A mean-field approach to elastically coupled hair bundles

Dierkes, Kai; Jülicher, Frank; Lindner, Benjamin

doi:10.1140/epje/i2012-12037-6

Cited by 18 publications

(19 citation statements)

References 41 publications

(66 reference statements)

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“…3e). We find that these measures of sensitivity and frequency selectivity increase with system size, consistent with prior theoretical studies [22]. For a system of 20 oscillators, the synchronization induced by nonisochronicity leads to a sensitivity increase of over 400-fold and a frequency selectivity increase of over 100-fold.…”

Section: Theoretical Resultssupporting

confidence: 89%

“…The inherent noise of each component is thus averaged out, and the signal-to-noise ratio (SNR) increases with increasing number of detectors. 37 The drawback to complete synchronization is that the system is then sensitive to only a small range of frequencies surrounding the characteristic frequency. Therefore, total synchronization would be an unfavorable state for the groups of coupled hair cells in the auditory systems, as they are responsible for detecting frequencies that span several octaves.…”

Section: Optimization Of Signal Detectionmentioning

confidence: 99%

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Synchronization and chaos in systems of coupled inner-ear hair cells

Faber

Bozovic

2021

Phys. Rev. Research

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Coupled hair cells of the auditory and vestibular systems perform the crucial task of converting the energy of sound waves and ground-borne vibrations into ionic currents. We mechanically couple groups of living, active hair cells with artificial membranes, thus mimicking in vitro the coupled dynamical system. We identify chimera states and frequency clustering in the dynamics of these coupled nonlinear, autonomous oscillators. We find that these dynamical states can be reproduced by our numerical model with heterogeneity of the parameters. Further, we find that this model is most sensitive to external signals when poised at the onset of synchronization, where chimera and cluster states are likely to form. We therefore propose that the partial synchronization in our experimental system is a manifestation of a system poised at the verge of synchronization with optimal sensitivity.

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Section: Theoretical Resultssupporting

confidence: 89%

Section: Optimization Of Signal Detectionmentioning

confidence: 99%

Synchronization and chaos in systems of coupled inner-ear hair cells

Faber

Bozovic

2021

Phys. Rev. Research

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“…However, Gaussian approximations generally do not extend beyond small noise; as noise is increased, the Gaussian approximation breaks down, and we will exhibit the emergence of a bimodal distribution crucial in the generation of noise-induced oscillations for larger noise levels. Beyond neuronal models and active rotators, similar phenomena were exhibited in hair bundles coupled with elastic forces [35] or more abstract cellular automata [36].…”

Section: Introductionmentioning

confidence: 71%

Noise-Induced Synchronization and Antiresonance in Interacting Excitable Systems: Applications to Deep Brain Stimulation in Parkinson’s Disease

Touboul

Piette²,

Venance³

et al. 2020

Phys. Rev. X

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We study the nonlinear dynamics of a surprising phenomenon arising in large networks of excitable elements in response to noise: while at low noise, solutions remain in the vicinity of the resting state and large-noise solutions show asynchronous activity, the network displays orderly, perfectly synchronized periodic responses at intermediate levels of noise. This noise-induced synchronization, distinct from classical stochastic resonance, is fundamentally collective in nature. Indeed, we show that, for noise and coupling within specific ranges, an asymmetry in the transition rates between a resting and an excited regime progressively builds up, leading to an increase in the fraction of excited neurons eventually triggering a chain reaction associated with a macroscopic synchronized excursion and a collective return to rest where this process starts afresh, thus yielding the observed periodic synchronized oscillations. We further uncover a novel antiresonance phenomenon in this regime: noise-induced synchronized oscillations disappear when the system is driven by periodic stimulation with frequency within a specific range (high relative to the spontaneous activity). In that antiresonance regime, the system is optimal for measures of information transmission. This observation provides a new hypothesis accounting for the efficiency of high-frequency stimulation therapies, known as deep brain stimulation, in Parkinson's disease, a neurodegenerative disease characterized by an increased synchronization of brain motor circuits. We further discuss the universality of these phenomena in the class of stochastic networks of excitable elements with specific coupling and illustrate this universality by analyzing various classical models of neuronal networks. Altogether, these results uncover some universal mechanisms supporting a regularizing impact of noise in excitable systems, reveal a novel antiresonance phenomenon in these systems, and propose a new hypothesis for the efficiency of high-frequency stimulation in Parkinson's disease.

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“…Randomness of individual hair bundle oscillations can be reduced in a system of coupled cells, resulting in higher amplification and sharper response [26][27][28]. Furthermore, in the bullfrog sacculus, mechanical coupling of a hair bundle via an overlaying otolithic membrane suppresses spontaneous oscillations [29,30], and the amplification mechanism may be rooted in the phenomenon of amplitude death as suggested by a recent modeling study [31,32].…”

Section: Introductionmentioning

confidence: 98%

Effect of bidirectional mechanoelectrical coupling on spontaneous oscillations and sensitivity in a model of hair cells

Amro

Neiman

2014

Phys. Rev. E

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Sensory hair cells of amphibians exhibit spontaneous activity in their hair bundles and membrane potentials, reflecting two distinct active amplification mechanisms employed in these peripheral mechanosensors. We use a two-compartment model of the bullfrog's saccular hair cell to study how the interaction between its mechanical and electrical compartments affects the emergence of distinct dynamical regimes, and the role of this interaction in shaping the response of the hair cell to weak mechanical stimuli. The model employs a Hodgkin-Huxley-type system for the basolateral electrical compartment and a nonlinear hair bundle oscillator for the mechanical compartment, which are coupled bidirectionally. In the model, forward coupling is provided by the mechanoelectrical transduction current, flowing from the hair bundle to the cell soma. Backward coupling is due to reverse electromechanical transduction, whereby variations of the membrane potential affect adaptation processes in the hair bundle. We isolate oscillation regions in the parameter space of the model and show that bidirectional coupling affects significantly the dynamics of the cell. In particular, self-sustained oscillations of the hair bundles and membrane potential can result from bidirectional coupling, and the coherence of spontaneous oscillations can be maximized by tuning the coupling strength. Consistent with previous experimental work, the model demonstrates that dynamical regimes of the hair bundle change in response to variations in the conductances of basolateral ion channels. We show that sensitivity of the hair cell to weak mechanical stimuli can be maximized by varying coupling strength, and that stochasticity of the hair bundle compartment is a limiting factor of the sensitivity.

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A mean-field approach to elastically coupled hair bundles

Cited by 18 publications

References 41 publications

Synchronization and chaos in systems of coupled inner-ear hair cells

Synchronization and chaos in systems of coupled inner-ear hair cells

Noise-Induced Synchronization and Antiresonance in Interacting Excitable Systems: Applications to Deep Brain Stimulation in Parkinson’s Disease

Effect of bidirectional mechanoelectrical coupling on spontaneous oscillations and sensitivity in a model of hair cells

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