@phdthesis{Oenel2008,
  author    = {{\"O}nel, Hakan},
  title     = {Electron acceleration in a flare plasma via coronal circuits},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29035},
  school      = {Universit{\"a}t Potsdam},
  year      = {2008},
  abstract  = {The Sun is a star, which due to its proximity has a tremendous influence on Earth. Since its very first days mankind tried to "understand the Sun", and especially in the 20th century science has uncovered many of the Sun's secrets by using high resolution observations and describing the Sun by means of models. As an active star the Sun's activity, as expressed in its magnetic cycle, is closely related to the sunspot numbers. Flares play a special role, because they release large energies on very short time scales. They are correlated with enhanced electromagnetic emissions all over the spectrum. Furthermore, flares are sources of energetic particles. Hard X-ray observations (e.g., by NASA's RHESSI spacecraft) reveal that a large fraction of the energy released during a flare is transferred into the kinetic energy of electrons. However the mechanism that accelerates a large number of electrons to high energies (beyond 20 keV) within fractions of a second is not understood yet. The thesis at hand presents a model for the generation of energetic electrons during flares that explains the electron acceleration based on real parameters obtained by real ground and space based observations. According to this model photospheric plasma flows build up electric potentials in the active regions in the photosphere. Usually these electric potentials are associated with electric currents closed within the photosphere. However as a result of magnetic reconnection, a magnetic connection between the regions of different magnetic polarity on the photosphere can establish through the corona. Due to the significantly higher electric conductivity in the corona, the photospheric electric power supply can be closed via the corona. Subsequently a high electric current is formed, which leads to the generation of hard X-ray radiation in the dense chromosphere. The previously described idea is modelled and investigated by means of electric circuits. For this the microscopic plasma parameters, the magnetic field geometry and hard X-ray observations are used to obtain parameters for modelling macroscopic electric components, such as electric resistors, which are connected with each other. This model demonstrates that such a coronal electric current is correlated with large scale electric fields, which can accelerate the electrons quickly up to relativistic energies. The results of these calculations are encouraging. The electron fluxes predicted by the model are in agreement with the electron fluxes deduced from the measured photon fluxes. Additionally the model developed in this thesis proposes a new way to understand the observed double footpoint hard X-ray sources.},
  language  = {en}
}
@phdthesis{Zoeller1999,
  author    = {Z{\"o}ller, Gert},
  title     = {Analyse raumzeitlicher Muster in Erdbebendaten},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0000122},
  school      = {Universit{\"a}t Potsdam},
  year      = {1999},
  abstract  = {Die vorliegende Arbeit besch{\"a}ftigt sich mit der Charakterisierung von Seismizit{\"a}t anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss dar{\"u}ber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus f{\"u}r die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen h{\"a}ufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die M{\"o}glichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird h{\"a}ufig als Vorl{\"a}uferphaenomen f{\"u}r starke Erdbeben gedeutet. Es wird eine neue Methode pr{\"a}sentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen erm{\"o}glicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erh{\"a}lt man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz daf{\"u}r nicht hoch genug, um eine Vorhersage im Sinne einer Aussage {\"u}ber den Ort, die Zeit und die St{\"a}rke eines zu erwartenden Hauptbebens zu erm{\"o}glichen.},
  language  = {en}
}
@phdthesis{Zou2007,
  author    = {Zou, Yong},
