ISI, SPIKE & SPIKE-Synchronization articles

Articles that apply ISI, SPIKE, SPIKE-Synchronization and SPIKE-Order

(A list of articles that apply event synchronization can be found here)

[179] Pérez-López R, Espinal A, Sotelo-Figueroa M, Guerra-Hernandez EI, Batres-Mendoza P, Rostro-Gonzalez H:

Evolutionary Deployment of Central Pattern Generators for Legged Robots Using Nengo

In: New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms (pp. 141-155). Cham: Springer Nature Switzerland (2024)     (SPIKE)

[178] Zhu G, Zhang Y, Wu J, Zheng M, Xu K:

Chaos shapes transient synchrony activities and switchings in the excitatory-inhibitory networks

Nonlinear Dynamics 1-16 (2024)                          (SPIKE-Sync)

[177] Walter A, Wu S, Tyrrell AM, McDaid L, McElholm M, Sumithran NT, Harkin J, Trefzer MA:

Artificial Neural Microcircuits as Building Blocks: Concept and Challenges

arXiv preprint arXiv:2403.16327 (2024)                             (SPIKE)

[176] Shabani H, Zrenner E, Rathbun DL, Hosseinzadeh Z:

Electrical Input Filters of Ganglion Cells in Wild Type and Degenerating rd10 Mouse Retina as a Template for Selective Electrical Stimulation

IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024)                 (ISI, SPIKE, PySpike)

[175] Bai X, Yu C, Zhai J:

Topological data analysis of the firings of a network of stochastic spiking neurons.

Frontiers Neural Circuits (2024)   (SPIKE, SPIKE-Sync, PySpike)

[174] Wang Z, Cruz L:

Spiking Neural Network with plasticity in the time domain recovers temporal information from a noisy pattern using reference spikes

Neurocomputing 565:126988 (2024)                       (SPIKE)

[163] Mougkogiannis P, Adamatzky A:

Recognition of sounds by ensembles of proteinoids

Materials Today Bio:100989 (2024), BioRxiv                


[172] Zhang XY, Bobadilla-Suarez S, Luo X, Lemonari M, Brincat SL, Siegel M, Miller EK, Love BC:

Adaptive stretching of representations across brain regions and deep learning model layers. 

bioRxiv 2023-12 (2023)         (ISI, SPIKE, PySpike)

[171] Terasa MI, Birkoben T, Noll M, Adejube B, Madurawala R, Carstens N, Strunskus T, Kaps S, Faupel F, Vahl A, Kohlstedt H:

Pathways towards truly brain-like computing primitives

Materials Today 69:41-53 (2023)             (ISI)

[170] Zuo S, Wang C, Wang L, Jin Z, Kusunoki M, Kwok SC:

Neural signatures for temporal-order memory in the medial posterior parietal cortex

bioRxiv 2023-08 (2023)                      (SPIKE)

[169] Fehrman C, Meliza CD:

Nonlinear Model Predictive Control of a Conductance-Based Neuron Model via Data-Driven Forecasting

arXiv:2312.14274 (2023) (ISI, SPIKE-Synchro, PySpike)

[168] Hölzel MB, Kamermans W, Winkelman BH, Howlett MH, De Zeeuw CI, Kamermans M:

A common cause for nystagmus in different congenital stationary night blindness mouse models

JPhysiology 601.23, 5317 (2023)                             (SPIKE-Sync)

[167] Nocon JC, Witter J, Gritton H, Han X, Houghton C, Sen K:

A robust and compact population code for competing sounds in auditory cortex

JNeurophysiology 130(3):775 (2023)                       (SPIKE)

[166] Lam D, Enright HA, Cadena J, George VK, Soscia DA, Tooker AC, Triplett M, Peters SK, Karande P, Ladd A, Bogguri C: 

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

Frontiers in Cellular Neuroscience (2023)             (SPIKE)

[165] Walter A, Wu S, Tyrrell AM, McDaid L, McElholm M, Sumithran NT, Harkin J, Trefzer MA:

Artificial Neural Microcircuits for use in Neuromorphic System Design

InALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. MIT Press (2023)         (SPIKE)

[164] Mougkogiannis P, Kheirabadi NR, Chiolerio A, Adamatzky A:

Electrical spiking activity of proteinoids-ZnO colloids

BioRxiv (2023)                    (ISI, SPIKE-Sync, SPIKY)

[163] Nocon JC, Gritton HJ, James NM, Mount RA, Qu Z, Han X, Sen K:

Parvalbumin neurons enhance temporal coding and reduce cortical noise in complex auditory scenes. 

Communications Biology 6(1):751 (2023)                           (ISI, RI-SPIKE, cSPIKE)

[162] X Wang, X Zhang, M Zheng, L Xu, K Xu:

Noise-induced coexisting firing patterns in hybrid-synaptic interacting networks

Physica A 615, 128591 (2023)       (SPIKE-Sync, PySpike)

[161] Nishizono R, Saijo N, Kashino M:

Highly reproducible eyeblink timing during formula car driving

iScience (2023)       (SPIKE, PySpike)

[160] Warwick RA, Heukamp AS, Riccitelli S, Rivlin‐Etzion M:

Dopamine differentially affects retinal circuits to shape the retinal code.

