analysis of the reconstructed cardiorespiratory coupling function, its time evolution and age dependence. We show that the direct and indirect respiratory modulations of the heart rate both decrease with age, and that the cardiorespiratory coupling becomes less stable and more time-variable.
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Experimental Realization of the Coupling Function Secure Communications Protocol and Analysis of Its Noise Robustness
(Institute of Electrical and Electronics Engineers (IEEE), 2018-10)
Nadzinski, Gorjan
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Dobrevski, Matej
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Anderson, Christopher
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McClintock, Peter V. E.
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Stefanovska, Aneta
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Inference of time-evolving coupled dynamical systems in the presence of noise
(2012-07-13)
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Duggento, Andrea
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McClintock, Peter V E
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Stefanovska, Aneta
A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.
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Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences
(The Royal Society, 2019-12-16)
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Pereira, Tiago
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McClintock, Peter V E
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Stefanovska, Aneta
Dynamical systems are widespread, with examples in physics, chemistry, biology, population dynamics, communications, climatology and social science. They are rarely isolated but generally interact with each other. These interactions can be characterized by coupling functions-which contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how each interaction occurs. Coupling functions can be used, not only to understand, but also to control and predict the outcome of the interactions. This theme issue assembles ground-breaking work on coupling functions by leading scientists. After overviewing the field and describing recent advances in the theory, it discusses novel methods for the detection and reconstruction of coupling functions from measured data. It then presents applications in chemistry, neuroscience, cardio-respiratory physiology, climate, electrical engineering and social science. Taken together, the collection summarizes earlier work on coupling functions, reviews recent developments, presents the state of the art, and looks forward to guide the future evolution of the field. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.
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Synchronization transitions caused by time-varying coupling functions
(The Royal Society, 2019-12-16)
Hagos, Zeray
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Newman, Julian
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Pereira, Tiago
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McClintock, Peter V E
Interacting dynamical systems are widespread in nature. The influence that one such system exerts on another is described by a coupling function; and the coupling functions extracted from the time-series of interacting dynamical systems are often found to be time-varying. Although much effort has been devoted to the analysis of coupling functions, the influence of time-variability on the associated dynamics remains largely unexplored. Motivated especially by coupling functions in biology, including the cardiorespiratory and neural delta-alpha coupling functions, this paper offers a contribution to the understanding of effects due to time-varying interactions. Through both numerics and mathematically rigorous theoretical consideration, we show that for time-variable coupling functions with time-independent net coupling strength, transitions into and out of phase- synchronization can occur, even though the frozen coupling functions determine phase-synchronization solely by virtue of their net coupling strength. Thus the information about interactions provided by the shape of coupling functions plays a greater role in determining behaviour when these coupling functions are time-variable. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.

Stankovski Tomislav

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