Department of Molecular and Integrative Physiology, Kansas University Medical Center, Kansas City, Kansas 66160-7401
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ABSTRACT |
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Samson, Frank K., Pascal Barone, W. Andrew Irons, Janine C. Clarey, Pierre Poirier, and Thomas J. Imig. Directionality Derived From Differential Sensitivity to Monaural and Binaural Cues in the Cat's Medial Geniculate Body. J. Neurophysiol. 84: 1330-1345, 2000. Azimuth tuning of high-frequency neurons in the primary auditory cortex (AI) is known to depend on binaural disparity and monaural spectral (pinna) cues present in broadband noise bursts. Single-unit response patterns differ according to binaural interactions, strength of monaural excitatory input from each ear, and azimuth sensitivity to monaural stimulation. The latter characteristic has been used as a gauge of neural sensitivity to monaural spectral directional cues. Azimuth sensitivity may depend predominantly on binaural disparity cues, exclusively on monaural spectral cues, or on both. The primary goal of this study was to determine whether each cortical response pattern corresponds to a similar pattern in the medial geniculate body (MGB) or whether some patterns are unique to the cortex. Single-unit responses were recorded from the ventral nucleus (Vn) and lateral part of the posterior group of thalamic nuclei (Po), tonotopic subdivisions of the MGB. Responses to free-field presentation of noise bursts that varied in azimuth and sound pressure level were obtained using methods identical to those used previously in field AI. Many units were azimuth sensitive, i.e., they responded well at some azimuths, and poorly, if at all, at others. These were studied further by obtaining responses to monaural noise stimulation, approximated by reversible plugging of one ear. Monaural directional (MD) cells were sensitive to the azimuth of monaural noise stimulation, whereas binaural directional (BD) cells were either insensitive to its azimuth or monaurally unresponsive. Thus BD and MD cells show differential sensitivity to monaural spectral cues. Monaural azimuth sensitivity could not be used to interpret the spectral sensitivity of predominantly binaural cells that exhibited strong binaural facilitation because they were either unresponsive or poorly responsive to monaural stimulation. The available evidence suggests that some such cells are sensitive to spectral cues. The results do not indicate the presence of any response types in AI that are not present in the MGB. Vn and Po contain similar classes of MD and BD cells. Because Po neurons project to the anterior auditory field, neurons in this cortical area also are likely to exhibit differential sensitivity to binaural disparity and monaural spectral cues. Comparison of these MGB data with a published report of cochlear nucleus (CN) single-unit azimuth tuning shows that MGB sensitivity to spectral cues is considerably stronger than CN sensitivity.
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INTRODUCTION |
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Sound localization is important for survival,
and neural mechanisms have evolved that utilize two available acoustic
cues for location. Binaural time and level disparities are available to
the brain as a consequence of the separation of the two ears on either
side of the head, and they are most important for left-right (azimuth)
localization. Spectral (pinna) cues derive from diffraction of
high-frequency broadband sounds primarily with the pinna and are most
important for up-down (vertical, elevation) and front-back localization
(Middlebrooks and Green 1991).
Many neurons in the cat's central auditory system are sensitive to the
azimuthal direction of noise bursts. They respond well to some sound
directions and poorly to others over a broad range of sound pressure
level (SPL) (Aitkin and Martin 1987; Barone et
al. 1996
; Clarey et al. 1992
, 1995
; Imig
et al. 1990
; Rajan et al. 1990
). Single-unit
azimuth tuning in the primary auditory cortex (AI) has been shown to
depend on binaural disparity and monaural spectral cues (Samson
et al. 1993
, 1994
). Whether cortical neurons' response
patterns reflect input from medial geniculate body (MGB) neurons with
similar response patterns or are unique to the cortex is not completely
understood. A major goal of this report is to analyze mechanisms
underlying azimuth sensitivity in the MGB. This will allow comparison
of neural response properties at these two levels of the auditory forebrain.
Cortical field AI receives ascending input from several subdivisions of
the MGB, including two tonotopic regions, the ventral nucleus (Vn) and
the lateral part of the posterior group of thalamic nuclei (Po)
(Imig and Morel 1985a,b
). These are major and
minor sources of input to AI, respectively, judging from the number of
neurons in each structure that is labeled by cortical injections of
horseradish peroxidase (Andersen et al. 1980
;
Morel and Imig 1987
). A large proportion of high (>4
kHz) best-frequency (BF) neurons in Vn and Po is azimuth sensitive
(Barone et al. 1996
), and in some cases this has been
shown to derive from monaural spectral inhibition (Clarey et al.
1995
; Imig et al. 1997
). In other cases azimuth
sensitivity depends on binaural mechanisms (Clarey et al.
1995
), consistent with results of dichotic stimulation studies
(Adrian et al. 1966
; Aitkin 1973
;
Aitkin and Dunlop 1968
; Aitkin and Webster
1972
; Altman et al. 1970
; Ivarsson et al.
1988
). Nevertheless monaural and binaural response patterns of
azimuth-sensitive MGB neurons have not been described in detail so the
extent to which they differ from those in field AI is unknown.
Neurons in Vn and Po provide a massive source of ascending input not
only to cortical field AI but also to the anterior auditory field
(AAF). AI receives input predominantly from the rostral part of
Vn, and AAF receives input predominantly from Po (Andersen et
al. 1980; Morel and Imig 1987
). Consequently,
information regarding directional mechanisms in Vn and Po neurons
provides important clues regarding directional mechanisms in these two
cortical fields. Finally, monaural spectral inhibition contributes to
azimuth sensitivity of CN neurons, especially those in the dorsal
cochlear nucleus (DCN) (Imig et al. 2000
). We shall
compare the effect of monaural spectral inhibition on the azimuth
sensitivity and tuning of DCN and MGB neurons to determine how spectral
inhibition changes between the DCN and the MGB. Some of these results
have been published in preliminary form (Samson et al.
1996
).
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METHODS |
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Single-unit recordings were obtained from the left MGB of 18 cats with clean external ears and normal thresholds estimated from unit
responses. All husbandry and experimental procedures were carried out
according to National Institutes of Health guidelines and using
protocols approved by the Institutional Animal Care and Use Committee
of the Kansas University Medical Center. Chronic recording procedures
were used in 14 cats and acute recording procedures for the remainder.
Acute recording procedures have been described in detail elsewhere
(Barone et al. 1996).