The Journal of Physiology DOI:10.1113/JP284215 (2023) (SPIKE, SPIKY)

[159] Azad F, Zare M, Amiri M, Keliris GA:

Analysis of the spike responses in the neuromorphic implementation of the two-compartmental model of hippocampal pyramidal neuron

J Comput Science 66, 101909 (2023)                                                          (ISI)

[158] Goshi N, Girardi G, Kim H, Gardner A, Seker E:

Electrophysiological Activity of Primary Cortical Neuron-Glia Mixed Cultures.

Cells 12, 821 (2023)                           (SPIKE, PySpike)

[157] Moradi F, van den Berg M, Mirjebreili M, Kosten L, Verhoye M, Amiri M, Keliris GA:

Early Classification of Alzheimer´s Disease Phenotype based on Hippocampal Electrophysiology in the TgF344-AD Rat Model

iScience (2023)                                                    (ISI)

[156] Sotomayor-Gomez B, Battaglia FP, Vinck M:

SpikeShip: A method for fast, unsupervised discovery of high-dimensional neural spiking patterns

PLoS Comput Biol 19(7): e1011335. (2023)                  (SPIKE, RI-SPIKE)

[155] Seifert M, Roberts PA, Kafetzis G, Osorio D, Baden T:

Birds multiplex spectral and temporal visual information via retinal On- and Off-channels 

Nature Comm 14(1):5308. BioRxiv (2023)   (ISI, SPIKE-Synchro, PySpike)

[154] Lam D, Sebastian A, Bogguri C, Hum NR, Ladd A, Cadena J, Valdez CA, Fischer NO, Loots GG, Enright HA:

Dose-dependent consequences of sub-chronic fentanyl exposure on neuron and glial co-cultures

Frontiers Toxic 95 (2022)                       (SPIKE)

[153] Birkoben T, Kohlstedt H:

Matter & Mind Matter. 

arXiv preprint arXiv:2204.12774 (2022)                           (ISI)

[152] Lee LH, Huang CS, Wang RW, Lai HJ, Chung CC, Yang YC, Kuo CC:

Deep brain stimulation rectifies the noisy cortex and irresponsive subthalamus to improve parkinsonian locomotor activities. 

NPJ Parkinson's Disease 8(1):1-8 (2022)                             (SPIKE, SPIKY)

[151] Luo Y, Shen H, Cao X, Wang T, Feng Q, Tan Z:

Conversion of Siamese networks to spiking neural networks for energy-efficient object tracking

Neural Computing and Applications 34(12):9967-82 (2022)                               (SPIKE, PySpike)

[150] Iredale JA, Stoddard JG, Drury HR, Browne TJ, Elton A, Madden JF, Callister RJ, Welsh JS, Graham BA:

Recording network activity in spinal nociceptive circuits using microelectrode arrays.

JoVE (Journal of Visualized Experiments) Feb 9(180):e62920 (2022) (A-SPIKE-Sync)

[149] Kreuz T, Senocrate F, Cecchini G, Checcucci C, Allegra Mascaro AL, Conti E, Scaglione A, Pavone FS:

Latency correction in sparse neuronal spike trains

J Neurosci Methods 109703 (2022)   [PDF]                                                                        (SPIKE-Sync, SPIKE-order)

[148] Bouillet T, Ciba M, Alves CL, Rodrigues FA, Thielemann C, Colin M, Buée L, Halliez S:

Revisiting the involvement of tau in complex neural network remodeling: analysis of the extracellular neuronal activity in organotypic brain slice co-cultures.

J Neural Eng 19(6):066026 (2022)                     (A-ISI, A-SPIKE, A-SPIKE-Sync, ARI-SPIKE)

[147] Blackwood EB, Shortal BP, Proekt A:

Weakly Correlated Local Cortical State Switches under Anesthesia Lead to Strongly Correlated Global States

JNeurosci 42(48):8980–8996 (2022)                                            (SPIKE-Synchro)

[146] Nocon JC, Gritton HJ, Han X, Sen K:

Differential Inhibitory Responses to Temporal Features Enhance Cortical Coding of Dynamic Stimuli: A Network Model

bioRxiv (2022)        (ISI, SPIKE, RI-SPIKE, cSPIKE)

[145] Nocon JC, Gritton HJ, James NM, Han X, Sen K:

Parvalbumin neurons, temporal coding, and cortical noise in complex scene analysis

bioRxiv (2022)             (ISI, RI-SPIKE, cSPIKE)

[144] Oesterle J, Krämer N, Hennig P, Behrens P:

Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models

J Comput Neurosci 50:485 (2022)                                                   (SPIKE, PySpike)

[143] Sperandeo A, Tamburini C, Noakes Z, Cabezas de la Fuente D, Keefe F, Petter O, Plumbly W, Clifton N, Li M, Peall K:

Cortical neuronal hyperexcitability and synaptic changes in SGCE mutation-positive myoclonus dystonia

Brain (2022)                 (SPIKE)

[142] Zhou, Tian C, Zhang X, Zheng M, Xu K:

