Abstract
We studied possibilities of classification of single spike neuron models by their intrinsic timescale parameters, because little is known about changes of timescale on spiking dynamics, and its influence on other spike properties and network dynamics such as synchronization. Using both FitzHugh-Nagumo (FHN) type and Terman-Wang (TW) type of theoretically tractable models, analysis of the phase response curve (PRC) found common and unique dynamic characteristics with respect to two parameters of timescale and injected current amplitude in the models. Also, a scheme of synchronization transition in the identical pair systems, in which two identical models mutually interact through the same model of synaptic response, was systematically explained by controlling these parameters. Then we found their common and unique synchronous behaviors.
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Sato, Y.D., Okumura, K., Shiino, M. (2010). Model Studies on Time-Scaled Phase Response Curves and Synchronization Transition. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_12
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DOI: https://doi.org/10.1007/978-3-642-17537-4_12
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