Surgical implant of a chronic recording chamber was carried out using inhalation anesthesia (0.8-1.5% isoflurane in O2) and standard aseptic procedures under veterinary supervision. Postoperative discomfort was ameliorated with analgesics. A stainless steel recording chamber was stereotaxically positioned over a craniotomy and fastened to the skull with dental acrylic and stainless steel screws. A stainless steel tube, used to secure the animal's head to a support rod during recording sessions, was attached to the chamber. The chamber was sealed with a stainless steel cap at times other than during recording sessions to protect the craniotomy from mechanical damage and infection. The dura mater was covered with a broad spectrum antibiotic ophthalmic ointment (bacitracin, neomycin, and polymyxin) prior to sealing the chamber.
Cats were allowed to recover fully from the surgery before the first
recording session, and thereafter recording sessions were scheduled at
2-wk or longer intervals. Animals were anesthetized during chronic
recording sessions to prevent movements. Anesthesia was induced with
isoflurane in O2 and atropine (0.1 mg/kg im) was
injected. Isoflurane was replaced with pentobarbital sodium, which was
maintained throughout the recording session with an intravenous
infusion pump at a rate sufficient to eliminate pinna reflexes and
spontaneous movements (~8.5 mg · kg1 · h
1).
Dexamethasone (2 mg/kg iv) was injected to reduce the possibility of
cerebral edema. Application of ophthalmic ointment prevented corneal
drying. Tracheal intubation ensured a patent airway. Breathing and
heart rates were monitored during the recording session, and temperature was maintained at 38°C using a thermostatically
controlled heating pad. Following the recording session, animals were
kept warm until they awakened from the anesthesia. Marking lesions were
placed during terminal recording sessions for histological localization
of recording sites. Each animal was given a lethal dose of anesthetic
at the end of the terminal recording session and perfused through the
heart with a 10% solution of formol saline. Brain sections 50-µm
thick were cut frozen in the transverse plane and were stained with
cresyl violet.
Recordings were carried out in an electrically shielded,
quasi-anechoic, sound-isolation chamber (Imig et al.
1990; Samson et al. 1993
, 1994
). The
anesthetized cat rested in a sling with its head rigidly fixed. The
head was positioned with the horizontal Horsley-Clarke plane tilting
forward and down at an angle of ~18° from horizontal, which
approximates the head position of an alert cat looking forward. The
ears were pulled to an upright position using strings that were glued
to the outer surfaces of each pinna. Sterility was maintained within
the recording chamber throughout the procedure. Paralene-insulated
tungsten microelectrodes (Frederick Haer) with nominal impedance
between 1 and 4 M
(measured in the brain) were advanced by a
hydraulic micromanipulator controlled from outside the sound chamber.
Electrode penetrations were oriented perpendicular to the
Horsley-Clarke horizontal plane.
Single-unit waveforms were isolated using an amplitude-window discriminator. Times of occurrence of action potentials were stored in computer disk files, with a resolution of 10 µs, for later analysis. A time window was used to reduce the effect of spontaneous discharge on the response of some neurons.
A semicircular array of 13 loudspeakers (Radio Shack 40-1310B) with
similar frequency response characteristics provided free-field sound
stimulation (Imig et al. 1997). These were spaced at
15° intervals in the horizontal plane that intersected the interaural axis. Loudspeakers had a usable frequency range between 4 and 40 kHz.
Sound direction could be varied by presenting sound from different
loudspeakers or by rotating the array. Stimulus generation, loudspeaker
switching, stimulus sequencing, and data collection were controlled by
a PDP 11/73 computer (Imig et al. 1997
; Samson et
al. 1993
, 1994
). The noise waveform was an electrical signal with a flat spectrum between 0 and 50 kHz and random amplitude distribution. The actual spectrum of the noise delivered to the animal
was shaped by the sound-generation system (mainly the loudspeaker).
In searching for single-unit responses, azimuth and SPL were systematically varied to increase the chance of exciting cells that might be selective to narrow ranges of azimuth and/or level. Sounds were sequentially presented at a repetition rate of 3 Hz and at 30° intervals across the frontal hemifield. At each azimuth, noise bursts were presented that ranged from 0 to 80 dB sound pressure level (SPL) in 20-dB steps. Single- and multi-unit BFs (the midpoint of the frequency range that excited units at 10-20 dB above lowest threshold) were assessed regularly to ensure that the electrode was located in a high-frequency representation. Tone- and noise-bursts had a duration of 50 ms with 5-ms linear rise-fall times. Frequency response areas were obtained for most units using 10 stimulus repetitions at each frequency-SPL combination. Tone bursts were presented that varied in frequency (one-quarter or one-eighth octave steps between 4 and 40 kHz) and level (10- to 20-dB steps from near threshold to 80 dB SPL).
Monaural stimulation was approximated by using an ear plug (ear mold
impression material, All American Lab.) to attenuate sound reaching one
ear. Attenuation varied between 32 and 70 dB in the range of 4-32 kHz,
between 35 and 55 dB at 2 kHz and 25 dB at 1 kHz (Samson et al.
1993, 1994
).
Single-unit spike counts were compared statistically to determine
whether ear plugging had a significant effect. Differences over all
azimuth-SPL combinations between binaural and monaural responses were
detected by an ANOVA on the ranks, in which the total number of spikes
obtained after 10 (occasionally 20) stimulus presentations at each
azimuth-SPL combination was entered as one response. If ANOVA revealed
significant differences, a post hoc 2 or a
Fisher exact probability test was applied to determine the azimuth-SPL
combinations at which differences existed. For each azimuth-SPL
combination, these tests compared the number of stimulus presentations
to which the cell was unresponsive, responded with one spike, or
responded with more than one spike. A Bonferroni correction of the
significance level (
) was used to control the error rate for
multiple comparisons (corrected
= uncorrected
/number of
comparisons). If no duplicated data sets were available (i.e., ANOVA
was inapplicable),
2 or Fisher exact
probability tests were directly applied in the same fashion of the post
hoc tests. Details about statistical analysis can be found else where
(Samson et al. 1993
, 1994
).
Some of this work represents part of the PhD research conducted by W. A. Irons.
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RESULTS |
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The MGB sample consisted of 98 well-isolated, azimuth-sensitive
(defined in the following text), single-unit waveforms (equivalently referred to as units, cells, or neurons) with BFs between 5 and 37 kHz.
