Transient sequences in a hypernetwork generated by an adaptive network of spiking neurons
2017 ◽
Vol 375
(2096)
◽
pp. 20160288
◽
Keyword(s):
We propose a model of an adaptive network of spiking neurons that gives rise to a hypernetwork of its dynamic states at the upper level of description. Left to itself, the network exhibits a sequence of transient clustering which relates to a traffic in the hypernetwork in the form of a random walk. Receiving inputs the system is able to generate reproducible sequences corresponding to stimulus-specific paths in the hypernetwork. We illustrate these basic notions by a simple network of discrete-time spiking neurons together with its FPGA realization and analyse their properties. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’.