  title     = {Exploring recurrences in quasiperiodic systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-16497},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {In this work, some new results to exploit the recurrence properties of quasiperiodic dynamical systems are presented by means of a two dimensional visualization technique, Recurrence Plots(RPs). Quasiperiodicity is the simplest form of dynamics exhibiting nontrivial recurrences, which are common in many nonlinear systems. The concept of recurrence was introduced to study the restricted three body problem and it is very useful for the characterization of nonlinear systems. I have analyzed in detail the recurrence patterns of systems with quasiperiodic dynamics both analytically and numerically. Based on a theoretical analysis, I have proposed a new procedure to distinguish quasiperiodic dynamics from chaos. This algorithm is particular useful in the analysis of short time series. Furthermore, this approach demonstrates to be efficient in recognizing regular and chaotic trajectories of dynamical systems with mixed phase space. Regarding the application to real situations, I have shown the capability and validity of this method by analyzing time series from fluid experiments.},
  language  = {en}
}
@phdthesis{Zillmer2003,
  author    = {Zillmer, R{\"u}diger},
  title     = {Statistical properties and scaling of the Lyapunov exponents in stochastic systems},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0001147},
  school      = {Universit{\"a}t Potsdam},
  year      = {2003},
  abstract  = {Die vorliegende Arbeit umfaßt drei Abhandlungen, welche allgemein mit einer stochastischen Theorie f{\"u}r die Lyapunov-Exponenten befaßt sind. Mit Hilfe dieser Theorie werden universelle Skalengesetze untersucht, die in gekoppelten chaotischen und ungeordneten Systemen auftreten. Zun{\"a}chst werden zwei zeitkontinuierliche stochastische Modelle f{\"u}r schwach gekoppelte chaotische Systeme eingef{\"u}hrt, um die Skalierung der Lyapunov-Exponenten mit der Kopplungsst{\"a}rke ('coupling sensitivity of chaos') zu untersuchen. Mit Hilfe des Fokker-Planck-Formalismus werden Skalengesetze hergeleitet, die von Ergebnissen numerischer Simulationen best{\"a}tigt werden. Anschließend wird gezeigt, daß 'coupling sensitivity' im Fall gekoppelter ungeordneter Ketten auftritt, wobei der Effekt sich durch ein singul{\"a}res Anwachsen der Lokalisierungsl{\"a}nge {\"a}ußert. Numerische Ergebnisse f{\"u}r gekoppelte Anderson-Modelle werden bekr{\"a}ftigt durch analytische Resultate f{\"u}r gekoppelte raumkontinuierliche Schr{\"o}dinger-Gleichungen. Das resultierende Skalengesetz f{\"u}r die Lokalisierungsl{\"a}nge {\"a}hnelt der Skalierung der Lyapunov-Exponenten gekoppelter chaotischer Systeme. Schließlich wird die Statistik der exponentiellen Wachstumsrate des linearen Oszillators mit parametrischem Rauschen studiert. Es wird gezeigt, daß die Verteilung des zeitabh{\"a}ngigen Lyapunov-Exponenten von der Normalverteilung abweicht. Mittels der verallgemeinerten Lyapunov-Exponenten wird der Parameterbereich bestimmt, in welchem die Abweichungen von der Normalverteilung signifikant sind und Multiskalierung wesentlich wird.},
  language  = {en}
}
@phdthesis{Zickfeld2003,
  author    = {Zickfeld, Kirsten},
  title     = {Modeling large-scale singular climate events for integrated assessment},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0001176},
  school      = {Universit{\"a}t Potsdam},
  year      = {2003},
  abstract  = {Erkenntnisse aus pal{\"a}oklimatologischen Studien, theoretischen Betrachtungen und Modellsimulationen deuten darauf hin, dass anthropogene Emissionen von Treibhausgasen und Aerosolen zu großskaligen, singul{\"a}ren Klimaereignissen f{\"u}hren k{\"o}nnten. Diese bezeichnen stark nichtlineare, abrupte Klima{\"a}nderungen, mit regionalen bis hin zu globalen Auswirkungen. Ziel dieser Arbeit ist die Entwicklung von Modellen zweier maßgeblicher Komponenten des Klimasystems, die singul{\"a}res Verhalten aufweisen k{\"o}nnten: die atlantische thermohaline Zirkulation (THC) und der indische Monsun. Diese Modelle sind so konzipiert, dass sie den Anforderungen der "Integrated Assessment"-Modellierung gen{\"u}gen, d.h., sie sind realistisch, recheneffizient, transparent und flexibel. Das THC-Modell ist ein einfaches, interhemisph{\"a}risches Boxmodell, das anhand von Daten kalibriert wird, die mit einem gekoppelten Klimamodell mittlerer Komplexit{\"a}t erzeugt wurden. Das Modell wird durch die globale Mitteltemperatur angetrieben, die mit Hilfe eines linearen Downscaling-Verfahrens in regionale W{\"a}rme- und S{\"u}ßwasserfl{\"u}sse {\"u}bersetzt wird. Die Ergebnisse einer Vielzahl von zeitabh{\"a}ngigen Simulationen zeigen, dass das Modell in der Lage ist, maßgebliche Eigenschaften des Verhaltens komplexer Klimamodelle wiederzugeben, wie die Sensitivit{\"a}t bez{\"u}glich des Ausmaßes, der regionalen Verteilung und der Rate der Klima{\"a}nderung. Der indische Monsun wird anhand eines neuartigen eindimensionalen Boxmodells der tropischen Atmosph{\"a}re beschrieben. Dieses enth{\"a}lt Parmetrisierungen der Oberfl{\"a}chen- und Strahlungsfl{\"u}sse, des