Units responded to noise bursts with one or a few spikes (a burst of
spikes in a few cases), and at minimal latencies of 4.7-32.7 ms
[10.2 ± 3.7 (SD) ms]. Five units also exhibited long latency
responses in the range of 43-200 ms, but these long-latency responses
are not included in this analysis. Once a unit was isolated, noise
bursts were presented from one of seven equally spaced azimuths in the
frontal hemifield (±90, ±60, ±30, and 0°) and occasionally at
15° intervals or behind the head. At each azimuth, stimulus level was
typically varied between 0-80 dB SPL in 10- or 20-dB steps. Spike
counts for 10 or 20 stimulus repetitions were normalized and displayed
as an azimuth-level response area (ALRA, e.g., Fig. 1A). Gross responses (GRs)
were obtained from each ALRA data set by averaging over level, and
these were plotted as a function of azimuth (e.g., Fig. 1C).
Azimuth function modulation, the percentage difference between maximum
and minimum normalized GR values (modulation, Fig.
2), was used as an index of azimuth
sensitivity. Cells with modulation 75% were classified as azimuth
sensitive. Such units responded well and with low thresholds at certain
azimuths and responded poorly if at all at others regardless of SPL
(e.g., Fig. 1A). Although this criterion for azimuth
sensitivity is arbitrary, it does allow identification of units whose
discharge is most strongly direction dependent, and its use allowed
comparison of these data with previous studies (Samson et al.
1993
, 1994
).
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Once an azimuth-sensitive unit was identified, its responses were obtained to monaural noise stimulation, approximated by unilateral ear plugging. Comparison of a unit's responses to monaural and binaural stimulation revealed the presence of binaural interactions, monaural excitatory inputs, and whether azimuth tuning (azimuth sensitivity and azimuth function shape) was dependent on monaural stimulation, binaural stimulation, or both.
Azimuth tuning of binaural directional (BD) cells depended predominantly on binaural stimulation. The vast majority was either insensitive to the azimuth of monaural noise bursts, i.e., responded well at each direction, or failed to respond to monaural stimulation. Three BD response classes were distinguished depending on whether cells exhibited inhibitory, facilitatory, or mixed binaural interactions. One class was composed of BD-EI cells (n = 33) that received excitatory input from one ear (usually the contralateral) and inhibitory input from the other, i.e., they exhibited binaural inhibition. Their responses to noise bursts were confined mainly to one lateral hemifield, as is the case for the example shown in Fig. 1. This unit was contralateral preferring, i.e., it exhibited lowest thresholds and highest discharge rates to contralateral sound directions (B-stim, A and C). It responded well to monaural contralateral noise bursts at each azimuth (C-stim, B and C). Greater monaural than binaural responsiveness at ipsilateral locations indicated that stimulation of the ipsilateral ear had an inhibitory effect. Azimuth-SPL combinations at which binaural responses were significantly smaller than monaural responses are indicated by circled minus signs in A. Eighteen of 33 BD-EI cells were studied using monaural stimulation of each ear, and they were excited only by stimulation of the ear on the preferred side. For the remainder, monaural responses were obtained only to stimulation of the ear on the preferred side.
A second response class was composed of BD-FI cells (n = 18) that exhibited both binaural facilitation and inhibition. They varied in azimuth preference, and examples of lateral and midline preferring cells are shown in Fig. 3. The left column shows the binaural response of a contralateral preferring cell (A) with a contralateral monaural response that was insensitive to azimuth (B). The cell was more responsive to binaural than to monaural stimulation throughout the contralateral quadrant, revealing the presence of binaural facilitation, and was less responsive to binaural than to monaural stimulation throughout the ipsilateral quadrant, revealing the presence of binaural inhibition (C). Circled plus and minus signs (A) indicate azimuth-SPL combinations for which binaural responses were significantly larger or smaller than monaural responses, respectively. The cell in the Fig. 3, right, was most responsive to binaural noise stimulation presented from the frontal midline (D). Contralateral monaural noise stimulation produced a weak, azimuth-insensitive response (E and F). The unit was unresponsive to ipsilateral monaural stimulation (F). Comparison of binaural and monaural responses showed the presence of strong binaural facilitation at the frontal midline, weaker binaural facilitation in the contralateral quadrant, and binaural inhibition in the ipsilateral quadrant (D and F). These examples show that combined binaural facilitation and inhibition can produce very different patterns of azimuth tuning.
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Most BD-FI cells (14/18) exhibited inhibition only on one side of the midline (e.g., Fig. 3), but a few (4/18) exhibited inhibition on both sides. The example in Fig. 4A showed greatest responsiveness and lowest thresholds to binaural stimulation at the midline. The cell was insensitive (<75% modulation) to the azimuth of contralateral monaural stimulation (B and C), and exhibited high-threshold responses to monaural ipsilateral stimulation (C). High-threshold responses to monaural stimulation were not uncommon, and we assume that they were usually, if not always, a result of leakage of sound through the ear plug. The midline response peak in this cell was created by a combination of facilitation and flanking inhibition (A and C).
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Ten of the 18 BD-FI units were tested with monaural stimulation of each ear, and in each stimulation of the ear on the preferred side was excitatory. Stimulation of the other ear produced little or no excitation; no response in 6/10 cases, high-threshold responses in 3/10 cases, and a weak low-threshold response in 1 case. Monaural responses were obtained only to stimulation of the ear on the preferred side for the remainder of the sample.
A third response class was composed of BD-F cells (n = 14) that exhibited binaural facilitation in the absence of inhibition. This group included nine predominantly binaural cells (Kitzes et
al. 1980) that were unresponsive to monaural stimulation or exhibited high-threshold monaural responses and five cells that exhibited low-threshold, weak monaural responses to stimulation of each
ear (n = 3), only the ipsilateral ear
(n = 1), or only the contralateral ear
(n = 1). Predominantly binaural (PB) cells varied in
azimuth preference and selectivity. Two of them were responsive only at
near midline locations, one of which is shown in Fig.
5 (A and B). Other
PB cells exhibited lowest thresholds at or near the midline but also
responded at more lateral directions (e.g., C-F).
Monaurally responsive BD-F cells also varied in azimuth preference.
Figure 6A shows the binaural
response of one cell that was most responsive and had lowest thresholds
near the midline and was responsive to monaural stimulation of each ear
(B and C). The cell was considerably less
responsive to monaural than to binaural stimulation (D). An
example of a monaurally responsive, midline-preferring cell is shown in
the Fig. 6, right. The cell's binaural response was somewhat variable
as seen by comparison of two ALRAs that were collected before
(E) and after ear plugging (F). In both cases,
the gross response was maximal at the midline and decreased in
magnitude toward each lateral pole (B-stim, H). There was a
weak response to monaural ipsilateral stimulation but not to
contralateral monaural stimulation. The ipsilateral monaural response
occurred at a low threshold and showed a central field azimuth
preference somewhat similar to that of the binaural response.
