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1Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary and 2Department of Otology and Laryngology, Harvard Medical School, Boston; and 3Program in Speech and Hearing Bioscience and Technology, Division of Health Science and Technology, Harvard/Massachusetts Institute of Technology, Cambridge, Massachusetts
Submitted 2 June 2004; accepted in final form 21 September 2004
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ABSTRACT |
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INTRODUCTION |
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Although requiring more invasive procedures, recordings from single auditory nerve (AN) fibers can provide more detailed insight into the functional state of the inner ear. The vast majority of AN fibers in the mammalian ear make synaptic contact with only a single inner hair cell (IHC), by means of one synaptic complex (Liberman 1980
; Spoendlin 1969; Spoendlin and Schrott 1988). Thus recording from a single AN provides a sensitive window into the microenvironment of a single sensory cell in the inner ear and a sensitive functional metric of the transducer apparatus on the specific IHC contacted and the neighboring outer hair cells that influence its local cochlear mechanics. Analysis of the fine timing patterns of spike discharges (e.g., the degree of phase-locking or the response adaptation) can provide insight into the processes involved in synaptic transmission between the hair cell and its primary sensory neuron. By sampling from numerous fibers in the same animal or mutant strain, a detailed picture can be assembled of the outputs of the sensory transduction and synaptic transmission machinery all along the cochlear duct.
There have been 2 previous reports of single-fiber activity from the mouse AN. These pioneering studies were not primarily interested in understanding cochlear mechanisms. One was aimed at validating the use of the galvanic skin response as a minimally invasive measure of cochlear sensitivity (Finck and Berlin 1965) and thus mainly collected data on single-fiber thresholds. The other was aimed at understanding the neurophysiological bases for critical bands and thus collected data on single-fiber thresholds and on the masking of tone responses by noise bands (Ehret and Moffat 1984). In contrast, our aim is to describe those fundamental aspects of auditory nerve response that provide the most insight into the mechanisms of transduction and synaptic transmission in the inner ear, especially when coupled with the use of targeted genetic modification in the mouse model. Thus our study was designed to provide a systematic description of the most fundamental response properties of the mouse AN response, including the distribution of spontaneous rates, tuning curves, rate versus level functions, dynamic range, response adaptation, degree of phase-locking, and the relations between spontaneous rate and the aforementioned response properties.
In the present study, we describe the spontaneous and sound-evoked discharge properties of a large number of AN fibers recorded from the CBA/CaJ strain and somewhat smaller set of recordings from the C57BL/6 strain. The former strain is important because it is commonly used in auditory research, and it retains excellent cochlear sensitivity throughout its life span (Jimenez et al. 1999; Li and Borg 1991; Zheng et al. 1999). The latter strain is of interest because it is often the background strain in which knockout mice have been produced (Mullen and Ryan 2001) and because it has also been extensively studied as a result of the presence of a type of age-related hearing loss (Ding et al. 1999; Henry and Lepkowski 1978; Li et al. 1993; Parham 1997; Willott 1986).
Comparisons between mouse AN physiology and that of other mammals is also of interest because the mouse cochlea is specialized for higher-frequency stimuli than cat, guinea pig, chinchilla, or gerbil, the other mammalian species in which AN responses have been well studied. Despite this important difference, we show that the fundamental aspects of AN response are qualitatively similar in the mouse. We further show that the responses of these 2 commonly used mouse strains are quantitatively similar as well.
The research described here is a component of a doctoral thesis, to be submitted in partial fulfillment of the requirements for a degree in Speech and Hearing Bioscience and Technology in the Health Science and Technology Division at Harvard and MIT.
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METHODS |
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The sound system consisted of dual electrostatic sound sources (TDT ED-1) and a Knowles electret microphone coupled to a probe tube. The sensitivity of the probe-tube microphone was calibrated for frequencies between 1.0 and 73 kHz using a calibrated Brüel & Kjær -in. condenser microphone in a coupler.
Distortion-product otoactoustic emissions (DPOAEs) were monitored throughout the experiments to assess cochlear stability. At the beginning of the experiments, before cerebellar aspiration, DPOAEs were measured with f2 frequencies from 5.6 to 45.2 kHz in half-octave steps. During single-fiber recordings, the DPOAEs were rechecked at the f2 nearest the characteristic frequency (CF) of each fiber studied. Data are included in the final database only if the thresholds for DPOAEs at 2f1 – f2 were 
5 dB re initial values. The DPOAE at 2f1 – f2 was recorded in response to primary tones f1 and f2, with f2/f1 = 1.2 and L2 = L1 – 10 dB. The ear-canal sound pressure waveform was amplified and digitally sampled at 4-µs intervals. Fast-Fourier transforms (FFTs) were computed from averaged sound pressure waveforms, and the DPOAE and surrounding noise floor were extracted.
Noise bursts of 50-ms were used as search stimuli. Tone bursts were used for all other sound-evoked measures (except phase-locking): they were 50 ms in duration, with 2.5-ms rise–fall and a repetition rate of 10/s. Tuning curves were measured under computer control, and represent isorate contours for response magnitude of 10 sp/s > spontaneous rate. Spontaneous rates were calculated from 10-s samples.
Because both cochlear nucleus cell types and AN fibers are encountered along the electrode track, a classification scheme based on poststimulus time histogram (PSTH) shape, first spike latency (FSL), and the coefficient of variation (CV) of the interspike intervals was developed to distinguish the 2 cell types. PSTHs used to characterize response type were based on 150–250 tone burst presentations at CF and were always presented at 30 dB above threshold. A measure of FSL (i.e., the mode of the FSL distribution) and the CV (i.e., the ratio of the SD to the mean of the interspike interval distribution) were both obtained from responses to 150 CF tone bursts at 30 dB above threshold. CV measures were derived only from spikes occurring 20–40 ms after tone-burst onset (i.e., excluding the initial and final 10 ms, where some spike intervals may include spontaneous discharge).
