Mechanoelectrical transduction assisted by Brownian motion: a role for noise in the auditory system
Entry by Richie Tay for AP 225 Fall 2012
Authors: Fernán Jaramillo, Kurt Wiesenfeld
The ear is potentially capable of detecting nanometer-scale vibrations, but Brownian motion of the sensory apparatus generates noise that is at least an order of magnitude larger. In this paper the authors showed that, rather than limiting our threshold of hearing, this thermal noise actually enhances the ear’s sensitivity to weak signals.
The mechanics of hearing
Inner hair cells in the cochlear each have hundreds of cylindrical stereocilia protruding from their apical surface; collectively these form hair bundles, the mechanosensitive organelles that gather and transmit auditory information (Figure 1a). The tips of the stereocilia are joined by filamentous tip links, which are believed to be connected to mechanosensitive ion channels (Figure 1b). Mechanical stimuli (in the form of sound waves) cause the stereocilia to slide along one another, thus altering the tension of the tip links and initiating signal transmission.
Stochastic resonance refers to a nonlinear cooperative phenomenon where the addition of low-level noise to a system improves the system’s ability to detect weak (information-carrying) signals. To illustrate, imagine a double-well potential curve which could correspond, for instance, to the low-energy “open” and “closed” states of an ion channel (Figure 2). The wells are separated by an energy barrier. A very weak signal will not excite a particle sitting in one well into the neighboring well, but the addition of some noise will occasionally allow transitions between the wells. Stochastic resonance occurs when these exit events become correlated with the weak signal, so that transitions become more regular, and the regularity/coherence improves with the addition of more noise. Beyond an optimum background noise, the frequency of transitions no longer correlates with the weak signal and coherence deteriorates.
Results and Discussion
A stiff glass probe capable of precise sub-nanometer motion was attached to the kinociliary bulb of patch-clamped hair cells from frog sacculi. To simulate hair-bundle Brownian motion, low-pass filtered white noise was used. In addition, a weak periodic signal (2 nm amplitude, 300 or 500 Hz) was provided. The signal-to-noise ratio (SNR) of the transduction current was then obtained.
In the absence of added noise (Figure 3a, the probe’s own Brownian motion is ~1 nm), the weak 300 Hz signal is undetectable from the background noise, but it emerged clearly with the addition of only a small amount of noise (Figure 3b). Further increasing the noise swamped the signal (Figure 2c).
Figures 4a and 4b show the noise-dependence of the SNRs of two different hair cells stimulated at two frequencies. The data was fitted to the gating spring model of mechanoelectrical transduction, which assumes that elastic elements act to keep transduction channels either open or closed. The observed noise dependence is characteristic of stochastic resonance, with an optimum noise level between 1.0 and 2.7 nm. This is a physiologically relevant noise range, since it is comparable to the Brownian motion observed in amphibian hair cells (2-3 nm) and that estimated for inner hair cells (2 nm).
Stochastic resonance increased SNR of transduction by up to twofold. This might not seem significant, but as the authors discussed, our auditory system’s enormous dynamic range (100 dB, or over five orders of magnitude) is compressed into hair bundle displacements between 0.2-200 nm, which makes a twofold gain in SNR fairly important. Due to the probe’s inherent noise, it was not possible to obtain SNRs in the complete absence of Brownian motion, but the authors surmised that weak signals would cease to be transduced without some background noise.
I find this paper interesting because it considers Brownian motion at the organelle level, and highlights its significance in sensory biology not as a mere noise generator but as an essential component of the sensory apparatus.