Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development

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STOCHASTIC RESONANCE IN THE SYNAPTIC TRANSMISSION BETWEEN HAIR CELLS AND VESTIBULAR PRIMARY AFFERENTS IN DEVELOPMENT

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A. FLORES, a* S. MANILLA, a N. HUIDOBRO, a B. DE LA TORRE-VALDOVINOS, a R. KRISTEVA, d I. MENDEZ-BALBUENA, b F. GALINDO, a M. TREVIN˜O c AND E. MANJARREZ a*

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a

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b

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c

Laboratorio de Plasticidad Cortical y Aprendizaje Perceptual, Instituto de Neurociencias, Universidad de Guadalajara, Mexico

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Department of Neurology, University of Freiburg, Breisacherstraße 64, 79106 Freiburg, Germany

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stages of development. Ó 2016 Published by Elsevier Ltd. on behalf of IBRO.

Instituto de Fisiologı´a, Beneme´rita Universidad Auto´noma de Puebla, Mexico

Key words: noise, vestibular, inner ear, mechanoreceptor, primary afferents, cupula.

Facultad de Psicologı´a, Beneme´rita Universidad Auto´noma de Puebla, Mexico

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Abstract—The stochastic resonance (SR) is a phenomenon of nonlinear systems in which the addition of an intermediate level of noise improves the response of such system. Although SR has been studied in isolated hair cells and in the hair-cell-sacculus afferent transmission of the amphibian auditory system, the occurrence of this phenomenon in the vestibular system in development is unknown. The purpose of the present study was to explore for the existence of SR via natural mechanical-stimulation in the hair cell-vestibular primary afferent transmission. In vitro experiments were performed on the posterior semicircular canal of the chicken inner ear during development. Our experiments showed that the signal-to-noise ratio of the afferent multiunit activity from E15 to P5 stages of development exhibited the SR phenomenon, which was characterized by an inverted U-like response as a function of the input noise level. The inverted U-like graphs of SR acquired their higher amplitude after the post-hatching stage of development. Blockage of the synaptic transmission with selective antagonists of the NMDA and AMPA/Kainate receptors abolished the SR of the afferent multiunit activity. Furthermore, computer simulations on a model of the hair cell – primary afferent synapse qualitatively reproduced this SR behavior and provided a possible explanation of how and where the SR could occur. These results demonstrate that a particular level of mechanical noise on the semicircular canals can improve the performance of the vestibular system in their peripheral sensory processing even during embryonic

*Corresponding authors. Address: Instituto de Fisiologı´ a, Beneme´rita Universidad Auto´noma de Puebla, 14 sur 6301, Col. San Manuel. A. P. 406, C.P. 72570 Puebla, Pue., Mexico. Tel: +52-22-22-441657; fax: +52-22-22-334511. E-mail addresses: Amira.fl[email protected] (A. Flores), [email protected] (E. Manjarrez). Abbreviations: IHC, inner hair cell; SNR, signal-to-noise ratio; SR, stochastic resonance. http://dx.doi.org/10.1016/j.neuroscience.2016.02.051 0306-4522/Ó 2016 Published by Elsevier Ltd. on behalf of IBRO. 1

INTRODUCTION

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The stochastic resonance (SR) is a counter-intuitive phenomenon of many physical and biological nonlinear systems that refers to the increase in the signal-to-noise ratio (SNR) on the output, obtained through an increase in the noise level on the input (Anishchenko et al., 1999; Gammaitoni et al., 1998, 2009; for reviews see Moss et al., 2004; McDonnell and Abbott, 2009; McDonnell and Ward, 2011; McDonnell et al., 2015). Typically, the plot of SNR vs. input noise is an inverted U-like function characterized by maximal enhancement of SNR at a specific noise amplitude value. The isolated hair cells of the vestibular and auditory systems have been studied in the context of their response to a variety of physical stimuli, i.e., caloric, electrical, chemical or mechanical. In 1991, Zenner and Zimmermann, demonstrated that isolated vestibular hair cells from the guinea pig can produce motility of the cell body or sensory hairs by direct caloric, electrical or chemical stimuli applied on these cells. Such mechanical responses of the vestibular cells could contribute to micromechanical non-linearities of stereociliary displacements and gain control. In this context, in 1998, Jaramillo and Wiesenfeld published a pioneering study about SR elicited by mechanical stimuli in whole-cell recordings of isolated hair cells from the frog sacculus. These authors demonstrated that mechanical Brownian motion of the hair bundle provides an optimal noise level that increases the sensitivity of mechanoelectrical transduction to weak signals. Thus the SR can be elicited by intrinsic mechanisms of the hair cells when mechanical noise is applied to the hair bundle. A subsequent study by Indresano et al. (2003) reported that mechanical noise applied in the bullfrog sacculus produced a SR effect in the acoustic information conveyed by the 8th nerve. This result demonstrated for the first time that mechanical noise enhances the signal transmission in the bullfrog sacculus via the SR phenomenon. The studies by Jaramillo and Wiesenfeld

