6 papers
Analysis of inverse stochastic resonance: Effects of neural excitability and timescale separation
Marius E. Yamakou, Torben Krüger, Torben Krüger +1
We analyze inverse stochastic resonance (ISR) in a bistable FitzHugh--Nagumo neuron driven by additive noise in the voltage variable, focusing on how neural excitability and timesc…
A Lyapunov stability proof and a port-Hamiltonian physics-informed neural network for chaotic synchronization in memristive neurons
Behnam Babaeian, Marius E. Yamakou
We study chaotic synchronization in a 5D Hindmarsh--Rose neuron model augmented with electromagnetic induction and a switchable memristive autapse. For two diffusively coupled iden…
Self-induced stochastic resonance: A physics-informed machine learning approach
Divyesh Savaliya, Marius E. Yamakou
Self-induced stochastic resonance (SISR) is the emergence of coherent oscillations in slow-fast excitable systems driven solely by noise, without external periodic forcing or proxi…
Effect of diversity distribution symmetry on global oscillations of networks of excitable units
Stefano Scialla, Marco Patriarca, Els Heinsalu +2
We investigate the role of the degree of symmetry of the diversity distribution in shaping the collective dynamics of networks of coupled excitable units modeled by FitzHugh-Nagumo…
Dynamical equivalence between resonant translocation of a polymer chain and diversity-induced resonance
Marco Patriarca, Stefano Scialla, Els Heinsalu +2
Networks of heterogeneous oscillators are often seen to display collective synchronized oscillations, even when single elements of the network do not oscillate in isolation. It has…
Inverse stochastic resonance in adaptive small-world neural networks
Marius E. Yamakou, Jinjie Zhu, Erik A. Martens
Inverse stochastic resonance (ISR) is a phenomenon where noise reduces rather than increases the firing rate of a neuron, sometimes leading to complete quiescence. ISR was first ex…