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arXiv · 2001.07913

Emergence of synchronised and amplified oscillations in neuromorphic networks with long-range interactions

Ilenia Apicella·Daniel Maria Busiello·Silvia Scarpetta·Samir Suweis
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Abstract

Neuromorphic networks can be described in terms of coarse-grained variables, where emergent sustained behaviours spontaneously arise if stochasticity is properly taken in account. For example it has been recently found that a directed linear chain of connected patch of neurons amplifies an input signal, also tuning its characteristic frequency. Here we study a generalization of such a simple model, introducing heterogeneity and variability in the parameter space and long-range interactions, breaking, in turn, the preferential direction of information transmission of a directed chain. On one hand, enlarging the region of parameters leads to a more complex state space that we analytically characterise; moreover, we explicitly link the strength distribution of the non-local interactions with the frequency distribution of the network oscillations. On the other hand, we found that adding long-range interactions can cause the onset of novel phenomena, as coherent and synchronous oscillations among all the interacting units, which can also coexist with the amplification of the signal.

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Ilenia Apicella, Daniel Maria Busiello, Silvia Scarpetta, Samir Suweis. 2020-01-22. Emergence of synchronised and amplified oscillations in neuromorphic networks with long-range interactions. https://arxiv.org/abs/2001.07913

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