The Right Delay: Detecting spike patterns with STDP and axonal delays

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dc.contributor.advisorHaselager, W.F.G.
dc.contributor.advisorSprinkhuizen-Kuyper, I.G.
dc.contributor.authorDatadien, A.H.R.
dc.date.issued2010-04-28
dc.description.abstractAxonal conduction delays are often ignored in simulations of spiking neural networks. Here, models of spiking neural networks with spike- timing-dependent plasticity, and conduction delays, are used in three sim- ulation experiments. The first two are based on studies by Masquelier et al. [10, 11], and the third is an expansion on their work. First, it is confirmed that a neuron can learn to detect the start of a repeating spatio-temporal spike pattern. Then, we confirm that multiple neurons can learn to detect multiple patterns, when they compete with each other through lateral inhibition. Finally, we show in a new experiment that by using axonal conduction delays, we can make a neuron sensitive to specific spatio-temporal spike patterns.en_US
dc.identifier.urihttp://theses.ubn.ru.nl/handle/123456789/71
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleThe Right Delay: Detecting spike patterns with STDP and axonal delaysen_US
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