Abstract
Axonal conduction delays should not be ignored in simulations of spiking neural networks. Here it is shown that by using axonal conduction delays, neurons can display sensitivity to a specific spatio-temporal spike pattern. By using delays that complement the firing times in a pattern, spikes can arrive simultaneously at an output neuron, giving it a high chance of firing in response to that pattern. An unsupervised learning mechanism called spike-timing-dependent plasticity then increases the weights for connections used in the pattern, and decreases the others. This allows for an attunement of output neurons to specific activity patterns, based on temporal aspects of axonal conductivity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Caporale, N., Dan, Y.: Spike Timing–Dependent Plasticity: A Hebbian Learning Rule. Annu. Rev. Neurosci. 31, 25–46 (2008)
Hebb, D.: The organization of behavior: A neuropsychological theory. John Wiley & Sons, Inc., New York (1949)
Izhikevich, E.: Simple model of spiking neurons. IEEE Transactions on Neural Networks 14(6), 1569–1572 (2003)
Izhikevich, E.: Which model to use for cortical spiking neurons? IEEE Transactions on Neural Networks 15(5), 1063–1070 (2004)
Izhikevich, E.: Polychronization: Computation with spikes. Neural Computation 18(2), 245–282 (2006)
Masquelier, T., Guyonneau, R., Thorpe, S.: Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains. PLoS ONE 3(1), e1377 (2008)
Masquelier, T., Guyonneau, R., Thorpe, S.: Competitive STDP-based spike pattern learning. Neural Computation 21(5), 1259–1276 (2009)
Nessler, B., Pfeiffer, M., Maass, W.: STDP enables spiking neurons to detect hidden causes of their inputs. In: Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C.K.I., Culotta, A. (eds.) Advances in Neural Information Processing Systems, vol. 22, pp. 1357–1365 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Datadien, A., Haselager, P., Sprinkhuizen-Kuyper, I. (2011). The Right Delay. In: Dobnikar, A., Lotrič, U., Šter, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2011. Lecture Notes in Computer Science, vol 6593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20282-7_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-20282-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20281-0
Online ISBN: 978-3-642-20282-7
eBook Packages: Computer ScienceComputer Science (R0)