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(1998) and Indresano et al. (2003), show that the SR can be generated in both, the hair cells and in the second stage of the sensory transmission: the auditory primary afferents via the hair cell-primary afferents transmission. The above-mentioned studies show that the SR has been extensively studied in sensory and motor systems, even in the isolated hair cells and hair-cell-sacculus afferent transmission of the auditory system (Jaramillo and Wiesenfeld, 1998 and Indresano et al., 2003); however, their physiological mechanisms in the synaptic transmission from the vestibular hair cells to the primary afferents during development are unknown. The study of SR in the synaptic transmission of the semicircular canals of the chicken inner ear during development is crucial to clarify the specific contribution of SR elicited by mechanical noise in the vestibular system, the organ of balance, which is a sensor of angular acceleration.

EXPERIMENTAL PROCEDURES

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Animal preparation

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Experiments were made using the isolated inner ear of the chicken (Gallus domesticus). We employed 17 embryos of 15, 17, 19 and 21 days (E15–E21) and three hatchlings of 5 days (P5). They were obtained from the ALPES poultry farm at Tehuaca´n, Puebla. The age of the embryos given in days was established by reference to the staging criteria of Hamburger and Hamilton (1951). The embryos were kept in incubation under strict temperature control, between 38.5 °C and 39.5 °C, and relative humidity of about 60% in a BGE33 incubator (Instrumentos de Laboratorio, Me´xico). Embryos were cooled at approx.
12 °C for 15 min. Then the embryos were extracted and immediately after the withdrawal reflex was abolished the animal was decapitated as described (Cortes et al., 2013; Galindo et al., 2013). Hatchling animals were first anesthetized intraperitoneally with sodium pentobarbital (6 mg/kg, Pfizer) and then decapitated as previously described (Cortes et al., 2013; Galicia et al., 2015). The otic capsule was immediately opened. The nerve of the posterior semicircular canal was dissected up to the brainstem. The cartilaginous otic capsule was cut and isolated from the cranium. All efforts were made to minimize animal suffering and to reduce the number of animals used for the experiments, as outlined in the ‘‘Guide for the Care and Use of Laboratory Animals” prepared by the National Academy of Science and published by the National Institutes of Health. The isolated inner ear was transferred to a recording chamber and continuously perfused with Ringer solution of the following composition (in mM): NaCl 124, KCl 5, CaCl2 2, NaH2PO4 2.2, NaHCO3 26, MgSO4 2, glucose 10. The pH of this solution was 7.3–7.4 after saturation with 95% O2 and 5% CO2 (Peusner and Giaume, 1997). The saline was warmed by a Temperature Controller (TC-102, Medical System Corporation) and was circulated through the chamber at a rate of 3–5 ml/min. The temperature of the bathing medium was kept at 37–39 °C during the experiments. A small opening, approximately 1 mm2, in the bony wall of the posterior semicircular canal

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was made, being careful not to disrupt the underlying membranous duct, through which the probe of the mechanical stimulating device was positioned as shown in Fig. 1A. The preparation was allowed to equilibrate for 30 min before recording.

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Mechanical stimulation

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A closed-loop mechanical stimulator-transducer (Chubbuck, 1966; Manjarrez et al., 2002a,b; MendezBalbuena et al., 2015) allowed measures of the displacement of the applied stimuli. The output of two independent function generators provided input to the stimulatortransducer (Fig. 1A). One of these (Tektronix CFG 253) generated a sinusoidal input waveform (test stimulus) while, the other (Wavetek Model 132), supplied the superimposed noise. The inner ear was held in a fixed position to ensure that the exposed semicircular canal remained over the indenter arm of the mechanical stimulation device, which consisted of a 0.5-mm diameter probe. The probe tip was used to apply sinusoidal duct displacements of the posterior semicircular canal. Fig. 1B shows the input–output curve for the extracellular multiunit activity versus the sinusoidal stimulus strength in zero noise conditions (control).

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Test sinusoidal-stimuli

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We obtained input–output curves for the multiunit response of the semicircular canal for each animal to mechanical sinusoidal stimulation. We applied a single sine frequency of 1.1 Hz with a magnitude of the probe tip displacement from 0 to 50 lm. This method of natural stimulation has proven to be reliable and reproducible (Dickman et al., 1988; Boyle and Highstein, 1991). This natural stimulation produced endolymph movement and consequent cupula deflections as illustrated in Fig. 1A. The arrow in Fig. 1B indicates the stimulation intensity employed for the test stimulus (the control). This intensity produced a multiunit activity in the nerve of the semicircular canal of about 30% of their maximal response. We verified that this stimulation strength did not affect the membranous duct of the semicircular canal neither the functional response of the vestibular organ in the semicircular canal (i.e., we verified that the amplitude of the multiunit activity did not change along the experiment).

