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Semi-flexible filaments interacting with molecular motors and immersed in rheologically complex and viscoelastic media constitute a common motif in biology. Synthetic mimics of filament-motor systems also feature active or field-activated filaments. A feature common to these active assemblies is the spontaneous emergence of stable oscillations as a collective dynamic response. In nature, the frequency of these emergent oscillations is seen to depend strongly on the viscoelastic characteristics of the ambient medium. Motivated by these observations, we study the instabilities and dynamics of a minimal filament-motor system immersed in model viscoelastic fluids. Using a combination of linear stability analysis and full non-linear numerical solutions, we identify steady states, test the linear stability of these states, derive analytical stability boundaries, and investigate emergent oscillatory solutions. We show that the interplay between motor activity, filament and motor elasticity, and fluid viscoelasticity allows for stable oscillations or limit cycles to bifurcate from steady states. When the ambient fluid is Newtonian, frequencies are controlled by motor kinetics at low viscosities, but decay monotonically with viscosity at high viscosities. In viscoelastic fluids that have the same viscosity as the Newtonian fluid, but additionally allow for elastic energy storage, emergent limit cycles are associated with higher frequencies. The increase in frequency depends on the competition between fluid relaxation time-scales and time-scales associated with motor binding and unbinding. Our results suggest that both the stability and oscillatory properties of active systems may be controlled by tailoring the rheological properties and relaxation times of ambient fluidic environments.
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Inhibition-based relaxation oscillations emerge in resonator networks
We investigate the mechanisms responsible for the generation of oscillations in mutually inhibitory cells of non-oscillatory neurons and the transitions from non-relaxation (sinusoidal-like) oscillations to relaxation oscillations. We use a minimal model consisting of a 2D linear resonator, a 1D linear cell and graded synaptic inhibition described by a piecewise linear sigmoidal function. Individually, resonators exhibit a peak in their response to oscillatory inputs at a preferred (resonant) frequency, but they do not show intrinsic (damped) oscillations in response to constant perturbations. We show that network oscillations emerge in this model for appropriate balance of the model parameters, particularly the connectivity strength and the steepness of the connectivity function. For fixed values of the latter, there is a transition from sinusoidal-like to relaxation oscillations as the connectivity strength increases. Similarly, for fixed connectivity strength values, increasing the connectivity steepness also leads to relaxation oscillations. Interestingly, relaxation oscillations are not observed when the 2D linear node is a damped oscillator. We discuss the role of the intrinsic properties of the participating nodes by focusing on the effect that the resonator’s resonant frequency has on the network frequency and amplitude.
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- Award ID(s):
- 1608077
- PAR ID:
- 10112501
- Date Published:
- Journal Name:
- Mathematical Modelling of Natural Phenomena
- Volume:
- 14
- Issue:
- 4
- ISSN:
- 0973-5348
- Page Range / eLocation ID:
- 405
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1051/mmnp/2019019
