The inner-ear labyrinth is filled with two lymphatic fluids, the perilymph and endolymph. An electrochemical potential difference between the two lymphatic fluids drives hair-cell mechano-transduction (Fettiplace and Kim, 2014). Although the inner-ear fluid system is connected to the cerebrospinal fluid of the brain through the cochlear and vestibular aqueducts and to the vascular system across the blood–labyrinth barrier, inner-ear fluid is virtually isolated from other body-fluid systems (Salt et al., 1986; Ohyama et al., 1988). Consequently, intervening in hearing health by delivering substances to the inner-ear fluid through the systemic circulation is challenging. The maintenance of inner-ear fluid composition is achieved locally by the secretion and absorption of ions and molecules through inner-ear epithelial cells (Wangemann and Marcus, 2017). As inner-ear fluid homeostasis is maintained locally, longitudinal electro-chemical gradients, including the endocochlear potential, may vary along the cochlear length (Schulte and Schmiedt, 1992; Sadanaga and Morimitsu, 1995; Hirose and Liberman, 2003).

The inner-ear fluid has been reported to be stationary, unlike other lymphatic fluids in the body (Salt and Hirose, 2018a). Thus, it is considered that substance transport in the inner-ear fluid is governed by diffusion (Salt and Plontke, 2005). Diffusion is an effective mechanism for a substance to travel along sub-micrometer distances (Berg, 1993). For instance, considering the diffusion speed of small molecules in water, it takes microseconds for neurotransmitters to diffuse across a 20 nm synaptic gap. In contrast, diffusion is inefficient for travel on the centimeter scale. It takes days for a drug applied at the round window to travel 30 mm to the apical end of the human cochlea. In practice, the substance would not reach the apex because it would be resorbed before traveling this distance. Studies on inner-ear drug delivery confirm this principle of physics: longitudinal mass transport along the inner-ear labyrinth is challenging (Salt et al., 2016; Lukashkin et al., 2020).

The two membranous openings of the inner ear, the oval and round windows, are sites for noninvasive local delivery of substances into the inner ear. Intratympanic injections of antibiotics and anti-inflammatory drugs have been attempted to manage inner-ear disorders despite limited efficacy (Lavigne et al., 2016; Salt and Plontke, 2018b). Releasing a substance at the end of a long, closed tube forms a steep gradient of concentration. Consequently, the substance does not reach distant regions (Salt and Hirose, 2018a), whereas, in the vicinity of drug release, the concentration is much higher than desired. One remedy is to inject fluid by making two perforations in the inner ear—one for intruding and the other for extruding (Borkholder et al., 2014; Tandon et al., 2016; Talaei et al., 2019). Such an invasive approach is often associated with the injection of a substantial fluid volume, larger than the entire perilymph in the inner ear (Szeto et al., 2020).

The tube-shaped organ of Corti (OoC) is lined with motile outer hair cells that are activated systematically with a large phase velocity (greater than a few m/s) toward the apex (Olson et al., 2012). A previous study suggests that outer-hair-cell motility can cause oscillatory fluid motion along the triangular fluid channel within the OoC (Karavitaki and Mountain, 2007). Recent measurements of OoC vibrations provide a possible explanation for how this longitudinal fluid flow is generated: outer hair cells operate like an area motor by deforming the OoC cross-sectional area (Jabeen et al., 2020; Guinan, 2022; Lin et al., 2024). Outer hair cells boost the OoC vibrations over the entire span of the traveling waves (Lee et al., 2016; Cooper et al., 2018; He et al., 2018; Fallah et al., 2019). In theory, peristaltic deformation of the OoC could induce non-oscillatory streaming along the tunnel of Corti (Shokrian et al., 2020). This peristaltic motion of the OoC has not been explored experimentally.

We hypothesized that outer hair cells agitated by sounds could induce advection of the cochlear fluids. To test this hypothesis, the transport of a neurotoxin along the scala tympani was measured. Kainic acid irreversibly damages afferent synapses with inner hair cells (Sun et al., 2001). Importantly, kainic acid does not affect the hair cells, unlike other popular substances used for inner-ear drug-delivery experiments, such as streptomycin and salicylate (Salt et al., 2016; Lukashkin et al., 2020). Kainic acid (10 mM) was administered at the round-window niche in young gerbils. Multichannel electrodes were inserted into the anteroventral cochlear nucleus (AVCN) to monitor drug effect along the tonotopic axis. The relation between the drug’s effect time and location was obtained while controlling sound and activity of outer hair cells, two factors that have not been considered in previous drug-delivery studies. To provide theoretical support for experimental observations, computer models were used to simulate inner-ear drug delivery in three steps: the virtual cochlea simulated OoC vibrations due to sound (Zhou and Nam, 2019) the Navier–Stokes equation including a nonlinear convective term was solved to obtain the drift of the Corti and scala fluids (Shokrian et al., 2020) and the diffusion-advection equation was solved to simulate the spatiotemporal change of kainic acid concentration in the cochlear fluids.