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Noisy stimuli

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Gaussian noise in the range from 0 to 250 Hz was continuously applied with the same indenter and it was superimposed to the test sinusoidal stimulation. Fig. 1D, F shows the power spectrum and the amplitude distribution of the noisy stimulus. We choose this broad bandwidth because it was more effective to produce SR effects in our preparation in our preliminary experiments. The range of the applied noise in our experiments was from 0 lm to 40 lm. It was adjusted to this amplitude range because within this range we found the optimal noise level which produced the maximal SR effect in our preliminary experiments. We also employed this range

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Fig. 1. Preparation and stimulation paradigm. (A) Scheme of the experimental arrangement. A probe tip was placed on the membranous duct to apply sinusoidal displacements. The output of two independent function generators provided the input to the stimulator-transducer. One of these supplied a sinusoidal waveform (signal) while the other generated superimposed noise (noise). The scheme illustrates that the natural stimulation can produce endolymph movement and a consequent cupula deflection. Extracellular multiunit recordings of the posterior semicircular canal nerve were obtained using a suction electrode (output). (B) Strength of the output power spectra peak (its amplitude) during periodic stimulation without noise versus the amplitude of the input sinusoidal duct displacements (input amplitude). The arrow indicates the magnitude of the probe-tip displacement used to study the SR phenomenon (test stimulus). (C) Example of the power spectrum of the noisy stimulus. (D) Example of the amplitude distribution of the noisy stimulus.

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of noisy mechanical indentation with confidence because the maximal indentation was about 15% of the mean diameter of the posterior semicircular canal in the chicken embryo from E15 to E17 (diameter of about 250 lm; see Bissonnette and Fekete, 1996). Moreover, we checked by histological observation that the membranous duct was intact after the experimental sessions. Antagonists of the NMDA and AMPA/Kainate receptors We analyzed the effect of selective NMDA and nonNMDA (AMPA/Kainate) antagonists in the SR of the vestibular afferents in chickens at P5. MK-801 10
6 M and NBQX 10
6 M were co-applied by bath substitution,

employing the same effective concentrations as in a previous study from our laboratory (Cortes et al., 2013).

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Recording

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Extracellular multiunit recordings of the posterior semicircular canal afferent fibers were obtained using a suction electrode (A-M Systems). This allows the detection of changes in the firing rate of much of the afferent fiber population. Extracellular multiunit activity was recorded with pre-amplifier filters (0.1 Hz to 10 kHz). Data acquisition of the input noise and of the multiunit activity was performed with a sampling rate of 20 kHz. The magnitude of the input noise was quantified by means of the standard deviation of the input

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displacement (rn of input noise). We estimated the effect of noise upon evoked potentials from the power spectra of the concurrent multiunit activity.

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Stimulation paradigm

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The stimulation scheme consisted of sequences that lasted 10 s, during which we applied, either a stimulus with noise superimposed or noise alone. We applied seven or fourteen sequences each with a different noise intensity level. The presentation order of the different noise levels was varied randomly to remove possible serial effects. We characterized SR by examining the peak amplitude (or area) of the rectified and integrated multiunit-activity-SNR for each input noise level (see next methods section for details). We plotted area of SNR as a function of the input noise level for each preparation.

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Computer simulations

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We adapted an inner hair cell (IHC) model developed by David Mountain and Alan Cody (1999) which replicates many of the fine details observed in the membrane potential of IHCs in response to sinusoidal mechanical stimuli (Mountain and Cody, 1999). The model used a realistic transducer conductance and a membrane time constant (sm = 0.2 ms), but it assumed that the basolateral membrane conductance was linear and that the tension-gated channels were the only apical channels. Therefore, the input for the model was the basilar membrane displacement (x(t)) whereas the output of this model was a filtered IHC receptor potential (Vm(t)). The relationship between the apical conductance gA(t) and IHC hair bundle displacement x(t) was described with the following equation:

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g max   gA ðtÞ ¼  x0
xðtÞ x1
xðtÞ  1 þ e S1 1 þ e S0

where x0 = 27 nm, x1 = 27 nm, S0 = 85 nm, S1 = 11 nm and gmax = 11.6 nS. This function allows for both, saturation at high input levels, as well as for a sigmoidal increase in amplitude variations in the mid-range of the function (Deligeorges and Mountain, 1997). The Vm(t) of the IHC was solved using a forward Euler method and was modeled by an equivalent circuit with an apical conductance (gA) that produced a receptor current using a driving force of EP-Vm(t), where EP was a driving potential of 125 mV. Therefore, the receptor potential Vm(t) resulting from this receptor current was influenced by the apical membrane capacitance (CA), the basolateral conductance (gB) and basolateral capacitance (CB), respectively. Also, the Vm(t) was finally low-pass filtered after transduction causing the model to lose phase-locking to the mechanical stimulus with increasing frequency. It also considered a basal resistance of 15.8 MX and a membrane equilibrium potential of
45 mV. An offset potential of about 1.4 mV was subtracted from the membrane potential of the simulated cells to adjust a basal firing rate of the auditory nerve around 35 Hz. To simulate the activity of the auditory nerve fiber we adapted once more the model developed by David