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The monaural responses of the two units illustrated in Fig. 6 exhibit azimuth sensitivity that may derive from monaural spectral cues. The ipsilateral monaural response of the lateral-preferring unit (C) would have met the 75% criterion for azimuth sensitivity if the high-threshold response, which presumably reflects leakage through the contralateral ear plug, were eliminated from the GR average. The ipsilateral monaural response of the midline preferring unit (I-stim, Fig. 6, G and H) clearly meets the 75% criterion for azimuthal sensitivity. In both cases, there is a similarity between the azimuth preference of the monaural and binaural responses, suggesting that sensitivity to monaural spectral cues may play a role in shaping these responses. Arguably, these should have been classified as monaural directional (MD) rather than BD cells as discussed later.
The directions at which a cell's binaural responses were largest and occurred at lowest thresholds define its azimuth preference. Azimuth preferences of BD cells differed among response classes. The azimuth at which lowest threshold response occurred (e.g., 0°, Fig. 5A) was measured for each cell. Lowest thresholds for BD-EI cells were located furthest from the midline, those for BD-F cells were closest to the midline, and those for BD-FI cells were in between (Fig. 7, left). Azimuth preferences for ipsilateral preferring cells were left-right reversed so that positive angles represent locations on the preferred side. The mean lowest threshold azimuth for the BD-EI class was significantly different from that for the BD-FI and BD-F classes (Fig. 7, legend). A second measure of azimuth preference was the best azimuth (BA, Fig. 2) which is based on response magnitude. The mean BA for BD-EI cells was located furthest from the midline, that for BD-F cells was closest to the midline, and that for BD-FI cells was in between (Fig. 7, right). Means for the three groups were significantly different from each other (Fig. 7, legend). The BA distributions are similar to lowest threshold azimuth distributions.
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MD cells were distinguished from BD cells by their greater sensitivity to the azimuth of monaural noise bursts and composed about one-third of the azimuth-sensitive sample (30/98). These cells responded well to monaural stimulation at some azimuths and poorly or not at all at others. The largest MD response class was composed of MD-E0 cells (n = 18) that were strictly monaural in the sense that their monaural and binaural responses were statistically indistinguishable. An example of such a cell is shown in Fig. 8. The unit was most responsive at 60° and least responsive at 30°. Differences between monaural and binaural responses were not significant, suggesting that azimuth tuning depended exclusively on stimulation of the contralateral ear. Responsiveness to stimulation of the other ear was not tested as was the case for most MD-E0 cells. However, four MD-E0 cells were tested using monaural stimulation of each ear, and each cell was found to be strictly monaural.
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A second MD response class was composed of MD-EI cells (n = 10) that exhibited binaural inhibition. Figure 9A shows an example whose binaural response was centered in the contralateral rear quadrant. It also exhibited a contralateral monaural response restricted to the same location (B). Nevertheless ipsilateral ear plugging caused an increase in responsiveness throughout the ipsilateral hemifield indicating that stimulation of the ipsilateral ear was inhibitory (C). One MD-EI cell was studied using monaural stimulation of each ear, and it was excited only by stimulation of the contralateral ear. All others were studied using monaural stimulation of only one ear.
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The role of binaural inhibition in shaping azimuth tuning varied among MD-EI cells. The shape of the response peak of the MD-EI cell shown in Fig. 9, left, depended only on monaural directional cues. Response peaks of other MD-EI cells depended on both monaural and binaural cues. The right border of the response peak in Fig. 9, right, was nearly identical under monaural and binaural conditions, indicating that it depended only on monaural cues. On the other hand, an increase in ipsilateral responsiveness under monaural conditions caused a decrease in the slope of the left border (C-stim, F), indicating that it was shaped by both monaural and binaural cues.
A third MD response class was composed of two MD-F cells that exhibited binaural facilitation, and one is shown in Fig. 10. This cell exhibited a response peak in the contralateral frontal quadrant (A), and the pattern of its contralateral monaural response (B) was indistinguishable from that of its binaural response, indicating that the cell derived azimuth tuning from monaural cues at the contralateral ear. However, the response peak was over twice as large to binaural than to contralateral monaural stimulation (C), showing that stimulation of the ipsilateral ear facilitated the response. The hemifield azimuth tuning of this cell to binaural tonal stimulation (not shown) suggested that it received inhibitory input from the ipsilateral ear. Nevertheless contralateral monaural responses were not recorded in the ipsilateral frontal field, so it is unclear whether or not this cell would exhibit binaural inhibition to noise stimulation.
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A MD-F cell with different characteristics is shown in Fig. 11. Unlike any BD cell but like a few MD-E0 cells, this cell was most responsive to sound directions on the side of the head contralateral to the ear that provided monaural excitatory drive (A). Its contralateral monaural azimuth tuning was similar to its binaural azimuth tuning (B). This showed that the cell derived azimuth sensitivity from monaural cues at the contralateral ear. The cell exhibited high-threshold responses to monaural stimulation of the ipsilateral ear (C). It was considerably more responsive to binaural than to monaural stimulation of either ear (A and D), revealing binaural facilitation.
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Patterns of azimuth tuning dependent on monaural spectral cues varied greatly among MD cells. This variety can be appreciated in the monaural responses of MD-EI and MD-F cells and in the monaural or binaural (equivalent to monaural) responses of MD-E0 cells. Many cells exhibited focal responses. Response peaks for contralaterally excited cells could be located within the contralateral rear quadrant (Fig. 12A), within the contralateral frontal quadrant (Fig. 10), on the frontal midline (Fig. 12B), or within the ipsilateral quadrant (Figs. 11B and 12C). Some cells exhibited multiple response peaks (Fig. 12D). In contrast to cells with focal responses, a few cells responded over a broader range of azimuths and exhibited decreased responsiveness over a relatively narrow range of azimuths (Figs. 8, 9, B and E, and 12, E and F). A few MD cells were ipsilaterally excited, and these also exhibited variation in breadth and location of response peaks. These examples show that spectral inhibition, which shapes the azimuth tuning of MD cells, varies greatly in spatial distribution.