Rate-level functions were measured at CF with 10–20 tone bursts per level. Levels (in 5-dB steps) were presented in random order and, if contact time permitted, also in sequential order. Rate versus level functions were fit using a modified version of a previously published model (Sachs et al. 1989). The input to the saturating nonlinearity was given an exponential 
(a free parameter), which allowed the function to have steeper slopes. The fitting procedure was done in Matlab using the function fminsearch, which performs a multidimensional unconstrained nonlinear minimization (Nelder–Mead). The root-mean-square (rms) error between the response data and the best-fit curve was used to determine goodness of fit. To eliminate "noisy" data runs, a maximum allowable rms error of 14 sp/s was arbitrarily set for inclusion into the final data base. Dynamic range was defined as the difference between sound pressure levels (SPLs) evoking 10 and 90% of the (model fit) maximum driven rate.
Measures of synchrony were obtained from postzero-crossing (PZC) histograms derived from the presentation of single tones of 15-s duration. The tone frequencies were constrained (f = 1.0, 1.6, 2.0, 2.5, or 4 kHz) so that an integer number of cycles fit in the digital buffer. When measuring phase-locking in AN response, care was taken to eliminate artifactual synchrony arising from microelectrode pick-up of cochlear microphonic potentials. A model developed by Johnson (1978) was used to compute a synchrony noise floor below which synchrony may be artifactual. According to the model, the synchronization index (SI) attributed to the microphonic artifact is given by
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is the ratio of the rms stimulus artifact amplitude to the peak spike amplitude; and t is the rise time of the spikes. Rise time t and ratio were calculated from measurements of digitized spike trains obtained during each synchrony measurement: the amplitude of the sine wave (microphonic) component at the stimulus frequency was extracted by FFT. Only the data for which the measured SI was 
2 times greater than SIartifact are included in this paper. |
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RESULTS |
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Because the auditory nerve (AN) in mouse is difficult to expose directly without compromising cochlear function, the AN was reached by electrode penetrations that first travel through the cochlear nucleus (CN), which can be readily exposed. Electrode angles and insertion area were chosen to avoid the anteroventral CN, which contains cells with AN-like responses in other mammalian species (Rouiller and Ryugo 1984). Based on surface landmarks, most electrodes penetrations entered through the anterior portions of the dorsal cochlear nucleus (DCN). Cell types encountered along the electrode track yielded poststimulus-time histograms (PSTHs) with "chopper," "onset," "pri-notch," and "primary-like" shapes. As expected, cells with chopper (Fig. 1C) tended to be seen superficially in the electrode tracks, whereas "primary-like" (AN) responses were almost exclusively seen at electrodes sites deeper than 1 mm from the point of penetration.
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), both of which were measured in response to tone bursts at the characteristic frequency. In cat, where AN and CN can be separately accessed by microelectrodes (with visible superficial landmarks identifying the Schwann–glial border separating these 2 structures), AN responses are more irregular (i.e., larger CV for interspike intervals) and show a smaller FSL than that of most CN cells with similar characteristic frequencies and spontaneous rates (Young et al. 1988).
In early experiments to develop effective criteria for differentiating AN fibers from CN cells, tone-burst responses were obtained and analyzed from all fibers encountered along each electrode pass, Fig. 1A shows the relationship between CV and FSL in fibers subjectively classified by PST shapes. Results suggest that mouse AN fibers have CVs 0.5 and FSLs 5 ms, which are similar to values reported for cat (Young et al. 1988). As in cat, there appears to be some overlap of CV and FSLs between AN and CN (e.g., for the "pri-notch" CN units) (Young et al. 1988). Nevertheless, the data in Fig. 1 suggest that the following criteria adopted for classification as AN fiber should provide the best trade-off between sensitivity and specificity: 1) CV 0.5, 2) FSL 5 ms, 3) electrode depth 1,000, and 4) "primary-like" PSTH.
In later experiments, the superficially located CN cells were bypassed to increase the yield of AN fibers in each animal studied. By the end of the experimental series, the mean yield of AN recordings had grown to 7/animal (with a maximum of 16/animal). Termination of the recording session was typically dictated by decreasing cochlear sensitivity leading to DPOAE threshold elevation beyond the 5-dB limit on threshold shift arbitrarily imposed to maintain data "purity."
Rate threshold and tuning
A fundamental property of AN fibers is their frequency selectivity, which is often quantified by "threshold" tuning curves that track isoresponse contours in the frequency–intensity plane (Fig. 2). Tuning curves were obtained for all mouse AN fibers encountered. As in other mammalian species, mouse AN tuning curves show sharply tuned "tips," defining a characteristic frequency (CF: frequency of maximum sensitivity) and broadly tuned low-frequency "tails." The data in Fig. 2 show populations of tuning curves obtained from 28 CBA/CaJ mice, clustered according to CF. Tuning curve shapes are remarkably similar across animals. As reported for other species, tuning curves from lower CF regions tend to be more "V-shaped," with a less obvious low-frequency tail. Tuning curves from C57BL/6 mice showed similar features.
