Event- synchronization articles

Articles that apply Event Synchronization or Delay Asymmetry

(A list of articles that apply ISI-distance, SPIKE-distance and SPIKE-synchronization can be found here)

This list comprises articles that were published until 2020. From this year on it is no longer updated.

[87] Schmid G, Braun DA:

Human group coordination in a sensorimotor task with neuron-like decision-making.

Scientific Reports 10(1):1-8 (2020)

[86] Lussu V, Niewiadomski R, Volpe G, Camurri A:

The role of respiration audio in multimodal analysis of movement qualities.

Journal on Multimodal User Interfaces 14(1):1-5 (2020)

[85] Jang HJ, Chung H, Rowland JM, Richards BA, Kohl MM, Kwag J:

Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortex.

Science Advances 6(17):eaay5333 (2020)

[84] Mondal S, Mishra AK, Leung LR:

Spatiotemporal characteristics and propagation of summer extreme precipitation events over United States: A complex network analysis.

Geophysical Research Letters 47(15):e2020GL088185 (2020)

[83] Conticello FR, Cioffi F, Lall U, Merz B:

Synchronization and delay between circulation patterns and high streamflow events in Germany.

Water Resources Research 56(4):e2019WR025598 (2020)

[82] Singh M, Krishnan R, Goswami B, Choudhury AD, Swapna P, Vellore R, Prajeesh AG, Sandeep N, Venkataraman C, Donner RV, Marwan N:

Fingerprint of volcanic forcing on the ENSO–Indian monsoon coupling.

Science Advances 6(38):eaba8164 (2020)

[81] Wolf F, Bauer J, Boers N, Donner RV:

Event synchrony measures for functional climate network analysis: A case study on South American rainfall dynamics.

Chaos: An Interdisciplinary Journal of Nonlinear Science 30(3):033102 (2020)

[80] Castellana D, Dijkstra HA:

Noise-induced transitions of the Atlantic Meridional Overturning Circulation in CMIP5 models.

Scientific Reports 10(1):1-9 (2020)

[79] Baratnezhad E, Rezghi M:

Rainfall Data Analysis of Iran using Complex Networks View.

IEEE 10th International Conference on Computer and Knowledge Engineering (ICCKE, 2020)

[78] Celikoglu A:

Earthquake spatial dynamics analysis using event synchronization method.

Physics of the Earth and Planetary Interiors, 106524 (2020)

[77] Yavari F, Amiri M, Rahatabada FN, Faloticoc E, Laschi C:

Spike train analysis in a digital neuromorphic system of cutaneous mechanoreceptor

Neurocomp 379, 343 (2020)

[76] Odenweller A, Donner RV:

Disentangling synchrony from serial dependency in paired event time series.

Physical Review E 101,052213 (2020)

[75] Bertini C, Mineo C, Moccia B:

Setting a methodology to detect main directions of synchronous heavy daily rainfall events for Lazio region using complex networks.

AIP Conf Proc 2116, 210003 (2019)

[74] Jang HJ, Chung H, Rowland JM, Richards BA, Kohl MM, Kwag J:

Distinct roles of parvalbumin and somatostatin interneurons in the synchronization of spike-times in the neocortex.

bioRxiv 671743 (2019)

[73] Ospeck M:

Are sleep spindles poised on supercritical Hopf bifurcations?

BioRxiv 512145 (2019)

[72] De Giorgis N, Puppo E, Alborno P, Camurri A:

Evaluating Movement Quality Through Intrapersonal Synchronization.

IEEE Trans Hum-Mach Syst 49, 304 (2019)

[71] Hassanibesheli F, Donner RV:

Network inference from the timing of events in coupled dynamical systems.

Chaos: Interdisc J Nonl Sci 29(8), 083125 (2019)

[70] Bakhshayesh H, Fitzgibbon SP, Janani AS, Grummett TS, Pope KJ:

Detecting synchrony in EEG: A comparative study of functional connectivity measures.

Comp Biol Med 105, 1 (2019)

[69] Niewiadomski R, Kolykhalova K, Piana S, Alborno P, Volpe G, Camurri A:

Analysis of movement quality in full-body physical activities.

ACM Transactions on Interactive Intelligent Systems (TiiS) 9, 1 (2019)

[68] Kurths J, Agarwal A, Shukla R, Marwan N, Rathinasamy M, Caesar L, Krishnan R, Merz B:

Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach.

Nonl Proc Geophys 26, 251 (2019)

[67] Ozturk U, Malik N, Cheung K, Marwan N, Kurths J:

A network-based comparative study of extreme tropical and frontal storm rainfall over Japan.

