Transformation of Binaural Response Properties in the Ascending Auditory Pathway: Influence of Time-Varying Interaural Phase Disparity
Matthew W. Spitzer1 and
Malcolm N. Semple2
1 Vision, Touch and Hearing Research Centre, Department of Physiology and Pharmacology, The University of Queensland, St. Lucia, Queensland 4072, Australia; and 2 Center for Neural Science, New York University, New York 10003
 |
ABSTRACT |
Spitzer, Matthew W. and Malcolm N. Semple. Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity. J. Neurophysiol. 80: 3062-3076, 1998. Previous studies demonstrated that tuning of inferior colliculus (IC) neurons to interaural phase disparity (IPD) is often profoundly influenced by temporal variation of IPD, which simulates the binaural cue produced by a moving sound source. To determine whether sensitivity to simulated motion arises in IC or at an earlier stage of binaural processing we compared responses in IC with those of two major IPD-sensitive neuronal classes in the superior olivary complex (SOC), neurons whose discharges were phase locked (PL) to tonal stimuli and those that were nonphase locked (NPL). Time-varying IPD stimuli consisted of binaural beats, generated by presenting tones of slightly different frequencies to the two ears, and interaural phase modulation (IPM), generated by presenting a pure tone to one ear and a phase modulated tone to the other. IC neurons and NPL-SOC neurons were more sharply tuned to time-varying than to static IPD, whereas PL-SOC neurons were essentially uninfluenced by the mode of stimulus presentation. Preferred IPD was generally similar in responses to static and time-varying IPD for all unit populations. A few IC neurons were highly influenced by the direction and rate of simulated motion, but the major effect for most IC neurons and all SOC neurons was a linear shift of preferred IPD at high rates
attributable to response latency. Most IC and NPL-SOC neurons were strongly influenced by IPM stimuli simulating motion through restricted ranges of azimuth; simulated motion through partially overlapping azimuthal ranges elicited discharge profiles that were highly discontiguous, indicating that the response associated with a particular IPD is dependent on preceding portions of the stimulus. In contrast, PL-SOC responses tracked instantaneous IPD throughout the trajectory of simulated motion, resulting in highly contiguous discharge profiles for overlapping stimuli. This finding indicates that responses of PL-SOC units to time-varying IPD reflect only instantaneous IPD with no additional influence of dynamic stimulus attributes. Thus the neuronal representation of auditory spatial information undergoes a major transformation as interaural delay is initially processed in the SOC and subsequently reprocessed in IC. The finding that motion sensitivity in IC emerges from motion-insensitive input suggests that information about change of position is crucial to spatial processing at higher levels of the auditory system.
 |
INTRODUCTION |
Despite its pivotal position within the central auditory pathway, the contribution of inferior colliculus (IC) to auditory information processing remains poorly understood. Afferent projections from at least nine brain stem nuclei converge on a single tonotopic representation within the central nucleus of the inferior colliculus (ICc). Anatomical studies indicate that, although there is some segregation of these converging afferents, any given locus within ICc receives input from multiple brain stem nuclei (Brunso-Bechtold et al. 1981
; Roth et al. 1978
). In recent years, physiological evidence has accumulated suggesting that many neuronal response properties established at lower levels of the brain stem are modified within the IC (e.g., Li and Kelly 1992
; Rees and Møller 1987
; Semple and Kitzes 1985
, 1987
). To date, however, there are few documented examples of response properties that may be directly attributed to processing within IC, e.g., interaural level sensitivity reflecting binaural suppression and facilitation (Semple and Kitzes 1987
) temporal response patterns shaped by intrinsic properties (Kuwada et al. 1997
). Understanding more about the transformation of response properties between brain stem nuclei and IC may thus provide valuable insight into the nature of neural processing within this nucleus.
In mammals interaural phase-disparity (IPD) of low frequency sound is used to localize sources and to detect signals in the presence of noise (Hirsh 1950
; Licklider 1948
; Rayleigh 1907
; Stevens and Newman 1936
; Wakeford and Robinson 1974a
,b
). IPD is initially encoded in the discharge of neurons in superior olivary complex (SOC) that detect differences in the timing of inputs from the two ears with a resolution of tens of microseconds (Goldberg and Brown 1969
). Noting the general similarity of IPD-tuned responses of neurons in the IC and auditory cortex to those obtained from the superior olive, many authors concluded that, after initial encoding in SOC, information about IPD is faithfully relayed to higher structures with little or no modification (Reale and Brugge 1990
; Stanford et al. 1992
; Yin and Chan 1990
).
