Учебники / Hearing - From Sensory Processing to Perception Kollmeier 2007

Fig. 3 Activation to low-frequency FM-tones as a function of stimulus intensity level or, equivalently, loudness level. The gray band indicates the 95% confidence interval of the quadratic polynomial fit through the data points of all subjects collectively

Table 1 The rate of increase in brain activation (mean±standard error [10−3%/dB]) in subjects with normal or impaired hearing, as a function of the physical intensity level (in dB SL) or perceptual loudness level (in dB EL) of the two stimulus types. The hypothesis that both subject groups show equal increase in activation was tested using an independent samples T-test, and rejected only for the high-frequency stimuli when calculated as a function of sound intensity level

In all individual subjects the activation increased significantly with the stimulus level (p<0.05). The average rates of increase in activation are listed in Table 1 for both subject groups. The increase rates did not differ significantly between the two groups.

3.2High Frequency Activation

The activation levels in response to the high-frequency stimuli are shown in Fig. 4.

a

b

Fig. 4 Activation to high-frequency FM-tones as a function of: a physical stimulus intensity level; b perceptual stimulus loudness level. Differences between the two subject groups were significant as a function of intensity level, but not as a function of loudness level. The gray band indicates the 95% confidence interval of the quadratic polynomial fit through the data points of all subjects collectively

Again, in all individual subjects the activation increased significantly (p<0.05) with stimulus intensity level (Fig. 4a). Moreover, in the impaired subjects the activation increased significantly more strongly as a function of stimulus intensity level than in the normal hearing subjects (Table 1).

The observed difference in brain activation between the two subject groups may be a direct reflection of the loudness recruitment phenomenon. To test this hypothesis, Fig. 4b displays the activation levels as a function of the equivalent loudness level. In all individual subjects the activation increased significantly with loudness level (p<0.05). However,

in contrast with the findings as a function of intensity level, the difference in the activation increase rate between both groups if calculated as a function of loudness level was not significant (Table 1).

4Discussion and Conclusions

In summary, we found that the loudness level of stimuli, in contrast with intensity level, related strongly to cortical brain activation even for groups of subjects with vastly different sound perception.

For the low-frequency stimuli, both groups of subjects displayed normal hearing thresholds and the fMRI response level did not show a significant difference in the rate of increase with sound level. However, for the high-frequency stimuli, hearing thresholds in the impaired subjects were worse than those in subjects with normal hearing. In addition, loudness recruitment was observed, as the equivalent loudness of high-frequency stimuli increased more strongly with intensity in impaired subjects than in normally hearing subjects. We also found that the cortical activation increased more strongly with intensity in impaired subjects than in normally hearing subjects. This suggests that the cortical activation level reflects stimulus loudness more closely than stimulus intensity. Indeed, in spite of the severely disturbed perception in the impaired subjects, the increase in cortical activation was not significantly different between both subject groups if expressed as a function of loudness.

While loudness recruitment is a symptom that is commonly associated with inner ear impairment, the corresponding neural mechanisms are poorly understood. It has been reported that the afferent signals in the auditory nerve fibers do not provide a simple representation of the excitation of the basilar membrane in people that display loudness recruitment (Heinz and Young 2004). Therefore, it remains unclear how the loudness percept is generated by the brain from available input signals, especially in pathological conditions.

The present study is the first to document the cortical responses related to loudness recruitment in humans using fMRI. Previous magnetoencephalography (MEG) studies have suggested that brain activity increases abnormally quickly with stimulus intensity in individuals with loudness recruitment (Morita et al. 2003). Our results agree with such findings and confirm that cortical activity is more closely related to the perceptual loudness level of sound than to its intensity level. This suggests that fMRI activation can be interpreted as a correlate of the subjective strength of the stimulus percept.

In contrast with suggestions that brain activation reflects the physical stimulus attributes in primary sensory cortices and relates to the stimulus percept only at higher levels of processing in the frontal cortices (de Lafuente and Romo 2005), we found that activation correlates well with perceptual attributes already at the level of the auditory cortices in the temporal lobes.