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Spontaneous rate
Auditory nerve fibers discharge spontaneously in the absence of sound (Kiang et al. 1965). Figure 4A shows the spontaneous rate (SR) distribution for the fiber populations sampled from the 2 strains in the present study. SRs ranged from 0 to 120 sp/s in both strains, with 49% (CBA/CaJ) and 67% (C57BL/6) of the fibers having SRs <20 sp/s. In contrast to many other mammalian species studied, such as cat (Kiang et al. 1965) or guinea pig (Tsuji and Liberman 1997), the SR distribution in mouse is not clearly bimodal. Although there is no clear relationship between fiber SR and CF (Fig. 4B), there is a clear relationship between fiber threshold and SR. As seen in other mammalian species (e.g., Liberman 1978), fibers with the lowest relative thresholds (with respect to the most sensitive fibers of similar CF) also had the highest SRs (Fig. 4C). There are no striking differences between data from CBA/CaJ versus C57BL/6 mice.
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PST histograms of AN fibers show a peak in discharge rate at tone-burst onset, which decays to a steady-state response (Kiang et al. 1965; Smith 1977). The ratio of peak to steady-state rate is one measure of response adaptation. In the present study, adaptation of mouse AN responses was studied using PST histograms of responses to CF tone bursts at 30 dB above threshold. The histograms were normalized by the number of tone burst presentations and the histogram bin width (0.5 ms) to give the instantaneous discharge rate.
Response adaptation is a function of both SR and CF in the mouse AN (Fig. 5, A and B). In CBA/CaJ mice, fibers with SR 1 sp/s had peak-to-steady state ratios from 2.2 to 7.4, whereas fibers with SR <1 sp/s had ratios between 1.6 and 4.2 (Fig. 5A). Fibers with the largest peak-to-steady state ratios had CF >20 kHz (Fig. 5B). The increase in peak-to-steady state ratio is attributed to an increase peak rate with CF. This difference can be seen from the superimposed PST histograms for high-SR (SR 1) fibers with CF <20 kHz versus CF >20 kHz (Fig. 5, C and D, respectively). All features of response adaptation appeared similar in CBA/CaJ and C57BL/6 strains.
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The dynamic range of single AN fibers in mouse was investigated by measuring discharge rate versus sound level for tone bursts at CF. The rate versus level data were fit by a modified version of an existing model (Sachs et al. 1989). Figure 6 shows examples of 2 rate-level functions, their model fits, and calculated dynamic ranges. The rms errors of the model fits in these 2 cases were 13.2 and 13.9 sp/s. Of 156 rate-level functions obtained from CBA/CaJ mice and 45 from C57BL/6, 92 and 41, respectively, had model fits with "acceptable" rms error (14 sp/s) and were included in the study.
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1 sp/s (Fig. 7A): group mean differences were statistically significant (P = 0.026, Student's t-test). There did not appear to be any relation between maximum discharge rate and CF (data not shown), and there were no obvious differences between the 2 strains studied.
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1 sp/s) fibers, the largest dynamic range was only 22.8 dB.
In data from guinea pig AN (Winter et al. 1990), rate-level functions have been categorized as "hard saturating," "sloping saturating," and "straight." In data from mouse, the great majority of rate-level functions, and all those with dynamic range <20 dB, showed hard saturation in response to tone bursts (Fig. 8, A and B). In contrast, fibers with dynamic ranges >20 dB showed "sloping saturation" or "straight" functions (Fig. 8, C and D). In both strains of mice, fibers with the largest dynamic range had SR <1 sp/s and relative threshold >10 dB.
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When AN fibers respond to low-frequency tones there is a correlation between the stimulus periodicity and the timing of spikes (Johnson 1980), as illustrated by the PZC histogram in Fig. 9C. In cat, where it has been most systematically studied, this phase-locking, or synchrony, falls off dramatically as stimulus frequency approaches 4 kHz (Johnson 1980). In the mouse AN, there are relatively few fibers with rate threshold <60 dB SPL at frequencies 4 kHz (e.g., Fig. 2). Thus given that high SPL tones elicit large cochlear microphonic potentials that can produce artifactual synchrony when picked up by the microelectrode, response synchrony could be studied systematically in only a few fibers. A model developed by Johnson (1978) was used to compute a synchrony noise floor for each recording (based on the ratio of microphonic size to spike size) to prevent pollution of data by these microphonic-based artifacts (see METHODS).
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DISCUSSION |
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In the present study, PST shape, response regularity, response latency, and location along the electrode track were used to distinguish AN fibers from CN units. Based on this classification scheme, the fiber population studied must be dominated by AN responses. However, CN units with "primary-like" responses could also be included, given that, in cat, there is some overlap in response latency and regularity measures between these CN cells and AN fibers (Young et al. 1988). CN cells that can generate primary-like responses include spherical and globular bushy cells (Blackburn and Sachs 1989; Smith et al. 1993).
Spherical bushy cells are located in the anterior anteroventral cochlear nucleus (AVCN). Our electrode angle and insertion point in the DCN is such that anterior AVCN is not traversed. Thus it is not likely that any of the present results are from spherical bushy cells. Globular bushy cells are located more posteriorly in the AVCN. Because globular cells are located near the AN root in mouse (Webster and Trune 1982) and have tone burst FSLs comparable to those of AN fibers (Young et al. 1988), it is possible that some globular cell responses were classified as AN fibers in the present database. Such inclusion would have minimal affect on the conclusions because globular cell responses are generally so similar to those of AN fibers. The greatest differences include a tendency toward larger SRs, maximum driven rates, and peak-to-steady state ratios in globular cells (Rhode and Smith 1986). Thus these aspects of mouse AN response may be slightly skewed toward higher values in the present study.
