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Simple model of spiking neurons
Abstract
A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
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“The neuron state transition influences downstream neural activity. Using classical neural models like Hodgkin-Huxley or integrate-and-fire (Izhikevich, 2003), the firing probability of a neuron i could be described as (see Equation 5):”
From The collapse of the wave function as the mediator of free will in prime neurons (2025) · cites this paper as Izhikevich, 2003
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Dynamical Systems in Neuroscience
Izhikevich, E. M. (2006) · The MIT Press eBooks · doi:10.7551/mitpress/2526.001.0001 · Cited by 3,776
Self-citationNEURAL EXCITABILITY, SPIKING AND BURSTING
Izhikevich, E. M. (2000) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127400000840 · Cited by 1,994
Self-citationIntrinsic firing patterns of diverse neocortical neurons
Connors, B. W., & Gutnick, M. J. (1990) · Trends in Neurosciences · doi:10.1016/0166-2236(90)90185-d · Cited by 1,440
Two networks of electrically coupled inhibitory neurons in neocortex
Gibson, J. R., Beierlein, M., & Connors, B. W. (1999) · Nature · doi:10.1038/47035 · Cited by 1,404
Weakly Connected Neural Networks
Hoppensteadt, F. C., & Izhikevich, E. M. (1997) · Applied mathematical sciences · doi:10.1007/978-1-4612-1828-9 · Cited by 1,261
Self-citationGray, C. M., & McCormick, D. A. (1996) · Science · doi:10.1126/science.274.5284.109 · Cited by 906
Parabolic Bursting in an Excitable System Coupled with a Slow Oscillation
Ermentrout, G. B., & Kopell, N. (1986) · SIAM Journal on Applied Mathematics · doi:10.1137/0146017 · Cited by 627
Bursts as a unit of neural information: selective communication via resonance
Izhikevich, E. M., Desai, N. S., Walcott, E. C., & Hoppensteadt, F. C. (2003) · Trends in Neurosciences · doi:10.1016/s0166-2236(03)00034-1 · Cited by 606
Self-citationIzhikevich, E. M. (2001) · Neural Networks · doi:10.1016/s0893-6080(01)00078-8 · Cited by 509
Self-citationGlobal and partial synchronism in phase-locked loop networks
Monteiro, L. H. A., Canto, N. C. F., Chauí‐Berlinck, J. G., Orsatti, F. M., & Piqueira, J. R. C. (2003) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2003.820441 · Cited by 24
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Bryson, A., Hatch, R. J., Zandt, B., Rössert, C., Berkovic, S. F., Reid, C. A., Grayden, D. B., Hill, S., & Petrou, S. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1906369117 · Cited by 59
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Torres, F., Basaran, A. C., & Schuller, I. K. (2022) · Advanced Materials · doi:10.1002/adma.202205098 · Cited by 56
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Wang, J., Li, T., Sun, C., Yan, R., & Chen, X. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.09.003 · Cited by 57
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Ashby, F. G., & Hélie, S. (2011) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2011.04.003 · Cited by 59
Financial Time Series Prediction Using Spiking Neural Networks
Reid, D. C., Hussain, A. J., & Tawfik, H. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103656 · Cited by 56
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Sharp, T., Galluppi, F., Rast, A. D., & Furber, S. B. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.03.001 · Cited by 56
Ferguson, K., Huh, C. Y. L., Amilhon, B., Williams, S., & Skinner, F. K. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00144 · Cited by 57
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Nugent, M. A., & Molter, T. W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0085175 · Cited by 55
Beyeler, M., Carlson, K. D., Chou, T.-S., Dutt, N. D., & Krichmar, J. L. (2015) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2015.7280424 · Cited by 55
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Wang, G., Wu, Y., Xiao, F., Ye, Z., & Jia, Y. (2022) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2022.127274 · Cited by 55
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Rahmati, V., Kirmse, K., Marković, D., Holthoff, K., & Kiebel, S. J. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004736 · Cited by 53
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Duan, S., Wei, X., Zhao, F., Yang, H., Wang, Y., Chen, P., Hong, J., Xiang, S., Luo, M., Shi, Q., et al. (2023) · Advanced Science · doi:10.1002/advs.202304121 · Cited by 51
Biamou, A. L. M., Tamba, V. K., Tagne, F. K., & Nzeukou, A. C. (2023) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2023.114267 · Cited by 52
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Lim, H., Kornijčuk, V., Seok, J. Y., Kim, S. K., Kim, I., Hwang, C. S., & Jeong, D. S. (2015) · Scientific Reports · doi:10.1038/srep09776 · Cited by 51
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Wang, C., Zhang, T., Chen, X., He, S., Li, S., & Wu, S. (2023) · eLife · doi:10.7554/elife.86365 · Cited by 61
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Wang, Z., Song, Y., Zhang, G., Luo, Q., Xu, K., Gao, D., Yu, B., Loke, D. K., Zhong, S., & Zhang, Y. (2024) · International Journal of Extreme Manufacturing · doi:10.1088/2631-7990/ad2fea · Cited by 49
Bayro-Corrochano, E. J. (2021) · IEEE Access · doi:10.1109/access.2021.3097756 · Cited by 49
Njitacke, Z. T., Tsafack, N., Ramakrishnan, B., Rajagopal, K., Kengne, J., & Awrejcewicz, J. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111577 · Cited by 49
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Schwab, B. C., Peter König, B., & Engel, A. K. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118179 · Cited by 48
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Njitacke, Z. T., Muni, S. S., Fozin, T. F., Leutcho, G. D., & Awrejcewicz, J. (2022) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0086182 · Cited by 48
Niedermeier, L., Chen, K., Xing, J., Das, A. K., Kopsick, J. D., Scott, E. O., Sutton, N. M., Weber, K., Dutt, N. D., & Krichmar, J. L. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892644 · Cited by 51
Ghanbarpour, M., Naderi, A., Ghanbari, B., Haghiri, S., & Ahmadi, A. (2023) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2023.3303941 · Cited by 48
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Theta Band Zero-Lag Long-Range Cortical Synchronization via Hippocampal Dynamical Relaying
Gollo, L. L., Mirasso, C. R., Atienza, M., Crespo‐García, M., & Cantero, J. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017756 · Cited by 46
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Reato, D., Cammarota, M., Parra, L. C., & Carmignoto, G. (2012) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2012.00081 · Cited by 50
Metadata
- Authors
- Izhikevich, E. M.
- Affiliations
- Neurosciences Institute (US)
- Corresponding author
- Izhikevich, E.M.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 2003-11
- Volume
- 14
- Issue
- 6
- Pages
- 1569-1572
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2164653071
- Cited by
- 4,828
- References
- 10
- Citations by year
- 2026: 263 · 2025: 412 · 2024: 364 · 2023: 393 · 2022: 376 · 2021: 317 · 2020: 280 · 2019: 267 · 2018: 274 · 2017: 250 · 2016: 192 · 2015: 248 · 2014: 211 · 2013: 186 · 2012: 180
- FWCI
- 13.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Neural Networks (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Keywords
- spiking neuron models, cortical neurons, bursting behavior, integrate-and-fire neurons, computational efficiency
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