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MD/BD classification of many cells was based on monaural GR azimuth
function modulation. An advantage of using GR modulation is that it
allows straightforward comparison of the present MGB results with
previous work in cortical field AI where GR modulation was also used to
distinguish MD and BD responses (Samson et al. 1993,
1994
). On the other hand, GR modulation reflects not only azimuth-dependent differences in unit responsiveness due to spectral inhibition but also azimuth-dependent differences in threshold produced
by head shadow. For example, the contralateral monaural responses of
some units show a decrease in GR magnitude in the ipsilateral quadrant
relative to the contralateral quadrant (e.g., C-stim Figs.
1C, 3C, and 4C). This is likely the
result of sound shadowing by the head that causes threshold increases
in the ipsilateral quadrant and consequently a decrease in GR magnitude
at these locations. To assess the effect of azimuth-threshold
dependency on classification of MD and BD responses, we used a second
measure of unit responsiveness that is unaffected by sound shadow (see Imig et al. 2000
). Figure
13 shows the method for calculation, using the monaural contralateral responses of the BD-EI cell shown in
Fig. 1. ALRA data are plotted as a family of level response functions,
one for each azimuth (Fig. 13A). Thresholds differ for the
functions, but in each discharge rate increases from threshold to about
the same plateau, showing that unit responsiveness is similar at each
azimuth. In B the level response functions are aligned with
respect to threshold. A measure of responsiveness was obtained for each
function by averaging the interpolated values at 1-dB intervals over a
10-dB range, usually 20-30 dB re: threshold. In the case of strongly
nonmonotonic responses, ranges of 10-20 or 15-25 dB re: threshold
were used to capture the peak of the level function. These values were
normalized (normalized threshold response, NTR) and are plotted as a
function of azimuth in C, together with another monaural NTR
data set for the same unit. Some azimuth-dependent differences in NTR
are apparent, but function profiles for the two data sets are quite
different, suggesting that random fluctuation in excitability, not
sound shadowing, is a major contributor to modulation. In contrast to
this example, many MD cells were completely unresponsive at some
azimuths. NTR was assigned a value of 0 at those azimuths, and
therefore NTR modulation for these cells was 100%.
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Classification of MD and BD monaural responses using GR and NTR measures and the 75% modulation criterion is compared for five response classes in Fig. 14. Data for BD-F cells are not shown because most were either unresponsive or poorly responsive to monaural stimulation. Units were categorized identically using either measure with the exception that an NTR response could not be obtained for some units. These were mainly BD-FI cells whose monaural responses were too irregular to identify a threshold at each azimuth with certainty (see legend). NTR and GR modulation values were positively correlated (r = 0.84) as expected because unit responsiveness makes a major contribution to both measures. For both GR and NTR measures, a wide range of modulation was exhibited by cells with BFs between 5 and 37 kHz, showing that differential sensitivity to monaural spectral cues extends over a wide range of high-frequency BFs. These results demonstrate that the minor contribution of azimuth-dependent threshold differences to GR modulation did not significantly affect classification of MD and BD responses.
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Comparison of MGB and AI responses
The MGB sample (n = 95) was compared with a
previously described AI sample (n = 98) (Samson
et al. 1993, 1994
) to identify response types that might be
unique to the cortex. Both data samples were obtained using identical
methods and categorized using the same criteria.
The results of the comparison revealed only minor differences between AI and MGB samples except that AI units exhibited stronger nonmonotonic level tuning than MGB units. The original AI sample was re-examined to ensure uniformity of criteria, and a few new units were added. There were no significant differences in the proportions of MD and BD units in the two samples (Fig. 15). Approximately 70% of the sample was classified as BD and 30% as MD in each location.
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For the purpose of comparing azimuth tuning, each cell was classified
as contralateral, ipsilateral, or midline. Cells with BAs (Fig. 2)
located >15° from the midline were classified as either
contralateral or ipsilateral. Cells were classified as midline if the
BA was located within 15° of the midline and function values were
25% on both sides of the midline (e.g., Fig. 5B). Cells
with midline BAs that did not meet the bilateral response reduction
criterion were classified as contra- or ipsilateral depending on
whether the cell was more responsive to contra- or ipsilateral
locations, respectively. For example, responses in Figs. 3,
D and F, and 6, A and D,
showed prominent midline peaks but were classified as contralateral
because function values at contralateral azimuths were >25%.
Contralateral cells predominated in both the MGB and AI samples with
smaller proportions of ipsilateral and midline cells (Fig.
16). Considering MD and BD cells as a
single group, there is no significant difference in the distribution of
contralateral, ipsilateral, and midline responses in the MGB and AI
samples. However, some differences are apparent within certain BD and
MD response classes. There is a higher proportion of ipsilateral BD-FI
and BD-F cells in AI than in the MGB (A). Midline cells in
AI were exclusively of the PB type, but in the MGB they comprised BD-FI
and BD-F types, the latter including both PB and monaurally excitable
cells. Within the MD samples, there was a higher proportion of
ipsilateral cells in MGB than in AI (B).
|
Cells were classified as contralateral or ipsilateral ear dominant if they received excitatory input predominantly from one ear or as neither ear dominant if they were unresponsive or responded to monaural stimulation of each ear. (Fig. 17). For the majority of units both in the MGB and AI, the contralateral ear was dominant with smaller percentages of ipsilateral dominant and neither-ear dominant cells. The AI and MGB ear dominance distributions were not significantly different. Some differences are apparent if one considers the MD and BD samples separately. There was a higher proportion of ipsilateral dominant BD-FI and BD-F cells in AI than in the MGB, (A), and there was a higher proportion of ipsilateral dominant MD cells in MGB than in AI (B). Although not identical, the distribution of ear dominance is quite similar to the distribution of contralateral, ipsilateral, and midline cells.
|
The preferred azimuth range (PAR, Fig. 2) in the frontal hemifield was used as an index of breadth of azimuth tuning. In the case of cells with multiple PARs, PAR width was equal to the sum of the PARs. Mean PAR in the MGB (49.3 ± 23.6°, n = 93) was slightly broader but not significantly different from that in AI (45.0 ± 24.9°, n = 98). Neither were there any significant differences between mean PARs in MGB and AI for any individual response class. However, MD cells were more narrowly tuned than BD cells in the MGB (MD: n = 30, 33.9 ± 19.2°; BD: n = 65, 56.2 ± 22.1°, t-test, P = 0.0001) and in AI (MD: n = 28, 30.6 ± 21.4°; BD: n = 70, 50.8 ± 24.0°, P = 0.0002).