Relevance to other data on auditory function in mouse
CF LIMITS AND COCHLEAR FREQUENCY MAPS. Information used by the CNS in processing auditory stimuli comes through the approximately 20,000 fibers of the AN. Thus the superposition of tuning curves obtained from mouse AN provides an informative overview of the threshold sensitivity of the auditory periphery (Fig. 10). Not surprisingly, the minimum envelope of these single-fiber data basically tracks the published behavioral thresholds obtained in a variety of mouse strains, at least for frequencies below 50 kHz. Because "threshold" is defined differently in each study, and because the behavioral studies use an intact pinna and free-field acoustics, absolute comparisons of threshold values are not warranted. The discrepancy above 50 kHz between single-fiber and behavioral data is likely attributable to the difficulties in accurately specifying the sound pressure at the eardrum in both cases.
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A low-frequency CF limit of 2.5 kHz is significantly higher than the value predicted by 2 older cochlear frequency maps for mouse (Ehret 1975; Ou et al. 2000), although it is about 1 octave lower than that suggested by the most recent map (Mueller et al. 2004). The oldest map (Ehret 1975) was derived by choosing values for the upper and lower limit of mouse hearing from behavioral measures and then fitting a power function of the type inferred for the human cochlear map based on psychophysically derived critical bands (Greenwood 1961). The lower limit chosen for mouse hearing was 0.8 kHz. As shown in Fig. 10, our data suggest that the perception of frequencies <2.5 kHz is mediated by excitation of the "tails" of the apical-most AN fibers, not by fibers with CFs of 0.8 kHz.
A second cochlear map for mouse was derived by comparing the patterns of noise-induced hair cell lesions to patterns of threshold shift seen in ABR responses (Ou et al. 2000). The data set did not include any frequency points below about 6 kHz, but the best-fit logarithmic function extrapolated to a value of 1.5 kHz for the apical-most CF in mouse. According to the present results, this value may also be too low by about 1 octave. A similar discrepancy between the cat cochlear map inferred by correlating lesion site to cochlear sensitivity changes was detected when a definitive map was derived by intracellular labeling of single physiologically characterized nerve fibers (Liberman 1982a).
Recently, a mouse map was more directly derived by injecting HRP extracellularly into the CN after recording neuronal responses and correlating CF with the locations of labeled terminals in the cochlea (Mueller et al. 2004). Although there were no data points for the apical cochlea (lowest CF was about 7 kHz), the best-fit logarithmic function extrapolated to a minimum CF value of 4.8 kHz. The present study shows that tuning in the cochlear apex extends at least down to 2.5 kHz. Thus the simple log-frequency-to-linear-distance relation, suggested by Mueller et al. (2004), should be modified to a function of the Greenwood type, such that frequency representation in the apical turn changes more slowly with distance, as is the case in cat (Liberman 1982a).
OTHER STUDIES OF AN RESPONSE AND BEHAVIORAL THRESHOLDS IN MOUSE.
Two previous studies, Finck and Berlin (1965) and Ehret and Moffat (1984), describe recordings from mouse AN fibers, using the CBA/J strain and the (outbred) NMRI strain, respectively. In both studies, electrode tracks traversed the CN to access the AN, and thus the possibility for unit misclassification exists. This possibility was acknowledged, but not addressed, by Finck and Berlin; Ehret and Moffat developed a classification scheme based on average FSL. Thus as in the present study, their database may include a small population of globular bushy cells in addition to the majority population representing AN response.
Aspects of AN physiology characterized in these previous studies included: response areas (i.e., tuning curves), thresholds at CF, masked thresholds to tone bursts in noise, and critical ratio bands. Because the present study did not examine noise masking, and previous studies did not directly quantify the sharpness of tuning curves, the only point of comparison among the 3 studies concerns the distribution of thresholds at CF. Threshold data from the 3 studies are compared in Fig. 10A, where all tuning curves from CBA/CaJ mice in the present study (gray lines) are superimposed on curves representing the minimum thresholds at CF for AN fibers sampled in the CBA/J (filled diamonds) and the NMRI strains (filled circles). Minimum thresholds for the NMRI strain are lower at most CF regions than those seen in the present study. However, data from the present study do not show the precipitous loss of sensitivity for CFs >30 kHz (see following text). Minimum threshold envelopes for the CBA/J data and the present CBA/CaJ data are remarkably similar for CFs <30 kHz. For higher CF regions, CBA/CaJ maintains low minimum thresholds out to the high-frequency limits of our acoustic system (about 70 kHz), whereas the CBA/J data show steeply sloping loss of threshold sensitivity. It is not clear whether these differences in high-frequency behavior reflect true interstrain differences in high-frequency sensitivity, differences in acoustic calibration procedure, or artifactual loss of sensitivity in the CBA/J arising from, for example, cochlear cooling in the anesthetized preparation (Brown et al. 1983).
Comparisons of single-fiber thresholds from the present study with behavioral thresholds for a number of mouse strains are also shown in Fig. 10. With the exception of an extremely low value for 1-kHz behavioral threshold in the NMRI mouse, all behavioral threshold functions agree reasonably well with the minimum single-fiber thresholds measured in CBA/CaJ in the present study (Fig. 10A). Note that none of the behavioral curves shows the precipitous threshold elevation for frequencies >30 kHz seen in the CBA/J single-fiber study. The reason for the discrepancy in high-frequency sensitivities between the behavioral and neural data for C57BL/6 (Fig. 10B) is not clear; however, it probably does not arise from incomplete sampling in the present study because there was a clear trend among fibers sampled showing threshold elevations for CFs above 15 kHz (e.g., Fig. 3A).