Short-term plasticity as a mechanism to regulate and retain multistability

Chaos, Solitons and Fractals 165, 112891 (2022)           (SPIKE-Synchro, PySpike)

[141] Wang X, Zhang X, Zheng M, Xu L, Xu K:

Noise-induce coexisting firing patterns in hybrid-synaptic interacting networks

arXiv (2022)                           (SPIKE-Synchro, PySpike)

[140] Yi JD, Akbari Y:

A critical role for spike synchrony in determining steep 1/f slopes in the setting of bursting EEG patterns

BioRxiv (2022)                   (SPIKE-Synchro, PySpike)

[139] Goshi N, Girardi G, da Costa Souza F, Gardner A, Lein PJ, Seker E:

Influence of microchannel geometry on device performance and electrophysiological recording fidelity during long-term studies of connected neural populations.

Lab on a Chip (2022)                        (SPIKE, PySpike)

[138] Hu M, Frega M, Tolner EA, van den Maagdenberg AM, Frimat JP, le Feber J:

MEA-ToolBox: an Open Source Toolbox for Standardized Analysis of Multi-Electrode Array Data. 

Neuroinformatics. Jun 9:1-6 (2022)                           (ISI)

[137] Peng L, Tang J, Ma J, Luo J:

The influence of autapse on synchronous firing in small-world neural networks.

Physica A 126956 (2022)                                                                (SPIKE)

[136] Iredale JA, Stoddard JG, Drury HR, Browne TJ, Elton A, Madden JF, Callister RJ, Welsh JS, Graham BA:

Recording Network Activity in Spinal Nociceptive Circuits using Microelectrode Arrays. 

J Vis Exp Feb 9;180:e62920 (2022)                           (A-SPIKE-Sync)

[135] Hajati F, Girosi F, Rafiei A:

EISI: Extended inter-spike interval for mental health patients clustering based on mental health services and medications utilisation.

Medical Engineering & Physics. Feb 21:103780 (2022)       (extended ISI)

[134] Macias S, Bakshi K, Smotherman M:

Faster repetition rate sharpens the cortical representation of echo streams in echolocating bats.

ENeuro 9(1) (2022)     (SPIKE-Synchro, SPIKY)

[133] Peng L, Tang J, Ma J, Luo J:

The influence of autapse on synchronous firing in small-world neural networks.

Physica A: Statistical Mechanics and its Applications:126956 (2022)     (SPIKE)

[132] Hilgen G, Kartsaki E, Kartysh V, Cessac B, Sernagor E:

A novel approach to the functional classification of retinal ganglion cells.

Open Biol. 12: 210367 (2022)         (SPIKE)

[131] Rahy R, Asari H, Gross CT:

Sensory-thresholded switch of neural firing states in a computational model of the ventromedial hypothalamus

Front Comput Neurosci 16 (2022)   (PySpike)

[130] Cecchini G, Scaglione A, 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.

PLoS Comput Biol 17: e1008963 (2021) [PDF] and bioRxiv [PDF]   (SPIKE-Synchro, SPIKE-Order, cSPIKE)

[129] Pajot N, Boukadoum M:

Synchrony-Based State Representation for Classification by Liquid State Machines.

In 2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI* CC) 181-188 (2021)


[128] Qin L, Zhang Y:

A reference spike train-based neurocomputing method for enhanced tactile discrimination of surface roughness

Neural Comp Appl 33:14793 (2021)       (ISI, SPIKE, SPIKE-Synchro)

[127] Gal E, Amsalem O, Schindel A, London M, Schuermann F, Markram H, Segev I:

The role of hub neurons in modulating cortical dynamics.

Front. Neural Circuits: (2021)       (SPIKE-Synchro, PySpike)

[126] Lazarevich I, Prokin I, Gutkin B, Kazantsev V:

Neural Activity Classification with Machine Learning Models Trained on Interspike Interval Time-Series Data.

BioRxiv: (2021)   (ISI, PySpike)

[125] Colombi I, Nieus T, Massimini M, Chiappalone M:

Spontaneous and Perturbational Complexity in Cortical Cultures.

Brain Sciences 11(11):1453 (2021) (SPIKE-Synchro, PySpike)

[124] Nocon JC, Gritton HJ, James NM, Han X, Sen K:

PV neurons improve cortical complex scene analysis by enhancing timing-based coding.

bioRxiv (2021) (ISI, SPIKE, RI-SPIKE, cSPIKE)

[123] Neru A, Assisi C:

Theta oscillations gate the transmission of reliable sequences in the medial entorhinal cortex.

ENeuro 0059-20.2021 (2021)               (SPIKE, PySpike)

[122] Gainutdinov A:

Method for analyzing the inhibition of cellular signals in the spike train format.

Saratov Fall Meeting 2020: Computations and Data Analysis: from Molecular Processes to Brain Functions (2021)   (SPIKE-Order)

[121] Enright HA, Lam D, Sebastian A, Sales AP, Cadena J, Hum NR, Osburn JJ, Peters SK, Petkus B, Soscia DA, Kulp KS:

Functional and transcriptional characterization of complex neuronal co-cultures.

