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J Neurophysiol (May 1, 2003). 10.1152/jn.00640.2002
Submitted on Submitted 6 August 2002; accepted in final form 31 December 2002
Department of Molecular and Integrative Physiology, Kansas University Medical Center, Kansas City, Kansas 66160-7401
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ABSTRACT |
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Poirier, Pierre, Frank K. Samson, and Thomas J. Imig. Spectral Shape Sensitivity Contributes to the Azimuth Tuning of Neurons in the Cat's Inferior Colliculus. J. Neurophysiol. 89: 2760-2777, 2003. We recorded high-best-frequency single-unit responses to free-field noise bursts that varied in intensity and azimuth to determine whether inferior colliculus (IC) neurons derive directionality from monaural spectral-shape. Sixty-nine percent of the sample was directional (much more responsive at some azimuths than others). One hundred twenty-nine directional units were recorded under monaural conditions (unilateral ear plugging). Binaural directional (BD) cells showed weak monaural directionality. Monaural directional (MD) cells showed strong monaural directionality, i.e., were much more responsive at some directions than others. Some MD cells were sensitive to both monaural and binaural directional cues. MD cells were monaurally nondirectional in response to tone bursts that lack direction-dependent variation in spectral shape. MD cells were unresponsive to noise bursts at certain azimuths even at high intensities showing that particular spectral shapes inhibit their responses. Two-tone inhibition was stronger where MD cells were unresponsive to noise stimulation than at directions where they were responsive. According to the side-band inhibition model, MD cells derive monaural directionality by comparing energy in excitatory and inhibitory frequency domains and thus should have stronger inhibitory side-bands than BD cells. MD and BD cells showed differences in breadth of excitatory frequency domains, strength of nonmonotonic level tuning, and responsiveness to tones and noise that were consistent with this prediction. Comparison of these data with previous findings shows that strength of spectral inhibition increases greatly between the level of the cochlear nucleus and the IC, and there is relatively little change in strength of spectral inhibition among the IC, auditory thalamus, and cortex.
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INTRODUCTION |
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Cats and other
mammals are capable of localizing the source of high-frequency,
broadband sounds with considerable accuracy. Binaural level disparities
are most important for left-right (azimuthal) localization. Diffraction
of sound with the pinna leads to direction-dependent variation in
high-frequency spectral shape (spectral shape cues) at the eardrum
(cat: Musicant et al. 1990
; Rice et al.
1992
, Xu and Middlebrooks 2000
; human:
Batteau 1967
, Shaw 1974
). Some
unilaterally deaf humans can localize broadband high-frequency sounds
(Butler 1975
; Hausler et al.
1983
; Slattery and Middlebrooks 1994
) presumably on the basis of monaural spectral shape. Monaural spectral shape cues
are important for up-down (elevational) localization (cats: May
2000; Sutherland et al. 1998a
,b
; humans:
Middlebrooks and Green 1991
; Wightman and Kistler
1997
). They also contribute to front-back localization and to a
lesser extent to left-right localization (Butler 1986
;
Butler et al. 1990
, Fisher and Freeman
1968
; Hebrank and Wright 1974
; May
2000
; Oldfield and Parker 1986
; Slattery and Middlebrooks 1994
; Wightman and Kistler
1997
).
High-frequency neurons in the inferior colliculus (IC) exhibit three
patterns of binaural interactions that act on binaural disparities to
shape azimuth tuning (Delgutte et al. 1999
;
Geisler et al. 1969
; Irvine 1986
;
Irvine and Gago 1990
; Rose et al. 1966
). Binaural inhibition suppresses responsiveness to sound directions on
one side of the head thus producing hemi-field selectivity. Binaural
facilitation enhances responsiveness to sound directions near the
midline to produce central-field selectivity. Mixed inhibitory and
facilitatory interactions suppress responsiveness to sound directions
on one side of the head, enhance responsiveness on the other, and
create receptive fields that vary from central-field to hemi-field.
Similar patterns of binaural interactions and azimuth tuning have been
described in the cat's superior colliculus (Hirsch et al.
1985
; Middlebrooks 1987
; Wise and Irvine
1985
), medial geniculate body (MGB) (Ivarsson et al.
1988
; Samson et al. 2000
), and primary auditory
cortex (AI) (Samson et al. 1994
).
We previously classified forebrain (MGB and AI) cells on the basis of
whether they derived directionality predominantly from binaural cues
(binaural directional or BD cells), monaural cues, or both monaural and
binaural cues (monaural directional or MD cells) (Clarey et al.
1995
; Samson et al. 1993
, 1994
, 2000
). Under monaural conditions, MD cells were responsive to noise bursts at
certain azimuths, and relatively unresponsive at others, even at high
sound pressure levels (SPLs). The direction-dependent variation in
responsiveness suggests that these cells are sensitive to monaural
spectral shape cues. Particular spectral shapes can apparently suppress
or inhibit a cell's response to noise, a phenomenon referred to as
spectral inhibition. Furthermore, the dependence of such cells'
directionality on monaural spectral shape cues is consistent with the
observation that they are monaurally responsive at each azimuth
(nondirectional) to tone bursts (Clarey et al. 1995
;
Imig et al. 1997
; Samson et al. 1993
,
2000
). Tone burst spectra are dominated by a single frequency
and thus show relatively little direction-dependent spectral-shape
variation. Spectral-shape sensitivity has also been shown to contribute
to the directionality of neurons in the dorsal cochlear nucleus (DCN).
Monaural directionality of DCN neurons is stronger than that of ventral
cochlear nucleus (VCN) neurons or auditory nerve fibers but is much
weaker than that seen in AI and the MGB (Imig et al.
2000
; Poon and Brugge 1993
; Rice et al.
1995
). Although sensitivity to monaural spectral shape cues has
been shown to contribute to the directionality of neurons at lower and
higher levels of the auditory pathway than the IC, there are no
published accounts of this phenomenon in the IC. Thus our first goal
was to determine the extent to which IC neurons exhibit monaural directionality.
Side-band inhibition appears to contribute to spectral inhibition in
the MGB as MD cells showed stronger two-tone inhibition at directions
where they were unresponsive to noise stimulation than at directions
where they were responsive (Imig et al. 1997
). According
to the side-band inhibition model, a MD neuron's responsiveness reflects the relative amounts of acoustic energy in its excitatory and
inhibitory frequency domains (Imig et al. 1997
).
Discharge rate increases at directions where there is more energy in
excitatory than inhibitory domains and decreases at directions where
there is more energy in inhibitory than excitatory domains. A second goal of this study was to test this hypothesis in the IC by determining if MD cells show stronger two-tone inhibition at directions where they
were unresponsive to noise stimulation than at directions where they
were responsive.
The side-band inhibition model predicts that MD cells should have
stronger and/or more extensive inhibitory side-bands than BD cells,
thus giving rise to their stronger monaural directionality. In accord
with the prediction, excitatory frequency domains of MD cells are about
half as wide as those of BD cells in the MGB (Imig et al.
1997
). Additionally, MD cells in both the MGB and AI show more
strongly nonmonotonic level response functions to noise stimulation as
compared with BD cells. Finally in both the MGB and AI, MD cells show
lower responsiveness to noise than tones, whereas BD cells show no
difference in responsiveness (Clarey et al. 1995
;
Imig et al. 1997
; Samson et al. 2000
).
These differences suggest the presence of stronger inhibitory processes
in MD cells than in BD cells. The third goal of this study was to
determine whether BD and MD cells in the IC exhibited similar
differences in these response properties.
Discharges of DCN neurons are inhibited when a spectral notch is
centered at best frequency (BF), a phenomenon known as notch inhibition
(Nelken and Young 1994
; Spirou and Young
1991
). Spectral notches are natural features of high-frequency
spectra at the eardrum. The number, depth, width, and center
frequencies of notches vary with sound direction, and they have been
implicated as playing an important role in directional hearing
(Huang and May 1996a
,b
; May and Huang
1996
; Musicant et al. 1990
; Rice et al.
1992
). Notch inhibition contributes to the directionality of
DCN neurons (Imig et al. 2000
). Delgutte et al.
(1999)
looked for evidence of notch inhibition in the responses
of IC single units, but their results were inconclusive. They used
binaural stimuli that were presented at relatively low SPLs, and these
may not be best suited for revealing spectral inhibition. Thus the
fourth goal of this study was to search for notch inhibition in the IC
using stimuli that we have found to reveal monaural directionality
previously, i.e., noise bursts presented over a broad range of SPLs
under monaural conditions.