Outer-hair-cell motility and sound properties, such as frequency, level, and bandwidth, were the parameters that we hypothesized to affect drug delivery. Testing these quantities and their combinations requires an extensive series of experiments. In this study, we present a control case and four test cases to focus on two major questions: whether sounds and outer-hair-cell motility affect inner-ear drug delivery. The control experiment was the drug delivery in near silence (‘Silence’). The test cases included (1) broadband sounds (0.1–12 kHz, 60 or 75 dB sound pressure level [SPL]) presented during drug delivery (‘Sound’), (2) the same broadband sounds presented, but with salicylic acid administered before kainic acid application (‘post-SA’), or an 80 dB SPL pure-tone at either (3) 0.5 kHz (‘LF-tone’), or (4) 3–6 kHz (‘MF-tone’).

Sounds affect inner-ear drug delivery

Before applying 10 mM kainic acid to the intact round window, the characteristic frequencies (CFs) of probing locations were identified (Figure 1A and D). Distortion product otoacoustic emissions (DPOAEs) were measured before and after drug delivery to confirm no change in outer-hair-cell motility during the experiment (Figure 1C and F). When pre- and post-delivery DPOAEs changed more than 5 dB at any frequency between 0.1 and 10 kHz, the results were excluded (four animals). In one set of experiments, over 90% of stimulus intervals were kept silent (approximately 55 s per minute, Figure 1A–C). In the other experiments, broadband sounds at a modest level (0.1–12 kHz, 60–75 dB SPL) were played during over 90% of the stimulus intervals (Figure 1D–F). Approximately 8% of time (4.6 s per minute) were used to acquire background neural activity and to measure responses to 30–40 dB SPL probe tones at three CFs. Under our experimental condition (4 µL of 10 mM kainic acid applied at the intact round window), neural responses were abolished after a few to several hundred minutes (Figure 1B and E). The effect time was defined as the latency following exposure at which the neural response dropped below 75% of its baseline value (t_E, Figure 1B). The drug effect was tonotopic, with higher CF locations being affected earlier (Figure 1G). In Figure 1H, the sound- and the silence-case response curves from similar CF locations (between 4.5 and 6.5 kHz) were averaged for comparison. Figure 1I presents the drug delivery data as the effect time (t_E) versus CF location. We acquired 34 data points from 13 gerbils for the sound protocol and 48 data points from 18 animals for the silence protocol. The trend line (broken curve) was obtained by fitting a curve to the silence-case data points with the 1D diffusion equation (Berg, 1993).

Figure 1

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To compare the effect times of the sound and silence cases despite varying delivery distances, the effect time was normalized by the trend values at respective CF locations and represented in dB (t_E in dB = 20log₁₀(t_E/t_Trend), Figure 1J). Average t_E over the entire CF range was significantly faster for the sound protocol than for the silent case (p=0.0045). Subsequent analyses of low- (<4.5 kHz) and mid-frequency (>4.5 kHz) regions further showed that broadband sound exposure increased the speed of drug delivery in the mid-CF region (>4.5 kHz, p<0.001) but not the low-CF region (<4.5 kHz, = 0.55; Figure 1K).

Outer-hair-cell motility was required for the sound effect

Motile outer hair cells boost cochlear responses to sounds. If the sound effect on cochlear drug delivery depends on fluid agitation from outer-hair-cell motility, inhibiting the motility should produce effect times similar to the silent condition. To test this hypothesis, before delivering kainic acid, salicylic acid was administered intraperitoneally (200 mg/kg) to inhibit outer-hair-cell motility (Figure 2A). DPOAEs were recorded before and after the salicylic acid application to confirm its effect (Figure 2B and E). After salicylate injection, neural responses decayed for 20–30 min to reach a steady state (Figure 2C and F). Because the salicylate effect raised the hearing threshold, the probe-tone level was increased by 15–20 dB prior to kainic acid application (typically from 30 to 50 dB SPL; the discontinuity in the response curve near 70 min was due to this increase in the probe tone level). The red-dashed vertical lines of Figure 2C and F indicate the timing of kainic acid application. Figure 2D and G present only the kainic acid application responses (the time span after the dashed vertical lines in panels B and E). Note that 75 dB SPL broadband sounds were played in the post-SA protocol. The two examples in Figure 2B–G also demonstrate the variance of the salicylate effect. In one case, DPOAEs decreased by <10 dB (re: 40 dB stimulation) and the neural responses to 30 dB SPL sound decreased by 40% (Figure 2C). In the other case, DPOAEs decreased by approximately 20 dB, and the neural responses to 30 dB SPL sound decreased to the noise floor (Figure 2F). For the post-SA protocol, we acquired 24 data points from eight animals. The post-kainate response decay of salicylate-treated ears followed the trend of the silence case despite use of the sound protocol (Figure 2H). Despite the sound stimulation, the effect time of the post-SA case was not different from the silence case (p=0.096) and was greater than the sound case (p<0.001, Figure 2J). Like the silence versus sound protocols comparison, the statistical difference was from the mid-CF locations, not from low-CF locations (Figure 2J). The post-SA results support the hypothesis that outer-hair-cell motility is required for faster inner-ear drug delivery with sound exposure.