Scientific reports 10(1):1-4 (2020)       (SPIKE, PySpike)

[120] Risi N, Aimar A, Donati E, Solinas S, Indiveri G:

A spike-based neuromorphic architecture of stereo vision.

Frontiers in Neurorobotics 14:93 (2020).         (?, PySpike)

[119] Hermiz J, Hossain L, Arneodo EM, Ganji M, Rogers N, Vahidi N, Halgren E, Gentner TQ, Dayeh SA, Gilja V:

Stimulus driven single unit activity from micro-electrocorticography.

Frontiers in Neuroscience 14:55 (2020).     (SPIKE)

[118] Gainutdinov A:

Method for measuring differences in the neuronal responses to social stimuli.

IEEE International Conference Nonlinearity, Information and Robotics (NIR, 2020)                    (SPIKE-Order, PySpike)

[117] Macias S, Bakshi K, Garcia-Rosales F, Hechavarria JC, Smotherman M:

Temporal coding of echo spectral shape in the bat auditory cortex.

PLoS Biology 8(11):e3000831 (2020)   (SPIKE-Synchro, SPIKY)

[116] Amichi L, Viana AC, Crovella M, Loureiro AA:

Understanding individuals' proclivity for novelty seeking. 

Proceedings of the 28th International Conference on Advances in Geographic Information Systems (2020)  (ISI-Diversity)

[115] Ciba M, Bestel R, Nick C, de Arruda GF, Peron T, Henrique CC, Costa LD, Rodrigues FA, Thielemann C:

Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity.

Neural computation 32(5):887-911 (2020)               (A-ISI, A-SPIKE, ARI-SPIKE, A-SPIKE-Synchro)

[114] O’Halloran DM:

Simulation model of CA1 pyramidal neurons reveal opposing roles for the Na+/Ca2+ exchange current and Ca2+-activated K+ current during spike-timing dependent synaptic plasticity. 

Plos one, 15(3), e0230327 (2020) (SPIKE-Synchro, PySpike)

[113] Kita K, Albergaria C, Machado AS, Carey MR, Müller M, Delvendahl I:

GluA4 enables associative memory formation by facilitating cerebellar expansion coding. 

bioRxiv (2020) (SPIKE-Synchro, PySpike)

[112] Carter J, Rego J, Schwartz D, Bhandawat V, Kim E:

Learning Spiking Neural Network Models of Drosophila Olfaction.

In International Conference on Neuromorphic Systems pp. 1-5 (2020)                               (ISI)

[111] Gainutdinov A:

Determination of responses to stimuli by the role of signal-triggering neurons in the network.

IEEE 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR, 2020)   (SPIKE-Order)

[110] Brill M, Schwab F:

T-Pattern Analysis and Spike Train Dissimilarity for the Analysis of Structure in Blinking Behavior.

Physiology & Behavior, 113163 (2020)                               (ISI)

[109] Johnson LA, Wang J, Nebeck SD, Zhang J, Johnson MD, Vitek JL:

Direct activation of primary motor cortex during subthalamic but not pallidal deep brain stimulation.

Journal of Neuroscience, 40(10), 2166-2177 (2020)                           (SPIKE-Synchro)

[108] Kreuz T, Houghton C, Victor JD:

Spike Train Distance

Encycl Comp Neurosci [PDF], (2020)               (ISI, SPIKE, SPIKE-Synchro)

[107] Tumulty JS, Royster M, Cruz L:

Columnar grouping preserves synchronization in neuronal networks with distance-dependent time delays

Phys Rev E 101, 022408 (2020)                                                       (SPIKE)

[106] 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)                                                     (ISI)

[105] Soucy JR, Askaryan J, Diaz D, Koppes AN, Annabi N, Koppes RA:

Glial cells influence cardiac permittivity as evidenced through in vitro and in silico models

Biofabrication 12, 015014 (2020)                                       (SPIKE)

[104] Amsalem O, Eyal G, Rogozinski N, Segev I:

An efficient analytical reduction of detailed nonlinear neuron models

Nature Comm 11, 288 (2020)             (ISI, SPIKE-Synchro)

[103] Garg S, Singh D:

Structural features recapitulate collective dynamics of inhibitory networks

BioArxiv, (2019)                  (SPIKE-Synchro, PySpike)

[102] Brouns T, Celikel T:

PASER for automated analysis of neural signals recorded in pulsating magnetic fields

BioArxiv, (2019)                                         (cSPIKE)

[101] Sihn D, Kim SP:

A Spike Train Distance Robust to Firing Rate Changes Based on the Earth Mover’s Distance

Front. Comput. Neurosci. 13:82 (2019)           (SPIKE, RI-SPIKE)

[100] Melanitis N, Nikita KS:

Biologically-inspired image processing in computational retina models

Comp Biol Med 113, 103399 (2019)                        (ISI, SPIKE)

[99] Lee S, Jang K:

Regularity of vehicle trips in urban areas

IEEE Intelligent Transportation Systems Conference (2019); DOI: 10.1109/ITSC.2019.8917025                (ISI)

[98] Tomlinson SB, Wong JN, Conrad EC, Kennedy BC, Marsh ED:

Reproducibility of interictal spike propagation in children with refractory epilepsy