Previous studies show that spectral inhibition is weaker in the
cochlear nucleus (CN) (Imig et al. 2000
) than in the MGB
and AI (Samson et al. 2000
). The fifth goal of this
study is to compare the strength of spectral inhibition in the IC with
that at lower and higher levels of the auditory system. This comparison
should indicate the extent to which spectral inhibition is generated between the CN and the IC, between the IC and the MGB, and between the
MGB and AI. Such a comparison is possible because recordings in the CN,
MGB, and AI studies were carried out under virtually identical
conditions to those used in the IC in this present study. Some of these
findings have been presented previously in abstract form
(Poirier et al. 1996
).
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METHODS |
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Twelve healthy young adult cats with clean external ears,
translucent eardrums and low-threshold single-unit responses were used
in the IC recording experiments. Experiments were carried out using
protocols approved by the Institutional Animal Care and Use Committee
of the University of Kansas Medical Center. We also performed an
analysis of strength of spectral inhibition on some previously
published data in the MGB and AI (Samson et al. 2000
) to
compare response properties of cells at different levels of the
auditory system. Details concerning single-unit recording, computer
control of data collection, data analysis, and sound generation have
been described previously (Barone et al. 1996
;
Imig et al. 2000
; Samson et al. 1993
, 1994
,
2000
).
Chronic recording procedures were used to increase the amount of data collected from each cat. The number of recording sessions per cat varied between 2 and 11 with an average of 4.7 per cat. Cats were prepared for chronic recording during an initial aseptic surgical procedure using general anesthesia. A recording chamber was positioned over a craniotomy either at a 10° angle from rostrodorsal to caudoventral or a 60° angle from caudodorsal to rostroventral to allow recording electrodes to pass beneath the tentorium and reach the left IC. During recording sessions, pentobarbital sodium anesthesia was used to eliminate pinna reflexes and spontaneous movements. Electrolytic marking lesions were placed during terminal recording sessions to aid in electrode track reconstruction.
Single-unit recordings were carried out in an electrically shielded, anechoic, sound-isolation chamber. The anesthetized cat rested in a sling. Its head was supported with the horizontal Horsley-Clarke plane tilting forward and down at an angle of ~18° from horizontal, and the ears were pulled to an upright position This approximates the head and pinna position of an alert cat looking forward.
Auditory waveform synthesis, acoustic calibration, stimulus timing and
sequencing, and data collection were controlled by a PDP 11/73
computer. Stimulus waveforms were generated at an output sample rate of
100 kHz using a 16-bit D/A converter (Boys Town National Research
Hospital), low-pass filtered at 40 kHz (Kemo VBF/8,
180 dB/octave) to
prevent aliasing, attenuated with computer controllable attenuators,
and amplified. Stimuli were 50 ms in duration including 5-ms linear
rise-fall times, typically repeated 10 times and presented at 2-5 Hz.
Spike times were stored in a computer data file with a resolution of
0.01 ms. A peristimulus time window of 0-60 ms was used for the
analysis of spike counts although in most cases this was unnecessary as
spontaneous activity was low or nonexistent and there were no responses
outside of this window.
A horizontal array of loudspeakers (Radio Shack 40-1310B) with similar
frequency response characteristics allowed the presentation of sounds
from different azimuths. The array was composed of 13 loudspeakers
spaced at 15° intervals along a 180° arc of an imaginary circle
(0.79 m radius) that was centered on the cat's head. Azimuth could be
varied by presenting sound from different loudspeakers or by rotating
the array about the head. Each loudspeaker was calibrated by placing a
microphone (B&K type 4133 1/2 in) at the center of the circle, aiming
it at the loudspeaker, and performing a fast Fourier transform on the
impulse response. Noise SPL was measured using the RMS voltage from the
microphone. Tables of maximum SPLs attainable at different frequencies
and for noise stimuli for each loudspeaker were stored in computer
files for use during experiments. Loudspeaker output increased from 4 kHz to a peak at 8 kHz at 20 dB/octave, decreased by 5 dB/octave
35 kHz, and then decreased at 60 dB/octave. A random number generator produced a frozen noise waveform with a flat spectrum (0-50 kHz) and
random amplitude distribution. The actual spectrum of the noise
delivered from the loudspeaker was shaped by the sound system (mainly
the loudspeaker).
Single-unit waveforms were identified using noise burst search stimuli
that varied in azimuth and SPL. Once a unit was isolated, tone bursts
were presented from a loudspeaker located at an azimuth that produced
the strongest response to noise stimulation, and the unit's BF was
determined using audiovisual criteria. BF is the frequency that
produced the maximum response at a SPL near lowest threshold. Next,
responses of high-BF (>4 kHz) units to noise and in some cases BF tone
bursts were recorded to characterize azimuth tuning. Azimuth-level data
sets consisted of a single-unit's responses to sounds that varied in
azimuth (typically frontal field -90 to +90° in 30° steps) and SPL
(typically from 0 to 80 dB in 10- or 20-dB steps). For all units,
azimuth was varied by presenting sound from different loudspeakers, and
these data are referred to as "multi-loudspeaker data sets."
Additionally, some units were presented sounds from different azimuths
using a single loudspeaker that was moved by rotating the loudspeaker
array. These data are referred to as "single-loudspeaker data
sets." Low-BF units were not studied as low-frequency
direction-dependent variation in spectral shape is relatively small
(Musicant et al. 1990
; Rice et al. 1992
)
and would not be expected to strongly influence unit directionality.
Frequency-level data sets consisted of a single-unit's responses to
tone bursts of varying frequency (8 steps per octave) and SPL (10- or
20-dB steps, from below threshold to 80 dB SPL). These were recorded
for the purpose of assessing breadth of frequency tuning and were
graphically displayed as excitatory frequency response areas. Tone
bursts were presented from a loudspeaker located at the azimuth where
the cell was most responsive to noise stimulation.
Stimuli were presented under binaural and "quasi-monaural"
(henceforth, "monaural") conditions, the latter produced using an
earplug to attenuate free-field sound reaching one ear. Ears were
plugged by injecting ear mold compound (Audalin, All American Mold Lab)
into the concha and ear canal and firmly pressing the material in place
to ensure a tight seal. The ear mold compound was a viscous fluid when
injected, but it cured to a soft plastic consistency that was easy to
remove, leaving no visible residues in the ear canal. New plugs were
made each time an ear was occluded. Earplug attenuation was estimated
using both acoustical and physiological measures. For acoustical
measurements (Samson et al. 1993
), the external auditory
canal was surgically opened near its junction with the bulla, and a
probe tube microphone was sealed in the opening with its tip near the
eardrum. The transfer function from the loudspeaker to the eardrum was
measured with and without the ear plugged (the earplug did not reach
the tip of the probe tube). The resulting frequency spectra were
subtracted. The difference spectrum (attenuation) varied between 32-70
dB in the range of 4 - 32 kHz (the useable frequency range for the
measurements). At most frequencies, attenuation ranged between 40 and
60 dB, with less attenuation occurring over a narrow range of frequency that corresponded with a notch in the spectrum of the unplugged ear.
Earplug attenuation was also measured physiologically. We compared a
single unit's noise burst thresholds with and without bilateral
earplugs as shown in Fig. 1. Sounds were
presented at the azimuth that produced the lowest threshold response
without earplugs (e.g., 30°, Fig. 3D). Threshold was ~0
dB SPL without ear plugs (no plug). Bilateral ear plugging caused the
threshold to increase to ~70 dB SPL. The earplugs were then removed
and threshold returned to 0 dB. This was typical of all cells so tested showing the reversibility of the method. The 31 units for which thresholds were compared under no plug and bilateral plug conditions showed an average increase in threshold of 51 dB after bilateral ear
plugging. This is an underestimate of the actual threshold shift
because 8/31 units did not respond at the highest level tested, and in
these cases, we took earplug attenuation to be equal to the difference
between threshold with no plugs and the highest stimulus level tested
with earplugs. Although thresholds increased by
40 dB in 29/31 units,
two units showed threshold increases of only 10-20 dB, presumably due
to poorly fitted plugs. Nevertheless, these data show that ear plugging
typically produced attenuation of
40 dB, consistent with the
acoustical measurements.
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RESULTS |
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Spike counts at each azimuth-level combination in a data set were
displayed as an azimuth-level response area (ALRA, e.g., Fig.
