Учебники / Hearing - From Sensory Processing to Perception Kollmeier 2007

4.2Other Implications

The Lombard reflex is characterized by an increase in vocal intensity, when the auditory feedback of the vocalizer’s own voice is masked by noise. It can be found in monkeys and humans (Brumm et al. 2004). Furthermore, deafened kittens and monkeys show an increase in vocal intensity, when compared with normal-hearing animals (Romand and Ehret 1984; Talmage-Riggs et al. 1972). This means that the intensity of one’s own voice is automatically up-regulated if it is less than a critical level above the acoustic background. Earlier studies assumed that the Lombard-reflex arc is located in the brainstem, because of its survival in decerebrated cats (Nonaka et al. 1997). With their unique properties of tonically modulating the afferent sensitivity to selfproduced sounds and little or reversed responding to external sounds, the excitatory AVU in the caudal POR are candidates for mediating the Lombard reflex. Their vocalization-related activity could provide the decisive difference in the cochlear responses to self-produced compared to external sounds over a large range of intensities of external sounds.

5Conclusion

The locations and activity patterns of most audio-vocal neurons with suppressed activity to self-produced vocalizations suggest that they are part of the medial olivocochlear system and function to protect the cochlea against overstimulation by own sounds. The location and activity patterns of most audiovocal neurons with increased activity to self-produced vocalization suggest that they are part of the lateral olivocochlear system. Their function is to modulate the activity of cochlear nerve fibers and/or to control the Lombard reflex.

Acknowledgments. The authors thank Ludwig Ehrenreich for technical support and Roland Tammer for medical support. This study was supported by the Deutsche Forschungsgemeinschaft, Ju 181/16-1.

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data lead to the hypothesis that the influence of lateral inhibition flanking the excitatory receptive fields of neurons is important for the determination of the widths of CBs and for their independence of sound intensity (Ehret et al. 1988; Ehret 1995). The major goal of our present studies on the inferior colliculus in the mouse is to test this hypothesis and to determine the relationship between inhibitory receptive fields and neural CBs.

2Methods

Single unit recordings were taken from the central nucleus of inferior colliculus (ICC) of anesthetized (ketamine, xylazine) house mice Mus musculus, hybrids of outbred strain NMRI and feral mice. For every neuron, the conventional single-tone excitatory tuning curve and two-tone response areas (Egorova et al. 2001, 2002) were measured to get the distribution of excitatory and inhibitory response areas in the neuron’s receptive field. Computercontrolled measurements were taken within the whole frequency range of hearing sensitivity of mouse (3–80 kHz) and over a broad range of sound levels: from the units’ tone-response thresholds up to 80 dB above of them, corresponding to a range of −20 to 90 dB SPL. Estimation of the neural CBs was made by simultaneous narrowband white noise masking with constant noise spectral level and variable bandwidth (96 dB/octave slope of the filter). First, a neuron’s response to tone bursts at its excitatory characteristic frequency (CFE) was masked by a continuous broadband noise. Then, the noise bandwidth was narrowed gradually and separately both from the high frequency and the low frequency sides until the tone response appeared again. The noise bandwidth that was just effective in masking the tonal response directly determined the lower and the upper boarders of the critical bands (Vartanian et al. 1999).

3Results and Discussion

3.1Coding of Critical Band Properties

The data presented here are based on recordings from 76 neurons. The main properties of the neuronal CBs in mouse ICC, their dependence on neuron’s CFE and sound intensity, are shown in Fig. 1a,b (Vartanian et al. 1999). Regression analysis (see equation and regression line as solid line in Fig. 1a) showed with high statistical significance (p<0.001) that CBs increased with an increase in the neuron’s CFE. This frequency dependence of neural CBs is very similar to the frequency dependence of psychophysically measured CBs in the mouse (Ehret 1976, line with open circles in

Fig. 1 a Critical bandwidths (left ordinate) measured in single units of the inferior colliculus (closed symbols) and from behavioral tests (line with open symbols; Ehret 1976) of the mouse as a function of the units’ characteristic frequencies or tone frequencies (abscissa). The regression line (solid line) of neural data follows the equation indicated in the figure. The line with closed symbols shows the relationship between cochlea place (in mm from the apex, right ordinate) and the representation of frequencies (abscissa). b Critical bandwidths (ordinate) of single units of the mouse inferior colliculus as a function of the sound pressure level of tones above response threshold (abscissa)

Fig. 1a). Both frequency dependencies of CBs agree with the pattern of frequency representation along the basilar membrane in house mice (Ehret 1975). Hence, the average CFE dependence of CBs reflects the general property of the auditory system which is the dependence of the auditory frequency resolution on the cochlear tonotopy.