Mountain (Deligeorges and Mountain, 1997; Singh and Mountain, 1997). Here, the calcium channel open probability in the IHC was estimated with a Boltzmann function of Vm(t). Therefore, depolarizations in the ICH triggered the vesicle release (1), which in turn increased the neurotransmitter concentration in the cleft (2), and then this activated postsynaptic receptors (3) leading to a proportional increase in the firing rate of the fiber (4). All these cascaded events were represented as low-pass filtered linear function of the previous step (Deligeorges and Mountain, 1997). For our simulations, we used 500 iterations per condition and mechanically stimulated the IHC at 1 Hz for 10 s (i.e., 10 cycles) with a stimulation onset of 5 s. The stimulation amplitudes ranged from 1 to 10 nm in increments of 1 nm and the injected noise was created using random numbers from a Gaussian distribution with zero mean and standard deviations ranging from 0 to 40. To calculate SNR in the model, we averaged the peak amplitude of all the responses (i.e., 10) produced by the input stimulus with or without injected noise and divided it by the average of 2 s of activity without input stimulus (taken from t = 2 s to t = 4 s; stimulus onset @ t = 5 s). We calculated the SNR for both the IHC (presynaptic) and for the auditory nerve fiber (postsynaptic). We subtracted the resting membrane potential from Vm before calculating the SNR of the IHC.

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Signal analysis and statistics

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In order to quantify the changes in the multiunit activity of the semicircular canal produced by the application of mechanical noise we rectified and integrated such multiunit response. To compute the SNR we employed the rectified and integrated multiunit signals of Fig. 3A, B according to the formula depicted in Fig. 3C. ‘‘|S+N|” represents the magnitude of the area of the rectified S+N signal. To test for any statistical difference in the multiunit activity between conditions ZN, ON and HN, we considered the area of SNR relative to control. Because we wanted to compare the conditions ZN vs. ON, HN vs. ON and ZN vs. HN, we performed statistical analysis on the area of SNR related to these three noise levels. Because our data were not normally distributed (Kolmogorov–Smirnov normality test, p < 0.05) and had no homogeneity of variances (Levene test, p < 0.05) we used a non-parametric Friedman’s ANOVA, under the null hypothesis that the dependent variable area of SNR was the same across the factors. Where the differences were significant we performed the Wilcoxon signed-rank test with the null hypotheses that the differences of the means between ZN
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HN, were zero.

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RESULTS

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Experimental results

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All preparations we examined exhibited SR-type responses in the afferent multiunit activity of the

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Fig. 2. Extracellular multiunit activity of the posterior semicircular canal nerve for three levels of noise. Left panel, Recordings obtained from the multiunit activity of afferents from the posterior semicircular canal for zero noise (ZN). Middle panel, the same as the left panel but for optimal noise (ON). Right panel, the same as the left panel but for high noise (HN). The gray traces correspond to the noise applied. The black and white vertical bars delimit and indicate the developmental stage of the animals employed.

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posterior semicircular canal elicited by noisy mechanical stimulation. To examine SR-like effects in the multiunit activity of the vestibular afferents in the developmental stages from E15 to P5 we applied mechanical noise on the semicircular canal, as described in the methods section. Fig. 2 shows multiunit recordings of the vestibular nerve obtained from 5 chickens at such ages. Note that there is an increase in the multiunit firing activity for the ON condition compared with ZN and HN. Fig. 3 shows how the SNR was calculated employing recordings as those illustrated in Fig. 2. For illustrative purposes in Fig. 3 we show this procedure for one animal. The upper panel of Fig. 3A illustrates three levels of input noise superimposed with the test sinusoidal stimulation (zero noise ZN, optimal noise ON, and high noise HN as indicated). The second panel of Fig. 3A shows the corresponding multiunit responses of the semicircular canal to the applied stimuli. The third panel of Fig. 3A illustrates the rectified and integrated multiunit responses. Note that the optimal noise produced an increase in the firing activity as well as an increase in the background response. Moreover, the HN stimulus produced an additional increase in the background response but a decrease in the firing multiunit activity elicited by the sinusoidal stimuli plus such HN. Following the same stimulation paradigm but

with the application of noise alone, we performed the corresponding rectification and integration of the evoked multiunit activity (see Fig. 3B). In order to compute the SNR we employed the rectified and integrated multiunit signals of Fig. 3A, B according to the formula depicted in Fig. 3C (see Experimental procedures for more explanation). The typical SNR obtained with this formula is illustrated in Fig. 3C for the three levels of noise ZN, ON and HN. Note that there is an optimal level of noise (ON) for which the SNR reaches a maximum; however, for HN the SNR decreases. We obtained similar responses as those illustrated in Fig. 3C for all the animals in different stages of development. Fig. 4 shows such experimental results for the semicircular canal multiunit responses of chickens at stages E15 (four animals), E17 (three animals), E19 (seven animals), E21 (three animals) and P5 (three animals), as indicated with the black and white vertical bars on the right panel. Note that the SNR for optimal noise in the embryos has a scale of 2, thus illustrating that the SNR for ON was increased up to 2 in embryos from E15 to E21 (see middle panel labeled with ON). However, for hatchling chickens at P5 such scale of the SNR is in the order of 6 and 12, thus indicating that the SNR reached for ON was increased up to 12. This Fig. 4 also shows that the SNR obtained at HN (third panel) for all the animals returns to values similar to