3A). Spike counts at each azimuth were averaged over SPL to
obtain an azimuth function (e.g., Fig. 3C). Azimuth function modulation, the percentage difference between minimum and maximum function values, was used as an index of azimuth sensitivity
(directionality). Cells with function modulation
75% were classified
as azimuth sensitive (directional). Such units typically responded well
with low thresholds at certain azimuths and relatively poorly and with higher thresholds at other azimuths. Many were completely unresponsive at certain azimuths even at high SPLs, (e.g., Fig. 3A). We
refer to azimuths where responsiveness is relatively low (
25% of
maximum) as azimuth function troughs, and azimuths where responsiveness is relatively high (
75% of maximum) as azimuth function peaks.
Multi-loudspeaker ALRA data sets were obtained for 425 single units
using noise stimulation under binaural conditions (B-stim, i.e.,
neither ear plugged). Sixty-nine percent of the sample of 425 units was
directional. This report focuses on the responses of 129 of the
directional units whose monaural responses were also recorded. This
sample excludes the responses of eight cells with unreliable responses
or minimum thresholds
50 dB SPL. The latter were excluded as
identification of spectral inhibition depends on recording responses
over a broader range of SPLs than was available for such cells.
Monaural and binaural responses were compared to assess binaural
interactions, the presence of monaural excitatory inputs, and the
relative contributions of binaural and monaural mechanisms to azimuth
tuning. Repeated monaural and/or binaural multi-loudspeaker ALRA data
sets were available for 85/129 units and were used to assess response
reliability. Response property measures (e.g., azimuth functions, level
functions, etc.) were based on averages of the repetitions.
Single-loudspeaker data sets were additionally obtained for 44 of the
85 units but were not used in the numerical analyses because the
single-loudspeaker data were not always collected using the same SPL
steps as were the multi-loudspeaker data. Later we show that the
single- and multi-loudspeaker data were indistinguishable, so limiting
analyses to multi-loudspeaker data has no significant effect on the
results. Most units (105/129) in this sample lacked spontaneous
activity. The remaining 24 units exhibited very low spontaneous
activity, of ~1 spike/s or less, and this represented ~1% or less
of the maximum rate of discharge during the stimulus.
Histological reconstruction of electrode tracks allowed identification
of recording sites for most (120/129) units in the sample. These sites
were found in either the central nucleus (n = 94/120)
or the dorsal cortex (n = 26/120) of the IC
(Berman 1968
; Morest and Oliver 1984
).
There were no obvious differences in response properties between these
two groups, so they were combined. BFs could be assigned for 127/129
units, and these ranged from 4 to 37 kHz [14.7 ± 6.5 (SD) kHz].
The two units for which BFs were indeterminate were responsive to a
broad range of high-frequency tone bursts.
Binaural directional (BD) and predominantly binaural (PB) cells
The BD group was composed of 68 cells that were nondirectional
(azimuth function modulation <75%) to noise bursts presented under
monaural conditions, showing that their directionality was dependent on
binaural cues. Comparison of monaural and binaural responses revealed
the presence of three patterns of binaural interactions: inhibition,
facilitation, and mixed inhibition and facilitation. Qualitative
classification of binaural interactions was usually clear-cut as
binaural inhibition created azimuth function troughs, binaural
facilitation created azimuth function peaks, and mixed inhibition and
facilitation created troughs and peaks, respectively. Nevertheless
classification of some cells was somewhat arbitrary, so we used two
objective criteria developed by Delgutte et al. (1999)
for classifying binaural interaction type and strength (Fig.
2A). Binaural interaction
strength (BIS) characterizes the difference between monaural and
binaural responses, and ranges from 0 (no difference) to 1 (large
difference). Binaural interaction type (BIT) indicates the relative
balance of binaural inhibition and facilitation with positive values
indicating greater facilitation and negative values indicating greater
inhibition. A scatter plot showing the joint distribution of BIS versus
BIT values for the sample of BD and PB units is shown in B. Delgutte et al. (1999)
used BIT criteria of -0.4 and
+0.7 to divide their sample into three binaural interaction classes of
facilitation, inhibition, and mixed facilitation and inhibition. We
have used these same criteria as they match closely our qualitative
classification.
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BD-EI cells (n = 45) exhibited binaural inhibition
(smaller binaural than monaural responses,
1.0
BIT <
0.4, Fig. 2B). Based on their responses to ear plugging,
we inferred that BD-EI cells in our sample received excitatory (E)
input from the contralateral ear and inhibitory (I) input from the
ipsilateral ear. Under binaural conditions, they were most responsive
to contralateral sound directions, i.e., were contralateral preferring.
A typical example is shown in Fig. 3,
top. This unit's ALRAs obtained under binaural (B-stim, i.e., neither ear plugged) and contralateral monaural conditions (C-stim, i.e., ipsilateral ear plugged) are shown in A and
B, respectively. The unit was unresponsive to stimulation
under ipsilateral monaural conditions (C, I-stim, i.e.,
contralateral ear plugged), although ipsilateral stimulation had an
inhibitory effect on responses in the ipsilateral field (compare C- and
B-stim). Of the 10 units tested under ipsilateral monaural conditions
(i.e., stimulation of the inhibitory ear), 9 were unresponsive or
responded only at high SPLs, the latter responses presumably resulting
from sound leakage through the earplug. One remaining unit responded
with weak low-threshold responses.
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BD-FI cells (n = 21) exhibited facilitation (larger
binaural than monaural responses) at some azimuth-level combinations
and inhibition at others (-0.4
BIT
+0.7, Fig.
2B). A typical example is shown in Fig. 3,
middle. Comparison of monaural and binaural azimuth
functions (F) shows facilitation at contralateral directions and inhibition at ipsilateral directions. This cell was responsive to
C-stim but not to I-stim, but some other BD-FI cells were responsive to
both C-stim and I-stim. Azimuth function peaks of BD-FI cells varied in
location. Most had contralateral or midline preferences and a few had
ipsilateral preferences.
BD-F (n = 2) and PB (n = 18)
cells exhibited binaural facilitation (+0.7 < BIT
+1.0,
Fig. 2B). BD-F cells responded under monaural conditions to
stimulation of one or both ears (Fig. 3G), whereas PB cells
were unresponsive or poorly responsive to stimulation of either ear
under monaural conditions (Fig. 3, H and I). Most PB cells
in the monaurally poorly responsive group responded only at high levels
under monaural conditions. We interpret the responses as resulting from
sound leakage though the earplug. A few PB cells responded very weakly
at low levels under monaural conditions. In these cases, the
distinction between PB and BD-F cells was rather arbitrary. Most PB and
BD-F cells had response peaks located near the midline. The azimuth
tuning of PB cells clearly depended on binaural disparities but lack of
response under monaural conditions precluded testing their monaural
directionality. Consequently we consider them as a separate group that
is not included in either the BD or monaural directional (MD) groups.
Single-loudspeaker data sets were obtained for 20 BD cells and 12 PB cells under monaural or binaural conditions or both. Azimuth functions obtained using a single loudspeaker are identified with an asterisk in the figures (e.g., Fig. 3C, see 5 B-stim*). The multi- and single-loudspeaker data showed no consistent differences, indicating that any differences in the frequency response characteristics between loudspeakers were so small that they did not significantly affect the response properties that we measured.
Patterns of monaural and binaural azimuth tuning in MD cells
MD cells (n = 43) were distinguished from BD and
PB cells by their directionality to noise bursts presented under
monaural conditions (i.e., azimuth function modulation
75%). Recall
that our definition of directionality depends on a cell's response over a broad range of SPL. Thus just because both MD and BD cells responded under monaural conditions to restricted ranges of azimuth at
SPLs near threshold, this does not make both types of cell directional.
Directionality (or lack thereof) is revealed in responses to higher
noise levels at which BD cells were responsive at all azimuths whereas
MD cells were not. MD-E0 cells (n = 17) had rather similar monaural and binaural azimuth function profiles showing that
sensitivity to monaural cues made a major contribution to their azimuth
tuning. Most MD-E0 cells (15/17) received excitatory input from the
contralateral ear. Figure 4 shows
examples of three MD-E0 cells with azimuth functions characterized by
relatively narrow peaks and broad troughs. The cell in Fig. 4,
top, responded well throughout the contralateral rear
quadrant, and it was relatively unresponsive at any direction in the
frontal field except at 90°. Cells in Fig. 4, middle and
bottom, had response peaks located at 0 and 60°,
respectively. Figure 5 shows two MD-E0
cells whose azimuth functions were characterized by narrow troughs. In
each case, the trough occurred at the same location regardless of
whether the cell was stimulated under monaural or binaural conditions.
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Some MD-E0 cells may be strictly monaural (low BIS values in Fig.