INTERSTRAIN DIFFERENCES AND THE CHOICE OF CBA/CAJ AND C57BL/6. The availability of transgenic and mutant lines with interesting auditory phenotypes makes the mouse a valuable model for the study of the auditory system; moreover, recording from single auditory nerve fibers provides a powerful tool for assessing the cochlear phenotype associated with any genetic manipulation. However, the interpretation of hearing results from mutant mouse lines is often complicated by the fact that these lines are created or maintained in several inbred mouse strains (e.g., C57BL/6, 129/SvEv, and FVB/N), and there can be clearcut interstrain differences in threshold sensitivity, especially as animals age, that complicate the selection of control animals. Although CBA/CaJ is not one of the inbred strains in which mutant or transgenic lines are typically available, it was chosen for the present study in that it is one of the most commonly used strains for the study of hearing because it does not show the premature age-related cochlear degeneration seen in these other strains.
A challenge in the use of single-fiber assays for phenotypic analysis in mouse is the time-consuming nature of the data collection, averaging only 5–10 units per 6-h experiment. Thus it is of practical importance to understand the nature of interstrain differences in AN response, so that informed decisions can be made as to the appropriateness of different "control" data sets. For example, is the present data set appropriate for comparison to data obtained in a knockout line maintained in a different background? Setting aside issues related to the premature onset of high-frequency threshold shifts in some of these non-CBA strains, the answer appears to be a cautious "yes." As described in more detail below, results from this work suggest that several fundamental aspects of mouse AN response are quantitatively similar to those of other mammalian species, such as the relation between sharpness of tuning and CF (Fig. 11) and the relation between SR and threshold sensitivity (Fig. 4C). Other properties are qualitatively similar, such as the relation between SR and dynamic range. Thus the likelihood of significant interstrain differences in these general properties seems remote. More directly relevant to the question, the limited comparison between CBA/CaJ and C57BL/6 AN data in the present study (e.g., Figs. 3–9) fails to reveal any obvious differences between these two strains.
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TUNING-CURVE TIPS VERSUS TAILS AND RATE VERSUS SYNCHRONY CODING. Tuning curves recorded from the mouse AN were qualitatively similar to those recorded in other mammalian species. They showed sharply tuned "tips" near the characteristic frequency and broadly tuned low-frequency "tails" (Fig. 2). As in other mammals, mouse AN fibers showed increasing sharpness of tuning with increasing CF (Fig. 3B). A more quantitative comparison of mean Q10dB values obtained from several mammalian species is shown in Fig. 11. The combined data suggest a common relationship between Q10dB and CF, with similar sharpness of tuning seen across several mammalian species, where CF regions overlap.
A more quantitative comparison of tuning-curve "tails" shows that low-frequency thresholds are significantly elevated in mouse compared with other mammalian species, such as cat (Liberman 1978), guinea pig (Evans 1972), chinchilla (Dallos and Harris 1978), and gerbil (Ohlemiller and Echteler 1990). For example, a direct comparison of mouse and cat tuning curves for fibers with CF near 15 kHz (Fig. 12) shows that, whereas thresholds in mouse increase monotonically for frequencies below CF and rise above 90 dB for frequencies <4 kHz, thresholds in cat show a second minimum at low frequencies and do not rise above 90 dB SPL until frequencies fall below about 0.2 kHz. These differences in low-frequency responses of high-CF fibers are likely a result of the roll-off in middle-ear transmission for frequencies <10 kHz in the mouse (Rosowski et al. 2003).
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). Thus in cat or guinea pig, and probably humans, low-frequency sensitivity is such that AN fibers spanning many octaves of CF will show phase-locked response to a moderate-level (80 dB), low-frequency (e.g., 1 kHz) tone. In mouse AN, by contrast, there would be almost no fibers responding to such a stimulus (see Fig. 10). This raises the question as to whether this mammalian ear specialized for high-frequency hearing has also developed specializations to shift the frequency range of AN phase-locking. Data in the present study suggest that this is not the case: the relation between maximum synchronization index and stimulus frequency appears to be fundamentally similar to that seen in other mammals (Fig. 9). Indeed, if anything, the high-frequency limit of synchronization occurs at a lower frequency than that in cat. Thus the data further suggest that phase-locking of AN response is not a particularly important component of mouse hearing.
SPONTANEOUS DISCHARGE AND SR GROUPS.
In cat and guinea pig, where it has been most exhaustively studied, differences in SR are strongly correlated with differences in other response properties such as threshold sensitivity (Liberman 1978), adaptation (Rhode and Smith 1985), susceptibility to forward masking (Relkin and Doucet 1991), and dynamic range (Winter et al. 1990), among others.
In cat, where data from hundreds of units can be obtained from individual animals under highly stable recording conditions, analysis of the relation between SR and threshold sensitivity suggested that 3 SR groups could be defined: high, medium, and low, with SR ranges of >18, 0.5 to 18, and <0.5 sp/s, respectively (Liberman 1978). Subsequent structure–function correlations using intracellular injection of neuronal tracers revealed that there are systematic differences among these 3 groups, in 1) locus of peripheral terminal on the IHC circumference (Liberman 1982b), 2) size and complexity of the synaptic apparatus within the IHC (Merchan-Perez and Liberman 1996), 3) degree of branching of the central axon (Fekete et al. 1984), and 4) the CN subdivisions to which they project (Liberman 1991, 1980). Many of the same structure–function relationships have been corroborated in the guinea pig, suggesting that the subdivision of AN fibers into SR-based groups is part of the fundamental mammalian plan (Tsuji and Liberman 1997).