Epilepsia 60, 898 (2019)                                                                         (SPIKE-order)

[97] Bardin JB, Spreemann G, Hess K:

Topological exploration of artificial neuronal network dynamics

Network Neurosci 3, 725 (2019)                                     (SPIKE, SPIKE-Synchro)

[96] Madar AD, Ewell LA, Jones MV:

Temporal pattern separation in hippocampal neurons through multiplexed neural codes

PLoS Comput Biol 15(4): e1006932 (2019)                                                     (SPIKE)

[95] Ouyang Q, Wu J, Shao Z, Wu M, Cao Z:

A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents

Front. Neuroinform. 13:27 (2019)                                                                           (ISI)

[94] Unakafova VA, Gail A:

Comparing Open-Source Toolboxes for Processing and Analysis of Spike and Local Field Potentials Data

Front. Neuroinform. 13:57 (2019)                                                               (SPIKY)

[93] Lam D, Enright HA, Cadena J, Peters SK, Sales AP, Osburn JJ, Soscia DA, Kulp KS, Wheeler EK,  Fischer NO:

Tissue-specific extracellular matrix accelerates the formation of neural networks and communities in a neuron-glia co-culture on a multi-electrode array.

Scientific Reports, 9, 4159 (2019)                                                       (SPIKE)

[92] Bradley JA, Strock CJ:

Screening for Neurotoxicity with Microelectrode Array

Curr Prot Toxicol 79, e67 (2019)       (ISI)

[91] Duarte R, Uhlmann M, van den Broek D, Fitz H, Petersson KM, Morrison A:

Encoding symbolic sequences with spiking neural reservoirs

International Joint Conference on Neural Networks (IJCNN) (2018)             (ISI, SPIKE, SPIKE-Synchro)

[90] Lama N, Hargreaves A, Stevens B, McGinnity TM:

Spike Train Synchrony Analysis of Neuronal Cultures

International Joint Conference on Neural Networks (IJCNN) 1-8 (2018)                    (ISI, SPIKE)

[89] Świetlik D, Białowąs J, Kusiak A, Cichońska D:

Memory and forgetting processes with the firing neuron model

Folia Morphol 77, 221 (2018)                    (ISI, also time-resolved)

[88] Du Y, Liu J, Fu S:

Information Transmitting and Cognition with a Spiking Neural Network Model

Chin Phys Lett 35, 090502 (2018)        (ISI)

[87] Bradley JA, Luithardt HH, Metea MR, Strock CJ:

In Vitro Screening for Seizure Liability Using Microelectrode Array Technology

Toxicol Sci 163, 240 (2018)    (ISI)

[86] Naudé J, Didienne S, Takillah S, Prévost-Solié C, Maskos U, Faure P:

Acetylcholine-dependent phasic dopamine activity signals exploratory locomotion and choices.

BioRxiv, (2018)                     (SPIKE)

[85] Lassus B, Naudé J, Faure P, Guedin D, Von Boxberg Y, La Cour CM, Millan MJ, Peyrin JM:

Glutamatergic and dopaminergic modulation of cortico-striatal circuits probed by dynamic calcium imaging of networks reconstructed in microfluidic chips.

Scientific reports, 8, 1 (2018)             (SPIKE-Synchro)

[84] Jouty J, Hilgen G, Sernagor E, Hennig MH:

Non-parametric Physiological Classification of Retinal Ganglion Cells in the Mouse Retina 

Front Cell Neurosci 12:481 (2018)                (ISI, SPIKE, PySPIKE)

[83] 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)                                        (SPIKE)

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

Blindfold learning of an accurate neural metric.

Proc Nat Ac Sci 201718710 (2018)                                                  (ISI, SPIKE, SPIKE-Synchro)

[81] 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)                            (ISI, SPIKE)

[80] Ciba M, Isomura T, Jimbo Y, Bahmer A, Thielemann C:

Spike-contrast: A novel time scale independent and multivariate measure of spike train synchrony

JNeurosci Methods 293, 136 (2018)                             (SPIKE)

[79] Yi Z, Zhang Y:

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

Neural Computing and Applications. 1-12 (2018)                (ISI, SPIKE)

[78] Williams MJ, Whitaker RM, Allen SM:

There and back again: Detecting regularity in human encounter communities.

IEEE Transactions on Mobile Computing 16:1744 (2017)                                   (ISI)

[77] Sun AY, Xia Y, Caldwell T, Hao Z:

Patterns of Precipitation and Soil Moisture Extremes in Texas, US: A Complex Network Analysis.

Advances in Water Resources 112, 203 (2017)                (SPIKE-Synchro)

[76] Aguirre LA, Portes LL, Letellier C:

Observability and synchronization of neuron models.

Chaos: An Interdisciplinary Journal of Nonlinear Science 27(10):103103 (2017)            (SPIKE)

[75] Zhu J, Liu X:

Measuring spike timing distance in the Hindmarsh–Rose neurons

Cogn Neurodyn (2017)                         (ISI)

[74] Madar AD, Ewell LA, Jones MV:

Pattern separation of spike trains by individual granule cells of the dentate gyrus.

