Thomas Kreuz
Affiliations: | Institute for complex systems (ISC) | CNR, Florence, Italy, Firenze, Toscana, Italy | |
University of California, San Diego, La Jolla, CA |
Area:
Computational Neuroscience, Signal Processing, Spike train synchronyWebsite:
http://www.fi.isc.cnr.it/users/thomas.kreuz/Google:
"https://scholar.google.com/citations?user=x7Dg3pgAAAAJ"Bio:
I am a computational neuroscientist with a physics background. My main field of interest is the development and application of methods to quantify the synchronization between two or more electrophysiological signals.
In recent years the focus of my attention has been on discrete signals and measures of spike train synchrony such as the SPIKE-distance. Currently, I concentrate on the development of methods to measure spike train synchrony between neuronal populations.
Before I worked on continuous signals, e.g. intracranial EEGs from epilepsy patients, and the objective was to evaluate the usefulness of synchronization measures for epileptic seizure prediction by means of a statistical validation.
In the past, another part of my work dealt with simulations of neuronal models (Hodgkin-Huxley, Fitzhugh-Nagumo) under the influence of noise. Finally, I did some work on nonlinear dynamics and nonlinear time series analysis.
Since 2010 I am on a permanent position as "Primo ricercatore" (senior researcher, equivalent to an associate professor) at the Institute of Complex Systems (ISC, Director: Antonio Politi) within the National Research Council (CNR) in Florence, Italy.
From 2007 to 2009 I was an EU Marie Curie Outgoing International Fellow (OIF). This fellowship lasted for three years and involved an international collaboration between two institutes in the US and in Italy. For the first two years (the outgoing phase) I was at the Institute of Nonlinear Science (INLS, Director: Henry D.I. Abarbanel) at the University of California, San Diego (UCSD), Ca, USA, while for the final year (the reintegration phase) I returned to the Institute of Complex Systems in Florence. In the two years before I was an EU Marie Curie Intra-European Fellow (EIF) at the Institute of Complex Systems.
Before that I worked at the John von Neumann Institute of Computing (NIC) at the Research Center Juelich, Germany (Director: Peter Grassberger) where I obtained my PhD in physics in 2003 (awarded by the University of Wuppertal, Germany). During this time I was also associated with the Neurophysics group (Head: Klaus Lehnertz) at the Department of Epilepsy at the University of Bonn, Germany (Director: Christian E. Elger).
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Mean distance: 15.45 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentorPeter Grassberger | grad student | 2000-2003 | Research Centre Juelich, Germany |
Klaus Lehnertz | grad student | 2000-2003 | University of Bonn, Germany |
Alessandro Torcini | post-doc | 2004-2006 | CNR |
Antonio Politi | post-doc | 2004-2007 | CNR, Florence, Italy |
Henry D I Abarbanel | post-doc | 2007-2009 | UCSD |
Children
Sign in to add traineeIrene Malvestio | grad student | ||
Nebojsa Bozanic | grad student | 2013-2015 | CNR, Florence, Italy |
Eero Raisanen | grad student | 2015-2018 | CNR, Florence, Italy |
Mario Mulansky | post-doc | 2014-2016 | CNR, Florence, Italy |
Publications
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Kreuz T, Senocrate F, Cecchini G, et al. (2022) Latency correction in sparse neuronal spike trains. Journal of Neuroscience Methods. 381: 109703 |
Adam I, Cecchini G, Fanelli D, et al. (2020) Inferring network structure and local dynamics from neuronal patterns with quenched disorder Chaos, Solitons & Fractals. 140: 110235 |
Satuvuori E, Mulansky M, Daffertshofer A, et al. (2018) Using spike train distances to identify the most discriminative neuronal subpopulation. Journal of Neuroscience Methods |
Satuvuori E, Kreuz T. (2018) Which spike train distance is most suitable for distinguishing rate and temporal coding? Journal of Neuroscience Methods |
Malvestio I, Kreuz T, Andrzejak RG. (2017) Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains. Physical Review. E. 96: 022203 |
Satuvuori E, Mulansky M, Bozanic N, et al. (2017) Measures of spike train synchrony for data with multiple time scales. Journal of Neuroscience Methods |
Kreuz T, Satuvuori E, Pofahl M, et al. (2017) Leaders and followers: quantifying consistency in spatio-temporal propagation patterns New Journal of Physics. 19: 043028 |
Mulansky M, Kreuz T. (2016) PySpike—A Python library for analyzing spike train synchrony Softwarex. 5: 183-189 |
Kreuz T, Mulansky M, Bozanic N. (2015) SPIKY: a graphical user interface for monitoring spike train synchrony. Journal of Neurophysiology. 113: 3432-45 |
Kreuz T, Bozanic N, Mulansky M. (2015) SPIKE-Synchronization: a parameter-free and time-resolved coincidence detector with an intuitive multivariate extension Bmc Neuroscience. 16 |