hydrologischen Kreislaufs und derHydrologie der Landoberfl{\"a}che. Trotz des hohen Idealisierungsgrades ist das Modell in der Lage, relevante Aspekte der beobachteten Monsundynamik, wie z.B. den Jahresgang des Niederschlags und das Eintritts- sowie R{\"u}ckzugsdatum des Sommermonsuns, zufrieden stellend zu simulieren. Außerdem erfasst das Modell die Sensitivit{\"a}tdes Monsuns bez{\"u}glich {\"A}nderungen der Treibhausgas- und Aerosolkonzentrationen, die aus komplexeren Modellen bekannt sind. Eine vereinfachte Version des Monsunmodells wird f{\"u}r die Untersuchung des qualitativen Systemverhaltens in Abh{\"a}ngigkeit von {\"A}nderungen der Randbedingungen eingesetzt. Das bemerkenswerteste Ergebnis ist das Auftreten einer Sattelknotenbifurkation des Sommermonsuns f{\"u}r kritische Werte der Albedo oder der Sonneneinstrahlung. Dar{\"u}ber hinaus weist das Modell zwei stabile Zust{\"a}nde auf: neben dem niederschlagsreichen Sommermonsun besteht ein Zustand, der sich durch einen schwachen hydrologischen Kreislauf auszeichnet. Das Beachtliche an diesen Ergebnissen ist, dass anthropogene St{\"o}rungen der plantetaren Albedo, wie Schwefelemissionen und/oder Landnutzungs{\"a}nderungen, zu einer Destabilisierung des indischen Monsuns f{\"u}hren k{\"o}nnten. Das THC-Boxmodell findet exemplarische Anwendung in einem "Integrated Assessment" von Klimaschutzstrategien. Basierend auf dem konzeptionellen und methodischen Ger{\"u}st des Leitplankenansatzes werden Emissionskorridore (d.h. zul{\"a}ssige Spannen an CO2-Emissionen) berechnet, die das Risiko eines THC-Zusammenbruchs begrenzen sowie sozio{\"o}konomische Randbedingungen ber{\"u}cksichtigen. Die Ergebnisse zeigen u.a. eine starke Abh{\"a}ngigkeit der Breite der Emissionskorridore von der Klima- und hydrologischen Sensitivit{\"a}t. F{\"u}r kleine Werte einer oder beider Sensitivit{\"a}ten liegt der obere Korridorrand bei weit h{\"o}heren Emissionswerten als jene, die von plausiblen Emissionsszenarien f{\"u}r das 21. Jahrhundert erreicht werden. F{\"u}r große Werte der Sensitivit{\"a}ten hingegen, verlassen schon niedrige Emissionsszenarien den Korridor in den fr{\"u}hen Jahrzehnten des 21. Jahrhunderts. Dies impliziert eine Abkehr von den gegenw{\"a}rtigen Emissionstrends innherhalb der kommenden Jahrzehnte, wenn das Risko eines THC Zusammenbruchs gering gehalten werden soll. Anhand einer Vielzahl von Anwendungen - von Sensitivit{\"a}ts- {\"u}ber Bifurkationsanalysen hin zu integrierter Modellierung - zeigt diese Arbeit den Wert reduzierter Modelle auf. Die Ergebnisse und die daraus zu ziehenden Schlussfolgerungen liefern einen wertvollen Beitrag zu der wissenschaftlichen und politischen Diskussion bez{\"u}glich der Folgen des anthropogenen Klimawandels und der langfristigen Klimaschutzziele.},
  language  = {en}
}
@phdthesis{Zheng2021,
  author    = {Zheng, Chunming},
  title     = {Bursting and synchronization in noisy oscillatory systems},
  doi       = {10.25932/publishup-50019},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-500199},
  school      = {Universit{\"a}t Potsdam},
  pages     = {iv, 87},
  year      = {2021},
  abstract  = {Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years. In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion. In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network. In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.},
  language  = {en}
}
@phdthesis{Zhelavskaya2020,
  author    = {Zhelavskaya, Irina},
  title     = {Modeling of the Plasmasphere Dynamics},
  doi       = {10.25932/publishup-48243},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-482433},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xlii, 256},
  year      = {2020},
  abstract  = {The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions. First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set. We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data. The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions. Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers. Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.},
  language  = {en}
}
@phdthesis{Zhang2008,
  author    = {Zhang, Bo},
  title     = {Magnetic fields near microstructured surfaces : application to atom chips},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-28984},
  school      = {Universit{\"a}t Potsdam},
  year      = {2008},