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Fig. 3. Typical results from one experiment. Recordings of the input signal plus noise (A) or noise alone (B) and the corresponding multiunit activity of the semicircular canal nerve for three levels of noise, zero noise (ZN), optimal noise (ON) and high noise (HN). The last panel in A and B shows the corresponding rectified and integrated multiunit activity as indicated. S+N, is for signal plus noise, and N, is for noise alone. The signal-to-noise ratio (SNR) was calculated by means of the formula in C. The traces in C show the SNR for the three levels of noise, ZN, ON and HN.

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those observed for the control condition of ZN (first panel). Furthermore, the upper panel of Fig. 5 shows the grand average of the SNR for all the animals illustrated in Fig. 4. Note that there is a consistent result of an increase in the SNR for the optimal level of noise (ON) compared to the SNR for ZN or HN. Such dramatic change can also be visualized by means of the wavelet plots of frequency versus time illustrated in the lower panel of Fig. 5, thus indicating that an optimal level of noise added to the test sinusoidal mechanical stimulation of the semicircular canal produces a facilitation of the multiunit responses to such sinusoidal stimuli. In order to analyze in more detail the profile of the change of the SNR versus the input noise level we computed the area of the SNR relative to control (ZN) for up to 14 levels of such input noise. Fig. 6A shows

the results for five chickens and different developmental stages as indicated. Note that these graphs exhibit a similar profile with an inverted U-like shape of the area of SNR as a function of the input noise level. A qualitative general description of these curves may apply to all. As the noise amplitude increases, the area of SNR value becomes larger. Hence, a positive slope and an upsurge of the function can be observed as the curve rises steeply and turns convex. A maximum value of area of SNR is reached and the slope becomes zero within a particular interval of noise amplitudes. Beyond such peak, with higher noise amplitudes, the slope becomes negative as the curve subsides gradually. This modulation of the area of SNR suggests quite strongly that the information transmitted throughout the peripheral vestibular system is modulated by the input noise. Fig. 6B illustrates pooled data of the ZN, ON and

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Fig. 4. SNR obtained from all the experiments for three levels of noise. Left panel, Signal-to-noise ratio (SNR) obtained from the rectified and integrated multiunit activity of afferents from the posterior semicircular canal. Middle panel, the same as the left panel but for optimal noise (ON). Right panel, the same as the left panel but for high noise (HN). The black and white vertical bars delimit and indicate the developmental stage of the animals employed for the SNR analysis.

Fig. 5. Grand average of the SNR. Upper panel, SNR obtained from the averaging of the traces illustrated in this figure for three levels of noise, zero noise (ZN), optimal noise (ON) and high noise (HN). The lower panel shows frequency-time maps obtained from wavelet analysis of the SNR illustrated in the upper panel.

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HN values of the area of SNR for all the animals. Fig. 6C shows the grand average of such values for every level of noise, as indicated. For each age group we performed the non-parametric Friedman’s ANOVA, to examine the

statistical significance of the change in the area of SNR, between the three conditions (ON, ZN and HN). In all groups we found significant differences, therefore, we performed the Wilcoxon signed-rank test between ZN

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Fig. 6. Statistical analysis of the SNR for all the experiments. (A) Area of SNR versus the standard deviation (SD) of the input noise for five different animals, as indicated by the label of their developmental stage E15, E17, E19, E21 and P5. The horizontal line represents the magnitude of a 95% confidence interval. (B) Area of SNR for three levels of noise for all the animals. (C) The same as C but for the grand average of the data pooled in B. (D) Mean values of the area of SNR versus the developmental stage.

Table 1. Statistical analysis of the area of SNR for the multiunit activity recorded in all groups of ages. Friedman’s ANOVA and the post hoc Wilcoxon signed-rank test were performed between ZN-ON and ON–HN conditions. Sig = significance. Developmental stages

E15 E17 E19 E21 P5

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Friedman’s ANOVA

Wilcoxon signed-rank test

n

Chi2

df

Significance

Sig. ZN–ON

Sig. ON–HN

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8.4 8 16.2 10.3 60

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0.015 0.018 0.0001 0.006 0.05

0.034 0.034 0.0025 0.0155 0.034

0.034 0.034 0.0025 0.0155 0.034

and ON and between ON and HN. The results are summarized in Table 1. An additional analysis was performed with the pooled data of all ages. The

Friedman’s ANOVA, revealed a statistically significant result (v2(2) = 50.6, p < 0.0001). A subsequent post hoc analysis, Wilcoxon signed-rank test, uncovered

