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)

[203] Kim M, Park S, Lee H, Lee J, Chou N, Shin H:

Depth‐Customizable 3D Electrode Array for Recording Functional Connectivity in the Brain

Advanced Electronic Materials 2500121 (2025)      (SPIKE-Sync, PySpike)

[202] Goshi N, Lam D, Bogguri C, George VK, Sebastian A, Cadena J, Leon NF, Hum NR, Weilhammer DR, Fischer NO, Enright HA:

Direct effects of prolonged TNF-α and IL-6 exposure on neural activity in human iPSC-derived neuron-astrocyte co-cultures

Front Cell Neurosci (2025)       (SPIKE)

[201] Wolff R, Polito A, Buccino AP, Chiappalone M, Tucci V

‘SpikeNburst’and ‘Nicespike’: Advanced Tools for Enhancing and Accelerating In Vitro High-Density Electrophysiology Analysis

bioRxiv 2025-02 (2025)       (SPIKE, RI-SPIKE)

[200] Marasco A, Lupascu CA, Tribuzi C. STSimM:

A new tool for evaluating neuron model performance and detecting spike trains similarity

J Neurosci Methods 415:110324 (2025)             (SPIKE, SPIKE-Sync, A-SPIKE, A-SPIKE-Sync)

[199] Kim E, Jeong E, Hong YM, Jeong I, Kim J, Kwon YW, Park YG, Lee J, Choi S, Kim JY, Lee JH:

Magnetically reshapable 3D multi-electrode arrays of liquid metals for electrophysiological analysis of brain organoids

Nature Communications 16(1):2011 (2025)       (SPIKE, PySpike)

[198] Lee LH, Ngan CY, Yang CK, Wang RW, Lai HJ, Chen CH, Yang YC, Kuo CC:

Motor cortex stimulation ameliorates parkinsonian locomotor deficits: effectual and mechanistic differences from subthalamic modulation

npj Parkinson's Disease 11(1):32 (2025)                                (SPIKE, SPIKY)

[197] Gauthier DW, James N, Auerbach BD:

Altered auditory feature discrimination in a rat model of Fragile X Syndrome

bioRxiv 2025-02 (2025)             (SPIKE, RI-SPIKE)

[196] Jarvis R, de Abreu Urbizagastegui PA, Bethi Y, Mehrabi A, Marcireau A:

Spikes2Vec: Efficiently Finding Repeating Structures in Brain Scale Spike Data

ICNS (2025)   (SPIKE, Julia implementation by George Datseris)

[195] Mougkogiannis PM, Adamatzky A:

On interaction of proteinoids with simulated neural networks

BioSystems 1;237:105175 (2025)         (SPIKE, SPIKY)

[194] Doorn N, van Putten MJ, Frega M:

Automated inference of disease mechanisms in patient-hiPSC-derived neuronal networks

Biorxiv 2024 May 23:2024-05 (2024)     (ISI)

[193] Köhler CA, Grün S, Denker M:

Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO)

arXiv preprint arXiv:2412.05021 (2024)     (SPIKY)

[192] Lee S, Chung WG, Jeong H, Cui G, Kim E, Lim JA, Seo H, Kwon YW, Byeon SH, Lee J, Park JU

Electrophysiological analysis of retinal organoid development using 3D microelectrodes of liquid metals

Advanced Materials 36(35):2404428 (2024)       (SPIKE)

[191] Zhang K, Deng Y, Liu Y, Luo J, Glidle A, Cooper JM, Xu S, Yang Y, Lv S, Xu Z, Wu Y:

Investigating Communication Dynamics in Neuronal Network using 3D Gold Microelectrode Arrays

ACS nano 18(26):17162-74 (2024)     (SPIKE)

[190] Baroni F, Fulcher BD:

Synchrony, oscillations, and phase relationships in collective neuronal activity: a highly comparative overview of methods

bioRxiv. May 5:2024-05 (2024)         (ISI, SPIKE, SPIKE-Sync, SPIKE-Order, SPIKY)

[189] Gaurav R, Stewart TC, Yi Y:

Legendre-SNN on Loihi-2: Evaluation and Insights

In NeurIPS Workshop Machine Learning with new Compute Paradigms (2024)   (ISI, SPIKE-Sync)

[188] Rondoni EH, Pizzinga M, Lanzarini F, Maranesi M, Albertini D, Bonini L, Russo E, Mazzoni A:

Unsupervised identification of stereotypical premotor firing patterns for the decoding of hand and mouth movements

IEEE Workshop on Complexity in Engineering (COMPENG) (pp. 1-5) (2024) (A-SPIKE)