More recently we demonstrated that IPD processing in IC is influenced by temporal variation of IPD, simulating the binaural cue produced by a moving sound source (Spitzer and Semple 1991
, 1993
). Because the form of temporal integration required to generate sensitivity to simulated motion is seemingly incompatible with temporal constraints of the mechanism mediating IPD detection in the SOC, it is likely that motion sensitivity arises as a result of further processing within IC. As such, the influence of simulated motion on IPD tuning of IC neurons may be indicative of an important transformation of the neural representation of spatial cues within IC.
Alternatively, it remains possible that the effect of simulated motion on responses of neurons in IC is simply a reflection of motion sensitivity established at the primary site of binaural interaction in the SOC. To distinguish between these alternative hypotheses, this study compares responses of substantial populations of neurons in IC and SOC to similar time-varying IPD stimuli. Previously, we demonstrated that SOC contains distinct populations of IPD-sensitive neurons that differed with respect to response properties and location within SOC (Spitzer and Semple 1995
). Phase-locking (PL) units were usually bilaterally excitable or monaurally inhibited and were located near the medial superior olive (MSO) or the hilus of the lateral superior olive (LSO). Nonphase-locking (NPL) units were usually monaurally unresponsive and were scattered throughout rostral, dorsal, and medial regions of SOC. Several lines of evidence suggest that PL units are the primary binaural neurons in MSO that provide the principal source of IPD-tuned input to IC. The exact identity and functional role of NPL units is less clear. Because interpretation of differences between response properties of neuronal populations in IC and SOC might be complicated by differences in response properties within SOC, responses of the different populations of SOC neurons will be treated separately in the following analyses.
 |
METHODS |
Procedures for surgery, physiological recording, stimulus generation, and data acquisition were described in previous studies (Spitzer and Semple 1993
, 1995
) and will be described only briefly here.
Surgical and recording procedures
Adult gerbils (Meriones unguiculatus) with clean external and middle ears were surgically anesthetized with intraperitoneal injections of pentobarbital sodium (60 mg/kg) followed by atropine sulfate (0.1 mg/kg). Rectal temperature was maintained at 37.5° with an electric heating pad, and the trachea was cannulated to prevent respiratory distress. The pinnae were removed, and sound delivery speculae were sealed around the external auditory meatus. Anesthesia was maintained throughout the recording session with supplemental intramuscular injections of ketamine (30 mg/kg/h). Two brain exposures were used. To record from SOC, electrodes were advanced through the foramen magnum at an angle of ~30°; to record from IC, a craniotomy of the intraparietal bone was performed, and electrodes were advanced through the exposed cerebellum toward IC.
Activity of single neurons was recorded extracellularly with platinum-plated tungsten electrodes with impedance of 1-5 M
at 1 kHz. Recorded signals were amplified (variable gain) and shaped with band-pass (typically 0.1-10 kHz) and 1/3-octave filters. Electrode penetrations were marked with electrolytic lesions by passing anodal current through the electrode. After the recording session, animals were overdosed with pentobarbital sodium and perfused with paraformaldehyde. Brains were sectioned at 50 µm and Nissl stained. Recording sites were verified by locating electrolytic lesions and electrode track marks in the Nissl-stained material (e.g., Fig. 1 in Spitzer and Semple 1995
).

View larger version (13K):
[in this window]
[in a new window]
| FIG. 1.
Distributions of suprathreshold best frequencies for the 3 samples of interaural phase disparity (IPD)-sensitive neurons. Responses were obtained with binaural beat stimuli with center frequencies spanning each unit's frequency response area at a single SPL, 30 dB above response threshold. Best frequency is defined as the frequency that produced the largest single response at any IPD.
|
|
Stimulus generation and data acquisition
Stimuli were generated by a digital system as described in a previous publication (Spitzer and Semple 1993
). Stimuli were presented dichotically via electrostatic transducers coupled to earpieces that were sealed around the external auditory meatus. Signal amplitude and phase near the tympanic membrane was measured with a condenser microphone coupled to a calibrated probe tube. Digital attenuators were adjusted under computer control so that signal level could be expressed as sound pressure level (SPL) in dB referenced to 20 µPa. In early experiments, phase corrections were applied either by manually compensating during stimulus configuration on-line or by retrospectively adding the phase correction off-line. In later experiments compensation was under direct computer control on-line. All acoustic stimuli were shaped digitally with a cosine ramp 5-20 ms in duration at onset and offset.