Figure 2

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Low-frequency tones were more effective

If the sound effect on cochlear drug delivery were due to fluid agitation, other sounds might be more effective than random noise. Vibrations along the cochlear partition propagate with decaying phase velocity toward the apex, before stalling shortly after reaching the sound’s CF location. The advective flow of the cochlear fluid is shaped by the vibration frequency and amplitude and by the phase velocity of traveling waves (Lighthill, 1992; Shokrian et al., 2020). To test the hypothesis that the type of sound stimulus impacts the effectiveness of drug delivery, especially in low-frequency regions, pure-tones at 80 dB SPL were played during inner-ear drug delivery, instead of broadband noise. In choosing the frequency of the pure tone, we considered the nature of cochlear traveling waves, guided by fluid-dynamics simulations (Zhou and Nam, 2019; Shokrian et al., 2020). The frequency of 0.5 kHz was chosen close to the low bound of the gerbil’s audible frequency range. The mid-frequency was selected from between 3 and 6 kHz to match the CF location of one of the electrode probes. High frequencies were not tested because they would not affect drug delivery to the apex of the cochlea (i.e., the traveling waves stop near the CF location.) If the sound facilitation were most prominent near the peak of traveling waves, the low-frequency tone would be inefficient in facilitating drug delivery to high- to mid-CF locations. Whereas, if the phase velocity were crucial for fluid agitation, the low-frequency sound should be advantageous because of its long tail region with high phase velocity. If the traveling wave pattern set the cochlear fluid flow, the sound-facilitation effect could stall at one location, similar to the traveling waves.

With the pure-tone protocol, 45 data points were acquired from 15 gerbils. In two example cases, the effect time at low-CF locations (CFs near 2 kHz) was 15 min for the case of the 0.5 kHz tone (Figure 3A) and 100 min for the 3.5 kHz tone (Figure 3B). In the mid-CF locations, the effect time did not differ for different tone frequencies: the effect time ranged between 8 and 12 min for CF locations between 5.9 and 6.3 kHz (red curves of Figure 3A and B). In some cases, especially toward the low-CF locations, the response curve had bimodal decay patterns (e.g., the cyan curve in Figure 3B), resulting in a broader distribution in the effect time. The overall plots of effect time versus location (Figure 3C and D) show that most data points are below the trend line of the control (silence) case. That is, the pure-tone stimulation facilitated the delivery throughout the cochlea. According to the statistical analysis of effect time differences between the silence and the pure-tone protocols (Figure 3E), low-frequency tones facilitated the drug delivery for both low- (p<0.001) and mid-CF locations (p=0.011). Mid-frequency tones facilitated for mid-CF locations (p<0.001) but not significantly for low-CF locations (p=0.084). Low-frequency tones were more effective than broadband noise especially at the apical low-CF locations (Figure 3F, p<0.0005 for all CF locations, p<0.00001 for apical locations with CF <4.5 kHz).

Figure 3

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Figure 4 summarizes our findings for all four cases–control (delivery in silence, Figure 4A and B), sound (broadband noise at 60 or 75 dB SPL, Figure 4C and D), post-SA sound (SA applied intraperitoneally [IP] or to the round window 30–40 min before kainic acid application, broadband noise at 75 dB SPL, Figure 4E and F), and pure-tone sound (either 0.5 kHz or 3–6 kHz at 80 dB SPL, Figure 4G and H). The broken trend lines shown in all panels are the same, obtained by a curve fit to the control (silence) data using the 1D diffusion equation. Broadband sounds decreased the effect time in the mid-CF locations (CF > 4.5 kHz) but had little effect in the low-CF locations (CF < 4.5 kHz, Figure 4C and D). While measurements at two levels (60 and 75 dB SPL) were pooled in Figure 1, they are distinguished in Figure 4C and D. Although the mean effect time of the 75 dB SPL data was smaller than for 60 dB SPL in the mid-CF region, supporting the sound-facilitation hypothesis, a larger sample number will be required to confirm the effect of sound level. The sound effect disappeared after inhibiting outer-hair-cell motility with salicylate (Figure 4E and F). In Figure 2, only IP-administered data of the post-SA case are presented. Figure 4E and F include additional data on the local (round window) application of salicylate before applying a solution containing 10 mM kainic acid and 100 mM salicylic acid. While the local delivery case reduced the mean effect time in the mid-CF region, the effect times of both post-SA cases were not significantly different from the control case. For the mid-CF region, the difference in mean effect time between the two post-SA cases was ascribed to the incomplete inhibition of outer hair cells in the local delivery case. The most prominent effect was observed when the drug was delivered while playing a low-frequency tone. For instance, 17 out of 18 effect times for the LF-tone case (red square symbols, Figure 4G and H) were below the trend line of the control (silence) case.