Climate dynamics, 53, 521 (2019)

[66] Boers N, Goswami B, Rheinwalt A, Bookhagen B, Hoskins B, Kurths J:

Complex networks reveal global pattern of extreme-rainfall teleconnections.

Nature, 566, 373 (2019)

[65] Niewiadomski R, Chauvigne L, Mancini M, Camurri A:

Towards a model of nonverbal leadership in unstructured joint physical activity.

Proc 5th Intern Conf Movem Comp 1 (2018)

[64] Kada H, Teramae JN, Tokuda IT:

Highly Heterogeneous Excitatory Connections Require Less Amount of Noise to Sustain Firing Activities in Cortical Networks.

Front Comp Neurosci 12, 104 (2018)

[63] Cui T, Caravelli F, Ududec C:

Correlations and clustering in wholesale electricity markets.

Physica A: Stat Mech Appl 492, 1507 (2018)

[62] Yi Z, Zhang Y:

A spike train distance-based method to evaluate the response of mechanoreceptive afferents.

Neural Computing and Applications. 1-12 (2018)

[61] Suchkov D, Sharipzyanova L, Minlebaev M:

Horizontal synchronization of neuronal activity in the barrel cortex of the neonatal rat by spindle-burst oscillations.

Front Cell Neurosci 12, 5 (2018)

[60] Holzbecher A, Kempter R:

Interneuronal gap junctions increase synchrony and robustness of hippocampal ripple oscillations.

Eur J Neurosci 48, 3446 (2018)

[59] Gardella C, Marre O, Mora T:

Blindfold learning of an accurate neural metric.

Proc Nat Ac Sci 201718710 (2018)

[58] Ozturk U, Marwan N, Korup O, Saito H, Agarwal A, Grossman MJ, Zaiki M, Kurths, J:

Complex networks for tracking extreme rainfall during typhoons.

Chaos: Interdisc J Nonl Sci 28, 075301 (2018)

[57] Latchoumane CFV, Jackson L, Sendi MSE, Tehrani KF, Mortensen LJ, Stice SL, Ghovanloo M, Karumbaiah L:

Chronic electrical stimulation promotes the excitability and plasticity of ESC-derived neurons following glutamate-induced inhibition in vitro.

Sci Rep 8, 1 (2018)

[56] Conticello F, Cioffi F, Merz B, Lall U:

An event synchronization method to link heavy rainfall events and large‐scale atmospheric circulation features.

Int J Climat 38, 1421 (2018)

[55] Seshadri S, Klaus A, Winkowski DE, Kanold PO, Plenz D:

Altered avalanche dynamics in a developmental NMDAR hypofunction model of cognitive impairment.

Transl Psych 8, 1 (2018)

[54] Agarwal A, Marwan N, Maheswaran R, Merz B, Kurths J:

Quantifying the roles of single stations within homogeneous regions using complex network analysis.

J Hydrol 563, 802 (2018)

[53] Mwaffo V, Keshavan J, Hedrick TL, Humbert S:

Detecting intermittent switching leadership in coupled dynamical systems.

Sci Rep 8, 10338 (2018)

[52] Zhi-qiang G, Hai-jing S, Su-hong HE, Guo-lin F:

Complex Network of extreme Precipitation in East Asia.

J Trop Meteo 426 (2017)

[51] Suhong H, Zhiqiang G, Fang Y, Guolin F:

Application of complex network method to the study of summer extreme precipitation in East Asia.

J Meteo 75, 894 (2017)

[50] Anzalone SM, Varni G, Ivaldi S, Chetouani M:

Automated prediction of extraversion during human–humanoid interaction.

Internat J Soc Rob, 9, 385 (2017)

[49] Lima CH, AghaKouchak A, Lall U:

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil.

Earth Sys Dyn, 8, 1071 (2017)

[48] Yi Z, Zhang Y:

Recognizing tactile surface roughness with a biomimetic fingertip: A soft neuromorphic approach.

Neurocomputing 244, 102 (2017)

[47] Campana C, Zubler F, Gibbs S, De Carli F, Proserpio P, Rubino A, Cossu M, Tassi L, Schindler K, Nobili L:

Suppression of interictal spikes during phasic rapid eye movement sleep: a quantitative stereo‐electroencephalography study.

J Sleep Res 26, 606 (2017)

[46] Asif-Malik A, Dautan D, Young AM, Gerdjikov TV:

Altered cortico-striatal crosstalk underlies object recognition memory deficits in the sub-chronic phencyclidine model of schizophrenia.