Shapes of level-response functions for binaural noise stimulation
varied from monotonic to nonmonotonic. Shapes of binaural and
dominant-ear monaural level response functions were similar for all but
five MGB units. NM strength was defined as the greatest response
reduction (in percent) that occurred with increasing SPL and could vary
between 0 and 100%. Level functions were obtained from ALRA data at
azimuths within the PAR (Fig. 2), and NM strength was measured at the
azimuth with the lowest threshold response. In most cases, this was
also the azimuth at which the maximum response occurred. If a unit
exhibited similar thresholds (difference <5 dB) at two or more
contiguous azimuths, responses were averaged to obtain a single level
function. Averaging was also used when replicated data sets were
available. For the MGB sample, the mean NM strength of MD-E0 (69.7 ± 37.0%) and MD-EI (89.4 ± 17.1%) groups was greater than that
of BD-EI (48.3 ± 35.9%), BD-FI (27.3 ± 35.0%), and BD-F
(38.2 ± 33.0%) groups. Analysis of variance showed a statistically significant difference between groups (P = 0.0001). A Tukey Kramer post hoc test showed that mean NM strength
for MD-EI cells was significantly greater than that of all BD cell classes, and mean NM strength for MD-E0 cells was significantly greater
than that of BD-F cells. NM strength values for MD and BD cells in AI
and the MGB were compared in a two-factor ANOVA in which one factor was
cell location (i.e., AI or the MGB) and the other factor was response
class (i.e., MD or BD). The test indicated that NM strength of AI cells
(66.4 ± 35.3%, n = 93) was significantly greater
than that of MGB cells (51.3 ± 38.7%, n = 92, P = 0.005). Additionally, NM strength of MD cells
(82.7 ± 27.8%, n = 57) was significantly greater
than that of BD cells (48.3 ± 36.7%, n = 128, P = 0.0001). Post hoc tests (unpaired, 2-tail
t-test; corrected = 0.05/4 = 0.0125) revealed
that NM strength of MD cells was significantly greater than that of BD cells at each site (i.e., AI and the MGB; P = 0.0001).
NM strength of MD cells in AI (91.3 ± 13.8%, n = 28) was greater than that of MD cells in the MGB (74.4 ± 34.9%,
n = 29, P = 0.021), and NM strength of
BD cells in AI (55.6 ± 36.3%, n = 65) was
greater than that of BD cells in the MGB (40.7 ± 35.8%,
n = 63, P = 0.033). Nevertheless these
differences were not statistically significant at the corrected
.
Vn and Po units exhibit similar response properties
Histological reconstruction of electrode tracks allowed
localization of 86/95 units to either Vn (n = 38) or Po
(n = 48). Each response class was represented in Vn and
Po with the exception of the two MD-F cells that were found only in Po.
There was no significant difference in the distribution of the response
classes in Po and Vn (2 test without the MD-F
cells). Neither was there any significant difference between Vn and Po
units with respect to the distribution of contralateral, ipsilateral,
and midline cells or the distribution of ear dominance. Regardless of
whether the entire sample of azimuth-sensitive cells was compared or
whether MD and BD groups were compared separately, neither mean breadth
of azimuth tuning nor NM strength showed significant differences
between Vn and Po.
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DISCUSSION |
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These results show that azimuth tuning of single units in the
cat's MGB is derived from sensitivity to monaural-spectral and binaural-disparity directional cues. Comparison of monaural and binaural responses to free-field noise stimulation allowed
identification of the presence of monaural excitatory inputs, the
presence of inhibitory and facilitatory binaural interactions, and a
unit's differential sensitivity to monaural spectral and binaural
disparity directional cues. Single units in cortical field AI
(Samson et al. 1993, 1994
) and in the cochlear nucleus
(Imig et al., 2000
) have been characterized using
identical methods, thus allowing detailed comparison with the MGB sample.
MGB neurons exhibit differential sensitivity to monaural spectral and binaural disparity directional cues
Many MGB neurons are sensitive to the azimuth of binaural noise
bursts, meaning that they respond well at some azimuths, and poorly or
not at all at others (Barone et al. 1996; Clarey
et al. 1995
). Neuron responses to monaural stimulation revealed
differential sensitivity to monaural spectral and binaural disparity
cues. MD cells are more sensitive to the azimuth of monaural noise
bursts than monaurally excitable BD cells (i.e., BD-EI and BD-FI
cells). Azimuth sensitivity of BD cells strongly depends on binaural
stimulation. Such differential sensitivity occurs in neurons with BFs
that span a broad high-frequency range.
We identified six azimuth-sensitive response classes based on
differences in monaural and binaural azimuth sensitivity, monaural excitatory inputs, and binaural interactions. The azimuth tuning of
neurons in each of these classes reflects varying contributions of
sensitivity to monaural and binaural directional cues. The azimuth
sensitivity of MD-E0 cells depends exclusively on monaural spectral
cues as MD-E0 responses reflect exclusively monaural input. We didn't
use ear plugging to study the responses of MGB neurons that were
insensitive to the azimuth of monaural noise stimulation, but the
presence of such cells in cortical field AI (Samson et al.
1993) strongly suggested their existence in the MGB. Presumably
monaural MGB cells vary greatly in sensitivity to monaural spectral
directional cues.
Both MD-EI and BD-EI cells exhibited binaural inhibition, indicating that the azimuth tuning of both response classes depended in part on binaural cues. MD-EI cells were distinguished from BD-EI cells by their greater monaural spectral sensitivity. And, although we divided EI cells into two classes, this does not mean that BD-EI cells were devoid of monaural spectral sensitivity. It is possible that monaural spectral sensitivity is continuously distributed among EI cells; however, the MD-BD division serves to distinguish those that exhibited greater and lesser spectral sensitivity.
Two MD cells exhibited binaural facilitation. Azimuth tuning and modulation under monaural and binaural conditions appeared similar suggesting that sensitivity to monaural spectral cues was the main contributor to azimuth tuning. Binaural facilitation appeared to amplify the magnitude of the monaurally shaped response in these cells.
BD-FI and BD-F cells represent a more challenging group regarding interpretation of the relative contribution of monaural-spectral and binaural-disparity sensitivity to azimuth tuning. Some BD-FI cells are quite similar to BD-EI cells in that their monaural responses to noise stimulation are relatively insensitive to azimuth (e.g., Fig. 3B). It seems that the azimuth tuning of these responses reflects sensitivity mainly to binaural disparity cues. On the other hand, the responses of a BD-FI midline-preferring cell (e.g., Fig. 3D) additionally appears to reflect sensitivity to spectral cues. This cell responded in front of the head but not behind it. The high-frequency binaural-disparity cue for a midline response is 0 dB interaural level difference (ILD), and this ILD should result from sounds presented on the midline, whether in front or behind the head. This cell's lack of a response behind the head strongly suggests that ILD alone is insufficient to account for the restricted frontal midline response and that spectral cues do play a role. On the other hand, the mechanism by which spectral cues affect the response is unknown.
The role of monaural spectral sensitivity in the azimuth tuning of BD-F cells is difficult to assess. In a few cases (e.g., Fig. 6), there is a similarity between monaural and binaural azimuth tuning, suggesting that sensitivity to spectral cues played a role. On the other hand, many BD-F cells are unresponsive (PB cells) or poorly responsive to monaural stimulation, so their monaural azimuth tuning cannot be used to assess spectral sensitivity.
Comparison of azimuth tuning to noise and tonal stimulation is one
means of assessing spectral contributions to azimuth tuning. Clarey et al. (1995) recorded single neuron responses in
AI and the MGB and noted that MD cells exhibited much broader azimuth tuning and less function modulation to BF-tones than to noise as
expected because tones do not cause spectral inhibition that strongly
shapes MD directional responses. In contrast, BD-EI and BD-FI hemifield
responses showed no significant noise/tone differences in breadth of
azimuth tuning or modulation, consistent with their lesser sensitivity
to monaural spectral cues. Interestingly, tonal stimulation of BD-F
cells with midline preference resulted in significantly broader tuning
and less modulation than did noise stimulation, although the difference
was smaller than for MD cells. These observations suggest that spectral
sensitivity contributes to the azimuth tuning of some BD-F cells.
Binaural interactions and azimuth preference
Binaural interactions have previously been shown to be a major
determinant of azimuth preference. ILD-sensitive neurons in the cat's
superior colliculus (Hirsch et al. 1985; Wise and
Irvine 1985
) exhibit binaural inhibition, binaural
facilitation, and mixed interactions. Cells exhibiting binaural
inhibition exhibit maximal responsiveness at ILDs corresponding to
lateral azimuths, cells exhibiting facilitation have maximal
responsiveness corresponding to near midline azimuths, and cells
exhibiting mixed interactions have maximal responsiveness corresponding
to intermediate locations. A similar relationship has been reported in
high-BF neurons in the cat IC (Delgutte et al. 1999
) and
in 60-kHz BF neurons in the mustache bat IC (Fusezzery et al.
1990; Wenstrup et al. 1988a
,b
). Ivarsson
et al. (1988)
reported similar results in the cat MGB except
that the mixed interaction class was not specifically identified.
Our results are consistent with the previous findings. Of the three
binaural interaction classes, mean azimuth preferences (lowest
thresholds and maximum responses) of BD-EI cells were most lateral,
those of BD-F cells were closest to the midline, and those of BD-FI
cells were in between. Nevertheless there was considerable overlap of
azimuth preferences between groups, and the overlap within the BD-F and
BD-FI groups is particularly noteworthy. Cells with midline azimuth
preference could exhibit PB (Fig. 5A), BD-FI (Fig.
3D), or monaurally excitable BD-F responses (Fig. 11A). BD-FI cells often exhibited lateral azimuth
preferences but some PB cells did as well (Fig. 5D) as
previously reported in AI (Samson et al. 1994).
The distinction between BD-F and BD-FI responses appears to be somewhat
artificial. Detection of binaural inhibition requires a monaural
excitatory response, and since this does not exist in PB cells,
binaural inhibition is not demonstrable even if it exists.
Ivarsson et al. (1988) recorded PB neurons with 0 dB ILD preference in the MGB in nitrous oxide anesthetized cats and found in
some cases that inhibition of spontaneous activity occurred at ILDs
corresponding to lateral azimuths. Consequently mixed facilitation and
inhibition contributed to these responses. Thus binaural inhibition may
contribute to azimuth tuning of some PB cells although it is not
detectable in barbiturate anesthetized cats.
Neural excitability may account for one difference that was noted
between AI and the MGB. All midline preferring cells in AI were of the
PB type, while those in the MGB included PB, BD-FI, and monaurally
excitable BD-F responses. In barbiturate-anesthetized cats, AI neurons
are less responsive than Vn and Po neurons (Barone et al.
1996). If cortical responsiveness was increased, some PB cells
might become monaurally excitable and binaural inhibition might become detectable.
A sizable proportion of MGB MD cells receive EI input, and the
inhibitory input typically completely suppresses responses at azimuths
throughout the quadrant on the side of the inhibitory ear. This is
similar to MD-EI cells that have been described in cortical field AI
(Samson et al. 1993). MD-EI cells are also found in the
IC (Poirier et al. 1996
), suggesting that this type of response is synthesized below the level of the MGB. Many DCN neurons also receive EI input, but the inhibition is much weaker and never completely abolishes the excitatory input in barbiturate anesthetized cats (Imig et al. 2000
). The stronger binaural
inhibition seen at higher levels must represent a different phenomenon.
Some MGB neurons exhibiting binaural facilitation derive azimuth
sensitivity from monaural spectral cues, including MD-F and perhaps
some BD-F and BD-FI cells. MD-F cells have not yet been described in
cortical field AI, although their presence could have been missed,
considering their apparent rarity in the MGB. On the other hand, MD
cells showing binaural facilitation are present in the IC
(Poirier et al. 1996).
Similarities and differences between thalamic and cortical responses
To a great extent, responses of MGB neurons were similar to
responses that were previously recorded in cortical field AI using identical methods (Samson et al. 1993, 1994
). With the
exception of MD-F responses, similar BD and MD response classes were
found in about the same proportions in both AI and MGB. The
distributions of azimuth preference and ear dominance were also similar
in both structures. But some differences between AI and MGB were seen. A higher proportion of BD-FI and BD-F ipsilateral preferring and ipsilateral dominant cells was found in AI than in the MGB. In contrast, there is a higher proportion of ipsilateral preferring MD
cells in the MGB than in AI. While these differences could possibly
reflect synthesis of new response properties in AI (Kitzes and
Doherty 1994
), the sample size is relatively small and may not
be sufficiently representative to draw strong conclusions.