The independence of neural CBs from sound intensity becomes evident in Fig. 1b. On average, neural CBs remain constant over an intensity range of up to at least 70 dB above the neurons’ tone-response thresholds. Thus, the fundamental properties of frequency resolution and critical band formation in hearing are present in the average activity of neurons in the mouse auditory midbrain.

3.2Critical Bands and Neural Excitatory and Inhibitory Receptive Fields

The ICC neurons have been divided into four classes based on the shape parameters of their excitatory frequency response areas, the steepness of slopes on the two sides of the excitatory frequency response areas, and the degree of overlap of excitatory and inhibitory frequency response areas (Vartanian et al. 2000; Egorova et al. 2001). Examples of the receptive fields of neurons of the four classes are shown in Fig. 2. The percentages of neurons in the classes were the following: class I, 35.5%; class II, 31.5%; class III, 29%; class IV, 4%.

Besides one or two excitatory characteristic frequencies (CFE), neurons often display two characteristic frequencies of inhibition, one below (CFLI)

Fig. 2 Examples of receptive field properties of single neurons of the four classes (class I–IV) of the mouse inferior colliculus. Excitatory response areas are indicated by stippling, inhibitory response areas by shades of gray (light gray: partial inhibition, dark gray: total inhibition). Critical bands (solid horizontal lines) are indicated for the different signal levels above the CFE threshold. CFE: neuron’s excitatory characteristic frequency; CFLI: characteristic frequency of inhibition below the CFE; CFHI: characteristic frequency of inhibition above the CFE; CFEL: lowfrequency CFE of class IV neuron; CFEH: high-frequency CFE of class IV neuron; CFCI: characteristic inhibitory frequency of central inhibitory area of class IV neuron. Abscissa: frequency, kHz; ordinate: sound level, dB SPL

and one above (CFHI) the CFE. The position of the CFLI and CFHI relative to the position of the CFE indicate whether or not lateral inhibition starts close to the center of the excitatory response area of a neuron and whether the neuron may be more sensitive to excitatory or inhibitory influences. Usually, class II neurons had the largest inhibitory areas with the strongest inhibition often covering a large part of the excitatory area. Inhibition in class I neurons never extended through the excitatory area. In class III neurons, inhibition was usually weak and inhibitory areas small or only unilateral.

The borders of the critical bands as indicated in Fig. 2 correlated with the shapes of excitatory and inhibitory response areas (Vartanian et al. 2000). CBs always extended at least through part of the excitatory area and often ended in the inhibitory areas. CBs never extended through areas of total inhibition, i.e. through areas in which a tone led to a total inhibition of the neuron’s response to a CFE tone. Thus, areas of total inhibition (dark gray areas in Fig. 2) always marked the limits of the critical band filters. The same relationship between inhibitory response areas and extensions of CBs has been found also in neurons of the cat ICC (Ehret and Merzenich 1988).

3.3Borders of Critical Bands and Characteristic Frequencies of Inhibition

The quantitative evaluation of the borders of CBs in relationship with the characteristic frequencies of inhibition showed highly significant correlations (p < 0.001) in class I–III neurons as indicated by the correlation coefficients

(r) of the linear regression lines in Fig. 3. Data of class IV are not included in this analysis because only few (3) neurons have been recorded. The slopes of the regression lines of the high-frequency borders of the CBs (CBHF) vs the characteristic frequencies of the high-frequency side inhibition (CFHI) are all very close to 1.0 indicating that the high-frequency borders of the neural critical bands are determined by the characteristic frequencies of the highfrequency inhibitory fields. The high-frequency borders of neural CBs (CBHF) can be calculated by subtracting 1.6 kHz (class I), 1.8 kHz (class II) or 3.4 kHz (class III) from the values of the characteristic frequencies of high-frequency inhibitory fields (CFHI). Thus, it is evident that, on average, CBs are strongly restricted in their extension towards high frequencies by the presence of high-frequency lateral inhibition.

The slopes of the regression lines of the low-frequency borders of the CBs (CBLF) vs the characteristic frequencies of the low-frequency side inhibition (CFLI) are close to 1.0 only for class I and class II neurons. For these neurons, the low-frequency borders of CBs (CBLF) can be calculated by adding 3 kHz (class I) or 1.7 kHz to the values of the characteristic frequencies of the lowfrequency inhibitory fields (CFLI). Compared to the high-frequency side, this adding of a frequency range to the CFLI in order to obtain the CBLF indicates that, on average, the inhibition on the low-frequency side is not as strong as on the high-frequency side to stop the extension of the CBs. It is clear,

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