Brain Struct Funct 222, 3179 (2017)

[45] Konapala G, Mishra A:

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA.

J Hydrol 555, 600 (2017)

[44] Mwaffo V, Butail S, Porfiri M:

Analysis of pairwise interactions in a maximum likelihood sense to identify leaders in a group.

Front Robot AI 4: 35 (2017)

[43] Alborno P, De Giorgis N, Camurri A, Puppo E:

Limbs synchronisation as a measure of movement quality in karate.

In Proceedings of the 4th International Conference on Movement Computing (2017)

[42] Grabow C, Macinko J, Silver D, Porfiri M:

Detecting causality in policy diffusion processes.

Chaos 26, 083113 (2016) (Directed)

[41] Dardard F, Gnecco G, Glowinski D:

Automatic Classification of Leading Interactions in a String Quartet.

ACM Transactions on Interactive Intelligent Systems (TiiS) 6, 5 (2016) (Directed)

[40] Rheinwalt A, Boers N, Marwan N, Kurths J, Hoffmann P, Gerstengarbe FW, Werner P:

Non-linear time series analysis of precipitation events using regional climate networks for Germany.

Climate Dynamics 46, 1065 (2016)

[39] Butail S, Mwaffo V, Porfiri M:

Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

Physical Review E 93, 042411 (2016) (Directed)

[38] Bustamante MG, Cruz FW, Vuille M, Apaéstegui J, Strikis N, Panizo G, Novello FV, Deininger M, Sifeddine A, Cheng H, Moquet JS:

Holocene changes in monsoon precipitation in the Andes of NE Peru based on δ 18 O speleothem records.

Quaternary Science Reviews 146, 274 (2016)

[37] Iqbal T, Rack S, Riek LD:

Movement Coordination in Human-Robot Teams: A Dynamical Systems Approach

IEEE Transactions on Robotics 32, 3 (2016)

[36] Kolykhalova K, Camurri A, Volpe G, Sanguineti M, Puppo E, Niewiadomski R:

A Multimodal Dataset for the Analysis of Movement Qualities in Karate Martial Art

IEEE Intelligent Technologies for Interactive Entertainment (INTETAIN) (2015)

[35] Tung JK, Gutekunst CA, Gross RE:

Inhibitory luminopsins: genetically-encoded bioluminescent opsins for versatile, scalable, and hardware-independent optogenetic inhibition.

Sci Rep. 5: 14366 (2015)

[34] Iqbal T, Riek LD:

A Method for Automatic Detection of Psychomotor Entrainment.

IEEE Transactions on affective computing 6 (2015)

[33] Chew G, Ang KK, So RQ, Xu Z, Guan C:

Combining Firing Rate and Spike-Train Synchrony Features in the Decoding of Motor Cortical Activity

IEEE Engineering in Medicine and Biology Society (EMBC), 1091 (2015)

[32] Boers N, Bookhagen B, Marengo J, Marwan N, von Storch JS, Kurths J:

Extreme Rainfall of the South American Monsoon System: A Dataset Comparison Using Complex Networks

JClimate 28, 1031 (2015)

[31] Ascoli A, Lanza V, Corinto F, Tetzlaff R:

Synchronization conditions in simple memristor neural networks

J Franklin Institute 352, 3196 (2015)

[30] Boers N, Bookhagen B, Marwan N, Kurths J:

Spatiotemporal characteristics and synchronization of extreme rainfall in South America with

focus on the Andes Mountain range

Clim-Dyn (2015)

[29] Marwan N, Kurths J:

Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems

Chaos 25, 097609 (2015)

[28] Rheinwalt A, Boers N, Marwan N, Kurths J, Hoffmann P, Gerstengarbe FW, Werner P:

Non‑linear time series analysis of precipitation events using regional climate networks for Germany

Clim-Dyn (2015)

[27] Iqbal T, Gonzales MJ, Riek LD:

Joint Action Perception to Enable Fluent Human-Robot Teamwork.

IEEE Int. Symposium on Robot and Human Interactive Communication (2015) (Directed)

[26] Rahbar F, Anzalone S, Varni G, Zibetti E, Ivaldi S, Chetouani M:

Predicting extraversion from non-verbal features during a face-to-face human-robot interaction.

