In einem klassischen Kontext bedeutet Synchronisierung die Anpassung der Rhythmen von selbst-erregten periodischen Oszillatoren aufgrund ihrer schwachen Wechselwirkung. <br /> Der Begriff der Synchronisierung geht auf den berühmten niederläandischen Wissenschaftler Christiaan Huygens im 17. Jahrhundert zurück, der über seine Beobachtungen mit Pendeluhren berichtete. Wenn zwei solche Uhren auf der selben Unterlage plaziert wurden, schwangen ihre Pendel in perfekter Übereinstimmung. <br /> Mathematisch bedeutet das, daß infolge der Kopplung, die Uhren mit gleichen Frequenzen und engverwandten Phasen zu oszillieren begannen. <br /> Als wahrscheinlich ältester beobachteter nichtlinearer Effekt wurde die Synchronisierung erst nach den Arbeiten von E. V. Appleton und B. Van der Pol gegen 1920 verstanden, die die Synchronisierung in Triodengeneratoren systematisch untersucht haben. Seitdem wurde die Theorie gut entwickelt, und hat viele Anwendungen gefunden. <br /> <br /> Heutzutage weiss man, dass bestimmte, sogar ziemlich einfache, Systeme, ein chaotisches Verhalten ausüben können. Dies bedeutet, dass ihre Rhythmen unregelmäßig sind und nicht durch nur eine einzige Frequenz charakterisiert werden können. <br /> Wie in der Habilitationsarbeit gezeigt wurde, kann man jedoch den Begriff der Phase und damit auch der Synchronisierung auf chaotische Systeme ausweiten. Wegen ihrer sehr schwachen Wechselwirkung treten Beziehungen zwischen den Phasen und den gemittelten Frequenzen auf und führen damit zur Übereinstimmung der immer noch unregelmäßigen Rhythmen. Dieser Effekt, sogenannter Phasensynchronisierung, konnte später in Laborexperimenten anderer wissenschaftlicher Gruppen bestätigt werden. <br /> <br /> Das Verständnis der Synchronisierung unregelmäßiger Oszillatoren erlaubte es uns, wichtige Probleme der Datenanalyse zu untersuchen. <br /> Ein Hauptbeispiel ist das Problem der Identifikation schwacher Wechselwirkungen zwischen Systemen, die nur eine passive Messung erlauben. Diese Situation trifft häufig in lebenden Systemen auf, wo Synchronisierungsphänomene auf jedem Niveau erscheinen - auf der Ebene von Zellen bis hin zu makroskopischen physiologischen Systemen; in normalen Zuständen und auch in Zuständen ernster Pathologie. <br /> Mit unseren Methoden konnten wir eine Anpassung in den Rhythmen von Herz-Kreislauf und Atmungssystem in Menschen feststellen, wobei der Grad ihrer Interaktion mit der Reifung zunimmt. Weiterhin haben wir unsere Algorithmen benutzt, um die Gehirnaktivität von an Parkinson Erkrankten zu analysieren. Die Ergebnisse dieser Kollaboration mit Neurowissenschaftlern zeigen, dass sich verschiedene Gehirnbereiche genau vor Beginn des pathologischen Zitterns synchronisieren. Außerdem gelang es uns, die für das Zittern verantwortliche Gehirnregion zu lokalisieren. / In a classical context, synchronization means adjustment of rhythms of self-sustained periodic oscillators due to their weak interaction. The history of synchronization goes back to the 17th century when the famous Dutch scientist Christiaan Huygens reported on his observation of synchronization of pendulum clocks: when two such clocks were put on a common support, their pendula moved in a perfect agreement. In rigorous terms, it means that due to coupling the clocks started to oscillate with identical frequencies and tightly related phases. Being, probably, the oldest scientifically studied nonlinear effect, synchronization was understood only in 1920-ies when E. V. Appleton and B. Van der Pol systematically - theoretically and experimentally - studied synchronization of triode generators. Since that the theory was well developed and found many applications. <br /> Nowadays it is well-known that certain systems, even rather simple ones, can exhibit chaotic behaviour. It means that their rhythms are irregular, and cannot be characterized only by one frequency. However, as is shown in the Habilitation work, one can extend the notion of phase for systems of this class as well and observe their synchronization, i.e., agreement of their (still irregular!) rhythms: due to very weak interaction there appear relations between the phases and average frequencies. This effect, called phase synchronization, was later confirmed in laboratory experiments of other scientific groups. <br /> Understanding of synchronization of irregular oscillators allowed us to address important problem of data analysis: how to reveal weak interaction between the systems if we cannot influence them, but can only passively observe, measuring some signals. This situation is very often encountered in biology, where synchronization phenomena appear on every level - from cells to macroscopic physiological systems; in normal states as well as in severe pathologies. With our methods we found that cardiovascular and respiratory systems in humans can adjust their rhythms; the strength of their interaction increases with maturation. Next, we used our algorithms to analyse brain activity of Parkinsonian patients. The results of this collaborative work with neuroscientists show that different brain areas synchronize just before the onset of pathological tremor. Morevoever, we succeeded in localization of brain areas responsible for tremor generation.