[187] Cadena JE:

Graph-Based Modeling for the Detection and Tracking of Sarin-Surrogate-Induced Neurotoxicity Using a Human-Relevant, In-Vitro Brain Model

Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States) (2024)          (SPIKE)

[186] Mougkogiannis PM, Adamatzky A:

Proteinoid-polyaniline neuromorphic composites for audio recognition

Smart Materials and Structures. Dec 18 (2024) (SPIKE-Sync, SPIKE-order, SPIKY)

[185] Miozzo F, Murru L, Maiellano G, di Iasio I, Zippo AG, Avendano AZ, Metodieva VD, Riccardi S, D’Aliberti D, Spinelli S, Canu T:

Disruption of the autism-associated Pcdh9 gene leads to transcriptional alterations, synapse overgrowth, and defective

network activity in the CA1

J Neurosci  44, 50 (2024) (ISI)

[184] Wang Z, Cruz L:

Trainable Reference Spikes Improve Temporal Information Processing of SNNs With Supervised Learning

Neural Comput 36(10):2136-69 (2024)         (SPIKE)

[183] Hussain MA, Grill WM, Pelot NA:

Highly efficient modeling and optimization of neural fiber responses to electrical stimulation

Nature Communications. 15(1):7597 (2024)     (SPIKE-Sync)

[182] Bogguri C, George VK, Amiri B, Ladd A, Hum NR, Sebastian A, Enright HA, Valdez CA, Mundhenk TN, Cadena J, Lam D:

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Front Cell Neurosc 18:1378579 (2024)     (SPIKE)

[181] Wang H, Singh S, Trappenberg T, Nunes A:

An Information-Geometric Formulation of Pattern Separation and Evaluation of Existing Indices

arXiv:2407.14798 (2024)     (SPIKE)

[180] Desai NS, Zhong C, Kim R, Talmage DA, Role LW:

A simple MATLAB toolbox for analyzing calcium imaging data in vitro and in vivo

J Neurosci Methods 110202 (2024)           (Matlab toolbox which includes ISI, SPIKE)

[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)

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

Electrical spiking activity of proteinoids-ZnO colloids

Neuromorph Comput Eng 4, 014007 (2024), BioRxiv doi.org/10.1101/2023.07.15.549138       (ISI, SPIKE-Sync, SPIKY)

[172] Mougkogiannis P, Adamatzky A:

Recognition of sounds by ensembles of proteinoids

Materials Today Bio:100989 (2024), BioRxiv https://doi.org/10.1101/2023.07.17.549338                

  (SPIKE, SPIKE-Sync, SPIKE-order, SPIKY)

[171] Fehrman C, Meliza CD:

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

J Neural Eng 21(5):056014 (2024)       (ISI, SPIKE, PySpike)

[170] 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)

[169] 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)

[169] 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)

[167] 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)

[166] 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)

[165] 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)

[164] 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)

[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 https://doi.org/10.1016/j.physa.2023.128591 (2023)       (SPIKE-Sync, PySpike)

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

Highly reproducible eyeblink timing during formula car driving

iScience https://doi.org/10.1016/j.isci.2023.106803 (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 https://doi.org/10.3390/cells12050821 (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 26(8) (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. https://doi.org/10.1371/journal.pcbi.1011335 (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 https://doi.org/10.1101/2022.10.20.513047 (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 https://doi.org/10.1101/2022.09.22.509092 (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 https://doi.org/10.1101/2021.09.11.459906 (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 http://dx.doi.org/10.1093/brain/awac365 (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 https://arxiv.org/pdf/2204.04605.pdf (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 https://doi.org/10.1101/2022.05.12.491724 (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)

    (ISI, SPIKE, A-ISI, A-SPIKE, ARI-SPIKE, SPIKE-Sync)

[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: https://doi.org/10.3389/fncir.2021.718270 (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: https://doi.org/10.1101/2021.03.24.436765 (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 https://doi.org/10.1101/2021.09.11.459906 (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 https://doi.org/10.1101/2020.12.04.412023 (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], doi.org/10.1007/978-1-4614-7320-6_409-2 (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, http://dx.doi.org/10.1101/2019.12.17.879726 (2019)                  (SPIKE-Synchro, PySpike)

[102] Brouns T, Celikel T:

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

BioArxiv, http://dx.doi.org/10.1101/739409 (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, https://doi.org/10.1101/242438 (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 https://doi.org/10.1007/s11571-017-9466-9 (2017)                         (ISI)

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

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

BioRxiv https://doi.org/10.1101/107706 (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:

SPIKE-order

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:

SPIKY

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:

SPIKE-distance.

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)