Figure 4

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The mechanism of sound facilitation for drug delivery was investigated with computer model simulations. Our computer model is distinguished from most cochlear mechanics models in three aspects. First, it incorporates the interactions between the Corti fluid and OoC structures. Second, the nonlinear advection term in the Navier–Stokes equation was not neglected. Finally, both diffusion and fluid advection were considered. Our simulated results support the hypothesis that the cross-sectional area change of the OoC performs like a peristaltic pump (i.e., active outer hair cells are the fluid pumps) (Shokrian et al., 2020). Figure 5 shows half of the cochlear fluid space—the scala tympani and the OoC fluid spaces (omitting the scala media and scala vestibuli). We simulated two cases: in the silence case, the drug delivery was purely governed by diffusion (Figure 5A). In the LF-tone case, both diffusive and advective mass transports contributed (Figure 5B–D). For the LF-tone case, a 1 kHz tone at 80 dB SPL sound was played continuously. The contours in Figure 5A and B represent the concentration of the substance at 30 min after the onset of delivery. As expected from Fick’s law and the log-scale plots of Figure 4, the gradient over distance decays logarithmically. That is, contour lines in Figure 5A have similar spacings in the log scale. However, such a logarithmic gradient was apparently disturbed between the 0.1 and 0.01 mM contour lines in Figure 5B. The contour line is stretched toward the right (red double-headed arrow) in the top Corti fluid layer and to the left (blue arrow) in the bottom scala fluid layer. This stretched contour line was due to the advective flow. In Figure 5C and D, the contour lines represent the streamlines (i.e., particles would drift along the contour lines). The red and blue colors indicate clockwise and counterclockwise circulation, respectively. Figure 5D presents the fluid streaming near the peak of the traveling wave (6–9.5 mm from the base, Corti fluid and top 120-µm-thick scala fluid). The maximum streaming velocity is as substantial as a few mm/s. Our simulation shows that active outer hair cells generate a strong stream toward the apex along the tunnel of Corti. The displaced fluid in the apex flows toward the base along the bottom of the scala tympani. The strong advection takes place in the tail of the traveling wave, over a few mm.

Figure 5

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We showed that sound exposure increases drug delivery from the round window to apical cochlear locations. Sound-facilitated drug delivery was compromised when outer-hair-cell motility was inhibited. Low-frequency tones were more effective than broadband noise in delivering substances to the apex of the cochlea. These results not only highlight new strategies for improving drug delivery throughout the cochlear spiral, but reveal a new function of outer hair cells, beyond sound amplification.

Neural responses near CF are amplified, showing enhanced tuning. In contrast, outer hair cells boost the vibrations in the OoC non-selectively (Cooper et al., 2018; He et al., 2018; Fallah et al., 2019). To reconcile the nonselective input (untuned OoC vibrations) and the selective output (tuned neural signals), previous studies suggest that outer hair cells accumulate their power along cochlear traveling waves, referred to as global amplification (Zagadou and Mountain, 2012; He et al., 2022). However, experimental evidence is incongruent with the global amplification theory (Fisher et al., 2012; Versteegh and van der Heijden, 2013; Dewey et al., 2019). According to the two-tone suppression experiment of Dewey et al., 2019, the suppression of outer hair cells far basal from the CF location does not affect the response at the CF location. Available evidence shows that the amplification due to outer-hair-cell action occurs between a location one half-octave basal to the peak and the peak location (Dong and Olson, 2013; Fallah et al., 2019). The present study provides new insights into the nonselective outer hair cell action.

Broadband action of outer hair cells helps cochlear-fluid circulation. Our pure-tone experiments (Figure 3) and simulation (Figure 5) show that the region of sound-facilitated drug delivery spanned regions far basal to the CF location of a given sound frequency. Such sound facilitation disappeared when outer-hair-cell motility was suppressed (Figure 2), which implied that active outer hair cells are the stirrers in the cochlea that drive lymphatic-fluid circulation. From an evolutionary perspective, mammals stretched their hearing organ to encode broader bandwidth with good frequency resolution. The longer cochlea might have entailed a challenge: maintaining the freshness of the stationary lymph along a long and narrow tube is nontrivial. For instance, a local failure in homeostasis could cascade along the cochlea, making the system vulnerable to disturbance or trauma. The OoC in the basal cochlea suffers from a maintenance burden: a greater influx of potassium (greater MET current) and a smaller clearance surface. We hypothesize that the longitudinal circulation of lymphatic fluid serves as a protective mechanism for the fluid homeostasis of the mammalian cochlea. One potential implication is that an acoustically rich environment could be beneficial in maintaining healthy hearing as well as recovering from damaged hearing.

Our study complements existing studies regarding cochlear fluid homeostasis and differs from previous studies in several ways. The intrastrial fluids (extracellular fluids in the stria vascularis) have been more thoroughly investigated because the three layers in the stria vascularis (marginal, intermediate, and basal cells) maintain the endocochlear potential (Wangemann, 2006). Equilibrium in the Corti fluid has been sparsely investigated because its electrochemical gradient is modest compared to that of the intrastrial fluids (Johnstone et al., 1989; Zidanic and Brownell, 1990). Local electrochemical balance in the cochlear fluids has been considered within a radial section (Quraishi and Raphael, 2008; Patuzzi, 2011; Nin et al., 2012). Our study is focused on the longitudinal (global) equilibrium along the cochlear coil and did not consider the equilibrium across the stria vascularis cell layers. To examine whether the longitudinal fluid flow driven by outer hair cells is strong enough to affect cochlear fluid homeostasis, future studies should measure the K⁺ equilibrium and recycling along the length of the Corti fluid under sound and silence conditions.

The nature of the streaming pattern supports the feasibility of targeted inner-ear drug delivery. Two characteristics implicated in the pure-tone experiments (Figure 3) became apparent in the model simulations (Figure 5): the advection caused by active outer hair cells created a ‘fast track’ and a ‘stalling point’ for mass transport. For instance, the span between locations 5.5 and 9 mm is the fast track of mass transport (the arrows of concentration contours in Figure 5B and the clockwise advective flow in Figure 5C). In this fast track, the distance between contour lines is much larger than the other regions or the pure diffusion case. The contour line in the fast track (black curve, Figure 5B) is stretched toward the apex in and near the Corti fluid and toward the base at the bottom of the scala tympani, indicating longitudinal fluid circulation. In contrast to the fast-track region, there was a stalling point where the transport stopped. The stacking contours near 10 mm in Figure 5B are caused by the countering circulation loops at 9 mm in Figure 5C. Taking advantage of these ‘fast tracks’ and ‘stalling points’, one could design a sequence of sounds to deliver a substance from the round window to a targeted location in the cochlea.

