Adi R. Bulsara

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We study the one-dimensional normal form of a saddle-node system under the influence of additive gaussian white noise and a static "bias current" input parameter, a model that can be looked upon as the simplest version of a type I neuron with stochastic input. This is in contrast with the numerous studies devoted to the noise-driven leaky integrate-and-fire(More)
Here, we consider a noisy, bistable, single neuron model in the presence of periodic external modulation. The modulation induces a correlated switching between states driven by the noise. The information flow through the system, from the modulation, or signal, to the output switching events, leads to a succession of strong peaks in the power spectrum. The(More)
We introduce a dynamical readout description for a wide class of nonlinear dynamic sensors operating in a noisy environment. The presence of weak unknown signals is assessed via the monitoring of the residence time in the metastable attractors of the system, in the presence of a known, usually time-periodic, bias signal. This operational scenario can(More)
Many neurons at the sensory periphery receive periodic input, and their activity exhibits entrainment to this input in the form of a preferred phase for firing. This article describes a modeling study of neurons which skip a random number of cycles of the stimulus between firings over a large range of input intensities. This behavior was investigated using(More)
We introduce a novel dynamical description for a wide class of nonlinear physical sensors operating in a noisy environment. The presence of unknown physical signals is assessed via the monitoring of the residence times in the metastable attractors of the system. We show that the presence of ambient noise, far from degrading the sensor operation, can(More)
A detailed theoretical analysis of the dynamics of a sinusoidally driven noisy asymmetric bistable system is presented. The results are valid for any two-state system, however, the specific case of the Duffing potential is considered in detail. The dynamics are considered in the weak noise limit, i.e., when the response of the system to the external(More)
Dynamical systems that operate near the onset of coupling-induced oscillations can exhibit enhanced sensitivity to external perturbations under suitable operating parameters. This cooperative behavior and the attendant enhancement in the system response (quantified here via a signal-to-noise ratio at the fundamental of the coupling-induced oscillation(More)
The use of nonlinear architectures for energy harvesting can significantly improve the efficiency of the conversion mechanism, as respect to the use of linear devices, especially when the mechanical energy is distributed over a wide frequency bandwidth. This is the case of energy harvesting form wideband vibrations. In this paper, performances of a(More)
A recent computational study of gain control via shunting inhibition has shown that the slope of the frequency-versus-input (f-I) characteristic of a neuron can be decreased by increasing the noise associated with the inhibitory input (Neural Comput. 13, 227-248). This novel noise-induced divisive gain control relies on the concommittant increase of the(More)
We consider a model of a neuron coupled with a surrounding dendritic network subject to Langevin noise and a weak periodic modulation. Through an adiabatic elimination procedure, the single-neuron dynamics are extracted from the coupled stochastic differential equations describing the network of dendrodendritic interactions.Our approach yields a“reduced(More)