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significant differences (p values are indicated in Fig. 6C). We also found that the maximal area of SNR exhibited its largest value in chickens at P5 compared to chickens in embryonic stages E15–E21 (Fig. 6D). We demonstrated that the continuous perfusion of a Ringer solution of low calcium–high magnesium abolish the SR. Fig. 7B shows that mechanical noise did not produce a response on the afferent activity as in the control case (Fig. 7A). This suggests that the mechanical noise requires neurotransmitter release from hair cells to primary afferents to produce their effects on the vestibular afferent electrical-activity. However, because all the postsynaptic activity was abolished with low calcium–high magnesium, it is not too surprising that the blockade of synaptic transmission abolished the SR. In order to demonstrate that mechanical noise modulates afferent activity via synaptic transmission we employed specific NMDA and non-NMDA (AMPA/ Kainate) antagonists instead of low calcium–high magnesium. Fig. 8 shows the effects of mechanical noise when the preparations (5 chickens at P5) were continuously perfused with MK-801+NBQX 10
6 M. Fig. 8A illustrates recordings of the extracellular multiunit activity of one chicken in control conditions and during the application of these antagonists. Note that in the case of the control conditions the mechanical ON produced and increase in the multiunit activity compared with ZN and HN. However, such relative increase in the multiunit activity for ON was abolished when the antagonists were applied in the perfusion. Fig. 8B shows the mean area of the SNR calculated from 5 chickens at P5 in control conditions. We performed the non-parametric Friedman’s ANOVA to examine statistical significance in the area of SNR, between the three conditions (ON, ZN and HN). In all groups we found significant differences (v2(2) = 8.4, p = 0.015), therefore, we performed the Wilcoxon signed-rank test between ZN and ON and between ON and HN. However, during the application of the antagonists MK-801+NBQX 10
6 M such significant differences were not observed (v2(2) = 1.2, p = 0.55) (Fig. 8C). Because previously it was demonstrated that the SR occurs in the hair cells (Jaramillo and Wiesenfeld, 1998), the results illustrated in Fig. 8 suggest that the SR observed in the postsynaptic element (i.e., the

vestibular afferent) is at least mediated by the synaptic transmission in specific NMDA and non-NMDA (AMPA/ Kainate) receptors. Furthermore, in order to explain in more detail this last point, about how and where the resonance is exactly generated, we developed a mathematical model of two compartments of the SR in the electrical activity of the hair cell and the primary vestibular afferent. This model will be useful to understand the underlying mechanisms in the SR that we observed in the primary vestibular afferents and how our study extends the experimental observations by Jaramillo and Wiesenfeld (1998).

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Computational model of inner hair cell and auditory nerve fiber

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To further explore the origins of SR at the auditory nerve fiber, we adapted and coupled a mathematical model of an IHC (Mountain and Cody, 1999) together with a model of the auditory nerve fiber (Deligeorges and Mountain, 1997; Singh and Mountain, 1997; Fig. 9A). For our simulations, we stimulated the IHC with mechanical displacements either with (ON) or without noise (ZN) at 1 Hz during 10 s and then calculated the SNR for both pre(Fig. 9B) and postsynaptic (Fig. 9C) elements. We took the SNR as the average of the peak of the 10 responses produced by the input stimulus divided by the average of 2 s of basal activity (see Methods; Fig. 9B, C). In Fig. 10 we illustrate the SNR plots as a function of the standard deviation of the input noise for a range of stimulation amplitudes. Both the ICH (Fig. 10A) and the auditory fiber (Fig. 10B) displayed SR when using small, un-saturating, input stimulation amplitudes combined with intermediate noise levels. Therefore, these results suggest that the SR may originate at the ICH and then propagates, synaptically, to the postsynaptic nerve fiber. Clearly, this observation does not exclude the possibility that the intrinsic properties of the postsynaptic element may also actively contribute to the SR observed at the nerve fiber.

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DISCUSSION

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To our knowledge, the present investigation documents the first explicit description of the occurrence of the SR phenomenon concerning the electrical activity of primary

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Fig. 7. The inverted U-like profile in the graphs of the area of SNR versus the input noise is abolished when the synaptic transmission is blocked. (A) Control, area of SNR versus the standard deviation (SD) of the input noise for three different animals. (B) The same as A but when low calcium-high magnesium was perfused. Please cite this article in press as: Flores A et al. Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development. Neuroscience (2016), http://dx.doi.org/10.1016/j.neuroscience.2016.02.051

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Fig. 8. Glutamatergic synaptic transmission of the posterior semicircular canal nerve is blocked with MK-801+NBQX. (A) Recordings from input signal and the corresponding extracellular multiunit activity of afferents from the posterior semicircular canal in the control condition and during perfusion of MK-801+NBQX 10
6 M. (B) Grand average of the area of SNR for three levels of noise in the control condition. (C) The same as B but when MK-801+NBQX were perfused.