Further work is needed before our findings can be used to address practical problems. Although we showed that low-frequency tone is superior to a high-frequency tone or a broadband sound in facilitating inner-ear drug delivery, we have not identified the optimal delivery scheme. While the gerbil cochlea is a better model to study longitudinal mass transport compared to the shorter mouse cochlea (12 mm versus 6 mm), substantial extrapolation is inevitable to predict drug delivery in the 34-mm-long human cochlea out of the present results. Extensive experiments would be needed to examine different SPLs at different frequencies and their combinations in a longer cochlea. Guidance from reliable theoretical models will help to design more efficient experiments and to interpret measured data more rigorously. Our present computer model incorporated the nonlinearity in advection-diffusion dynamics but did not implement the compressive nonlinearity of the sensitive cochlea. To analyze cochlear mass transport under stimulation by complex sounds, a model must address a long list of physical and physiological problems: deformable OoC, Corti fluid dynamics, nonlinear hair cell mechano-transduction, outer-hair-cell motility, permeable basilar membrane, nonlinear fluid dynamics including advection, diffusion solved simultaneously with advection, and the electrochemical equilibrium across the OoC. Our present model includes the essential components of these, but some are extensively simplified (e.g., outer-hair-cell motility, basilar membrane permeability), and some are absent (e.g., hair-cell nonlinearity, electrochemical equilibrium). Fortunately, there are other theoretical models that represent these aspects of cochlear physics and physiology that are lacking in our present study.

The data and the analysis codes used in this study are available at https://doi.org/10.6084/m9.figshare.27681999. The source codes to simulate Figure 5 are available at https://doi.org/10.6084/m9.figshare.27682281.

1. 1. Lee C
   2. Shokrian M
   3. Henry KS
   4. Carney LH
   5. Holt JC
   6. Nam J-H

   (2024) figshare

   Data and analysis codes (Lee, Shokrian, et al. 2024 eLife).

   https://doi.org/10.6084/m9.figshare.27681999
2. 1. Lee C
   2. Shokrian M
   3. Henry KS
   4. Carney LH
   5. Holt JC
   6. Nam J-H

   (2024) figshare

   Source codes for Figure 5 (Lee, Shokrian, et al. 2024 eLife).

   https://doi.org/10.6084/m9.figshare.27682281

1. Book

   1. Berg HC

   (1993)

   Random Walks in Biology

   Princeton: N.J., Princeton University Press.

   • Google Scholar
2. 1. Borkholder DA
   2. Zhu X
   3. Frisina RD

   (2014) Round window membrane intracochlear drug delivery enhanced by induced advection

   Journal of Controlled Release 174:171–176.

   https://doi.org/10.1016/j.jconrel.2013.11.021

   • PubMed
   • Google Scholar
3. 1. Choi JH
   2. Jung HK
   3. Kim T

   (2006) A new action potential detector using the MTEO and its effects on spike sorting systems at low signal-to-noise ratios

   IEEE Transactions on Bio-Medical Engineering 53:738–746.

   https://doi.org/10.1109/TBME.2006.870239

   • PubMed
   • Google Scholar
4. 1. Cooper NP
   2. Vavakou A
   3. van der Heijden M

   (2018) Vibration hotspots reveal longitudinal funneling of sound-evoked motion in the mammalian cochlea

   Nature Communications 9:3054.

   https://doi.org/10.1038/s41467-018-05483-z

   • PubMed
   • Google Scholar
5. 1. Dewey JB
   2. Applegate BE
   3. Oghalai JS

   (2019) Amplification and suppression of traveling waves along the mouse organ of corti: evidence for spatial variation in the longitudinal coupling of outer hair cell-generated forces

   The Journal of Neuroscience 39:1805–1816.

   https://doi.org/10.1523/JNEUROSCI.2608-18.2019

   • PubMed
   • Google Scholar
6. 1. Dong W
   2. Olson ES

   (2013) Detection of cochlear amplification and its activation

   Biophysical Journal 105:1067–1078.

   https://doi.org/10.1016/j.bpj.2013.06.049

   • PubMed
   • Google Scholar
7. 1. Fallah E
   2. Strimbu CE
   3. Olson ES

   (2019) Nonlinearity and amplification in cochlear responses to single and multi-tone stimuli

   Hearing Research 377:271–281.

   https://doi.org/10.1016/j.heares.2019.04.001

   • PubMed
   • Google Scholar
8. 1. Fettiplace R
   2. Kim KX

   (2014) The physiology of mechanoelectrical transduction channels in hearing

   Physiological Reviews 94:951–986.

   https://doi.org/10.1152/physrev.00038.2013

   • PubMed
   • Google Scholar
9. 1. Fisher JAN
   2. Nin F
   3. Reichenbach T
   4. Uthaiah RC
   5. Hudspeth AJ

   (2012) The spatial pattern of cochlear amplification

   Neuron 76:989–997.

