Synchronization and chaos in systems of coupled inner-ear hair cells
Abstract
Hair cells of the auditory and vestibular systems display astonishing sensitivity, frequency selectivity, and temporal resolution to external signals. These specialized cells utilize an internal active amplifier to achieve highly sensitive mechanical detection. One of the manifestations of this active process is the occurrence of spontaneous limit-cycle motion of the hair-cell bundle. As hair bundles under in vivo conditions are typically coupled to each other by overlying structures, we explore the role of this coupling on the dynamics of the system, using a combination of theoretical and experimental approaches. Our numerical model suggests that the presence of chaotic dynamics in the response of individual bundles enhances their ability to synchronize when coupled, resulting in significant improvement in the system's ability to detect weak signals. This synchronization persists even for a large frequency dispersion and when tens of oscillators comprise the system. Further, the amplitude and coherence of the active motion are not reduced upon increasing the number of oscillators. Using artificial membranes, we impose mechanical coupling on groups of live and functional hair bundles, selected from in vitro preparations of the sensory epithelium, allowing us to explore the role of coupling experimentally. Consistent with the numerical simulations of the chaotic system, synchronization occurs even for large frequency dispersion and a large number of hair cells. Further, the amplitude and coherence of the spontaneous oscillations are independent of the number of hair cells in the network. We therefore propose that hair cells utilize their chaotic dynamics to stabilize the synchronized state and avoid the amplitude death regime, resulting in collective coherent motion that could play a role in generating spontaneous otoacoustic emissions and an enhanced ability to detect weak signals.
- Publication:
-
Physical Review Research
- Pub Date:
- March 2021
- DOI:
- 10.1103/PhysRevResearch.3.013266
- arXiv:
- arXiv:2012.04761
- Bibcode:
- 2021PhRvR...3a3266F
- Keywords:
-
- Quantitative Biology - Neurons and Cognition;
- Physics - Biological Physics
- E-Print:
- Phys. Rev. Research 3, 013266 (2021)