234 D. Langers et al.

References

de Lafuente V, Romo R (2005) Neuronal correlates of subjective sensory experience. Nat Neurosci 8:1698–1703

Hall DA, Haggard MP, Akeroyd MA, Palmer AR, Summerfield AQ, Elliott MR, Gurney EM, Bowtell RW (1999) “Sparse” temporal sampling in auditory fMRI. Hum Brain Mapp 7:213–223

Heinz MG, Young ED (2004) Response growth with sound level in auditory-nerve fibers after noise-induced hearing loss. J Neurophysiol 91:784–795

Jäncke L, Shah NJ, Posse S, Grosse Ryuken M, Muller Gartner HW (1998) Intensity coding of auditory stimuli: an fMRI study. Neuropsychologia 36:875–883

McDermott HJ, Lech M, Kornblum MS, Irvine DR (1998) Loudness perception and frequency discrimination in subjects with steeply sloping hearing loss: possible correlates of neural plasticity. J Acoust Soc Am 104:2314–2325

Morita T, Naito Y, Nagamine T, Fujiki N, Shibasaki H, Ito J (2003) Enhanced activation of the auditory cortex in patients with inner-ear hearing impairment: a magnetoencephalographic study. Clin Neurophysiol 114:851–859

Oxenham AJ, Bacon SP (2003) Cochlear compression: perceptual measures and implications for normal and impaired hearing. Ear Hear 24:352–366

Comment to (Lütkenhöner and) Langers by Chait

In both studies, I wonder how much the responses observed are related to the properties of the acoustic environments in which the listeners operated. In general, does it make sense at all to talk about “perceptual loudness” without considering the specific acoustic context?

In Langers’ fMRI experiment, responses were recorded while listeners were exposed to high intensity machine noise.

In Lükenhöner’s experiments, stimuli with different intensities were presented in a randomized manner. Since your stimulus set included mostly low intensity stimuli, and since we know that listeners adjust to the properties of their acoustic environments (e.g. Dean et al. 2005) could it be that the particular stimulus set that you used influenced the responses you measure? Specifically, responses to rare high intensity stimuli might be different from those you might have observed if they were less rare. Similarly, might you have observed different responses to low-intensity stimuli if your mean intensity (across stimuli) was still lower?

References

Dean I, Harper NS, McAlpine D (2005) Neural population coding of sound level adapts to stimulus statistics. Nat Neurosci 8:1684–1689

Reply by Langers

I fully agree that the loudness percept will depend on the context, with regard to acoustic aspects (e.g. background noise) and possibly also with regard to other

aspects (e.g. subject alertness). Although, in this study, listeners were exposed to high intensity machine noise, a sparse acquisition paradigm was used such that stimuli were presented during long periods of silence (8 s) between consecutive scans, limiting forward/backward masking effects to negligible levels. However, other sources of ambient noise were inevitably present (e.g., a helium pump) that can indeed have affected the perceived loudness. In fact, stimuli at threshold (as determined in silence) were reported to be completely imperceptible in the noisy MR-environment. Still, the 10-dB stimuli were clearly audible. Also, the loudness of both low and high frequency stimuli will be affected by the presence of background noise, such that the resulting mismatch in loudness between the stimulus pairs in this experiment due to the difference in acoustic environment will likely be limited to values well below 10 dB; the higher intensity stimuli are expected to be affected less than that. In comparison, the reduction in dynamic range of intensities related to loudness recruitment in the included patients was much larger.

In summary, in my opinion this comment is certainly justified, but in practice the conclusion that fMRI brain activation more closely reflects stimulus loudness than stimulus intensity will remain valid.

Comment by Verhey

In your fMRI study you showed a more or less linear relation between activation and perceived loudness. You found some deviations at very low and at very high levels. Could this deviation be a consequence of the loudness scale used n the study. The perceived loudness was expressed on a scale which is essentially a phon scale. Would the authors expect a different relation (maybe even linear over the whole level range), if they used a different loudness scale such as the sone-scale?

Reply

Given that the non-linearities in the fMRI activation level as a function of stimulus intensity level had a negative sign when significant, with the strongest effects occurring near threshold, and given that the sone scale shows similar characteristics, the deviations from linearity in brain activation should be expected to become smaller when expressed as a function of loudness in sones, as compared to a phon-like scale. This is especially the case for the low-frequency data, for which non-linearities and threshold effects were strongest. In addition, some of the variability between subjects could possibly be accounted for, if there is a corresponding variability in loudness judgment (in sones).

However, although our data indicate that brain activation is more closely related to perceived stimulus levels (i.e., loudness measures) than to stimulus presentation levels (i.e., intensity measures), the variance in the activation data is too large to assess whether fMRI brain activation levels are a better neural correlate for either phon-based loudness or sone-based loudness scales.

analogue by a D/A converter (TDT DA 3-2) and low pass filtered at 8 kHz (TDT FT6). The output of the low pass filter was attenuated by a programmable attenuator (TDT PA4), led to a headphone buffer (TDT HB6), and presented monaurally via headphones (TDH 39).

In the loudness scaling procedure the stimuli were generated in Matlab with a sampling rate of 44.1 kHz. The stimuli were played by an Echo Audio Gina sound card, led to a headphone buffer (TDT HB6), and presented monaurally via headphones (TDH 39).