   https://doi.org/10.1016/j.neuron.2012.09.031

   • PubMed
   • Google Scholar
10. 1. Frisina RD
    2. Chamberlain SC
    3. Brachman ML
    4. Smith RL

    (1982) Anatomy and physiology of the gerbil cochlear nucleus: an improved surgical approach for microelectrode studies

    Hearing Research 6:259–275.

    https://doi.org/10.1016/0378-5955(82)90059-4

    • PubMed
    • Google Scholar
11. 1. Guinan JJ

    (2022) Cochlear amplification in the short-wave region by outer hair cells changing organ-of-Corti area to amplify the fluid traveling wave

    Hearing Research 426:108641.

    https://doi.org/10.1016/j.heares.2022.108641

    • Google Scholar
12. 1. He W
    2. Kemp D
    3. Ren T

    (2018) Timing of the reticular lamina and basilar membrane vibration in living gerbil cochleae

    eLife 7:e37625.

    https://doi.org/10.7554/eLife.37625

    • PubMed
    • Google Scholar
13. 1. He W
    2. Burwood G
    3. Porsov EV
    4. Fridberger A
    5. Nuttall AL
    6. Ren T

    (2022) The reticular lamina and basilar membrane vibrations in the transverse direction in the basal turn of the living gerbil cochlea

    Scientific Reports 12:19810.

    https://doi.org/10.1038/s41598-022-24394-0

    • PubMed
    • Google Scholar
14. 1. Hirose K
    2. Liberman MC

    (2003) Lateral wall histopathology and endocochlear potential in the noise-damaged mouse cochlea

    Journal of the Association for Research in Otolaryngology 4:339–352.

    https://doi.org/10.1007/s10162-002-3036-4

    • PubMed
    • Google Scholar
15. 1. Jabeen T
    2. Holt JC
    3. Becker JR
    4. Nam JH

    (2020) Interactions between passive and active vibrations in the organ of corti in vitro

    Biophysical Journal 119:314–325.

    https://doi.org/10.1016/j.bpj.2020.06.011

    • PubMed
    • Google Scholar
16. 1. Johnstone BM
    2. Patuzzi R
    3. Syka J
    4. Syková E

    (1989) Stimulus-related potassium changes in the organ of Corti of guinea-pig

    The Journal of Physiology 408:77–92.

    https://doi.org/10.1113/jphysiol.1989.sp017448

    • PubMed
    • Google Scholar
17. 1. Karavitaki KD
    2. Mountain DC

    (2007) Evidence for outer hair cell driven oscillatory fluid flow in the tunnel of corti

    Biophysical Journal 92:3284–3293.

    https://doi.org/10.1529/biophysj.106.084087

    • PubMed
    • Google Scholar
18. 1. Lavigne P
    2. Lavigne F
    3. Saliba I

    (2016) Intratympanic corticosteroids injections: a systematic review of literature

    European Archives of Oto-Rhino-Laryngology 273:2271–2278.

    https://doi.org/10.1007/s00405-015-3689-3

    • PubMed
    • Google Scholar
19. 1. Lee HY
    2. Raphael PD
    3. Xia A
    4. Kim J
    5. Grillet N
    6. Applegate BE
    7. Ellerbee Bowden AK
    8. Oghalai JS

    (2016) Two-dimensional cochlear micromechanics measured in vivo demonstrate radial tuning within the mouse organ of corti

    The Journal of Neuroscience 36:8160–8173.

    https://doi.org/10.1523/JNEUROSCI.1157-16.2016

    • PubMed
    • Google Scholar
20. 1. Lighthill J

    (1992) Acoustic streaming in the ear itself

    Journal of Fluid Mechanics 239:551.

    https://doi.org/10.1017/S0022112092004531

    • Google Scholar
21. 1. Lin WC
    2. Macić A
    3. Becker J
    4. Nam JH

    (2024) Asymmetric vibrations in the organ of Corti by outer hair cells measured from excised gerbil cochlea

    Communications Biology 7:600.

    https://doi.org/10.1038/s42003-024-06293-4

    • PubMed
    • Google Scholar
22. 1. Liu Y
    2. Gracewski SM
    3. Nam JH

    (2017) Two passive mechanical conditions modulate power generation by the outer hair cells

    PLOS Computational Biology 13:e1005701.

    https://doi.org/10.1371/journal.pcbi.1005701

    • PubMed
    • Google Scholar
23. 1. Long GR
    2. Talmadge CL
    3. Lee J

    (2008) Measuring distortion product otoacoustic emissions using continuously sweeping primaries

    The Journal of the Acoustical Society of America 124:1613–1626.

    https://doi.org/10.1121/1.2949505

    • PubMed
    • Google Scholar
24. 1. Lukashkin AN
    2. Sadreev II
    3. Zakharova N
    4. Russell IJ
    5. Yarin YM

    (2020) Local drug delivery to the entire cochlea without breaching its boundaries

    iScience 23:e100945.

    https://doi.org/10.1016/j.isci.2020.100945

    • PubMed
    • Google Scholar
25. 1. Marnell D
    2. Jabeen T
    3. Nam JH

    (2018) Hydrostatic measurement and finite element simulation of the compliance of the organ of Corti complex

    The Journal of the Acoustical Society of America 143:735.