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afferents of the chicken semicircular canal during development. Because the co-application of a cocktail of selective antagonists: MK-801 (NMDA receptor antagonist) and CNQX (AMPA/Kainate receptor antagonist) abolished the SR, we suggest that such SR is mediated by the glutamate synaptic transmission between hair cells and primary afferents in the chicken. We employed this mix of antagonists because in previous studies from our laboratory we demonstrated that under these experimental conditions the basal discharge of the chicken vestibular afferents can be abolished. Our present results obtained in the chicken vestibular system are consistent with the study by Indresano et al. (2003) made in the bullfrog sacculus. Both findings assumed that the SR observed in the primary afferents was first generated in the hair cells (the first stage of sensory encoding, as demonstrated by Jaramillo and Wiesenfeld (1998)), and then transmitted to the primary afferents. In fact, Jaramillo and Wiesenfeld (1998) showed that the physiological mechanism by which the SR occurs in isolated hair cells is by an enhancement in the mechanoelectrical transduction produced by an intermediate level of the noisy motion of the hair bundle.

Our numerical simulations in the model of hair cell – primary afferent are consistent with the experimental results obtained by Jaramillo and Wiesenfeld (1998). In our model we observed that the SR is first generated in the receptor potential of the hair cell and then transmitted to the primary afferent via synaptic mechanisms. In this context, our model provides clues of how and where the SR phenomenon occurs in our animal preparation. Our study establishes that the flow of rotational information that reaches the central vestibular system may be optimized by the addition of noise on the peripheral vestibular system, even during embryonic stages of development from E15 to E21 and at posthatching stage (P5). In this context, it is tempting to speculate that it may be possible to introduce mechanical noise artificially into the inner ear to improve their abilities to detect weak rotations of the head in the space. Our finding that the SR phenomenon occurs at embryonic stages of development, from E15 to E21 (see Fig. 6A, D), is consistent with the similar maturation reached at these stages in the semicircular canals (Bissonnette and Fekete, 1996). For example, Fig. 3 in

Please cite this article in press as: Flores A et al. Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development. Neuroscience (2016), http://dx.doi.org/10.1016/j.neuroscience.2016.02.051

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Fig. 9. Stochastic resonance in a hair cell- primary afferent model. (A) Scheme of the hair cell-primary afferent model. (B) Mechanical displacement either without (ZN; green traces) or with small (ON; red traces) or high noise (HN; blue traces) produces a membrane potential response in the IHC model. (C) The firing rate of the vestibular afferent is modulated by the depolarizations produced in the IHC. Note how for both pre- (B) and postsynaptic elements (C), the SNR plots reveal a range of input noise amplitudes at which SR is observed. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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the article by Bissonnette and Fekete (1996) clearly shows that the diameter of semicircular canals of chicken embryos at E15 and E17 is similar, thus suggesting that the physiological responses of sensory organs at such stages are also similar and functional. From E17 to E21 the semicircular canals are still functional as inferred from our Fig. 6D. This result is in line with the known fact that during hatching at day E21 the hatchlings can move their head and partly control their movements, showing a maturation of the vestibular organs. Furthermore, this result is consistent with previous results from our laboratory, showing that both the vestibular and auditory primary afferents exhibit spontaneous electrical activity during early stages of development (Cortes et al., 2013; Galicia et al., 2015; see also Galicia et al., 2013). It is not surprising that the vestibular system can be functional at embryonic stages of development given that the semicircular canals have been sensors of angular acceleration for 450 million years (Baker and Gilland, 1996). On the other hand, here it is important to mention that we chose the chicken as animal model for our experiments instead of mice or rats because it has largest semicircular duct dimensions (Muller, 1999) even at embryonic stages. The application of noise on the isolated vestibular system is not new. Previous studies showed that the application of rotational noisy acceleration modulates afferent activity from the isolated semicircular canal (O´Leary and Dunn, 1976). However, in such studies the SR phenomenon was not examined neither the

contribution of the synaptic transmission in the vestibular SR. On the other hand, in the field of the vestibular research in in vivo preparations there are many studies about the SR phenomenon produced by noisy Galvanic vestibular stimulation (which is a type of transcranial-electrical-stimulation). During such electrical stimulation the electrical current is delivered transcutaneously to the vestibular afferents through electrodes placed over the mastoid bones (Lund and Broberg, 1983; Fitzpatrick and Day, 2004). However, although this type of vestibular stimulation is effective to produce SR in the vestibular system it also produces effects in the autonomic function (Yamamoto et al., 2005), in visual memory (Wilkinson et al., 2008), in the voluntary movement (Smetanin et al., 1987; Se´verac Cauquil and Day, 1998), in the sensorimotor performance in novel vestibular environments (Moore et al., 2015). Such effects could be due to the activation of cranial nerves that are sending direct inputs to different regions in the brain. In fact there is evidence that noisy Galvanic vestibular stimulation of imperceptible intensity modulates the amplitude of EEG synchrony patterns (Kim et al., 2013), thus confirming the widespread targets in the brain of this type of vestibular stimulation (Lobel et al., 1998). Therefore, the noisy Galvanic vestibular stimulation is not a natural stimulus, thus activating several pathways which makes difficult to explore mechanisms of SR directly in the synapses between the hair cells and the primary afferents in the vestibular system. In this context,

Please cite this article in press as: Flores A et al. Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development. Neuroscience (2016), http://dx.doi.org/10.1016/j.neuroscience.2016.02.051

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Fig. 10. Pre- and postsynaptic SNR in a hair cell-primary model. We simulated the inner hair cell (IHC) model coupled to the auditory nerve fiber model in response to input mechanical stimuli delivered to the IHC consisting of sinusoids with increasing amplitude (from 1 to 10 nm). (A) Average SNR as a function of the standard deviation of the input noise for the IHC model. (B) Average SNR plots for the response properties, to IHC stimulations, of the auditory nerve fiber. SR is observed when combining un-saturating input amplitudes with small input noise. The range of all axes was adjusted to facilitate visualization of the SNR curves.

