Synchronization analysis of time series obtained from anesthetized rats during painful action

O. E. Dick

Izvestiya VUZ. Applied Nonlinear Dynamics, Tome 32 (2024) no. 2, pp. 209-222.

Résumé

The purpose of this work is to determine the possibility of detecting changes in the relationships between such physiological rhythms as the activity of neurons in the reticular formation of the medulla oblongata, fluctuations in the blood pressure and respiration in anesthetized rats before and during the development of a pathological state associated with painful colorectal distension. This stretch mimics the pain localized in the lower abdomen in patients with irritable bowel syndrome and it is accompanied by responses of the brain neurons, fluctuations in the blood pressure and respiration. The analysis of changes in the relationships of these rhythms consisted in identifying phase synchronization between the time series of the variability of neuronal activity intervals and the variability of blood pressure intervals at the respiratory rate before and during pain exposure. Methods. To solve this problem, the synchrosqueezed wavelet transform method was applied, which makes it possible to effectively calculate the instantaneous frequencies and phases of non-stationary signals. As indicators of synchronization, we used the values of the index and the duration of phase synchronization as a time interval during which the value of the synchronization index is close to 1. Results. It has been established that the pain effect provides an adjustment of the frequency of the neuronal activity variability and the occurrence of synchronization between this activity and the blood pressure variability at the respiratory rate or causes an adjustment of the frequency of the blood pressure variability and the occurrence of synchronization between the blood pressure variability and the respiratory rhythm. It was found that the pain effect increases the duration of phase synchronization between the variability of the blood pressure and the respiratory rhythm or reduces the duration of phase synchronization between the variability of neuronal activity and the respiratory rhythm. Conclusion. The effect of painful colorectal distension on changes in the parameters of phase synchronization between physiological rhythms in anesthetized rats was studied in detail.

Détail

Keywords: synchrosqueezed wavelet transform, phase synchronization, physiological rhythms

Bibliographie

[1] Ticos C. M., Rosa Jr. E., Pardo W. B., Walkenstein J. A., Monti M., “Experimental real-time phase synchronization of a paced chaotic plasma discharge”, Phys. Rev. Lett., 85:14 (2000), 2929–2932 | DOI

[2] DeShazer D. J., Breban R., Ott E., Roy R., “Detecting phase synchronization in a chaotic laser array”, Phys. Rev. Lett., 87:4 (2001), 044101 | DOI

[3] Boccaletti S., Kurths J., Osipov G., Valladares D. L., Zhou C. S., “The synchronization of chaotic systems”, Physics Reports, 366:1–2 (2002), 1–101 | DOI | MR | Zbl

[4] Boccaletti S., Allaria E., Meucci R., Arecchi F. T., “Experimental characterization of the transition to phase synchronization of chaotic CO2 laser systems”, Phys. Rev. Lett., 89:19 (2002), 194101 | DOI

[5] Ponomarenko V. I., Prokhorov M. D., Bespyatov A. B., Bodrov M. B., Gridnev V. I., “Deriving main rhythms of the human cardiovascular system from the heartbeat time series and detecting their synchronization”, Chaos, Solitons Fractals, 23:4 (2005), 1429–1438 | DOI | Zbl

[6] Bespyatov A. B., Bodrov M. B., Gridnev V. I., Ponomarenko V. I., Prokhorov M. D., “Experimental observation of synchronization between the rhythms of cardiovascular system”, Nonlinear Phenomena in Complex Systems, 6:4 (2003), 885–893

[7] Hramov A. E., Koronovskii A. A., Ponomarenko V. I., Prokhorov M. D., “Detecting synchronization of self-sustained oscillators by external driving with varying frequency”, Phys. Rev. E, 73:2 (2006), 026208 | DOI | MR

[8] Hramov A. E., Koronovskii A. A., Ponomarenko V. I., Prokhorov M. D., “Detection of synchronization from univariate data using wavelet transform”, Phys. Rev. E, 75:5 (2007), 056207 | DOI | MR

[9] Moskalenko O. I., Koronovskii A. A., Khramov A. E., Zhuravlev M. O., “Otsenka stepeni sinkhronnosti rezhima peremezhayuscheisya fazovoi sinkhronizatsii po vremennomu ryadu: Modelnye sistemy i neirofiziologicheskie dannye”, Pisma v ZhETF, 103:8 (2016), 606–610 | DOI

[10] Dik O. E., Glazov A. L., “Parametry fazovoi sinkhronizatsii v elektroentsefalograficheskikh patternakh kak markery kognitivnykh narushenii”, ZhTF, 91:4 (2021), 678–688 | DOI

[11] Dick O. E., Glazov A. L., “Estimation of the synchronization between intermittent photic stimulation and brain response in hypertension disease by the recurrence and synchrosqueezed wavelet transform”, Neurocomputing, 455 (2021), 163–177 | DOI

[12] Rangaprakash D., Pradhan N., “Study of phase synchronization in multichannel seizure EEG using nonlinear recurrence measure”, Biomedical Signal Processing and Control, 11 (2014), 114–122 | DOI

[13] Kiselev A. R., Mironov S. A., Karavaev A. S., Kulminskiy D. D., Skazkina V. V., Borovkova E. I., Shvartz V. A., Ponomarenko V. I., Prokhorov M. D., “A comprehensive assessment of cardiovascular autonomic control using photoplethysmograms recorded from the earlobe and fingers”, Physiol. Meas, 37:4 (2016), 580–595 | DOI