BioRxiv (2017)             (SPIKE)

[73] 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)           (ISI, SPIKE)

[72] Qi D, Xiao Z, Liu S, Jiao Y:

Spike Trains Synchrony with Changed Neuronal Networks Parameters in a Hippocampus CA3 Small-World Network Model.

Information Science and Control Engineering Proc. 1721 (2017)                                    (ISI)

[71] Palazzolo G, Moroni M, Soloperto A, Aletti G, Naldi G, Vassalli M, Nieus T, Difato F:

Fast wide-volume functional imaging of engineered in vitro brain tissues.

Scientific Reports 7 (2017)                                                 (SPIKE-Synchro)

[70] Kreuz T, Satuvuori E, Mulansky M:


Scholarpedia, 12(7):42441 (2017)                                             (SPIKE-Synchro, SPIKE-order)

[69] 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)                       (Introduces A-ISI, A-SPIKE, A-SPIKE-Synchro)

[68] 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)     (SPIKE-Synchro, introduces SPIKE-order)

[67] Yi Z, Zhang Y:

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

Neurocomputing 244, 102 (2017)                                   (ISI, SPIKE)

[66] Ravello CR, Escobar MJ, Palacios A, Perrinet LU:

Differential response of the retinal neural code with respect to the sparseness of natural images

Arxiv 1611:06834v1 (2016)                         (SPIKE)

[65] Kuroda K, Hasegawa M:

Method for Estimating Neural Network Topology Based on SPIKE-Distance

LNCS 9886, 91 (2016)                                         (SPIKE)

[64] Mulansky M, Kreuz T:

PySpike - A Python library for analyzing spike train synchrony

Software X 5, 183 and arXiv [PDF] (2016)    [PDF] (Python source codes for ISI, SPIKE, SPIKE-Synchro)

[63] Zapata-Fonseca L, Dotov D, Fossion R, Froese T:

Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties.

Frontiers in Psychology, 7 (2016)                     (SPIKE)

[62] Koutsou A, Kanev J, Economidou M, Christodoulou C:

Integrator or coincidence detector---what shapes the relation of stimulus synchrony and the operational mode of a neuron?

Mathematical Biosciences and Engineering 13,521 (2016)                       (SPIKE)

[61] Espinal A, Rostro-Gonzalez H, Carpio M, Guerra-Hernandez EI, Ornelas-Rodriguez M, Puga-Soberanes HJ, Sotelo-Figuero MA, Melin P:

Quadrupedal robot locomotion: a biologically inspired approach and its hardware implementation

ComputIntelNeurosci 5615618 (2016)                                 (SPIKE)

[60] Espinal A, Rostro-Gonzalez H, Carpio M, Guerra-Hernandez EI, Ornelas-Rodriguez M, Sotelo-Figuero MA:

Design of Spiking Central Pattern Generators for Multiple Locomotion Gaits in Hexapod Robots by Christiansen Grammar Evolution

Front Neurorobot 10:6 (2016)                                    (SPIKE)

[59] Vlachos I, Deniz T, Aertsen A, Kumar A:

Recovery of dynamics and function in spiking neural networks with closed-loop control

PLoS Comput Biol 12.2, e1004720 (2016)                   (SPIKE)

[58] Dura-Bernal S, Li K, Neymotin SA, Francis JT, Principe, JC, Lytton WW:

Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm

Frontiers in Neurocience 10:28 (2016)                                   (SPIKE, SPIKE-Synchro)

[57] Rodrigues AC, Cerdeira HA, Machado BS:

The influence of hubs in the structure of a neuronal network during an epileptic seizure

Eur. Phys. J. Special Topics 225, 75 (2016)                                                           (SPIKE)

[56] Chen YL, Yu LC, Chen Y:

Reliability of weak signals detection in neurons with noise

Sci China Tech Sci 59, 411 (2016)                                                                     (ISI)

[55] Qu J, Wang R, Du Y, Yan C:

An Improved Method of Measuring Multiple Spike Train Synchrony.

Ch. 105, R. Wang and X. Pan (eds.), Advances in Cognitive Neurodynamics (V), Springer Science+Business Media Singapore (2016)                                       (ISI)

[54] Hino H, Takano K, Murata N:

mmpp: A Package for Calculating Similarity and Distance Metrics for Simple and Marked Temporal Point Processes.

R Journal 7, 237 (2015)       (R source codes for ISI)

[53] Bockhorst T, Homberg U:

Amplitude and dynamics of polarization-plane signaling in the central complex of the locust brain.

Journal of Neurophysiology 113, 3291 (2015)                             (Variation of ISI)

[52] Takano K, Hino H, Yoshikawa Y, Murata N:

Patchworking multiple pairwise distances for learning with distance matrices.

International Conference on Latent Variable Analysis and Signal Separation 287 (2015)                                     (ISI)

[51] Bockhorst T, Homberg U:

Compass Cells in the Brain of an Insect Are Sensitive to Novel Events in the Visual World

PLoS ONE 10(12):e0144501 (2015)                          (Variation of ISI)

[50] Qu J, Wang R, Du Y:

Measuring effects of different noises in a model using ISI-distance methods.