Static IPDs were generated by dichotic presentation of tone pips that differed only in starting phase. Time-varying IPD stimuli were generated through the use of binaural beats or interaural phase modulation (IPM). Binaural beats were generated by presenting tones with onset time and starting phase identical, but at slightly different frequencies, to the two ears, resulting in an apparent cyclic modulation of interaural phase at a beat frequency (fb) equal to the difference of the tone frequencies at the two ears. By our convention, beat frequency is positive when the tone frequency is higher at the ear contralateral to the recording site, corresponding to simulated motion toward contralateral space. The average of the frequencies at the two ears is referred to as the "center frequency."
IPM stimuli were generated as previously described (Spitzer and Semple 1993
). Briefly, a tone pip was presented to one ear, and a phase-modulated tone with identical carrier frequency, onset time, and SPL was presented to the other ear. All phase-modulated signals used in this study were generated with a single modulating waveform, consisting of a triangular wave with a frequency of 2 Hz, amplitude of 45°, and starting phase of 0°. The IPM stimuli that were thus generated consisted of repetitive back and forth linear excursions through a 90° (peak to peak) range of IPD. The range through which IPD was modulated (i.e., 0-90°, 45-135°, etc.) was adjusted by varying the starting phase of the modulated signal.
An event timer logged the occurrence of discriminated action potentials as well as stimulus zero crossings with a resolution of 1 µs. Event times were stored in a first-in/first-out buffer, from which they were retrieved by the host computer.
Data analysis
Responses to binaural stimuli were analyzed with circular statistics as previously described (Spitzer and Semple 1993
). The relationship of neuronal response times to circular stimulus variables (tone period, beat period, and static IPD) was quantified with two variables derived from the mean vector calculated for each response (Batschelet 1981
). Mean phase, calculated as the direction of the mean vector, provides a measure of the central tendency of a circular distribution. Vector strength (r), calculated as the length of the mean vector, provides a measure of the degree of concentration about the mean phase. PL was assessed by calculating r relative to the period of the tonal stimulus at one ear. A response was said to exhibit significant phase-locking if r differed significantly from 0 at a probability level of P < 0.01 as assessed by the Rayleigh test (Batschelet 1981
). IPD tuning of responses was measured by calculating r and mean phase relative to either the period of a binaural beat (rbeat) or static IPD (rstatic). A response exhibited IPD tuning if r differed significantly from 0, and mean phase provided an indication of the preferred IPD. For responses to static IPD, mean vectors were calculated by treating responses collected at equally spaced IPDs as binned data. Calculation of mean vectors relative to tone and beat periods treated each spike as an individual unit vector, unless otherwise noted (see figure legends).
 |
RESULTS |
We recorded responses from a total sample of 54 SOC units and 226 IC units, all of which exhibited statistically significant IPD-tuning (P < 0.01). General response properties of the SOC unit sample were documented in a previous study (Spitzer and Semple 1995
). In that report we provided evidence that the SOC contains at least two separate populations of IPD-sensitive neurons that can be differentiated on the basis of monaural and binaural response properties and location. Units that exhibited statistically significant PL responded with short latencies, were usually located near MSO, and tended to respond to monaural stimulation of either ear. NPL units responded with longer latencies, were distributed throughout SOC, and tended to be unresponsive to monaural stimulation of at least one ear. Throughout the present analysis PL and NPL-SOC units will be treated as separate populations. For this comparison responses were collected from a new sample of 212 IPD-sensitive neurons from ICc in 31 gerbils. Data from 14 units from a previously described sample (Spitzer and Semple 1993
) were also used.
Best frequencies at suprathreshold SPLs were determined with binaural beat stimuli for 122 ICc units, 19 PL-SOC units, and 16 NPL-SOC units. Responses were recorded with a set of binaural beats with center frequencies spanning the frequency response area and at an SPL
30 dB above response threshold (typically 70 dB SPL). Best frequency was defined as the frequency that produced the largest response. The distributions of best frequencies thus obtained for the three unit populations are shown in Fig. 1. In general, responses documented here were obtained at or near best frequency. We also obtained IPD-tuned responses from the low frequency tails of the response areas of two ICc units and two NPL-SOCs unit that were not sensitive to IPD at their best frequencies. In one additional NPL-SOC unit that showed only weak IPD sensitivity at best frequency (1.5 kHz), recordings were obtained at a much lower frequency (800 Hz). Finally, it is worth noting that IPD-tuned responses at frequencies >2.5 kHz were obtained from eight ICc units and two NPL-SOC units.
Responses to static and time-varying stimuli
Previously we showed that IPD tuning of IC neurons is sharper in response to time-varying than static stimuli (Spitzer and Semple 1991
). Consequently, it was of interest to compare responses to static and time-varying stimuli in both SOC and IC. Responses to static and time-varying IPD stimuli of two similarly tuned units from IC and PL-SOC are shown in Fig. 2. In both cases the response maxima and minima occur at approximately the same phase angles under both stimulus conditions, resulting in similar mean phase values (
). However, discharges of the IC unit, but not the SOC unit, were more tightly clustered about the peak of the response to time-varying than to static stimuli, as reflected in the vector strength (r) values. This difference is due in large part to the fact that the response to time-varying stimuli completely ceases at unfavorable IPDs, whereas a small response to static stimuli is present at the least favorable IPD.

View larger version (30K):
[in this window]
[in a new window]
| FIG. 2.
Equivalent IPD-tuning curves generated from responses to static and time-varying IPD stimuli demonstrate similar IPD sensitivity for an inferior colliculus (IC) unit (A) and a phase-locked (PL)-superior olivary complex (SOC) unit (B). Responses to +1 Hz binaural beats are shown as period histograms binned relative to the beat period. For each unit responses are normalized to the maximum response within each stimulus condition to facilitate comparison of IPD between static and time-varying conditions. Vector strengths (r) and mean phase ( ) are indicated for response to each stimulus condition. All stimuli were presented in 2 repetitions of 10-s duration.
|
|
The generality of properties illustrated by the previous examples is demonstrated in Figs. 3 and 4. A comparison of the mean phase of responses to static and time-varying IPD stimuli for 39 SOC units and 53 IC units demonstrates the close agreement of estimates of preferred IPD under both stimulus conditions in both unit populations (Fig. 3). All responses were obtained at or near best frequency, as defined above. The beat frequency used to generate time-varying stimuli (±1 Hz) is within the range of beat frequencies where human listeners hear a single moving sound image (Licklider et al. 1950
) and is below the range of beat frequencies that influence mean phase in most neurons (see EFFECTS OF CHANGING RATE AND DIRECTION OF SIMULATED MOTION). In Fig. 4A vector strengths for the same set of responses to static and time-varying stimuli are plotted against each other. The majority of points fall near or above the line of unity, indicating that responses to time-varying stimuli are generally more sharply tuned than responses to static stimuli. Close inspection of the scatter reveals that a disproportionate number of the points falling close to the line are PL-SOC units. Conversely, of the points located most distant from the line, a disproportionate number correspond to IC units. Thus PL-SOC units tend to have equivalent tuning sharpness for static and time-varying stimuli, whereas many IC units and NPL-SOC units are more sharply tuned to time varying stimuli. This point is illustrated more explicitly in Fig. 4B. Here the difference between vector strengths for the different stimulus conditions was calculated for each unit sampled. As expected the distributions of values for IC units and NPL-SOC units are biased to high positive values, indicating sharper tuning to time-varying stimuli, whereas the values for PL-SOC units are more tightly clustered about 0. A one-way analysis of variance confirmed a significant between-groups effect (P < 0.01). Posthoc comparisons of all pairs of means (Newman-Keuls) confirmed that the PL-SOC distribution differed significantly from the NPL-SOC (P < 0.05) and IC (P < 0.01) distributions and that the NPL-SOC and IC distributions were not significantly different.

View larger version (19K):
[in this window]
[in a new window]
| FIG. 3.