In cat, guinea pig, chinchilla, and rabbit (Fig. 13A) the SR distribution is fundamentally bimodal, and fibers from the lower peak in the SR distribution have higher thresholds than those from the high rate peak (Tsuji and Liberman 1997). Although the SR distribution in the mouse is not as clearly bimodal as in these other species, the general relation between SR and threshold sensitivity is maintained (although the evidence for discrete SR groups rather than a continuum of response is not clear). Recent ultrastructural work in mouse suggests that, in this species, as previously reported in cat and guinea pig, the AN terminals contacting the modiolar side of the IHC are lower in mitochondrial content than those on the pillar side (Francis et al. 2004). In cat, these mitochondrion-poor afferents have been definitively identified as corresponding to the high-threshold low-SR group. Thus the same anatomical differences may underlie the observed SR-based heterogeneity of response in mouse.
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), another high-frequency animal, and to high-CF AN fibers in gerbil (Ohlemiller and Echteler 1990), where the SR distribution varies dramatically with CF. As can be seen in Fig. 13B, for rat, mouse, and the basal turn of gerbils, the SR distribution is not clearly bimodal and is shifted toward lower spontaneous rates. This association between a compressed SR distribution and high-frequency hearing is interesting, given that robust background discharge may be most useful at frequencies <4 kHz, where response synchronization occurs, and where synchrony rises at lower SPLs than the average rate (Fig. 9, A and B).
As for cat (Rhode and Smith 1985) and guinea pig (Muller and Robertson 1991), response adaptation in mouse AN is related to fiber SR (Fig. 5A) and CF (Fig. 5B). In both cat and guinea pig, response adaptation for fibers with CF <4 kHz was smaller than the response adaptation in fibers of higher CF (Muller and Robertson 1991; Rhode and Smith 1985). Given that phase-locking occurs for frequencies <4 kHz (Johnson 1980), Rhode and Smith (1985) hypothesized that the lower peak rates observed in cat low-CF fibers were attributed to an interaction between phase-locking and rapid adaptation. In mouse, there was a difference in response adaptation between fibers with CF below versus above 20 kHz (Fig. 5). This CF-related difference clearly cannot be correlated with the presence or the absence of synchrony; rather, it likely arises from CF-related changes in the kinetics of synaptic transmission.
DYNAMIC RANGE IN THE AUDITORY PERIPHERY.
Rate versus level functions for AN responses to CF tone bursts have been best studied in cat (Sachs et al. 1989), guinea pig (Winter et al. 1990), and gerbil (Ohlemiller et al. 1991). In all 3 of these mammals, dynamic ranges depend strongly on SR: low-threshold, high-SR fibers show hard rate-saturation and small dynamic ranges, whereas high-threshold, low-SR fibers show sloping saturation or nonsaturating rate versus level functions with significantly larger dynamic ranges. Data in the present study show that the mouse AN has fundamentally the same behavior (Fig. 7); thus these SR-related differences in dynamic range also appear to be part of a general mammalian plan.
A striking difference between AN properties in mouse versus other mammals is the small dynamic range of the low-threshold, high-SR fibers. For example, Fig. 14 compares dynamic ranges for high- and low-SR AN fibers from the present study to data from cat (Guinan and Stankovic 1996), which were derived according to exactly the same stimulation and analysis protocols. The great majority (>90%) of high-SR fibers in the mouse had dynamic range values <18 dB, whereas the majority (>70%) of high-SR fibers in cat showed dynamic ranges >18 dB. Gerbil high-SR fibers (Ohlemiller et al. 1991) have been shown to have even higher dynamic range values (25–40 dB). Quantitative data for guinea pig are not available, although visual inspection of rate-level functions shown by Winter et al. (1990) suggest that dynamic ranges in this species for high-SR fibers are comparable to those in cat.
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): high-frequency fibers, with CFs above the limits of phase-locking, show a smaller mean dynamic range (about 25 dB) than low-CF fibers (about 35 dB). The existence of steeper rate versus level functions in mouse high-SR fibers might be expected to subserve an enhanced ability to detect small changes in stimulus intensity at levels near threshold. However, existing measurement of intensity difference limens in mouse do not suggest any extraordinary abilities compared with other mammalian species investigated (Fay 1988).
The steepness of rate versus level functions in mouse could arise at several stages in cochlear processing. Comparison of basilar membrane displacement versus level functions for tones at CF near the base of the cochlea in mouse (Legan et al. 2000) compared with other mammals (Robles and Ruggero 2001) do not suggest striking differences in slope (Fig. 15). Thus the basis for the observed differences in dynamic range must arise within the inner hair cell, the auditory nerve, or the synaptic transmission between the two.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: M. C. Liberman, Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary, 243 Charles St., Boston, MA 02114 (E-mail; mcl{at}epl.meei.harvard.edu)
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REFERENCES |
|---|
|
Blackburn CC and Sachs MB. Classification of unit types in the anteroventral cochlear nucleus: PST histograms and regularity analysis. J Neurophysiol 62: 1303–1329, 1989.
Borg E, Engstrom B, Linde G, and Marklund K. Eighth nerve fiber firing features in normal-hearing rabbits. Hear Res 36: 191–201, 1988.[CrossRef][Web of Science][Medline]
Brown MC, Smith DI, and Nuttall AL. Anesthesia and surgical trauma: their influence on the guinea pig compound action potential. Hear Res 10: 345–358, 1983.[CrossRef][Web of Science][Medline]
Dallos P and Harris D. Properties of auditory nerve responses in absence of outer hair cells. J Neurophysiol 41: 365–383, 1978.