2C), but in other cases, repeated data sets revealed
consistent differences between monaural and binaural responses. The
cell in Fig. 4, bottom, shows weak binaural inhibition at
60 and
90° to noise stimulation. Weak binaural inhibition also
appears to be present in its responses to 17-kHz tonal stimulation
(Fig. 4I). Nevertheless, binaural inhibition by itself was
insufficient to produce directional responses to tonal stimulation, and
the azimuth tuning to noise stimuli is so similar under monaural and binaural conditions that it must be attributed predominantly to a
monaural mechanism. The binaural responses of the cell in Fig. 4F were consistently larger than the monaural response,
revealing binaural facilitation. The BIS is above the average for the
MD-E0 sample, but again, the azimuth tuning is so similar under
monaural and binaural conditions that it must be attributed
predominantly to a monaural mechanism. The cell in Fig. 5F
shows weak mixed interactions but these do not produce the peak and
trough in the azimuth function that is typical of stronger mixed
interactions. Although this binaural interaction doesn't have an
obvious effect on azimuth tuning, it does contribute to level tuning as
responses to C-stim were consistently more strongly nonmonotonic than
to B-stim (Fig. 5, D and E). Thus the MD-E0
designation does not imply that cells were necessarily monaural only
that azimuth tuning was predominantly determined by a monaural mechanism.
The azimuth tuning of MD-BD cells (n = 26) showed strong contributions from both monaural and binaural mechanisms. Depending on pattern of binaural interactions, such cells were classified as MD-EI (n = 14), MD-FI (n = 7), or MD-F (n = 5) according to the same BIT criteria used to classify BD cells (MD-BD, Fig. 2C). Binaural interactions had the same effect on responses of MD-BD cells as they had on BD cells, i.e., binaural inhibition created azimuth function troughs, mixed inhibition and facilitation created troughs and peaks, and binaural facilitation created or enhanced peaks in the azimuth function. MD-EI cells were unresponsive at the same location in both monaural and binaural azimuth functions (e.g., Figure 6, top at +30° and middle top at +90°). Most (12/14) MD-EI cells received excitatory input from the contralateral ear. An example of a MD-FI cell that had a response peak located near the midline is shown in Fig. 6, middle bottom. It was responsive to C-stim but not I-stim. C- and B-stim noise-burst azimuth-functions showed troughs at +90°, suggesting that monaural spectral inhibition also contributed to binaural azimuth tuning (I). A MD-F cell (Fig. 6, bottom) showed minimal and maximal responsiveness at the same locations in monaural and binaural azimuth functions, but it was considerably more responsive at 0 and -30° to B-stim than to C-stim (responses to I-stim were not obtained). A monaural response trough at +60° contributes to binaural azimuth tuning in this cell.
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Some MD-BD cells exhibited monaural response troughs that were not seen in their binaural azimuth functions (MD-EI, n = 4; MD-FI, n = 4; MD-F, n = 3). Although none of these responses are illustrated, an example of a monaural trough that does not obviously appear in the binaural response is seen in Fig. 6, middle top. This cell shows a trough to C-stim at -90°, but it isn't obvious that this monaural trough contributes to binaural azimuth tuning because it lies within a broader trough that is created by binaural inhibition. Two MD-FI cells and one MD-F cell showed troughs at a particular azimuth under monaural but not binaural conditions. These cells exhibited monaural directionality that did not obviously contribute to their binaural directionality.
The use of a multi-loudspeaker array to present sounds from different azimuths presents a potential ambiguity in interpretation of these results. Loudspeakers had similar but slightly different frequency-response characteristics, therefore use of different loudspeakers to vary azimuth also produced some loudspeaker-dependent variations in spectral composition of noise stimuli. Thus one might question whether the response modulation that occurred was a function of single-unit sensitivity to sound direction or to differences among loudspeaker frequency response characteristics. As a control, ALRA data sets for noise stimulation under monaural and/or binaural conditions were obtained for 12 MD cells using a single loudspeaker and moving its location to vary azimuth. This control removes the contribution of differences in loudspeaker frequency response characteristics to sound spectra at different directions, leaving only the contribution of direction-dependent differences in acoustic diffraction. These single-loudspeaker data are shown in azimuth functions marked by asterisks in Figs. 4I (5 B-stim*), 5, C (5 C-stim* and 8 B-stim*) and F (7 B-stim*), and 8A (3 B-stim*). There were no systematic differences between multi- and single-loudspeaker data sets showing that azimuth function response modulation was due to direction-dependent differences in monaural spectral shape produced by acoustical diffraction rather than differences in the frequency-response characteristics of loudspeakers.
Monaural directionality is greater to noise than to tone bursts
If monaural directionality depends on monaural spectral shape
cues, then MD cells should exhibit greater monaural directionality to
noise bursts that show relatively large direction-dependent variation
in spectral shape than to BF-tone bursts whose narrow spectra allow for
relatively little variation. Monaural ALRA data sets were obtained for
both BF-tone and noise burst stimulation for a sample of 16 MD cells.
Each MD cell showed considerably greater azimuth function modulation
for noise than tones (e.g., Figs. 4I, 5, C and
F, and 6I). Figure
7 shows a comparison of tone and noise
modulations for the entire MD sample (
). The average modulation for
noise (90.9%) was significantly greater than that for BF tones
(38.8%, paired 2-tailed t-test, P < 0.0001).
|
Binaural directionality to BF tones and noise was compared for eight BD-EI and BD-FI cells (Fig. 7). The average azimuth function modulation for noise (92.6%) was slightly greater than that for BF-tones (90.6%), and the difference was not statistically significant. This suggests that BD cell directionality does not strongly depend on spectral shape cues. PB cells (n = 8) showed greater variation in their sensitivity to bandwidth. The average azimuth function modulation for noise (94.9%) was greater than that for BF-tones (81.5%, paired 2-tailed t-test, P = 0.11). For most PB cells, modulation was similar for noise and tones, but for a few, tone modulation was much less than noise modulation. The lack of PB cell response under monaural conditions precluded any inference regarding the contribution of monaural spectral-shape cues to their azimuth tuning. However, these results indicate that the directionality of some PB cells was more dependent on stimulus bandwidth than was the directionality of others.
Effect of sound direction on strength of two-tone inhibition
According to the side-band inhibition model, a MD cell derives monaural directionality from a noise stimulus by comparing the amount of energy in its excitatory and inhibitory frequency domains. Spectral shape changes with sound direction, thus the relative amount of energy in excitatory and inhibitory frequency domains also changes. At sound directions corresponding with azimuth function peaks, there is presumably a relatively greater amount of energy in excitatory domains than inhibitory domains causing an increase in responsiveness. At sound directions corresponding with azimuth function troughs, there is presumably relatively more energy in inhibitory domains than excitatory domains causing a decrease in responsiveness. We have tested this hypothesis using a two-tone stimulation paradigm, in which stimuli are composed of two frequency components that were presented simultaneously. A constant frequency component, F1, located at BF, caused the cell to discharge when presented alone. F1 was presented in combination with a variable frequency component (F2) that by itself often had no effect on discharge, but when presented simultaneously with F1 it could cause a decrease (2-tone inhibition) or increase (2-tone facilitation) in responsiveness relative to the response to F1 alone. According to the side-band inhibition hypothesis, two-tone inhibition in MD cells should be stronger at azimuth function troughs than at peaks.
Figure 8B shows a MD cell's ALRA that was obtained under monaural conditions and encompasses the full 360° of azimuth. Responses were similar under monaural and binaural conditions including a response trough at 60° (A). This cell's frequency response area is shown in C. Tone bursts were presented in eighth octave steps between 2 and 40 kHz, and a single excitatory domain was revealed with a BF of 17 kHz. A `constant-SPL F1' two-tone paradigm, as described in the figure legend, revealed two low-threshold, inhibitory domains (gray shading C), one overlapping the excitatory domain and extending to higher frequencies, and the other centered near 6 kHz.
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To compare two-tone responses at different sound directions, we used an "equal-amplitude" two-tone paradigm in which the amplitudes of F1 and F2 were identical in the electrical two-tone signal that was generated by the computer. The equal-amplitude frequency components in the two-tone signal paralleled the equal-amplitude composition of frequency components in the flat spectrum of the electrical signal of the noise stimulus. The relative amplitudes of frequency components in both noise and two-tone stimuli reaching the eardrum were in general unequal due to the transfer function of the sound system (mainly the loudspeaker) and diffraction of sound by the head and pinna. Nevertheless, the relative amplitudes of the frequency components in the two-tone stimulus were equal to the relative amplitudes of the corresponding frequency components in the noise stimulus because the sound system and acoustical diffraction had the same effect on both. Thus direction-dependent differences in two-tone response functions should reflect direction-dependent differences in cross-frequency excitatory-inhibitory interactions produced by the noise stimulus.
Figure 8D shows the cell's responses to six levels of the equal-amplitude two-tone stimuli that ranged from 80 dB attenuation (dBA) to 30 dBA. F2 varied between 5 and 31 kHz, and individual symbols at 3 and 38 kHz indicate responses to the F1 tone alone at the appropriate level (dBA) that were obtained before and after each two-tone series. A two-tone response that is smaller than the F1-alone response indicates two-tone inhibition. A prominent area of two-tone inhibition was seen near 20 kHz, corresponding with the high-frequency inhibitory domain seen in C. Additionally there was a region of weak inhibition that corresponds with the 6-kHz inhibitory domain in C. A two-tone response that is larger than the F1-alone response indicates two-tone facilitation, and facilitation was seen in two-tone responses between 7 and 15 kHz, and between 26 and 31 kHz.
Equal-amplitude two-tone stimuli were presented from directions corresponding to a trough (60°, D) and a peak (30°, E) in the azimuth function. Two-tone inhibition and facilitation are seen at each direction but inhibition is stronger at the trough than at the peak. The two-tone response decreases to near 0 spikes per stimulus at the trough (D) and to a minimum of about one spike per stimulus at the peak (E).
The individual equal-amplitude data (D and E) were averaged across level, normalized as a percentage of response to F1 alone, and the normalized functions are shown in F. Responses <100% represent two-tone inhibition and responses >100% represent two-tone facilitation. The normalized functions exhibit the major patterns of inhibition and facilitation seen in the functions for individual levels. Prominent two-tone inhibition is seen at both directions between 18 and 24 kHz but is stronger in response to stimuli delivered at the trough than at the peak. Additionally both functions show weak two-tone inhibition in the range of 6-7 kHz, although inhibition is a bit stronger to stimuli delivered from the trough than from the peak. Two-tone facilitation is seen in both functions, and the patterns are not identical. If two-tone facilitation contributes to monaural directionality, facilitation would be expected to be stronger at peak than at trough directions. The greatest difference in two-tone facilitation appears in the range of 12-15 kHz, but facilitation is stronger at the trough than at the peak direction. This is opposite of the expectation if two-tone facilitation was to contribute to increased responsiveness at the peak direction.
Figure 9 shows frequency response areas (left) and normalized, equal-amplitude, two-tone functions (right) for four different MD cells. Azimuth functions for the cells in Fig. 9, middle top, middle bottom, and bottom, are illustrated in other figures. The lower two frequency response areas do not show inhibitory domains because those data were not collected. The strongest inhibitory response to the entire set of two-tone stimuli occurred at the trough in each of these cells as was the case for all MD cells that were tested. The two cells in Fig. 9, top and middle top, showed inhibition in frequency domains above and below F1 that was stronger at the trough than the peak. The cells in the third and fourth rows showed inhibition at F2 frequencies above F1, and the inhibition was stronger at the trough than at the peak. Consistent direction-dependent differences in inhibition were not apparent at F2 frequencies below F1 in these cells.
|
Eight MD cells were tested using the equal-amplitude two-tone paradigm. Normalized two-tone data (e.g., Fig. 9, right) were plotted for each cell as a scatter plot in Fig. 10 to further evaluate the relationship between responses to two-tone stimuli from trough and peak directions. Each point in the scatter plot represents a cell's averaged, normalized response at peak and trough directions to two-tone stimuli with the same F2 frequency. Different points represent normalized responses to two-tone stimuli that differ in F2 frequency. Shading of different quadrants indicates whether two-tone inhibition occurs at both peak and trough (dark), either peak or trough but not both (light) or neither peak or trough. (unshaded). Conversely, shading indicates whether two-tone facilitation occurs at peak and trough (unshaded), either peak or trough but not both (light), or neither peak or trough (dark). We use the term facilitation to include all instances in which the response to the two-tone stimulus was larger than the response to F1 alone. In some cases, the cell did not respond to F2 alone (e.g., Figure 8), and in other cases, both F1 and F2 produced excitatory responses when presented alone (e.g., Fig. 9, bottom). In Fig. 10A, all points were located in the lower left quadrant of the graph, showing that each two-tone pair produced inhibition at both directions. In all other cases, responses showed a mixture of two-tone inhibition and facilitation, depending on sound direction, and the particular frequency composition of the two-tone stimulus.
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In some cells, most points were located above the diagonal line of unity slope showing that normalized two-tone responses for most F2 frequencies were smaller at trough that at peak directions. A paired t-test was performed on data from each cell, and in the case of three cells (A, B, and F), responses at the trough were found to be significantly smaller than at the peak (P values are shown in figure panels). I shows the sum of data for the eight cells. Responses at the trough (91.9 ± 39.3%, mean ± SD) were on average smaller than responses at the peak (96.4 ± 29.7%), and the difference was statistically significant (P < 0.03). To more directly answer the question whether two-tone inhibition was stronger at trough than at peak directions, a t-test was performed on all normalized responses that showed two-tone inhibition to stimuli delivered from the peak, trough, or both directions. These data are located in the darkly and lightly shaded quadrants of I and exclude responses that showed facilitation at both directions (unshaded quadrant). The difference in response magnitude was statistically significant (n = 93, trough, 72.5 ± 30.4%; peak, 83.6 ± 23.8%, P < 0.0000006) showing that two-tone inhibition was stronger at trough than at peak directions in the tested sample of MD cells. Two-tone facilitation could in theory also contribute to monaural directionality if two-tone facilitation were stronger at the peak than at the trough. To address this question, a t-test was performed on all responses that showed two-tone facilitation to stimuli delivered from either the peak, trough, or both directions (unshaded and lightly shaded quadrants of panel I). There was no significant difference in response (n = 73, trough, 117.3 ± 27.6%; peak, 115.0 ± 20.6%, P < 0.43) showing that two-tone facilitation does not contribute significantly to monaural directionality of this sample.
MD cells exhibit stronger inhibitory response attributes than BD cells
According to the side-band inhibition model, MD cells exhibit stronger monaural directionality than BD cells because they have stronger inhibitory side-bands. Stronger inhibitory side-bands might be expected to cause MD cells to exhibit narrower frequency tuning and more strongly nonmonotonic rate level functions than BD cells and cause MD cells to respond with lower discharge rates to noise than tone-burst stimulation. Of the 93 cells for which we had frequency tuning data, 80 had a single excitatory frequency domain and 13 had two excitatory domains. In these latter cells, the two excitatory domains had thresholds within 20 dB of each other and were separated by a frequency range throughout which the cell was not excited by tones <60 dB above threshold. There was no obvious relationship between unit classification and the presence of two excitatory domains (13%, 6/46 BD cells; 8%, 1/12 PB cells; 17%, 6/35 MD cells). Tonal responses for 87 cells were sufficiently complete to allow measurement of excitatory bandwidth at 30 dB re threshold. In the case of a few cells with strongly nonmonotonic level tuning (e.g., Fig. 9A), width was measured at a lower level because the cell was unresponsive at 30 dB. In the case of cells with two excitatory domains, the two bandwidths were averaged to obtain a single value. Responses to tone bursts were obtained under binaural conditions for PB cells and under monaural conditions for most BD and MD cells (see legend of Fig. 11). ANOVA showed a significant bandwidth difference among groups (P < 0.0001). The BD group average bandwidth (1.27 ± 0.84 octaves, n = 46) was significantly greater than the MD (0.63 ± 0.34 octaves, n = 30, P < 0.001) and PB averages (0.63 ± 0.31 octaves, n = 11, P < 0.05). There was no significant difference between the MD and PB groups (post hoc t-test with Bonferroni correction).
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Level-response-function nonmonotonicity for binaural noise bursts was compared for different groups of azimuth-sensitive units (Table 1). Nonmonotonic (NM) strength was defined as the greatest percentage reduction from maximum response with increasing SPL and could vary between 0% (maximum response at highest SPL) and 100% (no response at an SPL higher than that at which the maximum occurred). ANOVA showed a significant difference in nonmonotonic strength among groups for noise (P < 0.001) and BF tone stimulation (P < 0.002). For both noise and BF tone stimulation, average NM strength of MD cells was significantly greater than that of BD cells but not significantly different from that of PB cells. The difference between the BD and PB averages closely approached significance (Table 1).
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The maximum responsiveness (Rmax) of individual cells to noise and tone bursts was obtained from azimuth-level data sets and frequency-level data sets, respectively. The noise and tone Rmaxs were obtained under identical binaural or monaural conditions for each cell. Most BD and MD cells were tested under monaural conditions, and PB cells were tested under binaural conditions (see legend of Fig. 11). Figure 11 is a scatter plot that compares each cell's Rmax for noise and tone bursts. As a group, MD cells were significantly less responsive to noise (2.6 ± 2.0 spikes/stimulus) than tones (4.5 ± 4.4 spikes/stimulus, P < 0.005, paired t-test). In contrast, the combined BD-EI and BD-FI cells showed no significant differences in responsiveness to noise (3.6 ± 3.4 spikes/stimulus) and tones (3.4 ± 3.0 spikes/stimulus P < 0.35) nor did the PB group (noise, 2.7 ± 1.9, vs. tone, 2.4 ± 1.5 spikes/stimulus, P < 0.52). These comparisons of frequency tuning, nonmonotonicity of level-response functions, and responsiveness to noise and tones are consistent with the idea that MD cells have stronger inhibitory sidebands than BD cells.
Relationship between spectral notches and azimuth function troughs
Monaural azimuth functions of some MD cells exhibited a response
trough at a single azimuth (e.g., Figs. 5 and 6). Response troughs may
occur in azimuth functions of DCN neurons when BF coincides with
spectral notch center frequency (Imig et al. 2000
). We
examined our data to determine whether a similar phenomenon occurs in
the IC. Spectral notches with center frequencies in the range of 9-13
kHz vary systematically as a function of sound-source direction
(Rice et al. 1992
). In the frontal horizontal plane, notches with lower center frequencies are located further from the
stimulated ear than those with higher center frequencies (spectral notch data, Fig. 12). If spectral
notches produce azimuth function troughs, then troughs should occur at
the same locations as spectral notches with center frequency equal to
unit BF. Three MD cells are illustrated with BFs in this range, and
they show the expected relationship. The cell with the lowest BF (8.5 kHz, Fig. 5, top) has a trough located at
30°, furthest
from the stimulated ear. The cell with the highest BF (13 kHz, Fig. 6,
top) has a trough located at +30°, closest to the
stimulated ear. And a cell with an intermediate BF (11 kHz, Fig. 5,
bottom) has a trough in an intermediate location. Figure 12
shows the relationship between BF and response trough location for all
MD cells that exhibited single-azimuth troughs. The contralateral ear
was excitatory for all but one of these cells, and for this one, the
location of the trough was reversed in sign so that data are plotted as
if the contralateral ear were excitatory in each case. Eight units had
BFs between 8.5 and 13 kHz. The slope of the linear regression line fit
to these data closely parallels the slope of the line connecting the
spectral notch data points, although it is displaced 10-15° toward
the left ear.
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Comparison of strength of spectral inhibition in the IC, MGB, and AI
We compared the strength of spectral inhibition in the IC with
that in the MGB and AI. A measure of strength of spectral inhibition for MD cells was obtained from their monaural-noise azimuth functions. We counted the number of azimuth function values that were
25% of
maximum out of the seven azimuths at which each cell was tested (±90,
±60, ±30, 0°). We reasoned that spectral inhibition caused responsiveness to decrease to
25% in the monaural responses of MD
cells, so that the greater number of azimuths at which responsiveness was
25%, the stronger the spectral inhibition. Data for the MGB and
AI were obtained from previous work from this laboratory (Samson et al. 2000
). The number of azimuths at which responsiveness
was
25% showed a small increase at successively higher levels (IC, n = 43, 2.3 ± 1.5; MGB, n = 30, 2.7 ± 1.6; AI, n = 28, 3.0 ± 1.7), but the
differences were not statistically significant.
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DISCUSSION |
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Comparison of single-unit responses to noise bursts delivered
under monaural and binaural conditions allowed identification of
monaural and binaural contributions to directionality in the IC.
Directional cells were by definition those that exhibited
75%
azimuth-dependent modulation in responsiveness, where responsiveness is
taken as an average response to a wide range of SPLs. Thus directional
cells responded well at certain azimuths and relatively poorly, if at
all, at others, even at high SPLs. BD cells were directional under
binaural but not monaural conditions. On the other hand, MD cells were
directional under both binaural and monaural conditions. This shows
that MD cells were more sensitive to directional cues present in
monaural noise bursts than were BD cells.
MD cells in the IC were directional to noise but not tone bursts under
monaural conditions. Similar findings have been reported for MD cells
in AI and the MGB (MGB: Imig et al. 1997
; AI:
Samson et al. 1993
; MGB and AI: Clarey et al.
1995
). From these results, we infer that MD cells derive
directionality from direction-dependent spectral shape variation that
is present to a much greater extent in noise than in tone bursts. We
are unaware of any other potential directional cue present in noise
bursts and so feel that this assumption is reasonable.
All high-frequency neurons in the auditory system exhibit directional
responses to low-level stimulation under monaural conditions, i.e.,
they are responsive at some directions and not others (e.g., Moore et al. 1984
) (monaural ALRAs in this report). If
one views the magnitude of a neuron's spike discharge as reflecting
the amount of energy falling in its excitatory frequency domain (energy detector model), then low-level monaural directionality is expected due
to sound amplification by the pinna and sound shadowing by the head.
Given high-level stimuli, an energy detector would be expected to
respond well to all directions. Auditory nerve fibers (Poon and
Brugge 1993
; Rice et al. 1995
) and many BD cells
in the IC, MGB, and AI do respond well at all directions to monaural stimulation (Samson et al. 1994
, 2000
). In contrast, MD
cells are relatively unresponsive to noise bursts at certain azimuths even at high SPLs, a characteristic that is inconsistent with the
energy detector model. A deep spectral notch, for example, may cause a
reduction in sound level of 20 dB or so at its center frequency. A
notch at BF might cause a low-level noise stimulus to drop below
threshold. If a cell is responding only to the amount of energy near
BF, then an increase in stimulus level by
20 dB should result in a
response. But this does not occur as can be seen in the ALRAs of the MD
cells. These cells failed to respond or responded only weakly at
certain azimuths regardless of SPL.
According to the side-band inhibition hypothesis, the responsiveness of a MD cell depends on the relative balance of acoustic energy in the cell's excitatory and inhibitory frequency domains. Spectral shapes that increase energy in excitatory relative to inhibitory frequency domains produce an increase in responsiveness, shapes that increase energy in inhibitory relative to excitatory domains produce a decrease in responsiveness. Assume that a notch (or some other spectral feature) reduces energy in an excitatory domain relative to adjacent inhibitory domains. Raising SPL of a noise burst does not cause the cell to respond because energy increases not only in the excitatory domain but also in inhibitory domains. Because inhibition predominates, the cell does not discharge. Although there is no direct evidence that "spectral inhibition" is a result of synaptic inhibition, neither is "side-band inhibition" believed to result entirely from synaptic inhibition. Nevertheless, because the term "side-band inhibition" is commonly accepted, then "spectral inhibition" should be likewise accepted as both appear to reflect common mechanisms.
The side-band inhibition hypothesis gains support from finding that
two-tone inhibition is stronger at directions where an MD cell is
relatively unresponsive to a noise stimulus than at directions where it
is responsive. Similar findings have been previously reported in the
MGB (Imig et al. 1997
). MD cells commonly showed
two-tone facilitation in addition to two-tone inhibition, and two-tone
facilitation has previously been reported in the IC (cat: Ehret
and Merzenich 1988
; mouse: Egorova et al. 2001
, bat: Mittmann and Wenstrup 1995
; Wenstrup et al.
1999
; Yan and Suga 1996
). In theory, two-tone
facilitation could also contribute to monaural directionality, but our
data suggest that it is not a significant factor.
Noise bursts containing artificially produced spectral notches inhibit
the discharge of DCN neurons when center frequency coincides with BF
(Nelken and Young 1994
; Spirou and Young
1991
). Noise bursts containing naturally occurring spectral
notches also inhibit the responses of DCN neurons. Troughs in
noise-burst azimuth functions occurred at locations where
spectral-notches' center frequencies were expected to coincide with
unit BF (Imig et al. 2000
). The present results strongly
suggest that notch inhibition can also account for response troughs in
some IC MD cells' azimuth functions based on the same reasoning. When
a notch is centered at a cell's BF, it reduces energy in an excitatory
frequency domain with respect to inhibitory domains, thus causing a
decrease in responsiveness. Changing sound-source direction causes the
notch to shift in frequency away from the cell's excitatory domain, energy increases in excitatory relative to inhibitory domains, and the
cell's responsiveness increases. The result is a trough in the cell's
azimuth function where the notch was centered at BF. Spectral notches
with center frequencies in the range of 9-13 kHz show a linear
relationship to azimuth in the horizontal plane (Rice et al.
1992
) that parallels azimuth function trough location for IC
neurons with BFs in the same range. This is the expected result if a
trough is created when a spectral notch is centered at a cell's BF.
There is about a 10-15° disparity between the acoustic and IC neural
data. It is not surprising that a similar disparity was found in the
DCN because both the IC and DCN studies used the same protocol for head
and pinna orientations. At least two factors could account for the
disparity between the neural and acoustic data. The disparity may be
due to differences in pinnae and head orientation used to obtain the
acoustic and neural data as spectral notch location is known to depend
on pinna orientation (Young et al. 1996
). Additionally,
disparities of this magnitude are found in acoustical measurements
among individual animals (Xu and Middlebrooks 2000
).
The side-band inhibition model of spectral inhibition can in theory
account for the peak-shaped azimuth functions exhibited by some MD
cells in the IC and in the MGB and AI (Imig et al. 1997
;
Samson et al. 1993
, 2000
). One can imagine that a cell
with a strong inhibitory and relatively weak excitatory frequency
domain would be inhibited by noise stimulation except at locations
where energy in the inhibitory domain was reduced relative to the
excitatory domain. This could occur when a spectral notch is centered
on the inhibitory domain. In this case, the cell is unresponsive at
most azimuths because of spectral inhibition and responds at one or a
few azimuths because of spectral disinhibition. While we have focused
on notches, there is no reason to believe that notches are the only
spectral shape to which MD cells are sensitive.
Delgutte et al. (1999)
described directional responses
of IC neurons using virtual space stimuli. Ten neurons showed troughs in their midline elevation functions, and in 4/10, there was a spectral
notch corresponding to unit BF at that location. This finding appears
somewhat inconsistent with our results that indicated spectral notches
corresponded with response troughs for all MD cells with BFs in the
range of 8.5-13 kHz. It is quite possible that the apparent
inconsistencies between the two sets of data reflect methodological
differences. Delgutte et al. (1999)
used a single rather
low level of stimulation. We used a broad range of SPLs, and thus
response troughs in our data are not level-dependent and indicate
locations where spectral inhibition is strongest. Additionally,
Delgutte et al. (1999)
used binaural stimulation so it
is possible that binaural interactions may have contributed to troughs
in their data. We presented stimuli under monaural conditions and thus
only monaural cues could contribute to troughs.
According to the side-band inhibition model of spectral inhibition, MD
cells should have stronger and/or broader inhibitory frequency domains
than BD cells. Response properties of MD and BD cells in the IC showed
several significant differences that are consistent with this
prediction. MD cells exhibited significantly narrower excitatory
frequency domains and greater nonmonotonic strength to noise and BF
tone bursts than BD cells. Additionally, MD cells had lower discharge
rates to noise than tones, whereas BD cells had similar discharge rates
to tones and noise. Together these differences suggest that MD cells
receive stronger inhibitory input than BD cells. MD and BD groups in
the MGB and AI show similar differences in frequency tuning,
nonmonotonic strength to noise stimuli, and discharge rates to noise
and tones (Clarey et al. 1995
; Imig et al.
1997
; Samson et al. 2000
). These data suggest a
common mechanism of monaural directionality at these different sites in
the auditory system.
Monaural spectral inhibition makes a relatively modest contribution to
the azimuth tuning of BD-EI, BD-FI, and BD-F cells in the IC. The
contribution to PB cells cannot be determined using the method of
monaural/binaural response comparison because PB cells do not respond
under monaural conditions. Stimulus bandwidth appears to be important
for the directionality of at least some PB cells as their
directionality to tonal stimulation is much less than that to noise.
These findings regarding BD, MD, and PB cells are consistent with
previous observations in the MGB and AI (Clarey et al.
1995
). Our data are insufficient to determine whether
spectral-dependent directionality reflects monaural spectral inhibition
in monaural inputs to PB cells, a binaural mechanism of spectral
sensitivity, or both.
The azimuth preferences and patterns of binaural interactions that we
observed using free-field stimulation and ear plugging are consistent
with those expected from previous studies using independent earphone
stimulation of each ear. Most cells had azimuth preferences that varied
from near the midline to the contralateral pole, although a few had
ipsilateral preferences in agreement with previous studies. Three
patterns of binaural interactions could be recognized that contributed
strongly to azimuth tuning. These include binaural inhibition, mixed
binaural facilitation and inhibition, and binaural facilitation.
Previous studies reported similar patterns of binaural interactions in
the IC of cats using noise, tones, clicks, and virtual space noise
bursts delivered through earphones sealed to the ears (e.g.,
Delgutte et al. 1999
; Geisler et al.
1969
; Irvine 1986
; Irvine and Gago
1990
; Rose et al. 1966
).
Previous work shows that directional tuning of some IC neurons in the
cat is dependent on stimulus bandwidth. Aitkin and Martin (1987)
observed that 28% of their sample of high-frequency
neurons was sensitive to the azimuth of broadband noise but not tone
bursts. Neurons in the IC of the bat are more sensitive to the azimuth of two-tone stimuli consisting of a BF tone and a second tone in an
inhibitory frequency domain than to BF tones presented alone (Zhou and Jen 2000
). These results show that
directionality depends on stimulus bandwidth but don't indicate
whether the mechanism was binaural or monaural.
Azimuth tuning of IC neurons to noise burst stimulation may reflect
predominantly binaural interaction, predominantly monaural spectral
inhibition, or a combination of both. It is possible that the variety
of response patterns described here are the result of two independent
processes, binaural mechanisms that determine different types and
strengths of binaural interactions, and monaural mechanisms that
determine the strength of spectral inhibition. While this seems to be
consistent with our IC data, we would not have suggested this based on
our data from the MGB and auditory cortex as MD cells showing
facilitation or mixed binaural interactions were much less commonly
identified in those structures (Samson et al. 1993
,
2000
). Nevertheless, there were a few. It is possible that
these types of responses really are less frequently encountered in the
forebrain or that we simply failed to recognize them as often.
Binaural interactions that contribute to IC neural directionality are
believed to originate in the superior olivary system, the dorsal
nucleus of the lateral lemniscus and IC (literature reviewed by
Delgutte et al. 1999
; Tollin and Yin
2002a
). The sources of MD sensitivity are much less certain. MD
sensitivity may be transmitted from lower levels of the auditory system
to the IC, generated locally within the IC, or both.
DCN neurons are more sensitive to spectral shape and show greater
monaural directional sensitivity than ventral cochlear nucleus (VCN)
neurons (Imig et al. 2000
; Young et al.
1992
) or auditory nerve fibers (Poon and Brugge
1993
; Rice et al. 1995
). DCN neurons provide
excitatory input to the IC (Semple and Aitkin 1980
), and Davis (2002)
has demonstrated that some IC neurons
receive input predominantly from the DCN. Thus it is possible that at
least some MD cells in the IC receive input directly from the DCN.
Although VCN neurons appear less sensitive to spectral shape than DCN
neurons, it is unknown whether or not neurons in most of the brain stem
nuclei that receive input from the VCN are sensitive to spectral shape.
The exception is the lateral superior olive (LSO) that receives
excitatory input from the ipsilateral VCN and inhibitory input from the
contralateral VCN via relay in the medial nucleus of the trapezoid body
(Schwartz 1992
). Tollin and Yin (2002b)
used virtual space stimuli to experimentally investigate the
contribution of binaural disparities and spectral shape in producing
azimuth tuning in LSO neurons. They found that binaural inhibition
acting on interaural level differences was most important and that
spectral shape variation made little contribution. They suggested that
LSO neurons are likely major contributors to ILD-sensitive IC neurons
that exhibit binaural inhibition. In our study, BD-EI cells might be
expected to be recipients of LSO input as their directionality depends
predominantly on binaural disparities and not on spectral shape.
Although neurons in DCN pathways may be more sensitive to spectral
shape than neurons in VCN pathways, both appear to be important for
accuracy of monaural, spectral-shape-dependent sound localization in
cats. Lesion of the dorsal acoustic stria, that carries DCN fibers to
the IC, causes a decrease in accuracy of reflex orientation to noise
bursts that vary in elevation, suggesting that the DCN plays an
important role in this spectral-shape dependent localization behavior.
On the other hand, the same lesion does not cause an increase in
minimum audible angle in elevation (May 2000;
Sutherland et al. 1998a
,b
), suggesting that the VCN
pathways convey sufficient monaural spectral shape information for this
localization task. It appears that both the DCN and VCN pathways could
potentially convey information that ultimately contributes to the MD
responses in the IC.
IC neurons exhibit greater monaural directionality than DCN or VCN
neurons showing that much of the MD sensitivity in IC neurons appears
to be generated above the level of the CN and quite possibly within the
IC. DCN neurons are more sensitive to monaural spectral shape cues than
VCN neurons or auditory nerve fibers (Poon and Brugge
1993
; Rice et al. 1995
), but DCN spectral
sensitivity cannot account for that seen in the IC. Only ~2% (1/61)
of the presumed output neurons recorded in the DCN exhibited
noise-burst azimuth-function modulation
75% (Imig et al.
2000
), whereas an estimated 23% of the high BF cells in the IC
exhibit noise-burst azimuth-function modulation
75%. This estimate
is based on the fact that 69% of the IC neurons that we recorded were
directional and that 33% (43/129) of the directional cells that were
tested showed monaural directionality (0.33 * 0.69 = 0.23).
Furthermore, peak-shaped monaural azimuth functions are found in the IC
but not the DCN (Imig et al. 2000
). These are presumably
a result of spectral disinhibition that depends on very strong
inhibitory side-bands. Such strong inhibition is not present in the CN
and could be produced locally within the IC. Iontophoretic injection of
GABAergic and glycinergic agonists and antagonists show that inhibitory
mechanisms within the IC contribute to side-band inhibition
(Davis 2002
; Faingold et al. 1991
;
Fuzessary and Hall 1996
; Pollak and Park 1993
; Vater et al. 1992
; Yang et al.
1992
). As side-band inhibition is believed to be an important
basis for monaural directionality, this suggests that much MD
sensitivity may be generated with the IC.
Our data do not show compelling evidence for a significant increase in
strength of spectral inhibition in the MGB and AI as compared with the
IC. The estimated proportion of high-frequency cells that are
monaurally directional is slightly lower in the forebrain as compared
with the IC. MD cells comprise ~23% of the high-frequency sample in
the IC and ~18% of the samples in the MGB and AI (Barone et
al. 1996
; Samson et al. 2000
). The estimated strength of spectral inhibition is sequentially greater from the IC to
the MGB to AI, but the difference is not statistically significant. It
appears that there are significant increases in spectral inhibition between the level of auditory nerve fibers and the DCN and between the
DCN and the IC but relatively little additional change between the IC
and the forebrain.
On the basis of this comparison, it is not unreasonable to assume that
MD responses in the MGB and AI at least in part reflect response
properties that are transmitted from lower levels. Nevertheless, inhibitory side-bands are also locally generated in each structure (MGB: Suga et al. 1997
; auditory cortex: Chen and
Jen 2000
; Wang et al. 2000
), and this could
contribute to MD responses in the forebrain. Some cells in the MGB and
IC have frequency tuning characterized by two or more excitatory
domains. In the MGB, a significantly higher proportion of MD cells than
BD cells had multiple excitatory domains (Imig et al.
1997
), but this was not true in the IC sample. Overall, the MGB
sample contained a somewhat higher proportion of cells with two or more
excitatory domains (15/65, 23%) than the IC sample (13/93, 14%). It
is possible that generation of MD responses with multiple excitatory
frequency domains in the MGB could account for these differences.
Delgutte et al. (1999)
questioned the validity of the
ear plugging method due in part to the effect of sound leakage through the earplug and in part due to the reproducibility of attenuation produced by multiple earplug insertions. There is no doubt that greater
interaural cross-talk occurs with the ear-plugging method than with
earphones sealed to each ear. Nevertheless attenuation produced by
earplugs is adequate to answer the questions we asked. Ear plugging by
injection of ear mold compound typically produces attention of 40-60
dB in the frequency range to which our sample of cells was most
sensitive (>4 kHz). This amount of attenuation was sufficient to
unambiguously identify a neuron's binaural interactions and monaural
directionality. There was a minor problem of interpreting whether the
high-threshold monaural responses obtained during ear plugging in some
cells were really monaural responses or responses to sound leaking
though the ear plug. We opted for the latter interpretation although
this has no major bearing on the major findings in this report.
Additionally, similarity of neural responses to repeated sets of
binaural stimuli (e.g., azimuth functions in Figs. 1, 3, 4-6, and 8)
separated by insertion and removal of one or more earplugs shows that
ear plugging had an effect only when the earplug was in place. Plugging
had no lasting effect on a unit's response after the plug was removed.
Similarity of neural responses to repeated stimulus sets under monaural
conditions separated by removal and reinsertion of the earplug shows
that similar attenuation was typically produced each time the ear was plugged. Our data are completely consistent with previous studies regarding the types of binaural interactions and the relationship of
binaural interaction types to receptive field locations, including those reported by Delgutte et al. (1999)
. Sound leakage
through the earplug does not have a significant effect on
interpretation of binaural interactions. We cannot think of a way that
sound leakage could cause the patterns of spectral inhibition that were apparent in our data. Thus while the issues raised by Delgutte et al. (1999)
are certainly potential problems, our results
suggest that they do not seriously hinder data interpretation.
Some unilaterally deaf humans are able to localize sounds with
considerable accuracy in all three dimensions, showing that monaural
spectral shape cues potentially could provide information useful for
right-left localization (Slattery and Middlebrooks 1994
). Nevertheless it is generally believed that normal
listeners, under binaural conditions, do not rely on spectral shape
cues for localization in this dimension (Middlebrooks
1992
; Middlebrooks and Green 1991
;
Wightman and Kistler 1992
, 1997
). This raises the
question of the possible function of MD cells in the IC that derive
azimuth sensitivity from monaural spectral shape cues. Front-back
confusion is believed to result because binaural disparities are
identical or nearly so at directions that are symmetrical with respect
to the interaural axis. MD cells presumably could provide useful
information to resolve front-back confusion because monaural spectral
shape cues are not symmetrical about the interaural axis. Cell's
deriving azimuth tuning predominantly from binaural disparities might
be expected to show symmetrical azimuth tuning about the interaural
axis, and an example of a BD-EI cell in the MGB with symmetrical tuning
has previously been published (Fig. 1 in Samson et al.
2000
). Spectral shape cues do not exhibit interaural axis
symmetry (Musicant et al. 1990
; Rice et al.
1992
), so MD cells would be expected to show nonsymmetrical
azimuth tuning about the interaural axis, as is the case (e.g., Figs.
4, top, and 8, A and B). Examples of
other MD cells with nonsymmetrical front-back azimuth tuning have also
been illustrated in AI (Samson et al. 1993
) and the MGB
(Samson et al. 2000
). Thus azimuth sensitivity dependent
on monaural spectral shape variation may play a role in front-back
localization. Monaural spectral shape sensitivity may also play a role
in minimum audible angle (MAA) tasks that require detection of whether
the location of two sound sources is the same or different not the
actual location of the source. Unilaterally deafened cats can detect
differences in the elevation of a sound source with similar accuracy to
normal cats, suggesting that cats normally utilize monaural shape
sensitivity in this task (Sutherland et al. 1998a
). We
are unaware of studies that have tested unilaterally deafened cats for
MAA sensitivity in azimuth. Binaural disparities are generally believed
to contribute strongly to MAA sensitivity in azimuth at least near the
median plane (Middlebrooks and Green 1991
; Mills
1958
). The degree to which monaural spectral shape cues may
contribute to MAA sensitivity in azimuth, especially near the lateral
poles, under normal listening conditions is unknown. Experiments using
virtual space stimuli in which monaural spectral-shape and binaural
disparity cues are independently manipulated offer an opportunity to
shed light on this question.
| |
ACKNOWLEDGMENTS |
|---|
We thank C. Bailey for careful preparation of histological materials, data analysis and preparation of illustrations and H. Cheng for computer programming. We also thank anonymous reviewers whose considerable effort has resulted in significant improvement of the manuscript.
Support for this work was provided by National Institutes of Health Grant DC-00173 and Core Support Grant HD-02528 and by the Fonds de la Recherche en Santé du Québec and the Fonds pour la Formation de Chercheurs et l'Aide à la Recherche (P. Poirier).
Present address of P. Poirier: 1080 Ste-Elisabeth #6, Montreal, P.Q., H2X 3V3 Canada.
| |
FOOTNOTES |
|---|
Address for reprint requests: T. J. Imig, Dept. of Molecular and Integrative Physiology, Kansas University Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160-7401 (E-mail: timig{at}kumc.edu).
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