Self-organized Short-Term Memory Mechanism in Spiking Neural Network
The paper is devoted to implementation and exploration of evolutionary development of the short-term memory mechanism in spiking neural networks (SNN) starting from initial chaotic state. Short-term memory is defined here as a network ability to store information about recent stimuli in form of specific neuron activity patterns. Stable appearance of this effect was demonstrated for so called stabilizing SNN, the network model proposed by the author. In order to show the desired evolutionary behavior the network should have a specific topology determined by “horizontal” layers and “vertical” columns.
Keywordsspiking neural networks spatio-temporal pattern recognition short-term memory neural network self-organization
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- 4.Kiselev, M.: Statistical Approach to Unsupervised Recognition of Spatio-temporal Patterns by Spiking Neurons. In: Proceedings of IJCNN 2003, Portland, Oregon, pp. 2843–2847 (2003) Google Scholar
- 5.Kiselev, M.: SSNUMDL - a network of spiking neurons recognizing spatio-temporal patterns. Neurocomputer 12, 16–24 (2005) (in Russian)Google Scholar
- 6.Kiselev, M.: Self-organized Spiking Neural Network Recognizing Phase/Frequency Correlations. In: Proceedings of IJCNN 2009, Atlanta, Georgia, pp. 1633–1639 (2009)Google Scholar
- 7.Kiselev, M.: One layer self-organized spiking neural network recognizing synchrony structure in input signal (in Russian). Neurocomputer 10, 3–11 (2009)Google Scholar