[14] Borovkova E. V., Karavaev A. S., Kiselev A. R., Shvarts V. A., Mironov S. A., Ponomarenko V. I., Prokhorov M. D., “Metod diagnostiki sinkhronizovannosti 0,1 Gts ritmov vegetativnoi regulyatsii serdechno-sosudistoi sistemy v realnom vremeni”, Annaly aritmologii, 11:2 (2014), 129–136 | DOI

[15] Hoyer D., Leder U., Hoyer H., Pompe B., Sommer M., Zwiener U., “Mutual information and phase dependencies: measures of reduced nonlinear cardiorespiratory interactions after myocardial infarction”, Medical Engineering Physics, 24:1 (2002), 33–43 | DOI

[16] Karavaev A. S., Prokhorov M. D., Ponomarenko V. I., Kiselev A. R., Gridnev V. I., Ruban E. I., Bezruchko B. P., “Synchronization of low-frequency oscillations in the human cardiovascular system”, Chaos, 19:3 (2009), 033112 | DOI

[17] Shiogai Y., Stefanovska A., McClintock P. V. E., “Nonlinear dynamics of cardiovascular ageing”, Physics Reports, 488:2–3 (2010), 51–110 | DOI

[18] Stefanovska A., Haken H., McClintock P. V. E., Hožič M., Bajrović F., Ribarič S., “Reversible transitions between synchronization states of the cardiorespiratory system”, Phys. Rev. Lett., 85:22 (2000), 4831–4834 | DOI

[19] Lyubashina O. A., Mikhalkin A. A., Sivachenko I. B., “Neironalnye perestroiki na supraspinalnom urovne, sposobstvuyuschie kishechnoi giperalgezii pri kolite”, Integrativnaya fiziologiya, 2:1 (2021), 71–78 | DOI

[20] Lyubashina O. A., Sivachenko I. B., Mikhalkin A. A., “Impaired visceral pain-related functions of the midbrain periaqueductal gray in rats with colitis”, Brain Research Bulletin, 182 (2022), 12–25 | DOI

[21] Pikovskii A., Rozenblyum M., Kurts Yu., Sinkhronizatsiya: Fundamentalnoe nelineinoe yavlenie, Tekhnosfera, M., 2003, 496 pp.

[22] Rosenblum M. G., Cimponeriu L., Bezerianos A., Patzak A., Mrowka R., “Identification of coupling direction: Application to cardiorespiratory interaction”, Phys. Rev. E, 65:4 (2002), 041909 | DOI

[23] Ponomarenko V. I., Prokhorov M. D., Bespyatov A. B., Bodrov M. B., Gridnev V. I., “Deriving main rhythms of the human cardiovascular system from the heartbeat time series and detecting their synchronization”, Chaos, Solitons Fractals, 23:4 (2005), 1429–1438 | DOI | Zbl

[24] Kralemann B., Frühwirth M., Pikovsky A., Rosenblum M., Kenner T., Schaefer J., Moser M., “In vivo cardiac phase response curve elucidates human respiratory heart rate variability”, Nature Communications, 4 (2013), 2418 | DOI

[25] Zhang Q., Patwardhan A. R., Knapp C. F., Evans J. M., “Cardiovascular and cardiorespiratory phase synchronization in normovolemic and hypovolemic humans”, European Journal of Applied Physiology, 115:2 (2015), 417–427 | DOI

[26] Daubechies I., Ten Lectures on Wavelets, SIAM Publication, CBMS-NSF Regional Conference Series in Applied Mathematics Philadelphia, Pennsylvania, 1992, 369 pp. | DOI | MR | Zbl

[27] Li D., Li X., Cui D., Li Z. H., “Phase synchronization with harmonic wavelet transform with application to neuronal populations”, Neurocomputing, 74:17 (2011), 3389–3403 | DOI

[28] Daubechies I., Lu J., Wu H.-T., “Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool”, Applied and Computational Harmonic Analysis, 30:2 (2011), 243–261 | DOI | MR | Zbl

[29] Wu H.-T., Chan Y.-H., Lin Y.-T., Yeh Y.-H., “Using synchrosqueezing transform to discover breathing dynamics from ECG signals”, Applied and Computational Harmonic Analysis, 36:2 (2014), 354–359 | DOI | Zbl

[30] Wu H.-T., Lewis G. F., Davila M. I., Daubechies I., Porges S. W., “Optimizing estimates of instantaneous heart rate from pulse wave signals with the synchrosqueezing transform”, Methods. Inf. Med, 55:5 (2016), 463–472 | DOI

[31] Lyubashina O. A., Sivachenko I. B., Sokolov A. Y., “Differential responses of neurons in the rat caudal ventrolateral medulla to visceral and somatic noxious stimuli and their alterations in colitis”, Brain Research Bulletin, 152 (2019), 299–310 | DOI

[32] Thakur G., Brevdo E., Fučkar N. S., Wu H.-T., “The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications”, Signal Processing, 93:5 (2013), 1079–1094 | DOI | MR

[33] Mormann F., Lehnertz K., David P., Elger C. E., “Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients”, Physica D, 144:3–4 (2000), 358–369 | DOI | Zbl