  abstract  = {Microfabricated solid-state surfaces, also called atom chip', have become a well-established technique to trap and manipulate atoms. This has simplified applications in atom interferometry, quantum information processing, and studies of many-body systems. Magnetic trapping potentials with arbitrary geommetries are generated with atom chip by miniaturized current-carrying conductors integrated on a solid substrate. Atoms can be trapped and cooled to microKelvin and even nanoKelvin temperatures in such microchip trap. However, cold atoms can be significantly perturbed by the chip surface, typically held at room temperature. The magnetic field fluctuations generated by thermal currents in the chip elements may induce spin flips of atoms and result in loss, heating and decoherence. In this thesis, we extend previous work on spin flip rates induced by magnetic noise and consider the more complex geometries that are typically encountered in atom chips: layered structures and metallic wires of finite cross-section. We also discuss a few aspects of atom chips traps built with superconducting structures that have been suggested as a means to suppress magnetic field fluctuations. The thesis describes calculations of spin flip rates based on magnetic Green functions that are computed analytically and numerically. For a chip with a top metallic layer, the magnetic noise depends essentially on the thickness of that layer, as long as the layers below have a much smaller conductivity. Based on this result, scaling laws for loss rates above a thin metallic layer are derived. A good agreement with experiments is obtained in the regime where the atom-surface distance is comparable to the skin depth of metal. Since in the experiments, metallic layers are always etched to separate wires carrying different currents, the impact of the finite lateral wire size on the magnetic noise has been taken into account. The local spectrum of the magnetic field near a metallic microstructure has been investigated numerically with the help of boundary integral equations. The magnetic noise significantly depends on polarizations above flat wires with finite lateral width, in stark contrast to an infinitely wide wire. Correlations between multiple wires are also taken into account. In the last part, superconducting atom chips are considered. Magnetic traps generated by superconducting wires in the Meissner state and the mixed state are studied analytically by a conformal mapping method and also numerically. The properties of the traps created by superconducting wires are investigated and compared to normal conducting wires: they behave qualitatively quite similar and open a route to further trap miniaturization, due to the advantage of low magnetic noise. We discuss critical currents and fields for several geometries.},
  language  = {en}
}
@phdthesis{Zeuschner2022,
  author    = {Zeuschner, Steffen Peer},
  title     = {Magnetoacoustics observed with ultrafast x-ray diffraction},
  doi       = {10.25932/publishup-56109},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-561098},
  school      = {Universit{\"a}t Potsdam},
  pages     = {V, 128, IX},
  year      = {2022},
  abstract  = {In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress. In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling. The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.},
  language  = {en}
}
@phdthesis{Zemanova2007,
  author    = {Zemanov{\´a}, Lucia},
  title     = {Structure-function relationship in hierarchical model of brain networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-18400},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {The mammalian brain is, with its numerous neural elements and structured complex connectivity, one of the most complex systems in nature. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex networks. Here, we try to shed some light on the relationship between structural and functional connectivities by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the cortical areas by a subnetwork of interacting excitable neurons (multilevel model) and by a neural mass model (population model). With weak couplings, the multilevel model displays biologically plausible dynamics and the synchronization patterns reveal a hierarchical cluster organization in the network structure. We can identify a group of brain areas involved in multifunctional tasks by comparing the dynamical clusters to the topological communities of the network. With strong couplings of multilevel model and by using neural mass model, the dynamics are characterized by well-defined oscillations. The synchronization patterns are mainly determined by the node intensity (total input strengths of a node); the detailed network topology is of secondary importance. The biologically improved multilevel model exhibits similar dynamical patterns in the two regimes. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.},
  language  = {en}
}