Publications - Journal articles
[44] Cecchini G,
Scaglione A, Allegra Mascaro AL, Checcucci C, Conti E, Adam I, Fanelli D, Livi R,
Pavone FS, Kreuz T:
Cortical propagation as a biomarker for recovery after stroke
bioRxiv [PDF] (accepted for publication in PLoS Comput Biol, 2021).
[43] Adam I, Cecchini G, Fanelli D, Kreuz T, Livi R, di Volo M, Allegra Mascaro AL, Conti E,
Scaglione A, Silvestri L, Pavone FS:
Inferring network structure and local dynamics from neuronal patterns with quenched
disorder
Chaos Solitons and Fractals 140, 110235 and arXiv [PDF] (2020).
[42] Kreuz T, Houghton C, Victor JD:
Spike Train Distance
Encycl Comp Neurosci [PDF], DOI: doi.org/10.1007/978-1-4614-7320-6_409-2 (2020).
[41] Satuvuori E, Mulansky M, Daffertshofer A, Kreuz T:
Using spike train distances to identify the most discriminative neuronal subpopulation
JNeurosci Methods, 308, 354 [PDF] and arXiv [PDF] (2018).
[40] Satuvuori E, Kreuz T:
Which spike train distance is most suitable for distinguishing rate and temporal coding?
JNeurosci Methods 299, 22 [PDF] and arXiv [PDF] (2018).
[39] Malvestio I, Kreuz T, Andrzejak RG:
Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains
Physical Review E 96, 022203 [PDF] (2017).
[38] Kreuz T, Satuvuori E, Mulansky M:
SPIKE-order
Scholarpedia 12(7):42441 (2017).
[37] Satuvuori E, Mulansky M, Bozanic N, Malvestio I, Zeldenrust F, Lenk K, Kreuz T:
Measures of spike train synchrony for data with multiple time-scales
JNeurosci Methods 287, 25 [PDF] and arXiv [PDF] (2017).
[36] Kreuz T, Satuvuori E, Pofahl M, Mulansky M:
Leaders and followers: Quantifying consistency in spatio-temporal propagation patterns
New J. Phys. 19, 043028 [PDF] and arXiv [PDF] (2017).
[35] Mulansky M, Kreuz T:
PySpike - A Python library for analyzing spike train synchrony
Software X 5, 183 [PDF] and arXiv [PDF] (2016).
[34] Mulansky M, Bozanic N, Sburlea A, Kreuz T:
A guide to time-resolved and parameter-free measures of spike train synchrony
IEEE Proceeding on Event-based Control, Communication, and Signal Processing (EBCCSP) 1-8 and arXiv [PDF] (2015).
[33] Kreuz T, Mulansky M, Bozanic N:
SPIKY: A graphical user interface for monitoring spike train synchrony
JNeurophysiol 113, 3432 (2015) [PDF].
[32] Bozanic N, Mulansky M, Kreuz T:
SPIKY
Scholarpedia 9(12), 32344 (2014).
[31] Andrzejak RG,
Mormann F, Kreuz T:
Detecting determinism from point processes
Physical Review E 90, 062906 (2014) [PDF].
[30] Kreuz T, Chicharro D, Houghton C, Andrzejak RG,
Mormann F:
Monitoring spike train synchrony
J Neurophysiol 109, 1457
(2013) [PDF].
[29] Kreuz T:
SPIKE-distance
Scholarpedia 7(12),
30652 (2012).
[28] Houghton C,
Kreuz T:
On the efficient calculation of van Rossum
distances
Network:
Computation in neural systems 23, 48
(2012)
[PDF].
[27] Kreuz T:
Measures of neuronal signal synchrony
Scholarpedia 6(12), 11922 (2011).
[26] Kreuz T:
Measures of spike train synchrony
Scholarpedia 6(10),
11934 (2011).
[25] Andrzejak RG,
Kreuz T:
Characterizing unidirectional couplings between point processes
and flows
Eur Phys Lett 96, 50012 (2011)
[PDF].
[24] Chicharro D, Kreuz T, Andrzejak RG:
What can spike train distances tell us about the neural code?
J Neurosci Methods 199, 146 (2011)
[PDF].
[23] Kreuz T,
Chicharro D, Greschner M, Andrzejak RG:
Time-resolved and time-scale adaptive measures of spike train synchrony
J Neurosci Methods 195, 92 (2011) [PDF].
[22] Haas JS*,Kreuz T*, Torcini A, Politi A, Abarbanel HDI:
Rate maintenance and resonance in the entorhinal cortex
Eur J Neurosci 32, 1930 (2010)
[PDF].
[21] Kreuz T, Chicharro D, Andrzejak RG, Haas JS, Abarbanel HDI:
Measuring multiple spike train synchrony
J Neurosci Methods 183, 287 (2009) [PDF].