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our present research is important because it allowed to demonstrate that the SR phenomenon can occur at their first processing stage, in the peripheral vestibular system. We observed a higher SR in the mature chickens P5 than in the embryos E15–E21. It could be explained in part by the maturation stage of the mechanoelectrical transduction system of the hair cells in which the SR also occurs (Lindner et al., 2005) and it could be related to improvement in the peripheral synaptic transmission, increased myelination, etc., which also produces higher compound action potentials that increase as a function of age (Jones and Jones, 2000). It is interesting that although the higher SR was observed in hatchlings P5, we observed a clear and robust SR at earlier stages of development in embryos E15–E21. This last result is consistent with the finding that the fetal sheep in utero also exhibits vestibular caloric responses by cooling and heating of the middle ear with implanted cooper-tube heal exchangers (Abrams et al., 1998). Internally generated ‘‘random” neuronal activity in the central (and peripheral) nervous system of the behaving animal is probably not noise, in the sense of undesired activity masking the relevant activity, but is part of the

‘‘information” or it helps to improve the quality of the information generation or processing executed in a given structure (Segundo et al., 1994; Traynelis and Jaramillo, 1998; Moss et al., 2004). Hence, an important goal in Neuroscience has been the understanding of random fluctuations in the peripheral and central nervous system activity, their genesis in space and time, and their various roles. For this purpose, the study of the effect of noise in isolated preparations, as the employed here, is a powerful approach. In the present study we demonstrated the impact of mechanical noise on the synaptic transmission of the hair cell-primary afferent synapses of the vestibular system. The physiological effect of SR in sensory neurons (including the vestibular system) is the improvement of signal detection. For this reason, this phenomenon has been explored in diverse preparations of the peripheral and central nervous system, in mechanoreceptor cells of the crayfish (Douglass et al., 1993), cutaneous mechanoreceptors (Collins et al., 1996a,b; Richardson et al., 1998), in the cricket cercal sensory system (Levin and Miller, 1996), in isolated hair cells (Jaramillo and Wiesenfeld, 1998), in human hearing (Garver and Moss,

Please cite this article in press as: Flores A et al. Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development. Neuroscience (2016), http://dx.doi.org/10.1016/j.neuroscience.2016.02.051

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1995; Henry, 1999; Zeng et al., 2000), in the spinal somatosensory integration (Manjarrez et al., 2003), in human muscle spindles (Cordo et al., 1996), in the motor system (Martinez et al., 2007), in the sensorimotor system (Mendez-Balbuena et al., 2012; Trenado et al., 2014a,b) and in multisensory systems (Manjarrez et al., 2007; Lugo et al., 2008; Mendez-Balbuena et al., 2015). Moreover, it has been shown that the postural sway of both young and elderly subjects during quiet standing can be significantly reduced by applying mechanical noise to the feet via vibrating insoles (Priplata et al., 2002, 2006). In the same context, stochastic galvanic vestibular stimulation has been employed to improve balance in humans (Mulavara et al., 2011; Samoudi et al., 2015; Goel et al., 2015) and to improve stability during locomotion in rats (Samoudi et al., 2012) and humans (Mulavara et al., 2015). The semicircular canals are part of the peripheral vestibular system and serve as an organ of balance, contributing in the postural and visual stabilization during motion in a three-dimensional environment. Sensory cells in these canals are located in the crista and are sensitive to angular accelerations of the head. Each canal is filled with a fluid called endolymph. In this context, we show that the afferent multiunit activity of the posterior semicircular canal nerve, evoked by mechanical stimuli, was increased when appropriate amounts of noise were added. We conclude that information transmission in semicircular canal afferents of the chicken vestibular system are enhanced by optimal noise via the SR phenomenon.

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Acknowledgments—This work was partly supported by the following grants: J28904-N (A.F); Fondo Ricardo J. Zevada (A.F); CONACYT 251406 y 220862 (M.T), CONACyT Fronteras de la Ciencia 536 (E.M) and CONACyT 229866 (E.M), and VIEPPIFI-FOMES-PROMEP-BUAP-Puebla (E.M), Me´xico. FOMESBUAP and VIEP-BUAP 174101 and Ca´tedra Marcos Moshinsky (E.M), Me´xico.

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(Accepted 22 February 2016) (Available online xxxx)

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