Ding DL, McFadden SL, Wang J, Hu BH, and Salvi RJ. Age- and strain-related differences in dehydrogenase activity and glycogen levels in CBA and C57 mouse cochleas. Audiol Neurootol 4: 55–63, 1999.[CrossRef][Medline]
Ehret G. Age-dependent hearing loss in normal hearing mice. Naturwissenschaften 61: 506–507, 1974.[Web of Science][Medline]
Ehret G. Masked auditory thresholds, critical ratios, and scales of the basilar membrane of the housemouse (Mus musculus). J Comp Physiol 103: 329–341, 1975.[CrossRef]
Ehret G and Moffat AJ. Noise masking of tone responses and critical ratios in single units of the mouse cochlear nerve and cochlear nucleus. Hear Res 14: 45–57, 1984.[CrossRef][Web of Science][Medline]
el Barbary A. Auditory nerve of the normal and jaundiced rat. I. Spontaneous discharge rate and cochlear nerve histology. Hear Res 54: 75–90, 1991.[CrossRef][Web of Science][Medline]
Evans EF. The frequency response and other properties of single fibres in the guinea-pig cochlear nerve. J Physiol 226: 263–287, 1972.
Fay RR. Hearing in Vertebrates: A Psychophysics Databook. Worcester, MA: Hefferman Press, 1988.
Fekete DM, Rouiller EM, Liberman MC, and Ryugo DK. The central projections of intracellularly labeled auditory nerve fibers in cats. J Comp Neurol 229: 432–450, 1984.[CrossRef][Web of Science][Medline]
Finck A and Berlin CI. Comparison between single unit responses in the auditory nerve amd GSR determined thresholds in mice. J Audit Res 5: 1–9, 1965.
Francis HW, Rivas A, Lehar M, and Ryugo DK. Two types of afferent terminals innervate cochlear inner hair cells in C57BL/6J mice. Brain Res 1016: 182–194, 2004.[CrossRef][Web of Science][Medline]
Greenwood D. Critical bandwidth and the frequency coordinates of the basilar membrane. J Acoust Soc Am 33: 1344–1356, 1961.[CrossRef]
Guinan JJ Jr and Stankovic KM. Medial efferent inhibition produces the largest equivalent attenuations at moderate to high sound levels in cat auditory-nerve fibers. J Acoust Soc Am 100: 1680–1690, 1996.[CrossRef][Web of Science][Medline]
Heffner H and Masterton B. Hearing in glires: domestic rabbit, cotton rat, feral house mouse, and kangaroo rat. J Acoust Soc Am 68: 1584–1599, 1980.[CrossRef]
Henry KR and Lepkowski CM. Evoked potential correlates of genetic progressive hearing loss. Age-related changes from the ear to the inferior colliculus of C57BL/6 and CBA/J mice. Acta Otolaryngol 86: 366–374, 1978.[Medline]
Jimenez AM, Stagner BB, Martin GK, and Lonsbury-Martin BL. Age-related loss of distortion product otoacoustic emissions in four mouse strains. Hear Res 138: 91–105, 1999.[CrossRef][Web of Science][Medline]
Johnson DH. The relationship of post-stimulus time and interval histograms to the timing characteristics of spike trains. Biophys J 22: 413–430, 1978.[Web of Science][Medline]
Johnson DH. The relationship between spike rate and synchrony in responses of auditory-nerve fibers to single tones. J Acoust Soc Am 68: 1115–1122, 1980.[CrossRef][Web of Science][Medline]
Kiang NY-S, Watanabe T, Thomas EC, and Clarke LF. Discharge Patterns of Single Fibers in the Cat's Auditory Nerve. Cambridge, MA: MIT Press, 1965.
Legan PK, Lukashkina VA, Goodyear RJ, Kossi M, Russell IJ, and Richardson GP. A targeted deletion in alpha-tectorin reveals that the tectorial membrane is required for the gain and timing of cochlear feedback. Neuron 28: 273–285, 2000.[CrossRef][Web of Science][Medline]
Li HS and Borg E. Age-related loss of auditory sensitivity in two mouse genotypes. Acta Otolaryngol 111: 827–834, 1991.[Medline]
Li HS, Hultcrantz M, and Borg E. Influence of age on noise-induced permanent threshold shifts in CBA/Ca and C57BL/6J mice. Audiology 32: 195–204, 1993.[Web of Science][Medline]
Liberman MC. Auditory-nerve response from cats raised in a low-noise chamber. J Acoust Soc Am 63: 442–455, 1978.[CrossRef][Web of Science][Medline]
Liberman MC. Morphological differences among radial afferent fibers in the cat cochlea: an electron-microscopic study of serial sections. Hear Res 3: 45–63, 1980.[CrossRef][Web of Science][Medline]
Liberman MC. The cochlear frequency map for the cat: labeling auditory-nerve fibers of known characteristic frequency. J Acoust Soc Am 72: 1441–1449, 1982a.[CrossRef][Web of Science][Medline]
Liberman MC. Single-neuron labeling in the cat auditory nerve. Science 216: 1239–1241, 1982b.
Liberman MC. Central projections of auditory-nerve fibers of differing spontaneous rate. I. Anteroventral cochlear nucleus. J Comp Neurol 313: 240–258, 1991.[CrossRef][Web of Science][Medline]
Merchan-Perez A and Liberman MC. Ultrastructural differences among afferent synapses on cochlear hair cells: correlations with spontaneous discharge rate. J Comp Neurol 371: 208–221, 1996.[CrossRef][Web of Science][Medline]
Mikaelian DO, Warfield D, and Norris O. Genetic progressive hearing loss in the C57-b16 mouse. Relation of behavioral responses to cochlear anatomy. Acta Otolaryngol 77: 327–334, 1974.[Medline]
Mueller M, von Huenerbein K, Silivi Hoidis, and Smolders JWT. A physiological place-frequency map of the cochlea in the mouse. Assoc Res Otolaryngol Abs 382, 2004.
