DocumentCode
423718
Title
Information transformation from a spatiotemporal pattern to synchrony through STDP network
Author
Hosaka, Ryosuke ; Ikeguchi, Tohru ; Nakamura, Hikoichiro ; Araki, Osamu
Author_Institution
Graduate Sch. of Sci. & Eng., Saitama Univ., Japan
Volume
2
fYear
2004
fDate
25-29 July 2004
Firstpage
1475
Abstract
Recent experimental results show the sensitivity of synaptic plasticity to the timing of synaptic events and postsynaptic firings (spike timing dependent plasticity: STDP). Although a number of studies have been made on STDP, little is known about the effect of STDP on the relation between external input patterns to the recurrent neural network and its output spikes. In this study, we examine this relation by computer simulations of a spiking neural network with STDP. We have found that STDP organizes the neural network to transform an external spatiotemporal input pattern into a synchronous firing, and the synchrony is much dependent on the spatiotemporal structure of the external input. This result suggests that the original of the synchrony propagate through feed-forward network may be generated by the recurrent neural network respond to the external input.
Keywords
digital simulation; feedforward neural nets; information theory; recurrent neural nets; spatiotemporal phenomena; computer simulations; feedforward network; information transformation; postsynaptic firing timings; recurrent neural network; spatiotemporal pattern structure; spike timing dependent plasticity network; spiking neural network; synaptic event timings; synaptic plasticity sensitivity; synchronous firing; Computer aided instruction; Computer simulation; Electronic mail; Feedforward systems; Neural networks; Neurons; Rats; Recurrent neural networks; Spatiotemporal phenomena; Timing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-8359-1
Type
conf
DOI
10.1109/IJCNN.2004.1380170
Filename
1380170
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