All noises were low-noise noise (LNN) with a peak factor, defined as W = x4 / `x2j2 of approximately 1.7 for each bandwidth applied in the experiments. The noises were generated from pink noise with a method similar to the method described by Kohlrausch et al. (1997). Besides restricting the bandwidth by zeroing the components in the power spectrum outside the original bandwidth, a pink noise was created by performing an appropriate amplitude transformation. The entire procedure provided a pink noise with a well-defined bandwidth. The noises were gated with a raised-cosine rise and fall of 6.67 ms. The nominal duration of such a rise and fall is 1.67 ms shorter than the duration between the half-amplitude points and amounts thus to 5.0 ms. The intensity level of the reference signal was roved between 54 dB SPL and 66 dB SPL.

The test and reference signals were band-limited noise signals geometrically centered around 2000 Hz. In the loudness matching procedures the reference signal had a bandwidth of 800 Hz and the test signals had bandwidths of 1600, 3200, and 6400 Hz. Two durations were measured: 25 and 1000 ms. In the loudness scaling procedure no reference bandwidth was needed and test signals had bandwidths of 400, 3200 and 6400 Hz. Two durations were measured: 25 and 400 ms. The calibration of all signals was based on the longterm rms level of each signal measured in dB SPL. Sound pressure levels were measured using the artificial ear B&K 4153 and the sound level meter B&K 2260 Investigator.

2.2Procedures

The first loudness matching procedure (called matching 1) was an adaptive two-interval, two-alternative forced choice procedure similar to the procedure used by Verhey and Kollmeier (2002). In each trial the subject heard two sounds, a reference signal and a test signal, separated by a 400-ms silent interval. Test and reference signals were presented in random order and with equal a priori probability. The listeners indicated which signal was louder by pressing a button on a two-button console. A simple one-up one-down procedure was used, which converges at the 50% point of the psychometric function. The initial step size of 4 dB was decreased to 2 dB after the second reversal in the adaptive tracking procedure and held constant for the next eight reversals. To reduce biases several interleaved tracks were used.

The second loudness matching procedure (called matching 2) is a variation on the first procedure (van Beurden and Dreschler 2005) and was intended to increase the accurateness of the loudness matching procedure. Matching is a very difficult task, especially around the equal loudness point. This procedure was designed to make matching close to the equal loudness point easier by changing the task from differentiating the louder of two signals to discriminating if there is a loudness difference in a signal pair or not. Instead of comparing the loudness of two signals, the task is to compare the loudness differences of two sound pairs. In each trial the subject heard two pairs of sounds, each pair consisting of a reference signal and a test signal, separated by 400 ms. The two sound pairs were separated by 800 ms. The reference signal had the same level in both pairs, but – at random – one of the two test signals had a level increase of 2 dB (this value is just above the just noticeable difference; see Ozimek and Zwislocki (1996). In each stimulus presentation the position of test and reference was randomized, but the order was the same for both sound pairs in a single presentation.

Listeners indicated in which sound pair the loudness difference was larger by pressing a button. A simple one-up one-down procedure was used, converging to the 50% point of the psychometric function. If a listener indicated that the interval containing the intensity increase had the greater loudness difference, the levels of the test signals were decreased – otherwise they were increased.

All starting levels were chosen randomly from a set of levels ranging from − 6 to 6 dB with respect to the level of the reference signal. The initial step size of 4 dB was decreased to 2 dB after the second reversal in the adaptive procedure and held constant for the next eight reversals. A reversal was defined as a change in choice for the interval with the greater loudness difference between, the interval with and without the 2-dB level increase. The level difference between test and reference signal yielding the same loudness was determined by calculating the average of the levels within the uncertainty region for the last six reversals (Fig. 1). Randomization of the position of the 2-dB level increase ensured that subjects were not able to follow the adaptive procedure.

We expected this task to be less sensitive to a shift to the comfortable loudness level and to ignoring the fixed reference sound compared to the task in the conventional procedure. Because of this assumption and because presentation of one track at a time lets the subjects better focus their attention to the small loudness differences of the signals under consideration, no interleaving tracks were applied in this procedure. Roving is applied to help the subject to focus on loudness and to ignore other differences as pitch.

The loudness scaling procedure used was the Oldenburg-Adaptive CAtegorical LOudness Scaling (ACALOS) procedure designed by Brand and Hohmann (2002). This is a loudness scaling procedure with 11 response categories, 5 named categories, 4 un-named intermediate categories and 2 limiting categories, which correspond to categorical loudness levels from 0 to 50. The level assigned to a given loudness category x is termed the “categorical loudness level” Lx.