Browsing by Author "Andrzejak, Ralph Gregor"

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  • Andrzejak, Ralph Gregor; Rummel, Christian; Mormann, Florian; Schindler, Kaspar A. (Nature Publishing Group, 2016)
    Conceptually and structurally simple mathematical models of coupled oscillator networks can show a rich variety of complex dynamics, providing fundamental insights into many real-world phenomena.A recent and not yet fully ...
  • Grau Leguia, Marc (Universitat Pompeu Fabra, 2019-03-15)
    Un problema principal de la ciència de xarxes és com reconstruir (inferir) la topologia d’una xarxa real a partir de senyals mesurades de les seves unitats internes. Entendre la arquitectura d’una xarxa complexa és clau, ...
  • Chicharro Raventós, Daniel (Universitat Pompeu Fabra, 2011-04-07)
    We study two methods of data analysis which are common tools for the analysis of neuronal data. In particular, we examine how causal interactions between brain regions can be investigated using time series reflecting the ...
  • Ruzzene, Giulia; Omelchenko, Iryna; Schöll, Eckehard; Zakharova, Anna; Andrzejak, Ralph Gregor (American Institute of Physics (AIP), 2019)
    We propose a method to control chimera states in a ring-shaped network of nonlocally coupled phase oscillators. This method acts exclusivelyon the network’s connectivity. Using the idea of a pacemaker oscillator, we ...
  • Andrzejak, Ralph Gregor; Laiou, Petroula (American Physical Society, 2017)
    The understanding of interacting dynamics is important for the characterization of real-world/nnetworks. In general real-world networks are heterogeneous in the sense that each node of the/nnetwork is a dynamics with di ...
  • Serrà Julià, Joan; Serra, Xavier; Andrzejak, Ralph Gregor (Institute of Physics (IOP), 2009)
    There is growing evidence that nonlinear time series analysis techniques can be used to successfully characterize, classify, or process signals derived from realworld dynamics even though these are not necessarily deterministic ...
  • Laiou, Petroula (Universitat Pompeu Fabra, 2017-10-05)
    The characterization of interactions between coupled dynamics from their signals is important for the understanding of real-world systems. The particular aspect of the detection of directional interactions has a central ...
  • Malvestio, Irene (Universitat Pompeu Fabra, 2019-02-21)
    An important problem in neuroscience is the assessment of the connectivity between neurons from their spike trains. One recent approach developed for the detection of directional couplings between dynamics based on ...
  • Leguia, Marc G.; Andrzejak, Ralph Gregor; Levnajić, Zoran (Institute of Physics (IOP), 2017)
    Topologies of real-world complex networks are rarely accessible, but can often be reconstructed from experimentally obtained time series via suitable network reconstruction methods. Extending our earlier work on methods ...
  • Andrzejak, Ralph Gregor; Ruzzene, Giulia; Malvestio, Irene (American Institute of Physics (AIP), 2017)
    Networks of coupled oscillators in chimera states are characterized by an intriguing interplay of synchronous and asynchronous motion. While chimera states were initially discovered in mathematical model systems, there ...
  • Leguia, Marc G.; Martínez, Cristina G. B.; Malvestio, Irene; Tauste Campo, Adrià; Rocamora, Rodrigo; Levnajić, Zoran; Andrzejak, Ralph Gregor (American Physical Society, 2019)
    Inferring the topology of a network using the knowledge of the signals of each of the interacting units is key to understanding real-world systems. One way to address this problem is using data- driven methods like ...
  • Andrzejak, Ralph Gregor; Ruzzene, Giulia; Malvestio, Irene; Schindler, Kaspar A.; Schöll, Eckehard; Zakharova, Anna (American Institute of Physics (AIP), 2018)
    We study two-layer networks of identical phase oscillators. Each individual layer is a ring network for which a non-local intra-layer coupling leads to the formation of a chimera state. The number of oscillators and their ...
  • Serrà Julià, Joan; Kantz, Holger; Serra, Xavier; Andrzejak, Ralph Gregor (Institute of Electrical and Electronics Engineers (IEEE), 2011)
    Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. ...
  • Chicharro Raventós, Daniel; Andrzejak, Ralph Gregor (American Physical Society, 2009)
    To detect directional couplings from time series various measures based on distances in reconstructed state spaces were introduced. These measures can, however, be biased by asymmetries in the dynamics' structure, noise ...
  • Rummel, Christian; Abela, Eugenio; Andrzejak, Ralph Gregor; Hauf, Martinus; Pollo, Claudio; Müller, Markus; Weisstanner, Christian; Wiest, Roland G.; Schindler, Kaspar A. (Public Library of Science (PLoS), 2015)
    BACKGROUND/nEpilepsy surgery is a potentially curative treatment option for pharmacoresistent patients. If non-invasive methods alone do not allow to delineate the epileptogenic brain areas the surgical candidates undergo ...
  • Malvestio, Irene; Kreuz, Thomas; Andrzejak, Ralph Gregor (American Physical Society, 2017)
    The detection of directional couplings between dynamics based onmeasured spike trains is a crucial problem in the understanding of many different systems. In particular, in neuroscience it is important to assess the ...
  • Chicharro Raventós, Daniel; Kreuz, Thomas; Andrzejak, Ralph Gregor (Elsevier, 2011)
    Time scale parametric spike train distances like the Victor and the van Rossum distances/nare often applied to study the neural code based on neural stimuli discrimination./nDifferent neural coding hypotheses, such as rate ...