The detection for phase locking in a forced oscillator with dual attractors and ill-defined phase structure is hard until a quantitative approach was constructed for detecting phase locking via stroboscopic method. We study the route to weak phase locking in a chaotic system ¡§Chua oscillator¡¨ with complex attractor structure by analyzing the stroboscopic points. The onset of weak phase locking detected by using this statistical approach and the critical coupling strength calculated by conditional Lyapunov exponent are matched well. Detailed structure of phase locking intensity is described by the Arnold tongue diagram. Moreover, we apply this approach on three hyper-chaotic systems with multi-scroll attractor, including hyper-chaotic Rössler system, hyper-chaotic Lorenz system, and modified MCK oscillator. The weak phase locking between hyper-chaotic system and a periodic or a chaotic driving force is observable following the condition of stroboscopic point concentration.

Fast neural oscillations known as beta (12-30Hz) and gamma (30-100Hz) rhythms are recorded across several brain areas of various species. They have been linked to diverse functions like perception, attention, cognition, or interareal brain communication. The majority of the tasks performed by the brain involves communication between brain areas. To efficiently perform communication, mathematical models of brain activity require representing neural oscillations as sustained and coherent rhythms. However, some recordings show that fast oscillations are not sustained or coherent. Rather they are noisy and appear as short and random epochs of sustained activity called bursts. Therefore, modeling such noisy oscillations and investigating their ability to show interareal coherence and phase synchronization are important questions that need to be addressed. In this thesis, we propose theoretical models of noisy oscillations in the gamma and beta bands with the same properties as those observed in in \textit{vivo}. Such models should exhibit dynamic and statistical features of the data and support dynamic phase synchronization. We consider networks composed of excitatory and inhibitory populations. Noise is the result of the finite size effect of the system or the synaptic inputs. The associated dynamics of the Local Field Potentials (LFPs) are modeled as linear equations, sustained by additive and/or multiplicative noises. Such oscillatory LFPs are also known as noise-induced or quasi-cycles oscillations. The LFPs are better described using the envelope-phase representation. In this framework, a burst is defined as an epoch during which the envelope magnitude exceeds a given threshold. Fortunately, to the lowest order, the envelope dynamics are uncoupled from the phase dynamics for both additive and multiplicative noises. For additive noise, we derive the mean burst duration via a mean first passage time approach and uncover an optimal range of parameters for healthy rhythms. Multiplicative noise is shown theoretically to further synchronize neural activities and better explain pathologies with an excess of neural synchronization. We used the stochastic averaging method (SAM) as a theoretical tool to derive the envelope-phase equations. The SAM is extended to extract the envelope-phase equations of two coupled brain areas. The goal is to tackle the question of phase synchronization of noise-induced oscillations with application to interareal brain communication. The results show that noise and propagation delay are essential ingredients for dynamic phase synchronization of quasi-cycles. This suggests that the noisy oscillations recorded in \textit{vivo} and modeled here as quasi-cycles are good candidates for such neural communication. We further extend the use of the SAM to describe several coupled networks subject to white and colored noises across the Hopf bifurcation ie in both quasi-cycle and limit cycle regimes. This allows the description of multiple brain areas in the envelope-phase framework. The SAM constitutes an appropriate and flexible theoretical tool to describe a large class of stochastic oscillatory phenomena through the envelope-phase framework.

A study on phase synchronization in large populations of nonlinear dynamical systems is presented in this thesis. Using the well-known Rossler system as a prototypical model, phase synchronization in one oscillator with periodic external forcing and in two-coupled nonidentical oscillators was explored at first. The study was further extended to consider three-dimensional lattices and globally coupled populations of nonidentical oscillators, in which the mathematical formulation that represents phase synchronization in the generalized N-coupled Rossler system was derived and several computer programs that perform numerical simulations were developed. The results show the effects of coupling dimension, coupling strength, population size, and system parameter on phase synchronization of the various Rossler systems, which may be applicable to studying phase synchronization in other nonlinear dynamical systems as well.