International Conference on Social Robotics, Paris, France. pp.10. (2015) (Directed)

[25] Rosário RS, Cardoso PT, Muñoz MA, Montoya P, Miranda JGV:

Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

Physica A 439, 7 (2015)

[24] Boers N, Donner RV, Bookhagen B, Kurths J:

Complex network analysis helps to identify impacts of the El Niño Southern Oscillation on moisture divergence in South America

Clim-Dyn (2014)

[23] Boers N, Rheinwalt A, Bookhagen B, Barbosa HMJ, Marwan N, Marengo JA, Kurths J:

The South American rainfall dipole: A complex network analysis of extreme events

Geophys. Res. Lett. 41, 7397 (2014)

[22] Boers N, Bookhagen B, Barbosa HMJ, Marwan N, Kurths J, Marengo JA:

Prediction of extreme floods in the eastern Central Andes based on a complex networks approach

Nature Communications 5, 5199 (2014) (Directed)

[21] Rehfeld K, Kurths J:

Similarity estimators for irregular and age-uncertain time series

Clim. Past. 10, 107 (2014)

[20] Su-Hong H, Tai-Chen F, Yan-Chun G, Yan-Hua H, Cheng-Guo W, Zhi-Qiang G:

Predicting extreme rainfall over eastern Asia by using complex networks

Chin Phys B 23, 059202 (2014) (Directed)

[19] Pfeiffer T, Draguhn A, Reichinnek S, Both M:

Optimized temporally deconvolved Ca2+ imaging allows identification of spatiotemporal activity patterns of CA1 hippocampal ensembles

Neuroimage 94, 239 (2014)

[18] Mörtl A, Lorenz T, Hirche S:

Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action.

PLoS ONE 9(4): e95195 (2014)

[17] Singh RD, Gibbons SJ, Saravanaperumal SA, Du P, Hennig GW, Eisenman ST, Mazzone A, Hayashi Y, Cao C, Stoltz GJ, Ordog T, Rock JR, Harfe BD, Szurszewski JH, Farrugia G:

Ano1, a Ca2+-activated Cl−channel, coordinates contractility in mouse intestine by Ca2+ transient coordination between interstitial cells of Cajal

J Physiol 592.18, 4051 (2014)

[16] Ascoli A, Lanza V, Corinto F, Tetzlaff R:

Emergence of synchronization in bio-inspired memristor-coupled oscillatory cells

NOLTA IEICE 5, 292 (2014)

[15] Ascoli A, Tetzlaff R, Lanza V, Corinto F, Gilli M:

Memristor plasticity enables emergence of synchronization in neuromorphic networks

IEEE Circuits and Systems (ISCAS) 2261, (2014)

[14] Rehfeld K, Kurths J:

Similarity estimators for irregular and age-uncertain time series

Clim. Past. 10, 107 (2014)

[13] Boers N, Bookhagen B, Marwan N, Kurths J, Marengo J:

Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System

Geophys. Res. Lett. 40, 4386 (2013)

[12] Wang CT, Lee CT, Wang XJ, Lo CC:

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

PLOS One 8, e62379 (2013)

[11] Malik N, Bookhagen B, Marwan N, Kurths J:

Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks.

Clim Dyn 39:971–987 (2012) (Directed)

[10] Varni G, Volpe G, Mazzarino B:

Towards a Social Retrieval of Music Content

Proc IEEE Conf on Social Computing, Privacy, Security, Risk and Trust (2011) (Directed)

[9] Varni G, Volpe G, Camurri A:

A system for real-time multi-modal analysis of nonverbal affective social interaction in user-centric media

IEEE Trans on Multimedia, 12, 576 (2010) (Directed)

[8] Yu HH, Rosa MGP:

A simple method for creating wide-field visual stimulus for electrophysiology: Mapping and analyzing receptive fields using a hemispheric display.

J Vision 10, 15 (2010)

[7] Malik N, Marwan N, Kurths J:

Spatial structures and directionalities in monsoonal precipitation over south Asia.

Nonlinear Process Geophys 17:371–381 (2010) (Directed)

[6] Kreuz T, Chicharro D, Andrzejak RG, Haas JS, Abarbanel HDI:

Measuring multiple spike train synchrony.

J Neurosci Methods 183, 287 (2009) [PDF]

[5] Varni G, Camurri A, Coletta P, Volpe G:

Toward a Real-time Automated Measure of Empathy and Dominance

IEEE Computational Science and Engineering (2009) (Directed)

[4] Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A:

Measuring spike train synchrony.

J Neurosci Methods 165, 151 (2007) [PDF]

[3] Goldobin DS, Pikovsky A:

Antireliability of noise-driven neurons.

Phys. Rev. E 73:061906 (2006) (modified Event-Synchro)

[2] Zhou WX, Sornette D:

Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000.

Physica A: Statistical Mechanics and its Applications 330, 543 (2003)

[1] 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] (introduces Event-Synchro/Directed)