    https://doi.org/10.1121/1.5023206

    • PubMed
    • Google Scholar
26. 1. Nam JH
    2. Fettiplace R

    (2010) Force transmission in the organ of Corti micromachine

    Biophysical Journal 98:2813–2821.

    https://doi.org/10.1016/j.bpj.2010.03.052

    • PubMed
    • Google Scholar
27. 1. Nam JH
    2. Fettiplace R

    (2012) Optimal electrical properties of outer hair cells ensure cochlear amplification

    PLOS ONE 7:e50572.

    https://doi.org/10.1371/journal.pone.0050572

    • PubMed
    • Google Scholar
28. 1. Nam JH

    (2014) Microstructures in the organ of Corti help outer hair cells form traveling waves along the cochlear coil

    Biophysical Journal 106:2426–2433.

    https://doi.org/10.1016/j.bpj.2014.04.018

    • PubMed
    • Google Scholar
29. 1. Nin F
    2. Hibino H
    3. Murakami S
    4. Suzuki T
    5. Hisa Y
    6. Kurachi Y

    (2012) Computational model of a circulation current that controls electrochemical properties in the mammalian cochlea

    PNAS 109:9191–9196.

    https://doi.org/10.1073/pnas.1120067109

    • PubMed
    • Google Scholar
30. 1. Ohyama K
    2. Salt AN
    3. Thalmann R

    (1988) Volume flow rate of perilymph in the guinea-pig cochlea

    Hearing Research 35:119–129.

    https://doi.org/10.1016/0378-5955(88)90111-6

    • PubMed
    • Google Scholar
31. 1. Olson ES
    2. Duifhuis H
    3. Steele CR

    (2012) Von Békésy and cochlear mechanics

    Hearing Research 293:31–43.

    https://doi.org/10.1016/j.heares.2012.04.017

    • PubMed
    • Google Scholar
32. 1. Patuzzi R

    (2011) Ion flow in stria vascularis and the production and regulation of cochlear endolymph and the endolymphatic potential

    Hearing Research 277:4–19.

    https://doi.org/10.1016/j.heares.2011.01.010

    • PubMed
    • Google Scholar
33. 1. Prodanovic S
    2. Gracewski SM
    3. Nam JH

    (2019) Power dissipation in the cochlea can enhance frequency selectivity

    Biophysical Journal 116:1362–1375.

    https://doi.org/10.1016/j.bpj.2019.02.022

    • PubMed
    • Google Scholar
34. 1. Quraishi IH
    2. Raphael RM

    (2008) Generation of the endocochlear potential: a biophysical model

    Biophysical Journal 94:L64–L6.

    https://doi.org/10.1529/biophysj.107.128082

    • PubMed
    • Google Scholar
35. 1. Sadanaga M
    2. Morimitsu T

    (1995) Development of endocochlear potential and its negative component in mouse cochlea

    Hearing Research 89:155–161.

    https://doi.org/10.1016/0378-5955(95)00133-x

    • PubMed
    • Google Scholar
36. 1. Salt AN
    2. Thalmann R
    3. Marcus DC
    4. Bohne BA

    (1986) Direct measurement of longitudinal endolymph flow rate in the guinea pig cochlea

    Hearing Research 23:141–151.

    https://doi.org/10.1016/0378-5955(86)90011-0

    • PubMed
    • Google Scholar
37. 1. Salt AN
    2. Plontke SKR

    (2005) Local inner-ear drug delivery and pharmacokinetics

    Drug Discovery Today 10:1299–1306.

    https://doi.org/10.1016/S1359-6446(05)03574-9

    • PubMed
    • Google Scholar
38. 1. Salt AN
    2. Hartsock JJ
    3. Gill RM
    4. King E
    5. Kraus FB
    6. Plontke SK

    (2016) Perilymph pharmacokinetics of locally-applied gentamicin in the guinea pig

    Hearing Research 342:101–111.

    https://doi.org/10.1016/j.heares.2016.10.003

    • PubMed
    • Google Scholar
39. 1. Salt AN
    2. Hirose K

    (2018a) Communication pathways to and from the inner ear and their contributions to drug delivery

    Hearing Research 362:25–37.

    https://doi.org/10.1016/j.heares.2017.12.010

    • PubMed
    • Google Scholar
40. 1. Salt AN
    2. Plontke SK

    (2018b) Pharmacokinetic principles in the inner ear: influence of drug properties on intratympanic applications

    Hearing Research 368:28–40.

    https://doi.org/10.1016/j.heares.2018.03.002

    • PubMed
    • Google Scholar
41. 1. Schulte BA
    2. Schmiedt RA

    (1992) Lateral wall Na,K-ATPase and endocochlear potentials decline with age in quiet-reared gerbils

    Hearing Research 61:35–46.

    https://doi.org/10.1016/0378-5955(92)90034-k

    • PubMed
    • Google Scholar
42. 1. Shokrian M
    2. Knox C
    3. Kelley DH
    4. Nam JH

    (2020) Mechanically facilitated micro-fluid mixing in the organ of Corti

    Scientific Reports 10:14847.

    https://doi.org/10.1038/s41598-020-71380-5

    • PubMed
    • Google Scholar
43. 1. Sun H
    2. Hashino E
    3. Ding DL
    4. Salvi RJ

    (2001) Reversible and irreversible damage to cochlear afferent neurons by kainic acid excitotoxicity

    The Journal of Comparative Neurology 430:172–181.