In this paper we present an approach to recover the dynamics from recurrences of a system and then generate (multivariate) twin surrogate (TS) trajectories. In contrast to other approaches, such as the linear-like surrogates, this technique produces surrogates which correspond to an independent copy of the underlying system, i. e. they induce a trajectory of the underlying system visiting the attractor in a different way. We show that these surrogates are well suited to test for complex synchronization, which makes it possible to systematically assess the reliability of synchronization analyses. We then apply the TS to study binocular fixational movements and find strong indications that the fixational movements of the left and right eye are phase synchronized. This result indicates that there might be one centre only in the brain that produces the fixational movements in both eyes or a close link between two centres.

In order to investigate the temporal characteristics of cognitive processing, we apply multivariate phase synchronization analysis to event-related potentials. The experimental design combines a semantic incongruity in a sentence context with a physical mismatch (color change). In the ERP average, these result in an N400 component and a P300-like positivity, respectively. The synchronization analysis shows an effect of global desynchronization in the theta band around 288ms after stimulus presentation for the semantic incongruity, while the physical mismatch elicits an increase of global synchronization in the alpha band around 204ms. Both of these effects clearly precede those in the ERP average. Moreover, the delay between synchronization effect and ERP component correlates with the complexity of the cognitive processes.

Orthostatic intolerance (OI), i.e., the inability to maintain stable arterial pressure during upright posture, is a major problem for astronauts after spaceflight. Therefore, one important goal of spaceflight-related research is the development of countermeasures to prevent post flight OI. Given the rarity and expense of spaceflight, countermeasure development requires ground-based simulations of partial gravity to induce appropriate orthostatic effects on the human body, and to test the efficacy of potential countermeasures. To test the efficacy of upright lower body positive pressure (LBPP) as a model for simulating cardiovascular responses to lunar and Martian gravities on Earth, cardiovascular responses to upright LBPP were compared with those of head-up tilt (HUT), a well-accepted simulation of partial gravity, in both ambulatory and cardiovascularly deconditioned subjects. Results indicate that upright LBPP and HUT induced similar changes in cardiovascular regulation, supporting the use of upright LBPP as a potential model for simulating cardiovascular responses to standing and moving in lunar and Martian gravities. To test the efficacy of a short exposure to artificial gravity (AG) as a countermeasure to spaceflight-induced OI, orthostatic tolerance limits (OTL) and cardiovascular responses to orthostatic stress were tested in cardiovascularly deconditioned subjects, using combined 70º head-up tilt and progressively increased lower body negative pressure, once following 90 minutes AG exposure and once following 90 minutes of -6º head-down bed rest (HDBR). Results indicate that a short AG exposure increased OTL of cardiovascularly deconditioned subjects, with increased baroreflex and sympathetic responsiveness, compared to those measured after HDBR exposure. To gain more insight into mechanisms of causal connectivity in cardiovascular and cardiorespiratory oscillations during orthostatic challenge in both ambulatory and cardiovascularly deconditioned subjects, couplings among R-R intervals (RRI), systolic blood pressure (SBP) and respiratory oscillations in response to graded HUT and dehydration were studied using a phase synchronization approach. Results indicate that increasing orthostatic stress disassociated interactions among RRI, SBP and respiration, and that dehydration exacerbated the disconnection. The loss of causality from SBP to RRI following dehydration suggests that dehydration also reduced involvement of baroreflex regulation, which may contribute to the increased occurrence of OI.

abstract: A 4-phase, quasi-current-mode hysteretic buck converter with digital frequency synchronization, online comparator offset-calibration and digital current sharing control is presented. The switching frequency of the hysteretic converter is digitally synchronized to the input clock reference with less than ±1.5% error in the switching frequency range of 3-9.5MHz. The online offset calibration cancels the input-referred offset of the hysteretic comparator and enables ±1.1% voltage regulation accuracy. Maximum current-sharing error of ±3.6% is achieved by a duty-cycle-calibrated delay line based PWM generator, without affecting the phase synchronization timing sequence. In light load conditions, individual converter phases can be disabled, and the final stage power converter output stage is segmented for high efficiency. The DC-DC converter achieves 93% peak efficiency for Vi = 2V and Vo = 1.6V. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第22828号 / 医博第4667号 / 新制||医||1047(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 村井 俊哉, 教授 古川 壽亮, 教授 高橋 淳 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21213号 / 情博第666号 / 新制||情||115(附属図書館) / 京都大学大学院情報学研究科先端数理科学専攻 / (主査)講師 青柳 富誌生, 教授 西村 直志, 准教授 田口 智清, 講師 水原 啓暁 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM