Medical Research Council, Institute of Hearing Research, University of Nottingham, Nottingham NG7 2RD, United Kingdom
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ABSTRACT |
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Palmer, Alan R.,
Dan Jiang, and
David McAlpine.
Desynchronizing responses to correlated noise: a mechanism for binaural
masking level differences at the inferior colliculus. We
examined the adequacy of decorrelation of the responses to dichotic
noise as an explanation for the binaural masking level difference
(BMLD). The responses of 48 low-frequency neurons in the inferior
colliculus of anesthetized guinea pigs were recorded to binaurally
presented noise with various degrees of interaural correlation and to
interaurally correlated noise in the presence of 500-Hz tones in either
zero or interaural phase. In response to fully correlated noise,
neurons' responses were modulated with interaural delay, showing
quasiperiodic noise delay functions (NDFs) with a central peak and side
peaks, separated by intervals roughly equivalent to the period of the
neuron's best frequency. For noise with zero interaural correlation
(independent noises presented to each ear), neurons were insensitive to
the interaural delay. Their NDFs were unmodulated, with the majority
showing a level of activity approximately equal to the mean of the
peaks and troughs of the NDF obtained with fully correlated noise.
Partial decorrelation of the noise resulted in NDFs that were, in
general, intermediate between the fully correlated and fully
decorrelated noise. Presenting 500-Hz tones simultaneously with fully
correlated noise also had the effect of demodulating the NDFs. In the
case of tones with zero interaural phase, this demodulation appeared to
be a saturation process, raising the discharge at all noise delays to
that at the largest peak in the NDF. In the majority of neurons,
presenting the tones in
phase had a similar effect on the NDFs to
decorrelating the noise; the response was demodulated toward the mean
of the peaks and troughs of the NDF. Thus the effect of added tones on
the responses of delay-sensitive inferior colliculus neurons to noise
could be accounted for by a desynchronizing effect. This result is
entirely consistent with cross-correlation models of the BMLD. However,
in some neurons, the effects of an added tone on the NDF appeared more
extreme than the effect of decorrelating the noise, suggesting the
possibility of additional inhibitory influences.
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INTRODUCTION |
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The binaural masking level difference (BMLD) is a
much investigated psychophysical phenomenon in which signals presented
to both ears, masked by a noise to both ears, are made more audible by
changes in the interaural phase of the masker or signal (Hirsh 1948; Licklider 1948
; see Colburn
1996
and Durlach and Colburn 1978
for
comprehensive reviews). A specific, well-documented case is the masking
of a 500-Hz tone that is identical at the two ears (So) by a noise that
is identical at the two ears (No). The 500-Hz tone can be made 12-15
dB more audible by inverting either the tone (S
) or the noise (N
)
at one ear but not both.
An account of the mechanisms of the BMLD can be given in terms of a
network of neurons that are sensitive to the interaural delay of the
signal (Colburn 1977). Such a network, consisting of
coincidence detectors fed by a series of delay lines, was first proposed by Jeffress (1948)
as an explanation of low-frequency binaural
hearing. This model can also be applied specifically to account for
binaural unmasking. In the case of the 500-Hz BMLD task described
previously, the model proposes that neurons perform a cross-correlation
of the activity in a single-frequency channel. Within that channel,
centered at the tone frequency, filtered noise components are
identical. Adding identical tones to the noise at the two ears produces
the same within-channel phase shifts, leaving the responses to the
noises still synchronized with each other. At most, the extra energy
within the channel results in a slightly higher discharge rate at the
coincidence detector output. However, when
-phase tones are added,
the within-channel noise components from each ear are subject to
unequal phase shifts, and the result is a desynchronization of the
inputs to the coincidence detector and hence a lower output. The
asymmetry between the extra coincident spikes caused by addition of
identical tones and the reduction in coincident spikes caused by
-phase tones underlies their improved detectability and hence the
BMLD.
In support of the general cross-correlation model, there is good
physiological evidence to indicate that medial superior olivary (MSO)
neurons act as interaural cross-correlators (Spitzer and Semple
1995; Yin and Chan 1990
), characteristics also
evident in the projection target of the MSO, the inferior colliculus
(IC) (Kuwada and Yin 1983
; Yin and Kuwada
1983a
,b
). Responses of many low-frequency IC neurons are
modulated with the interaural delay of binaural signals, showing
maximum discharge rates (peaks) at certain delays and minimum discharge
rates (troughs) at others. For tonal stimuli, the effect is to produce
a periodic delay function, the period being equal to that of the
stimulus waveform. For noise stimuli, the effect is to produce a damped
oscillatory (or quasiperiodic) noise delay function (NDF), which
commonly contains a central peak and attenuated side peaks separated
from the central peak by the period of the neuronal best frequency (BF)
(Yin et al. 1986
, 1987
). Reducing the interaural
correlation of dichotically presented noises demodulates the NDF
(Yin et al. 1987
); irrespective of the interaural delay,
neurons show a level of activity approximately equal to the mean of the
peaks and troughs of the NDF obtained with fully correlated noise. This
provides additional support for the cross-correlation model of
low-frequency binaural hearing.
In investigations into the neural basis of the BMLD, we found that
inverting the phase of a masked 500-Hz tone at one ear made it
detectable at a lower sound level in a majority of IC neurons
(Jiang et al. 1997a,b
). Inversion of the noise in one ear made So tones more detectable (unpublished data). Further, we found
that the most sensitive indicator of the presence of the S
tone in
No noise was a decrease in the level of activity caused by the masking
noise. For any specific IC neuron, the response to S
tones was
predictable from its sensitivity to the interaural delay of tones and
noises and could consist of either an increase or a decrease in the
discharge rate. These empiric physiological data are in good agreement
with cross-correlation models of the BMLD.
Here we investigate the adequacy of the desynchronization model to account for the BMLD at the neuronal level. Specifically, we examine whether desynchronization provides a sufficient explanation for the reduced levels of activity that we found in neurons of the IC when a 500-Hz tone signal was added to masking noise. We compared the activity of neurons to noises with different interaural correlation (producing desynchronization of the noise) to that when an identical binaural noise is presented simultaneously with a tonal signal. In the majority of instances, it appears that the reduced activity caused by addition of the 500-Hz signal could be accounted for by desynchronization of the activity due to the No noise. In some instances, however, the reduction in activity caused by the 500-Hz signal exceeded that predicted simply by desynchronization and could be a result of inhibition.
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METHODS |
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Anesthesia and surgical preparation
We recorded from 48 neurons in the ICs of 23 pigmented guinea
pigs weighing between 300 and 430 g, all of which were used in
experiments examining other aspects of low-frequency binaural processing. The small numbers of neurons analyzed in any one animal were not different qualitatively or quantitatively from the larger sample analyzed for other purposes. The animals were premedicated with
atropine sulfate (0.06 mg sc) and anesthetized with urethan (1.3 g/kg
in 20% solution ip). Further analgesia was obtained with phenoperidine
(1 mg/kg im). Supplementary doses of phenoperidine (0.5-1 mg/kg im)
were given on indication provided by the pedal withdrawal reflex. All
animals were tracheotomized, and core temperature was maintained at
37°C with a heating blanket. In some cases, the animal was
artificially ventilated with 95% oxygen-5% CO2, and
end-tidal CO2 was monitored. The animal was placed inside a
sound-attenuating room in a stereotaxic frame with hollow plastic specula replacing the ear bars. Pressure equalization within the middle
ear was achieved by a narrow polythene tube (0.5-mm external diam)
sealed into a small hole in the bulla on each side. The cochlear
condition was assessed by monitoring the cochlear action potential
(CAP) in the left ear at intervals throughout the experiment by using a
silver wire electrode on the round window. The threshold of the
filtered and amplified CAP to a series of short-tone bursts was
measured automatically (Palmer et al. 1986) at
selected frequencies (0.5, 1, 2, 4, 5, 7, 10, 15, 20, and 30 kHz). The
acoustic cross-talk between the two ears of our closed-field acoustic
system was previously reported; at frequencies from 0.5 to 10 kHz the
cross-talk was >50 dB down and was >45 dB at all frequencies
(Palmer et al. 1990
). These values are similar to those
reported in other studies in the guinea pig (Popelar et al.
1988
; Teas and Nielsen 1975
).
A craniotomy was performed on the right side, extending 2-3 mm rostral
and caudal of the interaural axis and 3-4 mm lateral from midline.
After removal of the dura, the exposed brain was covered with 1.5%
agar. Recordings were made with stereotaxically placed
tungsten-in-glass microelectrodes (Bullock et al. 1988) advanced by a piezoelectric motor (Burleigh Inchworm, IW-711-00) into
the IC through the intact cortex.
Stimulus presentation
The stimuli were delivered through sealed acoustic systems that consisted of a 12.7-mm condenser earphone (Brüel and Kjaer 4134), coupled to a damped 4-mm diam probe tube that fitted into the speculum. The outputs were calibrated a few millimeters from the tympanic membrane with a Brüel and Kjaer 4134 microphone fitted with a calibrated 1-mm probe tube. The sound system response on each side was flat to within ±5 dB from 0.1 to 10 kHz, and the left and right systems were matched to within ±2 dB over this range.
Stimuli
The stimuli used in this study were tones and noises presented
to the two ears. The noises used were digitally synthesized "frozen" noise with a bandwidth of 0.05-5 kHz and output at a sampling rate of 50 kHz via a digital-analog converter (TDT QDA2) and a
waveform reconstruction filter (Kemo VBF33, cutoff 5 kHz, slope 135 dB/octave). The noises were gated on and off with a 5-ms ramp, and
interaural delays were introduced during synthesis. Two independent
noise samples were synthesized with the method of Klatt (1980) in which
each sample is the sum of 16 values from a random number generator. The
noises were digitally filtered with a pass-band of 0.05-5 kHz. The
noise to the left ear was always the same frozen noise sample, whereas
that to the right was the sum of the two independently synthesized
noises. The proportions of the independent noises added together to
produce the right ear noise were selected to give specific values of
interaural correlation as described by Yin et al. (1986). The values
required for the noise scaling factors were first computed
theoretically to give interaural correlation values ranging from 0.0 (completely independent noises) to 1.0 (the same noise applied to both
ears) in increments of 0.1 by using the following equation
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(1) |
The 500-Hz tones used in conjunction with the noise were generated by a
Hewlett Packard 3325A waveform synthesizer and were presented to the
ears via a digital delay line set either to produce So (i.e.,
synchronous gating) or S (the tone to the right ear was delayed by
one half period of the tone frequency). The two-channel digital delay
line enabled the interaural delays of the tones to be set by computer
or manually with a resolution of 1 µs. The tone waveform was not
phase locked to the frozen noises. The tones were gated on and off
simultaneously with the noise stimuli.
Other tonal stimuli were digitally synthesized and output from a digital analog converter (TDT QDA2) and a waveform reconstruction filter (Kemo VBF33, cutoff 5 kHz, slope 135 dB/octave).
Data collection and analysis
Single neurons were isolated with 50-ms tone and/or noise bursts as search stimuli. The extracellularly recorded neural action potentials were amplified (Axoprobe 1A: ×100, and a further ×10 by using an in-house amplifier), filtered (155-1,800 Hz), converted to logic pulses by an amplitude discriminator and timed with 10-µs resolution (CED 1401 plus). The lowest binaural threshold to interaurally in-phase tones and the frequency at which it was obtained (BF) were determined audiovisually. The spontaneous rate was routinely measured over a 10-s period in the absence of controlled acoustic stimulation.
The following analyses were carried out in this study.
FREQUENCY-RESPONSE AREAS. These were obtained by presenting 50-ms tone bursts in a pseudorandom order at a rate of 5/s covering a frequency range from two octaves above to four octaves below the unit's BF in steps of 0.12 octaves and over a sound level range of 100 dB in 5-dB steps. The number of spikes elicited by a single frequency and level combination was counted and after smoothing displayed as graded blocks with densities proportional to the spike count at the appropriate frequency and level position. This analysis was run binaurally with a fixed interaural delay of zero interaural time delay (ITD) across all frequencies.
INTERAURAL PHASE DIFFERENCE (IPD) HISTOGRAMS.
IPD histograms were measured with binaural beat stimuli (Kuwada
et al. 1979). Digitally synthesized tones that differed by 1 Hz
to the two ears were used, resulting in a linear change in the binaural
phase disparity at a rate of 360°/s. The frequency of the signal
delivered to the left ear (contralateral to the recording site) was
always 1 Hz greater than that delivered to the right (ipsilateral) ear.
The duration of the stimulus was 3,000 ms, which included three
complete cycles of the entire range of possible IPDs. The stimulus was
repeated 10 times with an interstimulus interval of 6.5 s. The
best IPD, the corresponding mean best delay for the signal (SBD), and
the vector strength for each frequency were computed from the combined
middle two cycles (over the middle 2 s of the stimulus duration)
by using the method described by Goldberg and Brown (1969)
and Yin and
Kuwada (1983a)
. All neurons were tested with BF tones and with 500-Hz
tones. Because we were concerned with the most common BMLD condition we
only then analyzed units which responded to 500 Hz.
NDFS. NDFs were measured by presenting frozen noises with interaural time disparities over a range equal to 3 times the period of the neuron's BF, in 52 equal delay steps, starting from ipsilateral leading. The duration of the stimulus was 320 ms with three repetitions presented at one per second. NDFs were measured for a range of interaural correlations of the noise and also for noise identical at the two ears (No) in the presence of synchronously gated 500-Hz tones at a range of tone levels.
MASKED RATE-LEVEL FUNCTIONS (MRLFS).
MRLFs were obtained by running tone rate-level functions in the
presence of a noise masker at a fixed level. The masker noise was
either No or N (inverted at 1 ear). Tone rate-level functions were
generated by presenting tones (50-ms duration, rise-fall time 1 ms) and
noise (5 kHz bandwidth) simultaneously and varying the level of the
tone pseudorandomly over a maximum range of 100 dB in 1-dB steps. The
fixed noise level was arbitrarily chosen to be 7-15 dB above the No
noise threshold, a level at which a reasonable No-driven response and a
well-tuned NDF was obtained. Similar levels were used for the N
noise. Possible order effects were minimized by ensuring that each
stimulus was never >50 dB weaker than the one preceding it. The number
of spikes elicited by each tone was counted, and the average MRLF was
computed from 10 presentations at each level. The frequency of the tone
used was 500 Hz either interaurally in phase (So) or out of phase
(S
). The stimulus presentation consisted of alternating the
signal-plus-noise and the noise alone at a rate of 5/s. Only the
discharges in the signal-plus-noise interval were used to construct the
MRLFs.
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RESULTS |
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First, to provide the context for the desynchronization study, we provide examples of the discharge rate reductions in the IC that result from adding tones to noises.
Responses of IC neurons to signals evoking BMLDs
NOSO VERSUS NOS.
The MRLFs of two single neurons in the IC to 500-Hz So and S
tones
in the presence of No noise are illustrated in Fig.
1. Depending on the delay sensitivity to
tones and noise, the No noise is more or less effective in evoking a
steady level of neural activity, and the 500-Hz tones may cause either
increases or decreases in the noise-evoked activity. For the units
shown in Fig. 1, the So tone simply increases the discharge rate.
However, although the S
tone causes an increase in the discharge
rate over and above that caused by the noise, for the unit shown in
Fig. 1A, it causes a reduction in the discharge rate of the
unit in Fig. 1B. The relationship of such discharge rate
changes to the neuron's delay sensitivity was described in detail
elsewhere (Jiang et al. 1997a
,b
). The arrows in Fig. 1
indicate the masked thresholds for 500-Hz tones determined by a method
based on signal detection theory (Jiang et al. 1997a
),
and it can be seen that S
tones were often detectable at a lower
sound level than So tones, even in individual units. Thus the units in
Fig. 1 exhibit BMLDs in the same direction as the psychophysical data.
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NOSO VERSUS NSO.
The two units in Fig. 2 show the effects
of increasing the level of So tones in the presence of No and N
noises. The majority of units have a peak in their NDF near zero delay,
and the No noise is more effective in driving the unit than the N
noise (Fig. 2A). As the So tone is steadily increased in the
presence of either No or N
noise the discharge rate is increased in
Fig. 2A. However, for those units whose delay function is
characterized by a trough rather than a peak near zero interaural delay
(see Palmer et al. 1990
; Yin et al.
1986
), N
noise is more effective than No noise (Fig.
2B). Thus the unit shown in Fig. 2B is better activated by N
noise, and the So tone (also located at or near the
trough region) produces decreases in discharge rate in the presence of
either the No or N
noise. For the unit shown in Fig. 2B
the high level of activity caused by the N
noise is considerably reduced by the increasing level of the So tone. The No noise is relatively ineffective in driving the unit, but the So tone still produces a further decrease in discharge rate. The So tones produced increased response at a relatively high level in the presence of both
No and N
noise (possibly because the output is dominated by monaural
coincidences) (see Han and Colburn 1993
). The vertical arrows in Fig. 2 indicate the masked thresholds for the 500-Hz tones
computed with signal detection theory. In the examples shown the
threshold of the So signal in N
noise is lower for one of the units
(Fig. 2A) but higher for the other. Over our complete sample
of data measured in noise at 10 dB above threshold the So signal was
detectable at a lower level in N
noise than No noise in 33 of 62 neurons (unpublished data).
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Responses to noise as a function of the interaural cross-correlation
When the noise at the two ears is fully correlated (identical),
the NDF (Fig. 3, solid squares) has
pronounced peaks and troughs separated by a period equal to the unit BF
(see McAlpine et al. 1996; Palmer et al.
1990
; and Yin et al. 1986
). In all instances, the NDF became progressively less modulated as the interaural correlation of the noise was reduced. At zero interaural correlation, all but 1 of the 48 neurons showed NDFs that were not modulated with
interaural time delay. The one neuron that did not show a flat NDF, by
using uncorrelated noise, was one of seven neurons from earlier
experiments in which short-duration (50 ms) noise bursts were used.
This neuron (Fig. 3D) still showed some structure to its
NDF, although the variation in discharge rate with ITD was
substantially attenuated. However, the effect of decorrelating the
noise was not entirely stereotypical in that, although in Fig.
3A there was a progressive demodulation of the NDF toward the mean value of the function for a correlation of 1.0 (dotted horizontal line), in Fig. 3B an interaural correlation of
0.8 led to a small increase in the discharge across all delays. Also, the unit in Fig. 3D showed a decline in discharge rate at
all delays when the correlation was reduced from 1.0 to 0.8, and
subsequent decreases produced demodulation toward the mean of the 0.8 rather than that of the 1.0 function. These effects cannot be explained in terms of changes in responsiveness over time. Demodulation of the
NDF toward the mean value by decorrelating the noise at the two ears
was previously reported by Yin et al. (1987)
, and we only used the full
range of interaural correlations for these four units and one other
that responded in a similar manner. Subsequently, to save recording
time, we used only interaural correlations of 1.0 and 0.0.
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Of the 47 neurons for which NDFs were flat for zero correlation (i.e., discharge rate was not dependent on interaural time delay), more than one-half showed a discharge rate approximately equal to the mean value of the function at 1.0 interaural correlation (25/47). For units for which the major feature of the NDF is a trough not a peak, decorrelation led to a flat function at the level of the maximum of the fully correlated NDF (6/47). The discharge rate of the uncorrelated NDF for the remaining 16 units was below the mean of the correlated function, and in 11 of these the uncorrelated discharge rates approximated the minimum of the correlated NDF.
For comparison with the effects of 500-Hz tones on the responses to No
noise the discharge rate changes that occur at zero ITD on the NDFs are
most relevant. These discharge-rate changes are shown in Fig.
4 as a function of the noise correlation
for five units (Fig. 4, A and B) and as a
difference between 0 and 1.0 correlation for the whole sample (Fig. 4,
C and D). For some units, decorrelation produced
virtually no change in the discharge rate, as can be seen from the
closed circles in Fig. 4, A and B; these data
were from the unit also shown in Fig. 3A. From Fig. 3A it can be seen that the demodulation that occurs as a
result of decorrelation collapses the functions to the discharge rate measured at zero ITD. This would result in a decrease in the discharge rate at the noise best delay and an increase in the discharge rate at
the noise worst delay. This unit produced a very small BMLD for NoSo
versus NoS signals. Other units did produce quite large changes in
the discharge rate as the noise was decorrelated as can be seen from
the solid triangles in Fig. 4, A and B, which is
the same unit as shown in Fig. 3D. Figure 4, C
and D, shows the relationship between the best delay to the
noise and the change in discharge rate caused by decorrelation. The
largest decreases in discharge rate when the noise is decorrelated
occurred in units with best delays close to zero, as one would expect,
and the increases in discharge were generally associated with units
with long best delays. Five of the eight units showing increases had
troughs in their delay functions near zero ITD, and hence their noise best delays were displaced by large fractions of the BF period (Fig.
4D).
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In response to noise, the delay function is dominated by signal
components close to the unit BF such that the NDF is periodic at the BF
period (McAlpine et al. 1996; Palmer et al.
1990
; Yin et al. 1987
). Thus the responses on
the NDFs at ± one-half a period of the BF tone either side of
zero indicate the effect of decorrelation on the response to N
noise. For the individual neurons (Fig. 5, A and B) there
is a general tendency for the discharge rate to increase as the noise
is decorrelated. Decorrelation produces an increase in discharge rate
for most neurons with best delays near zero and a decrease for those
with best delays close to one-half a period of the BF away from zero
(Fig. 5, C and D).
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Comparison of the effects of interaural decorrelation with those of adding 500-Hz tones
Figure 6 shows an extensive data set
obtained from one IC neuron with a BF of ~250 Hz (Fig.
6A). On decorrelating the noise, the NDF was demodulated and
became flat at a discharge rate approximately equal to the mean of the
fully correlated NDF (Fig. 6B). In the presence of No noise,
increasing levels of the 500-Hz So tones caused a progressive increase
in the discharge rate, and the S tones caused a progressive decrease
(Fig. 6, C and D). The increase for So and the
decrease for S
is consistent with the responses to binaural beats
(Fig. 6E) in which So was close to the response maximum and S
was at the response minimum (marked by
arrows).
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Figure 6F shows a series of NDFs measured in the presence of
500-Hz So tones presented at a series of levels that are depicted on
the MRLFs of Fig. 6C by thin vertical lines. The NoSo masked threshold for this unit was 62 dB SPL. At 46 dB SPL, the So tone produced a small increase in the discharge to the noise at all ITDs.
This increase became larger as the level of the So tone was raised, but
even at 66 dB SPL clear peaks and troughs in the NDF were evident;
however, by 76 dB SPL the function was completely flat. The discharge
rate at the best delay saturates even at the lowest So level, and as
the So tone is increased in level the discharge rate at all other ITDs
also reaches this saturated rate. The NoS masked threshold of this
unit was 51 dB SPL, and a quite different pattern of changes takes
place as the level of the S
tone is increased (Fig. 6G).
Very little effect is seen at 46 dB SPL, but at higher levels the NDF
is progressively demodulated, reaching a discharge rate approximately
equal to that of the decorrelated NDF (horizontal dashed line). It
appears that for this unit, while So tones contribute extra coincident
inputs to the coincidence detectors, S
tones produce fewer
coincident inputs in a manner qualitatively similar to the effect of
decorrelating the noise. Full decorrelation of the responses to the
noise requires an S
tone at 76 dB SPL, a level 30 dB above that
producing a decrease in discharge rate. Responses, which we considered
to be equivalent to decorrelating the noise, were found in
32 of 48 neurons.
In contrast, the data shown in Fig. 7
depict a unit with BF of 700 Hz for which the responses to S tones
do not appear to mirror the effects of decorrelation. Figure
7B indicates that the effect of decorrelating the noise is
virtually indistinguishable from that in Fig. 6; decorrelation
demodulates the NDF to the mean. The MRLFs (Fig. 7, C and D)
also show increases in discharge for So and decreases for S
, and the
effects of 500-Hz So tones (Fig. 7F) on the NDF are similar
to those in Fig. 6F. The effect of S
tones over only a
20-dB range reduces the discharge rate evoked by the No noise to the
minimum of the NDF (Fig. 7G), a more profound reduction than
that caused by decorrelating the noise (dashed line). Effects such as
those in Fig. 7 were found in 13 of 48 neurons.
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In some instances (among the 13 described previously), we found mixed
responses (not shown) that appear to mirror the effects of
decorrelation (demodulation) for low levels of S but produce more
profound reductions in discharge at higher S
levels (reduction to
the minimum of the NDF). In these neurons it appears that, after first
decorrelating the responses to the noise, the high levels of tone
dominate the response and the output reduces to that characteristic of
the S
tone alone.
A radical departure from the simple desynchronization hypothesis is
shown by the final example (the only neuron showing this pattern) in
Fig. 8. Here, in a unit with BF at 500 Hz, decorrelation of the noise causes demodulation of the NDF toward
the mean of the correlated function (Fig. 8B). Note that the
lowest levels of the added tones [51 and 41 dB SPL (Fig. 8,
F and G)] were chosen to fall in the low-level
region of the response area (which is shown in relative tone levels: 0 dB at 500 Hz was 100 dB SPL). However, increasing the level of both So
and S tones reduced the discharge rate caused by the No noise (Fig.
8, C and D). One reason that this occurs is shown
by the binaural beat response in Fig. 8E, which reveals that
neither So nor S
tones occur near the peak of the unit's delay
sensitivity; the S
tone is at the minimum of the response and the So
tone falls on the medial edge of the response peak. Figure 8,
F and G, shows the effects on the NDF of
increasing the levels of So and S
tones. Unlike in previous
examples, both the So and S
tones demodulate the NDF toward the
baseline. In its simplest form, the prediction of the desynchronization
model is that only one of the tones should cause a decrease in the
noise-evoked activity and the other should cause an increase.
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We have no way of making a simple comparison of the effect of the added
tones to the effect of decorrelation because we did not a priori
determine what level of the tone should be compared with the fully
decorrelated noise (see DISCUSSION). Nevertheless, we can
compare the effects more indirectly. In Fig.
