2,373 research outputs found
Chaotic Dynamics Enhance the Sensitivity of Inner Ear Hair Cells
Hair cells of the auditory and vestibular systems are capable of detecting
sounds that induce sub-nanometer vibrations of the hair bundle, below the
stochastic noise levels of the surrounding fluid. Hair bundles of certain
species are also known to oscillate without external stimulation, indicating
the presence of an underlying active mechanism. We propose that chaotic
dynamics enhance the sensitivity and temporal resolution of the hair bundle
response, and provide experimental and theoretical evidence for this effect. By
varying the viscosity and ionic composition of the surrounding fluid, we are
able to modulate the degree of chaos observed in the hair bundle dynamics in
vitro. We consistently find that the hair bundle is most sensitive to a
stimulus of small amplitude when it is poised in the weakly chaotic regime.
Further, we show that the response time to a force step decreases with
increasing levels of chaos. These results agree well with our numerical
simulations of a chaotic Hopf oscillator and suggest that chaos may be
responsible for the sensitivity and temporal resolution of hair cells
Phase resetting reveals network dynamics underlying a bacterial cell cycle
Genomic and proteomic methods yield networks of biological regulatory
interactions but do not provide direct insight into how those interactions are
organized into functional modules, or how information flows from one module to
another. In this work we introduce an approach that provides this complementary
information and apply it to the bacterium Caulobacter crescentus, a paradigm
for cell-cycle control. Operationally, we use an inducible promoter to express
the essential transcriptional regulatory gene ctrA in a periodic, pulsed
fashion. This chemical perturbation causes the population of cells to divide
synchronously, and we use the resulting advance or delay of the division times
of single cells to construct a phase resetting curve. We find that delay is
strongly favored over advance. This finding is surprising since it does not
follow from the temporal expression profile of CtrA and, in turn, simulations
of existing network models. We propose a phenomenological model that suggests
that the cell-cycle network comprises two distinct functional modules that
oscillate autonomously and couple in a highly asymmetric fashion. These
features collectively provide a new mechanism for tight temporal control of the
cell cycle in C. crescentus. We discuss how the procedure can serve as the
basis for a general approach for probing network dynamics, which we term
chemical perturbation spectroscopy (CPS)
The Mid-Pleistocene Transition induced by delayed feedback and bistability
The Mid-Pleistocene Transition, the shift from 41 kyr to 100 kyr
glacial-interglacial cycles that occurred roughly 1 Myr ago, is often
considered as a change in internal climate dynamics. Here we revisit the model
of Quaternary climate dynamics that was proposed by Saltzman and Maasch (1988).
We show that it is quantitatively similar to a scalar equation for the ice
dynamics only when combining the remaining components into a single delayed
feedback term. The delay is the sum of the internal times scales of ocean
transport and ice sheet dynamics, which is on the order of 10 kyr. We find
that, in the absence of astronomical forcing, the delayed feedback leads to
bistable behaviour, where stable large-amplitude oscillations of ice volume and
an equilibrium coexist over a large range of values for the delay. We then
apply astronomical forcing. We perform a systematic study to show how the
system response depends on the forcing amplitude. We find that over a wide
range of forcing amplitudes the forcing leads to a switch from small-scale
oscillations of 41 kyr to large-amplitude oscillations of roughly 100 kyr
without any change of other parameters. The transition in the forced model
consistently occurs near the time of the Mid-Pleistocene Transition as observed
in data records. This provides evidence that the MPT could have been primarily
a forcing-induced switch between attractors of the internal dynamics. Small
additional random disturbances make the forcing-induced transition near 800 kyr
BP even more robust. We also find that the forced system forgets its initial
history during the small-scale oscillations, in particular, nearby initial
conditions converge prior to transitioning. In contrast to this, in the regime
of large-amplitude oscillations, the oscillation phase is very sensitive to
random perturbations, which has a strong effect on the timing of the
deglaciation events
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Closed-loop Characterization of Noise and Stability in a Mode-localized Resonant MEMS Sensor.
This paper presents results from the closed-loop characterization of an electrically coupled mode-localized sensor topology including measurements of amplitude ratios over long duration, stability, noise floor and the bandwidth of operation. The sensitivity of the prototype sensor is estimated to be -5250 in the linear operation regime. An input-referred stability of 84ppb with respect to normalized stiffness perturbations is achieved at 500s. When compared to frequency shift sensing within the same device, amplitude ratio sensing provides higher resolution for long term measurements due to the intrinsic common mode rejection properties of a mode-localized system. A theoretical framework is established to quantify noise floor associated with measurements validated through numerical simulations and experimental data. In addition, the operating bandwidth of the sensor is found to be 3.5Hz for 3dB flatness
Heteroclinic Ratchets in a System of Four Coupled Oscillators
We study an unusual but robust phenomenon that appears in an example system
of four coupled phase oscillators. We show that the system can have a robust
attractor that responds to a specific detuning between certain pairs of the
oscillators by a breaking of phase locking for arbitrary positive detunings but
not for negative detunings. As the dynamical mechanism behind this is a
particular type of heteroclinic network, we call this a 'heteroclinic ratchet'
because of its dynamical resemblance to a mechanical ratchet
Analysis of Vocal Disorders in a Feature Space
This paper provides a way to classify vocal disorders for clinical
applications. This goal is achieved by means of geometric signal separation in
a feature space. Typical quantities from chaos theory (like entropy,
correlation dimension and first lyapunov exponent) and some conventional ones
(like autocorrelation and spectral factor) are analysed and evaluated, in order
to provide entries for the feature vectors. A way of quantifying the amount of
disorder is proposed by means of an healthy index that measures the distance of
a voice sample from the centre of mass of both healthy and sick clusters in the
feature space. A successful application of the geometrical signal separation is
reported, concerning distinction between normal and disordered phonation.Comment: 12 pages, 3 figures, accepted for publication in Medical Engineering
& Physic
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