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STDP Provides the Substrate for Igniting Synfire Chains by Spatiotemporal Input Patterns

hosaka{at}nls.ics.saitama-u.ac.jp Graduate School of Science and Engineering, Saitama University, Sakura-ku, Saitama 338-8570, Japan

Osamu Araki

brainics{at}rs.kagu.tus.ac.jp Department of Applied Physics, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan

Tohru Ikeguchi

tohru{at}ics.saitama-u.ac.jp Graduate School of Science and Engineering, Saitama University, Sakura-ku, Saitama 338-8570, Japan

Spike-timing-dependent synaptic plasticity (STDP), which depends on the temporal difference between pre- and postsynaptic action potentials, is observed in the cortices and hippocampus. Although several theoretical and experimental studies have revealed its fundamental aspects, its functional role remains unclear. To examine how an input spatio- temporal spike pattern is altered by STDP, we observed the output spike patterns of a spiking neural network model with an asymmetrical STDP rule when the input spatiotemporal pattern is repeatedly applied. The spiking neural network comprises excitatory and inhibitory neurons that exhibit local interactions. Numerical experiments show that the spiking neural network generates a single global synchrony whose relative timing depends on the input spatiotemporal pattern and the neural network structure. This result implies that the spiking neural network learns the transformation from spatiotemporal to temporal information.In the literature, the origin of the synfire chain has not been sufficiently focused on. Our results indicate that spiking neural networks with STDP can ignite synfire chains in the cortices.

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				J.-P. Thivierge and P. Cisek Nonperiodic Synchronization in Heterogeneous Networks of Spiking Neurons J. Neurosci., August 6, 2008; 28(32): 7968 - 7978. [Abstract] [Full Text] [PDF]