Azimuth tuning of AI neurons to noise stimulation has previously been
reported to be significantly narrower than that in a combined sample of
Vn and Po neurons (Barone et al. 1996). Our results
showed somewhat narrower tuning in field AI than in the MGB, but the
difference was not statistically significant. This difference
presumably reflects sampling error, as the methods in both studies were identical.
Level tuning of AI neurons to noise stimulation varies from strongly
nonmonotonic to monotonic. Most strongly nonmonotonic units are also
azimuth sensitive (Imig et al. 1990), although the
significance of this association is unknown. Barone et al. (1996)
confirmed this relationship in a larger sample of AI
neurons and additionally failed to find a statistically significant
relationship between nonmonotonic level tuning and azimuth sensitivity
in the MGB. This suggests that the linkage of nonmonotonic level tuning and azimuth sensitivity is a cortical phenomenon. Our results show that
AI azimuth-sensitive neurons are significantly more strongly
nonmonotonic than MGB azimuth-sensitive neurons, confirming an earlier
report (Barone et al. 1996
). Additionally,
nonmonotonicity is stronger in AI than in the MGB for both BD and MD
groups, although in neither case does the difference reach statistical
significance. Nevertheless, these results indicate that the cortical
linkage between nonmonotonicity and azimuth sensitivity is associated with an increase in nonmonotonic strength that occurs in both MD and BD
response classes.
Neurons in Vn and Po exhibit similar response properties
Samples of neurons recorded from Po and Vn appear to exhibit quite
similar response properties. High-BF single-unit responses exhibiting
inhibitory, facilitatory, and mixed binaural interactions have
previously been described in Vn (Aitkin and Webster
1972; Ivarsson et al. 1988
) and Po
(Ivarsson et al. 1988
), and our results are consistent
with those findings. There was no obvious difference in the
distribution of response classes in each subdivision. The only two MD-F
cells in the sample were recorded in Po, although the sample size is
too small to attribute any significance to this difference.
Barone et al. (1996)
reported that breadth of azimuth
tuning and azimuth preference was similar for samples of Vn and Po
neurons, and our results confirm these findings. Breadth of azimuth
tuning is similar for Po and VN samples, regardless of whether the
entire sample or separate response classes were compared. We found that
there was no significant difference in nonmonotonic strength of level
tuning between Vn and Po samples. Barone et al. (1996)
reported that nonmonotonic strength was significantly greater in Vn
than Po, but this sample included both azimuth-sensitive and
-insensitive neurons. When the published data of Barone et al.
(1996)
were reexamined considering only the azimuth-sensitive sample, no significant difference was seen.
The cortical targets of neurons in Po and the rostral part of Vn, where
the vast majority of our recording sites were located, are cortical
fields AAF and AI, respectively (Andersen et al. 1980;
Morel and Imig 1987
). Presumably response properties of MD and BD cells in AI reflect inputs from corresponding response types
in rostral Vn. The finding of similar MD and BD response classes in Vn
and Po suggests that MD and BD responses are likely to be found in AAF
as well.
Mechanisms of MD sensitivity
Spectral-directional cues are represented by the head-related
transfer function (HRTF) that describes the free-field to
tympanic-membrane spectral transformation caused by diffraction of
high-frequency sounds by the pinna and head (e.g., in cat,
Musicant et al. 1990; Rice et al.
1992
). There is a unique HRTF pattern associated with each sound direction. MD cells' frequency response areas consist of
excitatory and inhibitory frequency domains, and azimuth sensitivity is
derived from the HRTF by antagonistic comparison of sound energy in
these domains (Imig et al. 1997
). Spectral notches are
salient features of the HRTF from which MD cells presumably derive
azimuth sensitivity. A spectral notch centered at BF will reduce sound energy in excitatory relative to inhibitory frequency domains, and thus
inhibit neural discharge (Imig et al. 1997
). Spectral notch inhibition has been described in the dorsal cochlear nucleus (DCN) (Joris 1998
; Nelken and Young
1994
; Spirou and Young 1991
; Young et al.
1992a
,b
), and neurons there exhibit greater spectral-dependent directional sensitivity than ventral cochlear nucleus (VCN) neurons (Imig et al. 2000
).
The extent to which MGB MD responses reflect neural activity processed
in the DCN is unknown, but there are clear differences in the pattern
and strength of spectral sensitivity in the two structures. The most
common pattern of azimuth tuning of DCN neurons is characterized by a
response null, a decrease in responsiveness over a narrow range of
azimuth (Imig et al. 2000). Commonly, MGB MD neurons had
azimuth functions characterized by narrow response peaks. The null
pattern was relatively uncommon, but it did occur in a few MD cells
(e.g., Figs. 8B, 9B, and 12E). This
shows that spectral inhibition suppresses responses over a wider range
of azimuth in the MGB than in the DCN. Azimuth function modulation of
the monaural response to noise reflects magnitude of spectral inhibition. GR azimuth-function modulation was
75% for
18% of MGB neurons and 2% (1/61) of DCN neurons.
These modulation differences show that spectral inhibition is
considerably stronger in the MGB than in the DCN.
The MGB estimate is based on the finding in this study that MD cells
composed 31% (31/99) of the azimuth-sensitive cells in Vn and Po, and
that 57% (124/217) of a sample of cells in these subdivisions was
azimuth sensitive (Barone et al. 1996). The DCN estimate
is based on unpublished GR modulation values for the DCN sample
described elsewhere (Imig et al. 2000
).
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ACKNOWLEDGMENTS |
---|
We thank C. Bailey for careful preparation of histological materials, data analysis, and preparation of illustrations, T. Gleason for skillful crafting of laboratory hardware, H. Cheng for computer programming, and J. Zhou for statistical analyses.
This work was supported by The National Institutes of Health (DC-00173 and HD-02528), The Phillip Fundation (P. Barone), Fonds de la Recherche en Santé du Québec (P. Poirier), and Fonds pour la Formation de Chercheurs et l'Aide à la Recherche (P. Poirier).
Present addresses: P. Barone, INSERM U371, 18 avenue du Doyen Lépine, 69675 BRON Cedex, France; W. A. Irons, 1117 South 22nd Dr., La Crosse, WI 54601; J. C. Clarey, The Bionic Ear Institute, 384-388 Albert St., East Melbourne, Victoria 3002, Australia; P. Poirier, 403-1100 St-Urbain, Montreal, Quebec H2Z 1W1, Canada.
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FOOTNOTES |
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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).
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 28 January 2000; accepted in final form 17 May 2000.
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REFERENCES |
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