Preferred IPD is generally similar in response to static and time-varying IPD stimuli for all unit populations. For each unit, mean phase of the response to a binaural beat is plotted against mean phase of the response to static IPD stimuli. Responses to binaural beats were converted to period histograms with the number of bins equal to the number of IPD values sampled with static stimuli. Mean phase was then calculated from the binned response. This procedure ensured that responses to static and time-varying IPD were measured with equivalent resolution.
|
|

View larger version (19K):
[in this window]
[in a new window]
| FIG. 4.
Comparison of sharpness of tuning to static and time-varying IPD stimuli for different unit populations. A: vector strengths are compared for IPD tuning functions obtained from responses to static (rstatic) and time-varying IPD stimuli (rbeat). PL-SOC units have equivalent vector strengths for the 2 conditions. For IC and nonphase-locked (NPL)-SOC units, IPD tuning is either equivalent or sharper for time-varying stimuli. Vector strengths for time-varying stimuli (+1-Hz binaural beats) were computed after binning response to match the resolution of the static tuning curve. B: difference between vector strengths for time-varying and static IPD is shown separately for each population.
|
|
Effects of changing rate and direction of simulated motion
Previously it was shown that responses of a small proportion of IPD-sensitive IC units are specifically sensitive to the direction and rate of motion simulated with binaural beats (Yin and Kuwada 1983
). However, the fact that IPD tuning can be influenced by certain aspects of simulated motion stimuli raises more general questions concerning effects of dynamic stimulus features on IPD-tuned responses. In addition, much of the previous characterization of IPD sensitivity derived from the use of time-varying stimuli. Consequently it is of interest to assess the effects of changing the rate and direction of simulated motion on responses of IPD-sensitive units and to compare responses of neurons in IC and SOC in this regard.
Effects of changing direction and rate of simulated motion were studied comprehensively in 44 IC units and 30 SOC units. Responses of most units in IC and all units in SOC were relatively uninfluenced by direction and rate of simulated motion, as illustrated by responses of a representative IC unit in Fig. 5. Sensitivity to IPD was assessed with binaural beats with beat frequencies typically spanning a range from ±0.1 to ±50 Hz in approximately third-decade steps and center frequencies equal to the units best frequency (as defined previously). For beat frequencies with absolute magnitude below 5 Hz, corresponding to low simulated motion velocities, increasing beat frequency caused a reduction in total level of discharge but otherwise had remarkably little effect (Fig. 5B). At higher beat frequencies the mean phase of the response shifted in proportion to the beat frequency. It has been well established by others that this is expected on the basis of the unit's firing latency alone. In a linear system, a constant delay gives rise to a linear phase-frequency function whose slope is equal to the delay. Replotted on a linear frequency scale with mean phase expressed in cycles (Fig. 5C) it is apparent that the function relating mean phase to beat frequency is linear, with a slope of 9.2 ms and a zero frequency intercept of 0.125 cycles (i.e., 45°). The slope of 9.2 ms is in approximate agreement with the 10.1-ms firing latency estimated from the response to monaural tone bursts with 5-ms rise times (not shown). In addition, the zero frequency intercept of the phase-frequency function is in close agreement with the mean phase of 41.1° estimated from the response to static IPD stimuli. In summary, other than the expected effects of firing latency, the IPD-tuned response of this unit showed remarkably little change over a range of beat frequencies spanning three orders of magnitude. These response properties were characteristic of most (35/44) IC units and all SOC units studied.

View larger version (31K):
[in this window]
[in a new window]
| FIG. 5.
IPD-tuned response of an IC unit is relatively unaffected by large variations in rate and direction of simulated motion. A: period histograms show responses to binaural beats with beat frequencies ranging from ±0.1 to ± 50 Hz (700-Hz center frequency, 50-dB SPL). B: vector strength, average level of evoked discharge (normalized to the maximum value), and mean phase of the responses are plotted as functions of beat frequency. C: function relating mean phase to beat frequency is replotted here on linear axes with mean phase expressed in cycles so that the slope is in units of seconds.
|
|
A small proportion of IC units (9/44) exhibited special sensitivity to the direction and/or rate of simulated motion. Responses of one such unit are shown in Fig. 6. For this unit, the response magnitude was strongly dependent on the sign and magnitude of the beat frequency. At the lowest and highest beat frequencies the response was minimal. Thus the response shows band-pass tuning with respect to beat frequency. Within the middle range of beat frequencies, where strong responses were elicited, the responses were stronger for negative than positive beat frequencies. In spatial terms, this is equivalent to a directional preference for sound sources moving from the contralateral to the ipsilateral hemifields. However, the beat frequencies at which this directional preference is most pronounced are well outside the range where listeners report a moving acoustic image (Licklider et al. 1950
) and correspond to ecologically unrealistic simulated motion velocities. Finally, unlike the previous example, the relation between mean phase of the response and beat frequency was nonlinear. This last observation could be interpreted as indicating either that the IPD-selectivity of the unit was influenced by simulated motion or, alternatively, that the discharge latency changed as a function of beat frequency.