Int. J. Biomath. 08, 1550043 (2015)                  (ISI)

[49] 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)                (ISI, SPIKE, SPIKY)

[48] Eisenman LN, Emnett, CM, Mohan J, Zorumski CF, Mennerick S:

Quantification of bursting and synchrony in cultured hippocampal neurons

JNeurophysiol, 114,1059 (2015)           (SPIKE)

[47] Du Y, Wang R, Cao J:

Parameter-dependent synchronization of coupled neurons in cold receptor model.

International Journal of Non-Linear Mechanics 70, 95 (2015)                    (ISI)

[46] Hoang H, Yamashita O, Tokuda IT, Sato M, Kawato M, Toyama K:

Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics

Front. Comput. Neurosci. 9:56 (2015)                                                                          (SPIKE)

[45] Rabinowitch TC, Knafo-Noam A:

Synchronous rhythmic interaction enhances children’s perceived similarity and closeness towards each other.

PLoS ONE 10(4): e0120878 (2015)                                                      (old SPIKE, Inter-personal synchronization)

[44] 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)                       (overview and math. properties ISI, SPIKE, SPIKE-Synchro)

[43] Kreuz T, Mulansky M, Bozanic N:

SPIKY: A graphical user interface for monitoring spike train synchrony.

JNeurophysiol 113, 3432 (2015) [PDF]                                     (ISI, SPIKE, introduces SPIKE-Synchro, SPIKY)

[42] Bozanic N, Mulansky M, Kreuz T:


Scholarpedia 9(12), 32344 (2014) (ISI, SPIKE, SPIKE-Synchro, SPIKY)


[41] Thibeault CM, O'Brien MJ, Srinivasa N:

Analyzing large-scale spiking neural data with HRLAnalysis™.

Frontiers in neuroinformatics, 8, 17 (2014)                                                        (SPIKE-Software)

[40] Diego Andilla F, Hamprecht FA:

Sparse Space-Time Deconvolution for Calcium Image Analysis

Advances in Neural Information Processing Systems 27, 64-72 (NIPS 2014)                          (SPIKE)

[39] Cutts CS, Eglen SJ:

Detecting pairwise correlations in spike trains: An objective comparison of methods and application to the study of retinal waves.

J Neurosci 34, 14288 (2014)              (comparison of correlation measures, but also includes SPIKE)

[38] Konstantoudaki X, Papoutsi A, Chalkiadaki K, Poirazi P, Sidiropoulou K:

Modulatory effects of inhibition on Feise activity in a cortical microcircuit model

Front. Neural Circuits 8: 1 (2014)                                         (old SPIKE)

[37] Andrzejak RG, Mormann F, Kreuz T:

Detecting determinism from point processes.

Physical Review E 90, 062906 (2014) [PDF]         (ISI, SPIKE)

[36] Sacre P, Sepulchre R:

Sensitivity Analysis of Oscillator Models in the Space of Phase-Response Curves: Oscillators As Open Systems.

Control Systems, IEEE 34, 50 (2014)                 (SPIKE, also time-resolved)

[35] Du Y, Wang R, Cao J:

Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model.

Discrete Dynamics in Nature and Society (Hindawi) 173894 (2014)           (ISI)

[34] Xu A, Du Y, Wang R, Cao J:

Interaction between different cells in olfactory bulb and synchronous kinematic analysis.

Discrete Dynamics in Nature and Society (Hindawi) 808792 (2014)           (ISI)

[33] Wang J, Liu S, Li X:

Quantification of synchronization phenomena in two reciprocally gap-junction coupled bursting pancreatic beta-cells.

Chaos, Solitons & Fractals 68, 65 (2014)                                                                  (ISI)

[32] Rusu CV, Florian RV:

A new class of metrics for spike trains

Neural Comput 26, 306 (2014)                                     (ISI, SPIKE, includes performance comparison)

[31] Dipoppa M, Gutkin BS:

Correlations in background activity control persistent state stability and allow execution of working memory tasks.

Front Comput Neurosci. 7: 139 (2013)                                     (SPIKE, including selective averaging)

[30] Qi D, Xiao Z:

Spike Trains Synchrony With Different Coupling Strengths in a Hippocampus CA3 Small-World Network Model.

Proceedings of the 2013 6th International Conference on Biomedical Engineering and Informatics (BMEI 2013)                                                                                                       (ISI, also time-resolved)


[29] Papoutsi A, Sidiropoulo K, Cutsuridis V and Poirazi P:

Induction and modulation of persistent activity in a layer VPFC microcircuit model.

Frontiers in Neural Circuits 7, 161 (2013)       (old SPIKE)

[28] Chen Y, Zhang H, Wang H, Yu L, Chen Y:

The Role of Coincidence-Detector Neurons in the Reliability and Precision of Subthreshold Signal Detection in Noise.

PLoS ONE 8(2): e56822 (2013)                  (ISI, also time-resolved)

[27] Kreuz T, Chicharro D, Houghton C, Andrzejak RG, Mormann F:

Monitoring spike train synchrony.

