scholarly journals Spiral wave initiation in excitable media

2018 ◽  
Vol 376 (2135) ◽  
pp. 20170379 ◽  
Author(s):  
V. S. Zykov
Keyword(s):  
Resting State ◽  
Spiral Wave ◽  
Dissipative Structures ◽  
Excitable Media ◽  
Excitation Wave ◽  
Practical Applications ◽  
Sustained Activity ◽  
Neuronal Tissues ◽  
Life Threatening ◽  
Mutual Collision

Spiral waves represent an important example of dissipative structures observed in many distributed systems in chemistry, biology and physics. By definition, excitable media occupy a stationary resting state in the absence of external perturbations. However, a perturbation exceeding a threshold results in the initiation of an excitation wave propagating through the medium. These waves, in contrast to acoustic and optical ones, disappear at the medium's boundary or after a mutual collision, and the medium returns to the resting state. Nevertheless, an initiation of a rotating spiral wave results in a self-sustained activity. Such activity unexpectedly appearing in cardiac or neuronal tissues usually destroys their dynamics which results in life-threatening diseases. In this context, an understanding of possible scenarios of spiral wave initiation is of great theoretical importance with many practical applications. This article is part of the theme issue ‘Dissipative structures in matter out of equilibrium: from chemistry, photonics and biology (part 2)’.

scholarly journals Phase-resolved analysis of the susceptibility of pinned spiral waves to far-field pacing in a two-dimensional model of excitable media

2010 ◽  
Vol 368 (1918) ◽  
pp. 2221-2236 ◽  
Author(s):  
Philip Bittihn ◽  
Amgad Squires ◽  
Gisa Luther ◽  
Eberhard Bodenschatz ◽  
Valentin Krinsky ◽  
...  
Keyword(s):  
Local Control ◽  
Spiral Wave ◽  
Spiral Waves ◽  
Excitable Media ◽  
Excitation Threshold ◽  
Far Field ◽  
Life Threatening ◽  
Discontinuous Phase ◽  
Rotating Wave ◽  
Spatio Temporal

Life-threatening cardiac arrhythmias are associated with the existence of stable and unstable spiral waves. Termination of such complex spatio-temporal patterns by local control is substantially limited by anchoring of spiral waves at natural heterogeneities. Far-field pacing (FFP) is a new local control strategy that has been shown to be capable of unpinning waves from obstacles. In this article, we investigate in detail the FFP unpinning mechanism for a single rotating wave pinned to a heterogeneity. We identify qualitatively different phase regimes of the rotating wave showing that the concept of vulnerability is important but not sufficient to explain the failure of unpinning in all cases. Specifically, we find that a reduced excitation threshold can lead to the failure of unpinning, even inside the vulnerable window. The critical value of the excitation threshold (below which no unpinning is possible) decreases for higher electric field strengths and larger obstacles. In contrast, for a high excitation threshold, the success of unpinning is determined solely by vulnerability, allowing for a convenient estimation of the unpinning success rate. In some cases, we also observe phase resetting in discontinuous phase intervals of the spiral wave. This effect is important for the application of multiple stimuli in experiments.

Size matters: Effects of the size of heterogeneity on the wave re-entry and spiral wave formation in an excitable media

2021 ◽  
Vol 31 (5) ◽  
pp. 053131
Author(s):  
Karthikeyan Rajagopal ◽  
Shaobo He ◽  
Anitha Karthikeyan ◽  
Prakash Duraisamy
Keyword(s):  
Spiral Wave ◽  
Wave Formation ◽  
Excitable Media

scholarly journals Prediction of Individual User’s Dynamic Ranges of EEG Features from Resting-State EEG Data for Evaluating Their Suitability for Passive Brain–Computer Interface Applications

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 988
Author(s):  
Ho-Seung Cha ◽  
Chang-Hee Han ◽  
Chang-Hwan Im
Keyword(s):  
Resting State ◽  
Brain Computer Interface ◽  
Low Cost ◽  
Mental States ◽  
Computer Interface ◽  
Practical Applications ◽  
Eeg Data ◽  
Brain States ◽  
Electroencephalogram Eeg ◽  
Eeg Features