    https://doi.org/10.1002/1096-9861(20010205)430:2<172::aid-cne1023>3.0.co;2-w

    • PubMed
    • Google Scholar
44. 1. Szeto B
    2. Chiang H
    3. Valentini C
    4. Yu M
    5. Kysar JW
    6. Lalwani AK

    (2020) Inner ear delivery: Challenges and opportunities

    Laryngoscope Investigative Otolaryngology 5:122–131.

    https://doi.org/10.1002/lio2.336

    • PubMed
    • Google Scholar
45. 1. Talaei S
    2. Schnee ME
    3. Aaron KA
    4. Ricci AJ

    (2019) Dye tracking following posterior semicircular canal or round window membrane injections suggests a role for the cochlea aqueduct in modulating distribution

    Frontiers in Cellular Neuroscience 13:471.

    https://doi.org/10.3389/fncel.2019.00471

    • PubMed
    • Google Scholar
46. 1. Tandon V
    2. Kang WS
    3. Robbins TA
    4. Spencer AJ
    5. Kim ES
    6. McKenna MJ
    7. Kujawa SG
    8. Fiering J
    9. Pararas EEL
    10. Mescher MJ
    11. Sewell WF
    12. Borenstein JT

    (2016) Microfabricated reciprocating micropump for intracochlear drug delivery with integrated drug/fluid storage and electronically controlled dosing

    Lab on a Chip 16:829–846.

    https://doi.org/10.1039/c5lc01396h

    • PubMed
    • Google Scholar
47. 1. Versteegh CPC
    2. van der Heijden M

    (2013) The spatial buildup of compression and suppression in the mammalian cochlea

    Journal of the Association for Research in Otolaryngology 14:523–545.

    https://doi.org/10.1007/s10162-013-0393-0

    • PubMed
    • Google Scholar
48. 1. Wangemann P

    (2006) Supporting sensory transduction: cochlear fluid homeostasis and the endocochlear potential

    The Journal of Physiology 576:11–21.

    https://doi.org/10.1113/jphysiol.2006.112888

    • PubMed
    • Google Scholar
49. Book

    1. Wangemann P
    2. Marcus DC

    (2017) Ion and fluid homeostasis in the cochlea

    In: Manley GA, Gummer AW, editors. Understanding the Cochlea. Springer. pp. 253–286.

    https://doi.org/10.1007/978-3-319-52073-5

    • Google Scholar
50. 1. Wong SJ
    2. Abrams KS
    3. Amburgey KN
    4. Wang Y
    5. Henry KS

    (2019) Effects of selective auditory-nerve damage on the behavioral audiogram and temporal integration in the budgerigar

    Hearing Research 374:24–34.

    https://doi.org/10.1016/j.heares.2019.01.019

    • PubMed
    • Google Scholar
51. 1. Zagadou BF
    2. Mountain DC

    (2012) Analysis of the cochlear amplifier fluid pump hypothesis

    Journal of the Association for Research in Otolaryngology 13:185–197.

    https://doi.org/10.1007/s10162-011-0308-x

    • PubMed
    • Google Scholar
52. 1. Zhou W
    2. Nam JH

    (2019) Probing hair cell’s mechano-transduction using two-tone suppression measurements

    Scientific Reports 9:4626.

    https://doi.org/10.1038/s41598-019-41112-5

    • PubMed
    • Google Scholar
53. 1. Zidanic M
    2. Brownell WE

    (1990) Fine structure of the intracochlear potential field.I.the silent current

    Biophysical Journal 57:1253–1268.

    https://doi.org/10.1016/S0006-3495(90)82644-8

    • PubMed
    • Google Scholar

Author details

1. Choongheon Lee

   1. Department of Otolaryngology, University of Rochester, Rochester, United States
   2. Department of Mechanical Engineering, University of Rochester, Rochester, United States

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Mohammad Shokrian and Kenneth S Henry

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3080-681X

2. Mohammad Shokrian

   Department of Mechanical Engineering, University of Rochester, Rochester, United States

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – review and editing

   Contributed equally with

   Choongheon Lee and Kenneth S Henry

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0360-323X

3. Kenneth S Henry

   1. Department of Otolaryngology, University of Rochester, Rochester, United States
   2. Department of Biomedical Engineering, University of Rochester, Rochester, United States
   3. Department of Neuroscience, University of Rochester, Rochester, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Investigation, Methodology, Writing – review and editing

   Contributed equally with

   Choongheon Lee and Mohammad Shokrian

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1364-318X

4. Laurel H Carney

   1. Department of Biomedical Engineering, University of Rochester, Rochester, United States
   2. Department of Neuroscience, University of Rochester, Rochester, United States
   3. Department of Electrical and Computer Engineering, University of Rochester, Rochester, United States

   Contribution

   Conceptualization, Resources, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4729-5702

5. J Christopher Holt

   1. Department of Otolaryngology, University of Rochester, Rochester, United States
   2. Department of Neuroscience, University of Rochester, Rochester, United States

   Contribution

   Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7908-083X

6. Jong-Hoon Nam

   1. Department of Mechanical Engineering, University of Rochester, Rochester, United States
   2. Department of Biomedical Engineering, University of Rochester, Rochester, United States
   3. Department of Neuroscience, University of Rochester, Rochester, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   jong-hoon.nam@rochester.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7477-5453

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