The Right Delay: Detecting Specific Spike Patterns with STDP and
Berlin : Springer
InDobnikar, A.; Lotric, U.; Ster, B. (ed.), ICANNGA 10  - Adaptive and natural computing algorithms - proceedings [Lecture Notes in Computer Science, 6593], pp. 90-99
ICANNGA 10 - 10th international conference, ICANNGA 2010, Ljubljana, Slovenia, April 14-16, 2011
Article in monograph or in proceedings
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SW OZ DCC KI
Dobnikar, A.; Lotric, U.; Ster, B. (ed.), ICANNGA 10  - Adaptive and natural computing algorithms - proceedings [Lecture Notes in Computer Science, 6593]
SubjectCognitive artificial intelligence; DI-BCB_DCC_Theme 2: Perception, Action and Control; DI-BCB_DCC_Theme 4: Brain Networks and Neuronal Communication
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.
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