49 citations · 167 across the 22 of their papers we have counts for
23 papers
Heterogeneity-enhanced stochastic resonance improves liquid-state computing in delayed spiking neural networks
Sandipan Nath, Marius E. Yamakou
We investigate the joint effects of stochastic forcing and quenched structural heterogeneity on stochastic resonance (SR) and liquid-state computation in a small-world network of e…
Interaction order controls stochastic-resonance enhancement and redistribution in delayed multiplex neural networks
Alina Schlabritz, Marius E. Yamakou
We investigate stochastic resonance in a hierarchy of delayed excitable systems, from a single FitzHugh--Nagumo neuron to single-layer and duplex networks with autaptic, pairwise,…
Analysis of inverse stochastic resonance: Effects of neural excitability and timescale separation
Marius E. Yamakou, Torben Krüger, Hermann Schulz-Baldes
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…
Reduced-order adaptive synchronization in a chaotic neural network with parameter mismatch: A dynamical system vs. machine learning approach
Jan Kobiolka, Marius E. Yamakou
In this paper, we address the reduced-order synchronization problem between two chaotic memristive Hindmarsh-Rose (HR) neurons of different orders using two distinct methods. The f…
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…
Self-induced-stochastic-resonance breathing chimeras
Jinjie Zhu, Marius E. Yamakou
The study in [Phys. Rev. Lett. 117, 014102 (2016)] discovered a novel type of chimera state known as coherence-resonance chimera (CRC), which combines the effects of coherence reso…
Synchronization in STDP-driven memristive neural networks with time-varying topology
Marius E. Yamakou, Mathieu Desroches, Serafim Rodrigues
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed…
Combined effects of STDP and homeostatic structural plasticity on coherence resonance
Marius E. Yamakou, Christian Kuehn
Efficient processing and transfer of information in neurons have been linked to noise-induced resonance phenomena such as coherence resonance (CR), and adaptive rules in neural net…
Quantifying and maximizing the information flux in recurrent neural networks
Claus Metzner, Marius E. Yamakou, Dennis Voelkl +2
Free-running Recurrent Neural Networks (RNNs), especially probabilistic models, generate an ongoing information flux that can be quantified with the mutual information $I\left[\vec…
Diversity-induced decoherence
Marius E. Yamakou, Els Heinsalu, Marco Patriarca +1
We analyze the effect of small-amplitude noise and heterogeneity in a network of coupled excitable oscillators with strong time scale separation. Using mean-field analysis, we unco…
Coherence resonance and stochastic synchronization in a small-world neural network: An interplay in the presence of spike-timing-dependent plasticity
Marius E. Yamakou, Estelle M. Inack
Coherence resonance (CR), stochastic synchronization (SS), and spike-timing-dependent plasticity (STDP) are ubiquitous dynamical processes in biological neural networks. Whether th…
Control of noise-induced coherent oscillations in three-neuron motifs
Florian Bönsel, Patrick Krauss, Claus Metzner +1
The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leadi…
Levy noise-induced self-induced stochastic resonance in a memristive neuron
Marius E. Yamakou, Tat Dat Tran
Self-induced stochastic resonance (SISR) is a subtle resonance mechanism requiring a nontrivial scaling limit between the stochastic and the deterministic timescales of an excitabl…
Chaotic Synchronization of memristive neurons: Lyapunov function versus Hamilton function
Marius E. Yamakou
We study the dynamical behaviors of this improved memristive neuron model by changing external harmonic current and the magnetic gain parameters. The model shows rich dynamics incl…
Optimal self-induced stochastic resonance in multiplex neural networks: electrical versus chemical synapses
Marius E. Yamakou, Poul G. Hjorth, Erik A. Martens
Electrical and chemical synapses shape the dynamics of neural networks and their functional roles in information processing have been a longstanding question in neurobiology. In th…
Dynamics of neural fields with exponential temporal kernel
Elham Shamsara, Marius E. Yamakou, Fatihcan M. Atay +1
We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equili…
Control of coherence resonance by self-induced stochastic resonance in a multiplex neural network
Yamakou E. Marius, Juergen Jost
We consider a two-layer multiplex network of diffusively coupled FitzHugh-Nagumo (FHN) neurons in the excitable regime. It is shown, in contrast to SISR in a single isolated FHN ne…
Stochastic FitzHugh-Nagumo neuron model in excitable regime embeds a leaky integrate-and-fire model
Marius E. Yamakou, Tat Dat Tran, Luu Hoang Duc +1
In this paper, we provide a complete mathematical construction for a stochastic leaky-integrate-and-fire model (LIF) mimicking the interspike interval (ISI) statistics of a stochas…
Weak-noise-induced transitions with inhibition and modulation of neural oscillations
Marius E. Yamakou, Jürgen Jost
We analyze the effect of weak-noise-induced transitions on the dynamics of the FitzHugh-Nagumo neuron model in a bistable state consisting of a stable fixed point and a stable unfo…