Welcome to the stoop group

Welcome to the Stoop Group. The Stoop group is a research group around Prof. Ruedi Stoop at the Institute of Neuroinformatics of University and ETH Zurich. The group is working in the following fields related to physics

  • biological computing
  • statistical physics
  • cochlear modeling

and is collaborating with other academic as well as industrial partners in the field.


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Latest journal publications

  • Fingerprints of a second order critical line in developing neural networks by K. Kanders, H. Lee, N. Hong, Y. Nam and R. Stoop, Communications Physics (in press, 2019).
  • Universality in the firing of minicolumnar-type neural networks by K. Kanders, N. Stoop and R. Stoop, Chaos 29, 093109 (2019).
  • Natural data structure extracted from neighborhood-similarity graphs by T. Lorimer, K. Kanders, and R. Stoop, Chaos Solitons and Fractals 119, 326-331 (2019).
  • Frequency sensitivity in mammalian hearing from a fundamental nonlinear physics model of the inner ear by K. Kanders, T. Lorimer, F. Gomez, and R. Stoop, Scientific Reports 7, 9931 (2017).
  • Avalanche and edge-of-chaos criticality do not necessarily co-occur in neural networks by K. Kanders, T. Lorimer, and R. Stoop, Chaos 27, 047408 (2017).
  • Clustering: How much bias do we need? by T. Lorimer, J. Held, and R. Stoop, Philosophical Transactions of the Royal Society A 375, 20160293 (2017).
  • Auditory power-law activation avalanches exhibit a fundamental computational ground state by R. Stoop and F. Gomez, Physical Review Letters 117, 038102 (2016).
  • Signal-coupled subthreshold Hopf-type systems show a sharpened collective response by F. Gomez, T. Lorimer, and R. Stoop, Physical Review Letters 116, 108101 (2016).
  • Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation by C. Albert, S. Ulzega, and R. Stoop, Physical Review E 93, 043313 (2016).
  • Big data naturally rescaled by R. Stoop, K. Kanders, T. Lorimer, J. Held, and C. Albert, Chaos Solitons and Fractals, 90, 81-90 (2016).
  • Mammalian cochlea as a physics guided evolution-optimized hearing sensor by T. Lorimer, F. Gomez, and R. Stoop, Scientific Reports 5, 12492 (2015).
  • Two universal principles shape the topological statistics of real-world networks by T. Lorimer, F. Gomez, and R. Stoop, Scientific Reports 5, 12353 (2015).
  • A Full Understanding of Things by R. Stoop, in "On Science - On Arts - On Society" (Proc. of the Digital Art Weeks), Seoul, South Korea (2015).
  • Macrosoping bursting in physiological networks: node or network property? by F.A.S. Ferrari, F. Gomez, T. Lorimer, R.L. Viana, and R. Stoop, New Journal of Physics 17, 055024 (2015).
  • Phase synchronization of coupled bursting neurons and the generalized Kuramoto model by F.A.S. Ferrari, R.L. Viana, S.R. Lopes, and R. Stoop, Neural Networks 66, 107-118 (2015).
  • A multiple time-scale framework for the understanding of the progression of Parkinson's disease by D.S. Andres, F. Gomez, F.A.S. Ferrari, D. Cerquetti, M. Merello, R. Viana, and R. Stoop, Phys. Rev. E 90, 062709 (2014).
  • Analysis of cascaded canonical dissipative systems and LTI filter sections by M. Reit, R. Stoop, and W. Mathis, Acta Technica 59, 79-96 (2014).
  • Neuronal entropy depends on the level of alertness in the parkinsonian Globus Pallidus in vivo by D.S. Andres, D. Cerquetti, M. Merello, and R. Stoop, Frontiers in Neurology, doi 10.3389/fneur.2014.00096 (2014).
  • Universal dynamical properties preclude standard clustering in a large class of biochemical data by F. Gomez, R.-L. Stoop and R. Stoop, Bioinformatics 30, 2486-2493 (2014).
  • Mammalian pitch sensation shaped by the cochlear fluid by F. Gomez and R. Stoop, Nature Physics 10, 530-536. (2014).
  • How the Ear Tunes In to Sounds: A Physics Approach by F. Gomez, V. Saase, N. Buchheim and R. Stoop, Phys. Rev. Appl. 1, 014003 (2014).
  • Pitch sensation involves stochastic resonance by S. Martignoli, F. Gomez and R. Stoop, Nature Sci. Rep. 3, 2676 (2013)
  • Parameter properties of electronic and biological circuits and systems by R.-L. Stoop, F. Gomez, R. Schönenberger, C. Baumann and R. Stoop, Proc. ECCTD (2013)
    • At Grammatical Faculty of Language, Flies Outsmart Men by R. Stoop, P. Nüesch, R.L. Stoop and L.A. Bunimovich, PLoS ONE 8 (8), e70284 (2013)
      • Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains by R.L. Stoop, V. Saase, C. Wagner, B. Stoop and R. Stoop, Phys. Rev. Lett. 110, 108105 (2013)
      • A full computation-relevant topological dynamics classification of elementary cellular automata by M. Schüle, R. Stoop,
        Chaos 22, 043143 (2012)
      • Shrimps: Occurrence, scaling and relevance by R. Stoop, S. Martignoli, P. Benner, R.-L. Stoop, Y. Uwate, International Journal of Bifurcation and Chaos 22, 1230032 (2012)
      • Analysis of the “Sonar Hopf” Cochlea by A. Kern, S. Martignoli, W. Mathis, W.-H. Steeb, R.-L. Stoop, R. Stoop, Sensors, 11 (5) 5808-5818 (2011)
      • Quantitative Assessment of the Log-Log-Step Method for Pattern Detection in Noise-Prone Environments by F. Gomez, R. Stoop, PLoS ONE, 6 (12) e28107 (2011)
      • Mesocopic comparison of complex networks based on periodic orbits by R. Stoop, J. Joller, Chaos, 21 (1) 016112 (2011)
      • Principles and Typical Computational Limitations of Sparse Speaker Separation Based on Deterministic Speech Features
        by A. Kern, R. Stoop, Neural Computation, 23 (9) 2358-2389 (2011)


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