J Neurophysiol 109, 1457 (2013) [PDF]                                                             (introduces SPIKE)

[26] Kreuz T:


Scholarpedia 7(12), 30652 (2012).     (SPIKE)

[25] Williams MJ, Whitaker RM, Allen SM:

Measuring individual regularity in human visiting patterns.

Proceedings of the ASE International Conf. on Social Computing, 117 (2012)   (multivariate ISI-diversity)

[24] Goulet J, van Hemmen JL, Jung SN, Chagnaud BP, Scholze B, Engelmann J:

Temporal precision and reliability in the velocity regime of a hair-cell sensory system: the mechanosensory lateral line of goldfish, Carassius auratus.

J Neurophysiol 107, 2581 (2012)                                                                                                             (ISI)

[23] Mitra A, Manitius A, Sauer T:

Prediction of Single Neuron Spiking Activity using an Optimized Nonlinear Dynamic Model.

IEEE EMBS 2543 (2012)     (old SPIKE)

[22] Michmizos KP, Sakas D, Nikita KS:

Parameter identification for a local field potential driven model of the Parkinsonian subthalamic nucleus spike activity.

Neural Networks 36, 146 (2012)            (variation of ISI)

[21] Jalili M:

Collective behavior of interacting locally synchronized oscillations in neuronal networks.

Commun Nonlinear Sci Numer Simulat 17, 3922 (2012)                               (ISI, also time-resolved)

[20] Wildie M, Shanahan M:

Establishing communication between neuronal populations through competitive entrainment.

Front Comp Neurosci 5, 62 (2012)                                                           (multivariate ISI-diversity)

[19] Qu J, Wang R, Du Y, Cao J:

Synchronization study in ring-like and grid-like neuronal networks.

Cogn Neurodyn 6, 21 (2012)       (ISI, also multivariate)


[18] Spencer MC, Downes JH, Xydas D, Hammond MW, Becerra VM, Whalley BJ, Warwick K, Nasuto SJ:

Spatio-temporal dependencies in functional connectivity in rodent cortical cultures.

J Behavioral Robotics 2, 156 (2012)             (old SPIKE)

[17] Lyttle D, Fellous JM:

A new similarity measure for spike trains: Sensitivity to bursts and periods of inhibition.

J Neurosci Methods 199, 296 (2011)             (comparison of measures, includes ISI, shows ISI is a metric)

[16] Kreuz T:

Measures of spike train synchrony.

Scholarpedia 6(10), 11934 (2011)       (ISI, SPIKE)

[15] Andrzejak RG, Kreuz T:

Characterizing unidirectional couplings between point processes and flows.

European Physics Letters 96, 50012 (2011) [PDF]                                                                             (ISI)

[14] 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]               (introduces old SPIKE, now obsolete, better use new SPIKE, see [27])

[13] Njap F, Claussen JC, Moser A, Hofmann UG:

Comparing Realistic Subthalamic Nucleus Neuron Models.

AIP Conference Proceedings 1371, 102 (2010)                                                               (ISI)

[12] Engelmann J, Gertz S, Goulet J, Schuh A, von der Emde G:

Coding of Stimuli by Ampullary Afferents in Gnathonemus petersii.

J Neurophysiol  104, 1955 (2010)                             (ISI)


[11] Dodla R and Wilson CJ:

Quantification of Clustering in Joint Interspike Interval Scattergrams of Spike Trains.

Biophysical Journal 98, 2535 (2010)                                                           (variation of ISI)

[10] Xiao Z, Tian X:

Neuronal Ensemble Coding of Spike Trains in the Hippocampus CA3 via Small-world Network

J Computers 5, 448 (2010)                                                     (ISI, also time-resolved)

[9] Ibarz JM, Foffani G, Cid E, Inostroza M and de la Prida LM:

Emergent Dynamics of Fast Ripples in the Epileptic Hippocampus.

J Neurosci, 30, 16249 (2010)                                                   (multivariate ISI)

[8] 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]                   (ISI)


[7] Du Y, Lu Q:

Noise effects on temperature encoding of neuronal spike trains in a cold receptor.

Chin. Phys. Lett. 27, 020503 (2010)                                     (ISI, also time-resolved)

[6] Du Y, Lu Q, Wang R:

Using interspike intervals to quantify noise effects on spike trains in temperature encoding neurons.

Cognitive Neurodynamics 4, 199 (2010)                                        (ISI, also time-resolved)

[5] Dodla R and Wilson CJ:

Asynchronous response of coupled pacemaker neurons.

Phys Rev Lett 102, 068102 (2009)                                                                               (ISI)

[4] Pfeiffer K, French AS:

GABAergic excitation of spider mechanoreceptors increases information capacity by increasing entropy rather than decreasing jitter.

J Neurosci 29, 10989 (2009)                                                                           (ISI)


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

Measuring multiple spike train synchrony.

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

[2] Escobar MJ, Masson GS, Vieville T, Kornprobst P:

Action recognition using a bio-inspired feedforward spiking network.

Int J Comput Vis 82, 284 (2009)                                        (ISI)

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

Measuring spike train synchrony.

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


A PhD thesis outside of neuroscience:

Williams MJ:

Periodic patterns in human mobility

PhD Thesis, Cardiff University (2013).                   (multivariate ISI-diversity)