9 we plot the change in the discharge
rate at zero ITD caused by full decorrelation (the value at 0 ITD in
the fully correlated NDF minus the value at zero in the uncorrelated
NDF) against the change in discharge rate caused by the added tones
(the rate to the tones minus the rate to the No noise). We computed
these values for the curves obtained when the tones were 10, 20, and 30 dB above the level at which there was a noticeable change in firing
rate as indicated by the MRLF (because the masked threshold was only
computed after the experiment the levels of tones are not exactly 10, 20, and 30 dB above the masked threshold). The lines plotted on each
curve are the regression fits. Even at 10 dB above threshold (Fig.
9B) there is a tendency for the S discharge rates to
covary with the desynchronization (R2 = 0.228),
and there is no such tendency for the So data (Fig. 9A;
R2 = 0.015). These trends are also apparent in
the plots for 20 dB (Fig. 9, C and D) and 30 dB
(Fig. 9, E and F) above threshold where the
covariation of the S
data with the decorrelation data becomes
progressively more pronounced (r2 increasing to
0.49 and then to 0.643). The So data remain essentially uncorrelated at
all tone levels.
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DISCUSSION |
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Although the BMLD is undoubtedly an indication of the use of two
ears to improve the detection of signals in noise, it does not directly
reflect the use of spatial positional cues in grouping and segregating
sounds (e.g., Jeffress and McFadden 1971). The BMLD is
measured in a threshold detection task and as such the tone signal is
detected as a change in the ongoing activity caused by the masking
noise rather than as a separate perceptual entity. Because at the ouput
of an auditory filter at 500 Hz the noise is essentially tonal with
random variations in amplitude and phase, a useful way of visualizing
this process is in the form of vector addition as suggested by Webster
(1951)
and as was used in subsequent descriptions of the BMLD (e.g.,
Jeffress and McFadden 1971
; Jeffress et al. 1952
,
1956
, 1962
). We use this form of representation in Fig.
10 to illustrate the effects of adding
So and S
tones to identical noises at the ears and to emphasise the
equivalence with uncorrelated noise signals. In Fig. 10A the
identical noises at the right and left ears at a single time instant
are indicated as the horizontal vectors. The phase of the noise signal
is essentially random, and thus the resultant vector will also vary
randomly in phase and amplitude. The addition of So signals produces an equal shift in the noise phases at both ears and thus has no effect on
the interaural cues. The amplitude of the resultant is increased by the
addition of the signal. By contrast, when S
tones are added to
identical noise signals, the phase shifts induced in the noise signals
are in opposite directions, as shown in Fig. 10B. In this
case, the addition of the signal generates an interaural phase and
level difference (see Jeffress and McFadden 1971
for detailed discussion) between the noise signals reaching each ear. Thus
at the coincidence detector the inputs would not arrive at the same
time and can be considered to be desynchronized. Again the phase of
the noise will vary randomly, but the effects of adding the S
tones
will always be equal and opposite. Finally, in Fig. 10C is
shown the equivalent vector representation for noise signals that are
independent (uncorrelated). One way of generating decorrelated noises
with different degrees of correlation is to add different amounts of
independent noises to a noise that is common at the two ears. The
vector diagram was drawn in this way to illustrate the similarities
with the NoS
condition in Fig. 10B. (Although we produced
the decorrelated noises in this paper by the addition of 2 independent
noises sources this is mathematically the same as decomposing the noise
into a common component and 2 independent components as shown.) The
independent noises at any instant generate interaural level and time
differences. Because the common noise source and the added noises have
independently random phases the effect will be random; at some instants
the signals at the two ears will be identical, but for most of the time
there will be interaural differences that will be larger the more the
noises are decorrelated. When the common noise component is absent this
represents uncorrelated noise at the two ears, and the interaural cues
will also be random. Thus adding independent noise sources to a common
source has the effect of desynchronizing the inputs to the coincidence
detectors and is therefore analogous to adding S
to No.
|
For some units at high tone levels the tone appeared to dominate the
response and reduce the discharge rate to that characteristic of the
S tone alone. However, for the majority even the highest levels of
tone that we presented only resulted in a demodulation of the NDF to
the mean level and thus appeared to be simply desynchronization rather
than a result of domination by the tone.
The range of discharge rates to uncorrelated noise may represent
different processes underlying the generation of the correlated noise
delay curves. For example, the curves for which the decorrelated rates
reached the correlated minima represent units for which the peaks but
not the troughs are generated by coincident activity from each ear. For
units characterized by a trough near zero delay it is the trough that
is generated by coincident activity, and the peaks are due to
noncoincident input (Yin and Kuwada 1983b). For the
units in which the decorrelated discharge rate coincided with the
average of the correlated, both the peaks and the troughs in the delay
functions must represent the response to specific phase relations of
the noise inputs from each side (after cochlear filtering). This is the
type of unit that was modeled by Colburn et al. (1990)
, where it was
shown that timed inhibition was not a necessary requirement for
producing discharge rates lower than to either ear alone. Indeed timed
inhibition seems implausible because different timing would be required
to match the one-half period at different frequencies.