[20] Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A:
Measuring spike train synchrony
J Neurosci Methods 165, 151 (2007) [PDF].
[19] Kreuz T, Luccioli S, Torcini A:
Coherence Resonance due to correlated noise in neuronal models
Neurocomputing 70, 1970 (2007) [PDF].
[18] Torcini A, Luccioli S, Kreuz T:
Coherent Response of the Hodgkin-Huxley neuron in the high input regime
Neurocomputing 70, 1943 (2007) [PDF].
[17]
Kreuz T, Mormann F, Andrzejak RG, Kraskov A, Lehnertz K, Grassberger P:
Measuring synchronization in coupled model systems: A comparison of different approaches
Phys D 225, 29 (2007) [PDF].
[16]
Kreuz T, Luccioli S, Torcini A:
Double coherence resonance in neuron models driven by discrete correlated noise
Phys Rev Lett 97, 238101 (2006) [PDF].
[15] Luccioli S, Kreuz T, Torcini A:
Dynamical response of the Hodgkin-Huxley model in the high-input regime
Phys Rev E 73, 041902 (2006) [PDF].
[14] Andrzejak RG, Mormann F, Widman G, Kreuz T, Elger CE, Lehnertz K:
Improved spatial characterization of the epileptic brain by focusing on
nonlinearity
Epilepsy Research 69, 30 (2006) [PDF].
[13]
Mormann F, Kreuz T, Rieke C, Andrzejak RG, Kraskov A, David P, Elger CE, Lehnertz K:
On the predictability of epileptic seizures
Clin Neurophysiol 116, 569 (2005) [PDF].
[12]
Kreuz T, Andrzejak RG, Mormann F, Kraskov A, Stoegbauer H, Elger CE, Lehnertz K,
Grassberger P:
Measure profile surrogates: A method to validate the performance of epileptic seizure prediction algorithms
Phys Rev E 69, 061915 (2004) [PDF].
[11]
Kraskov A, Kreuz T, Andrzejak RG, Stoegbauer H, Nadler W, Grassberger P:
Extracting phases from aperiodic signals
arXiv [PDF].
[10]
Andrzejak RG, Kraskov A, Stoegbauer H, Mormann F, Kreuz T:
On the necessity, strengths and caveats of bivariate surrogate techniques
Phys Rev E 68, 066202 (2003) [PDF].
[9]
Quian Quiroga R, Kraskov A, Kreuz T, and Grassberger P:
Reply to "Comment on 'Performance of different synchronization measures
in real data: A case study on electroencephalographic signals.'"
Phys Rev E 67, 063902 (2003) [PDF].
[8]
Rieke C, Mormann F, Andrzejak RG, Kreuz T, David P, Elger CE, Lehnertz K:
Discerning nonstationarity from nonlinearity in seizure-free and pre-seizure EEG
recordings from epilepsy patients
IEEE Trans Biomed Eng 50, 634 (2003) [PDF].
[7]
Mormann F, Kreuz T, Andrzejak RG, David P, Lehnertz K, Elger CE:
Epileptic seizures are preceded by a decrease in synchronization
Epilepsy Res. 53, 171 (2003) [PDF].
[6] Mormann F, Andrzejak RG, Kreuz T, Rieke C, David P, Elger CE, Lehnertz K:
Automated detection of a pre-seizure state based on a decrease in synchronization in intracranial EEG recordings
from epilepsy patients
Phys. Rev. E 67, 021912 (2003) [PDF].
[5] Lehnertz K, Mormann F, Kreuz T, Andrzejak RG, Rieke C, David P, Elger CE:
Seizure prediction by nonlinear EEG analysis
IEEE Trans Biomed Eng (Special Issue), 22 (1), 57 (2003) [PDF].
[4]
Andrzejak RG, Mormann F, Kreuz T, Rieke C, Kraskov A, Elger CE, Lehnertz K:
Testing the null hypothesis of the non-existence of a pre-seizure state
Phys Rev E 67, 010901 (2003) [PDF].
[3] Quian Quiroga R, Kreuz T, and Grassberger P:
Event Synchronization: A simple and fast method to measure synchronicity and time delay patterns
Phys Rev E 66, 041904 (2002) [PDF].
[2] Quian Quiroga R, Kraskov A, Kreuz T, and Grassberger P:
Performance of different synchronization measures in real data: A case study on electroencephalographic signals
Phys Rev E 65, 041903 (2002) [PDF].
[1] Lehnertz K, Andrzejak RG, Arnhold J, Kreuz T, Mormann F, Rieke C, Widman G,
Elger CE:
Nonlinear EEG analysis in epilepsy: Its possible use for interictal focus localization, seizure anticipation, and prevention
J Clin Neurophysiol 18, 209-222 (2001) [PDF].