With the recent development of low-cost wearable electroencephalogram (EEG) recording systems, passive brain–computer interface (pBCI) applications are being actively studied for a variety of application areas, such as education, entertainment, and healthcare. Various EEG features have been employed for the implementation of pBCI applications; however, it is frequently reported that some individuals have difficulty fully enjoying the pBCI applications because the dynamic ranges of their EEG features (i.e., its amplitude variability over time) were too small to be used in the practical applications. Conducting preliminary experiments to search for the individualized EEG features associated with different mental states can partly circumvent this issue; however, these time-consuming experiments were not necessary for the majority of users whose dynamic ranges of EEG features are large enough to be used for pBCI applications. In this study, we tried to predict an individual user’s dynamic ranges of the EEG features that are most widely employed for pBCI applications from resting-state EEG (RS-EEG), with the ultimate goal of identifying individuals who might need additional calibration to become suitable for the pBCI applications. We employed a machine learning-based regression model to predict the dynamic ranges of three widely used EEG features known to be associated with the brain states of valence, relaxation, and concentration. Our results showed that the dynamic ranges of EEG features could be predicted with normalized root mean squared errors of 0.2323, 0.1820, and 0.1562, respectively, demonstrating the possibility of predicting the dynamic ranges of the EEG features for pBCI applications using short resting EEG data.

INVERSE DISPERSION RELATION OF BZ-WAVES IN NONSTATIONARY GELS

1999 ◽  
Vol 09 (10) ◽  
pp. 2099-2104 ◽  
Author(s):  
W. HANKE
Keyword(s):  
Dispersion Relation ◽  
Point Of View ◽  
Excitable Media ◽  
Experimental Investigations ◽  
Theoretical Point ◽  
Bz Reaction ◽  
Inverse Dispersion ◽  
Sustained Activity ◽  
System A ◽  
Theoretical Considerations

The behavior of wave propagation, as well that of isolated waves as that of self-sustained activity, in excitable media is characterized by the dispersion relation of the system. For the Belousov–Zhabotinsky (BZ)-reaction as by far the best described system, a number of theoretical considerations and experimental investigations do exist. From the theoretical point of view the dispersion relation of the BZ-reaction has two branches, an upper "fast" or stable branch typified by singular solutions and a lower "slow" branch whose solutions are regular, with a connection between the two branches, defining the smallest possible period and the absolute refractory period of the system. Experimental data are usually located on the upper branch giving higher propagation velocity at increasing period. Only one set of results was published in the early 1970s with velocity being an increasing function of frequency. This set of data was stated to be "difficult to believe" in later papers. We now present here a more detailed study of a BZ-system with a dispersion relation with an increasing velocity at decreasing period, verifying the existence of an "inverse" dispersion relation at least in the nonstationary gels we have used.

scholarly journals Spiral Wave Formation in Three-Dimensional Excitable Media

1996 ◽  
Vol 77 (15) ◽  
pp. 3244-3247 ◽  
Author(s):  
Takashi Amemiya ◽  
Sándor Kádár ◽  
Petteri Kettunen ◽  
Kenneth Showalter
Keyword(s):  
Three Dimensional ◽  
Spiral Wave ◽  
Wave Formation ◽  
Excitable Media

scholarly journals Detecting spiral wave tips using deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Henning Lilienkamp ◽  
Thomas Lilienkamp
Keyword(s):  
Deep Neural Networks ◽  
Cell Model ◽  
Ex Vivo ◽  
Spiral Wave ◽  
Specific Situation ◽  
Cell Models ◽  
Noise Levels ◽  
Life Threatening ◽  
Spatio Temporal ◽  
Influence Of Noise

AbstractThe chaotic spatio-temporal electrical activity during life-threatening cardiac arrhythmias like ventricular fibrillation is governed by the dynamics of vortex-like spiral or scroll waves. The organizing centers of these waves are called wave tips (2D) or filaments (3D) and they play a key role in understanding and controlling the complex and chaotic electrical dynamics. Therefore, in many experimental and numerical setups it is required to detect the tips of the observed spiral waves. Most of the currently used methods significantly suffer from the influence of noise and are often adjusted to a specific situation (e.g. a specific numerical cardiac cell model). In this study, we use a specific type of deep neural networks (UNet), for detecting spiral wave tips and show that this approach is robust against the influence of intermediate noise levels. Furthermore, we demonstrate that if the UNet is trained with a pool of numerical cell models, spiral wave tips in unknown cell models can also be detected reliably, suggesting that the UNet can in some sense learn the concept of spiral wave tips in a general way, and thus could also be used in experimental situations in the future (ex-vivo, cell-culture or optogenetic experiments).

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