In some instances, the effect of adding S tones appeared to be more
profound than decorrelating the noise. Here it appeared that the
presence of an S
tone at sufficient level significantly reduced the
neuronal output in response to noise with any interaural delay. It is
tempting to suggest that the S
tones in this instance produce
inhibition of the activity. If the inhibition does not derive from the
lower brain stem it might be more local to the IC. This seems possible
in view of the inhibitory inputs to the IC that derive from a range of
lower nuclei (Faingold et al. 1991
; Oliver and
Shneiderman 1991
) and the fact that there is good evidence for
convergence onto delay-sensitive IC neurons (Kuwada et al. 1987
,
1996
; McAlpine et al. 1998
). One plausible
scenario for responses such as those shown in Fig. 7 would be for input
from both a direct MSO input to an IC neuron and from a trough unit via
an inhibitory interneuron (within IC or possibly from DNLL) (e.g., see
Cai et al. 1998
). The trough characteristic derives, in
the brain stem, from inhibition from one ear and excitation from the
other fed to a coincidence detector via paths of different length.
Troughs in such units tend to be close to zero interaural delay and
thus will result in little activity generated by So tones. S
tones
in contrast are generally not located near the trough and thus evoke
activity. At the higher level this means that there would be strong
inhibitory inflow from an interneuron fed by a trough unit for S
stimuli and little or none for So stimuli. Thus for the unit in Fig. 7,
although So tones gave responses such as those in Fig. 6, S
tones
did not demodulate the noise curves to the mean but rather at the
higher levels produced suppression at all noise delays.
The unit shown in Fig. 8 requires an alternative explanation. Both the
So and S tones appeared, at higher sound levels, to suppress
progressively the output at all noise delays. This type of response we
attributed (previously) to inhibitory inputs. Because both So and S
had a similar suppressive effect, the inhibition would need to be delay
independent and indeed might well be a result of a monaural inhibitory
input to the neuron (this possibility was not tested at the time). More
difficult to explain is the desynchronizing effect of the low level So
tones (Fig. 8F at 51 dB SPL). Because the noise delay curve
has a peak near zero interaural delay So tones at BF (500 Hz) should
also produce spikes at the coincidence detector and thus augment the
noise delay curve at all delays as in Figs. 6F and
7F rather than demodulating the noise responses. Clearly,
the So tones here act more like the S
tones in Fig. 7G,
and the desynchronizing effect is superceded at higher sound levels by
the delay-independent inhibitory effect of the 500-Hz tones. We have no
plausible explanation for the initially desynchronizing action of the
low-level So tones.
The most appropriate comparison between the effects of decorrelating
the noises at the two ears and adding extra tones would be to use that
level of tone that achieves the same degree of decorrelation. This can
be computed within each frequency channel (Durlach et al.
1986), and to achieve full decorrelation of the noise appears
to require a within-channel signal-to-noise ratio of 0 dB (van
de Par and Kohlrausch 1995
). Unfortunately, for physiological expediancy, while collecting data, we used fixed levels of the added
tones resulting in the within-channel signal-to-noise ratio varying as
the sample included BFs from 0.161 to 1.8 kHz, and the noise levels
were chosen specifically to give a good NDF (7-15 dB above binaural
noise threshold). We therefore resorted to the analysis shown in Fig.
9, where we show that the higher levels of tone (30 dB above the levels
at which they first affect the noise response) produce effects, which
covary with decorrelation.
These data are consistent with the hypothesis that the effect of adding
tonal signals to noise is equivalent to the effect of decorrelating the
noise at the two ears, in the majority of neurons. This is because the
synchronized input to the brain stem coincidence detectors caused by
identical noises at the two ears will be disrupted or desynchronized by
the addition of the S tone signals. However, in some neurons there
were effects of adding extra tones that could not be fully described in
terms of such a desychronization process.
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ACKNOWLEDGMENTS |
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We thank P. Moorjani for technical assistance, D. Marshall for computing the factors for producing decorrelated noise, and T. Shackleton and M. Akeroyd for providing valuable comments on early drafts of this paper.
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FOOTNOTES |
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Address for reprint requests: A. Palmer, MRC Institute of Hearing Research, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.
Received 11 May 1998; accepted in final form 23 October 1998.
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REFERENCES |
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