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Gerardo J Escalera Santos

Publications and source records attributed to Gerardo J Escalera Santos.

8 recordsLinked to original sources

New insights into multistability and complex resonances driven by subthreshold periodic signals in a neuronal model.

Understanding how neurons respond to weak external signals is crucial for accurate signal transmission and processing in both individual nerve cells and interconnected neuronal networks. One mechanism for the detection of these responses is through resonances. In this paper, we numerically investigate the firing patterns induced in a silent Huber-Braun neuron by a sinusoidal external force. We observe complex resonance patterns, including a sequence of frequency-locking exhibited in a Devil's Staircase structure. Furthermore, we also explore the emergence of multistability induced by the nonlinear resonance. This multistability manifests as the coexistence of three attractors, such as periodic spiking, chaotic spiking, and subthreshold oscillations. The dynamical behaviors are comprehensively analyzed using time series, bifurcation diagrams, phase portraits, and the basin of attraction. In addition, we compute the maximum Lyapunov exponent to verify chaotic regimes, and estimate the fractal dimension of basin boundaries using the uncertainty exponent. We also analyze the energy consumption of resonance-induced firing patterns and coexisting attractors. The results presented in this paper have important implications for understanding the detection of subthreshold signals and the encoding of stimulus information within a neuron's firing patterns.

Basins of attraction↗

Regulating noise-induced spiking using feedback.

We report successful manipulation of the noise provoked spiking behavior using delayed feedback control. Experiments were performed in a three electrode electrochemical cell under potentiostatic conditions. The uncontrolled system exhibited noise invoked oscillations whose regularity was quantified using normalized variance (NV). Superimposing delayed feedback, for appropriate values of delay (t), an enhancement in the regularity of the spike sequence was attained. Numerical simulations corroborated experimental observations.

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Intrinsic coherence resonance in an electrochemical cell.

We study the interaction of intrinsic electrochemical noise with autonomous nonlinear dynamics of a three-electrode electrochemical cell. The amplitude of this intrinsic (internal) noise, regulated by the concentration of chloride ions, is monotonically increased and the provoked dynamics is analyzed. The experimentally constructed coherence factor beta versus the concentration of the chloride ions' curve has a unimodal shape indicating the emergence of intrinsic coherence resonance. The abscissa for the maxima of this unimodal curve corresponds to the optimum value of intrinsic noise where maximum regularity of the invoked dynamics is observed.

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Stochastic resonance of electrochemical aperiodic spike trains.

Aperiodic stochastic resonance in an electrochemical system with excitable dynamics is characterized in experiments and simulations. Two different spike trains, one with stochastic and the other with chaotic interspike intervals, are imposed on the system as subthreshold aperiodic signals. Information transmission is quantified by the cross correlation between the subthreshold input signal and the noise induced system response. A maximum is exhibited in the input-output correlation as a function of the noise amplitude. Numerical simulations with an electrochemical model are in excellent agreement with the experimental observations.

Copper Sulfate↗

Effects of noise near a homoclinic bifurcation in an electrochemical system.

The interaction of external noise with an electrochemical oscillator (anodic dissolution of iron) has been studied experimentally on both sides of the homoclinic bifurcation. In the oscillatory regime the regularity of the limit cycle behavior was destroyed with increasing noise amplitude until no periodicity was observable any more. In contrast, the response of the excitable state (fixed point regime) became more regular at intermediate noise levels.

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Experimental evidence of coexisting periodic stochastic resonance and coherence resonance phenomena.

We report evidence of coexisting period stochastic resonance (PSR) and coherence resonance (CR) phenomena in an electrochemical cell. The anodic voltage (V) in the cell is chosen such that the anodic current (I) exhibits excitable fixed point behavior. Subsequently, the anodic voltage is modulated by an external perturbation that is a composite of a subthreshold periodic pulse signal and Gaussian white noise (GWN). As the amplitude of the GWN is increased, the regularity of the invoked dynamics is analyzed using normalized variance curve. The calculated resonance curve shows a double minima, implying the existence of two optimum noise levels where enhanced regularity of the induced spike sequence is detected. Numerical simulations corroborate experimental findings.

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Experiments on coherence resonance: noisy precursors to Hopf bifurcations.

Experimental and numerical evidence of coherence resonance in an electrochemical system is reported. External noise with a Gaussian distribution is superimposed on the system when the anodic current is exhibiting stationary (fixed point) dynamics below a supercritical Hopf bifurcation. The amplitude of the added stochastic perturbations is increased monotonically and the induced oscillatory behavior is analyzed. It is observed, both in experiments and in simulations, that the regularity of the noise induced current oscillations reaches a maximum value for an optimum noise level. This is indicative of coherence resonance and can be explained with a mechanism based on noisy precursors to a Hopf bifurcation.

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Resonances via deterministic and stochastic perturbations: a comparative study.

We study periodic and coherence resonances invoked by aperiodic yet deterministic perturbations. Chaotic perturbations with varying levels of intrinsic correlations are superimposed parametrically on an excitable chemical model. This enables us to analyze the system response and characterize the induced resonances as a function of correlation in the perturbing signal. Using standard measures such as normalized variance and normalized number of peaks, dynamics for different deterministic signals are quantified and eventually compared to resonances invoked via stochastic perturbations.

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