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K Wiesenfeld

Publications and source records attributed to K Wiesenfeld.

At least 19 recordsLinked to original sources
PubMed2001

Stochastic dynamics in a two-dimensional oscillator near a saddle-node bifurcation.

We study the oscillator equations describing a particular class of nonlinear amplifier, exemplified in this work by a two-junction superconducting quantum interference device. This class of dynamic system is described by a potential energy function that can admit minima (corresponding to stable solutions of the dynamic equations), or "running states" wherein the system is biased so that the potential minima disappear and the solutions display spontaneous oscillations. Just beyond the onset of the spontaneous oscillations, the system is known to show significantly enhanced sensitivity to very weak magnetic signals. The global phase space structure allows us to apply a center manifold technique to approximate analytically the oscillatory behavior just past the (saddle-node) bifurcation and compute the oscillation period, which obeys standard scaling laws. In this regime, the dynamics can be represented by an "integrate-fire" model drawn from the computational neuroscience repertoire; in fact, we obtain an "interspike interval" probability density function and an associated power spectral density (computed via Renewal theory) that agree very well with the results obtained via numerical simulations. Notably, driving the system with one or more time sinusoids produces a noise-lowering injection locking effect and/or heterodyning.

Journal Article↗
PubMed2001

Wavelets of excitability in sensory neurons.

We have investigated variations in the excitability of mammalian cutaneous mechanoreceptor neurons. We focused on the phase dynamics of an action potential relative to a periodic stimulus, showing that the excitability of these sensory neurons has interesting nonstationary oscillations. Using a wavelet analysis, these oscillations were characterized through the depiction of their period as a function of time. It was determined that the induced oscillations are weakly dependent on the stimulus frequency, and that lower temperatures significantly reduce the frequency of the phase response. Our results reveal novel excitability properties in sensory neurons, and, more generally, could prove significant in the deduction of mechanistic attributes underlying the nonstationary excitability in neuronal systems. Since peripheral neurons feed information to the CNS, variable responses observed in higher regions may be generated in part at the site of sensory detection.

Animals↗
PubMed2000

Theory of controlling stochastic resonance

The concept of controlling stochastic resonance has been recently introduced [L. Gammaitoni et al., Phys. Rev. Lett. 82, 4574 (1999)] to enhance or suppress the spectral response to threshold-crossing events triggered by a time-periodic signal in background noise. Here, we develop a general theoretical framework, based on a rate equation approach. This generic two-state theory captures the essential features observed in our experiments and numerical simulations.

Journal Article↗
PubMed1998

Mechanoelectrical transduction assisted by Brownian motion: a role for noise in the auditory system.

The organs of the vestibular, auditory and lateral line systems rely on a common strategy for the stimulation of their primary receptors, the hair cells: stimuli induce shear between hair cell epithelia and accessory structures to which hair bundles, the hair cells' mechanosensitive organelles, are attached. The inner hair cells of the cochlea, whose hair bundles are not attached to the overlying tectorial membrane, are a notable exception. Because their hair bundles are not restrained, they undergo significant Brownian motion, a characteristic traditionally thought to blunt the sensitivity of hearing. Contrary to this view, the work reported here indicates that Brownian motion of the hair bundle serves to enhance the sensitivity of mechanoelectrical transduction.

Animals↗
PubMed1995

Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs.

Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals. This phenomenon, called stochastic resonance, may find useful application in physical, technological and biomedical contexts.

Animals↗