Mullen LM and Ryan AF. Transgenic mice: genome manipulation and induced mutations. In: Handbook of Mouse Auditory Research From Behavior to Molecular Biology, edited by Willott JF. Boca Raton, FL: CRC Press, 2001, p. 457–474.
Muller M and Robertson D. Relationship between tone burst discharge pattern and spontaneous firing rate of auditory nerve fibres in the guinea pig. Hear Res 57: 63–70, 1991.[CrossRef][Web of Science][Medline]
Ohlemiller KK and Echteler SM. Functional correlates of characteristic frequency in single cochlear nerve fibers of the Mongolian gerbil. J Comp Physiol A Sens Neural Behav Physiol 167: 329–338, 1990.[Medline]
Ohlemiller KK, Echteler SM, and Siegel JH. Factors that influence rate-versus-intensity relations in single cochlear nerve fibers of the gerbil. J Acoust Soc Am 90: 274–287, 1991.[CrossRef][Web of Science][Medline]
Ou HC, Harding GW, and Bohne BA. An anatomically based frequency-place map for the mouse cochlea. Hear Res 145: 123–129, 2000.[CrossRef][Web of Science][Medline]
Palmer AR and Russell IJ. Phase-locking in the cochlear nerve of the guinea-pig and its relation to the receptor potential of inner hair-cells. Hear Res 24: 1–15, 1986.[CrossRef][Web of Science][Medline]
Parham K. Distortion product otoacoustic emissions in the C57BL/6J mouse model of age-related hearing loss. Hear Res 112: 216–234, 1997.[CrossRef][Web of Science][Medline]
Prosen CA, Dore DJ, and May BJ. The functional age of hearing loss in a mouse model of presbycusis. I. Behavioral assessments. Hear Res 183: 44–56, 2003.[CrossRef][Web of Science][Medline]
Relkin EM and Doucet JR. Recovery from prior stimulation. I: Relationship to spontaneous firing rates of primary auditory neurons. Hear Res 55: 215–222, 1991.[CrossRef][Web of Science][Medline]
Rhode WS and Smith PH. Characteristics of tone-pip response patterns in relationship to spontaneous rate in cat auditory nerve fibers. Hear Res 18: 159–168, 1985.[CrossRef][Web of Science][Medline]
Rhode WS and Smith PH. Encoding timing and intensity in the ventral cochlear nucleus of the cat. J Neurophysiol 56: 261–286, 1986.
Robles L and Ruggero MA. Mechanics of the mammalian cochlea. Physiol Rev 81: 1305–1352, 2001.
Rosowski JJ, Brinsko KM, Tempel BI, and Kujawa SG.The aging of the middle ear in 129S6/SvEvTac and CBA/CaJ mice: measurements of umbo velocity, hearing function, and the incidence of pathology. J Assoc Res Otolaryngol 4: 371–383, 2003.[CrossRef][Web of Science][Medline]
Rouiller EM and Ryugo DK. Intracellular marking of physiologically characterized cells in the ventral cochlear nucleus of the cat. J Comp Neurol 225: 167–186, 1984.[CrossRef][Web of Science][Medline]
Sachs MB, Winslow RL, and Sokolowski BH. A computational model for rate-level functions from cat auditory-nerve fibers. Hear Res 41: 61–69, 1989.[CrossRef][Web of Science][Medline]
Schalk TB and Sachs MB. Nonlinearities in auditory-nerve fiber responses to bandlimited noise. J Acoust Soc Am 67: 903–913, 1980.[CrossRef][Web of Science][Medline]
Smith PH, Joris PX, and Yin TC. Projections of physiologically characterized spherical bushy cell axons from the cochlear nucleus of the cat: evidence for delay lines to the medial superior olive. J Comp Neurol 331: 245–260, 1993.[CrossRef][Web of Science][Medline]
Smith RL. Short-term adaptation in single auditory nerve fibers: some poststimulatory effects. J Neurophysiol 40: 1098–1111, 1977.
Spoendlin H. Innervation patterns in the organ of Corti of the cat. Acta Otolaryngol 67: 239–254, 1969.[Medline]
Spoendlin H and Schrott A. The spiral ganglion and the innervation of the human organ of Corti. Acta Otolaryngol 105: 403–410, 1988.[Medline]
Tsuji J and Liberman MC. Intracellular labeling of auditory nerve fibers in guinea pig: central and peripheral projections. J Comp Neurol 381: 188–202, 1997.[CrossRef][Web of Science][Medline]
Webster DB and Trune DR. Cochlear nuclear complex of mice. Am J Anat 163: 103–130, 1982.[CrossRef][Web of Science][Medline]
Willott JF. Effects of aging, hearing loss, and anatomical location on thresholds of inferior colliculus neurons in C57BL/6 and CBA mice. J Neurophysiol 56: 391–408, 1986.
Winter IM, Robertson D, and Yates GK. Diversity of characteristic frequency rate-intensity functions in guinea pig auditory nerve fibres. Hear Res 45: 191–202, 1990.[CrossRef][Web of Science][Medline]
Young ED, Robert JM, and Shofner WP. Regularity and latency of units in ventral cochlear nucleus: implications for unit classification and generation of response properties. J Neurophysiol 60: 1–29, 1988.
Zheng QY, Johnson KR, and Erway LC. Assessment of hearing in 80 inbred strains of mice by ABR threshold analyses. Hear Res 130: 94–107, 1999.[CrossRef][Web of Science][Medline]
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