View larger version (29K):
[in this window]
[in a new window]
| FIG. 6.
Responses of an IC unit whose response is influenced by direction and rate of simulated motion. A: period histograms show responses to binaural beats with beat frequencies ranging from ±0.1 to 50 Hz (1,000-Hz center frequency, 80-dB SPL). B: strength of evoked discharge varies as a function of beat frequency. The effect of beat frequency on mean phase differs in the two directions. C: relation of mean phase to beat frequency is nonlinear.
|
|
Of 44 IC units tested, 9 had band-pass tuning to beat frequency, and 7 of these exhibited a considerable degree of directional preference. However, it should be noted that these quantitative data were recorded from a fraction of the units tested qualitatively for direction and rate sensitivity and that units that appeared sensitive were more likely to be studied quantitatively. Consequently, the proportion of direction/rate sensitive units cited above is almost certainly an overestimate of their frequency in the population.
Responses to shallow depth IPM stimuli
Previously we demonstrated that IPM stimulating portions of the IPD-tuning curve can elicit apparently anomalous responses in many IC units (Spitzer and Semple 1993
). It was proposed that this form of motion sensitivity could reflect temporal interactions between excitatory and inhibitory inputs that contribute to the IPD tuning of IC neurons. Thus sensitivity to simulated motion may be indicative of a fundamental transformation of the representation of IPD within IC. Alternatively, the temporal response properties of IC neurons could simply reflect the motion sensitive response properties of the neurons that provide their major excitatory input. To distinguish between these alternative hypotheses it was necessary to compare responses of IC and SOC neurons in the same preparation to equivalent IPM stimuli.

View larger version (24K):
[in this window]
[in a new window]
| FIG. 7.
Responses of a PL-SOC unit to interaural phase modulation (IPM) stimuli faithfully track instantaneous IPD. Stimulus carrier at both ears was 800 Hz, 70 dB SPL, 10-s duration. The signal at the contralateral ear was continuously phase modulated with a triangular modulating waveform (2-Hz modulation frequency, 45° depth). The initial phase of the carrier signal at the contralateral ear was offset by 135°, 90°, and 45° to produce the 3 stimuli. A: positioning of the 3 modulation stimuli relative to the static IPD-tuning curve. Positive-going portions of the modulation cycles are indicated by black arrows, and negative-going portions are indicated by gray arrows. B: period histograms of responses to the 3 stimuli are arranged such that portions of the positive-going halves of the modulation cycles that correspond to equivalent IPDs are in alignment. C: smoothed profiles of responses during the positive-going portions of each stimulus are plotted on a common IPD axis for ease of comparison.
|
|

View larger version (20K):
[in this window]
[in a new window]
| FIG. 8.
Responses of an IC unit to IPM stimuli are dependent on the temporal and spatial context of stimulation. All conventions and stimuli identical to Fig. 7, except binaural SPL was 80 dB and contralateral carrier phase offsets were 45°, 0° and 45°.
|
|
Responses of representative PL-SOC and IC neurons to equivalent sets of shallow depth IPM stimuli are shown in Figs. 7 and 8, respectively. In both examples the stimuli consist of three modulations through 90° ranges of IPD with centers separated by 45°, resulting in stimulation of discrete, partially overlapping segments of each unit's IPD-tuning function. In the absence of any special sensitivity to simulated motion the profiles of responses to modulations through overlapping ranges of IPD should superimpose, replicating the form of the underlying IPD-tuning function, as is the case for the PL-SOC neuron (Fig. 7). In contrast, responses of the IC neuron (Fig. 8) are remarkably discontiguous, demonstrating pronounced sensitivity to the temporal context of stimulation. The extent of this discontiguity can be appreciated by comparing the responses associated with 0° in the different stimuli. Modulation through the range of IPD associated with the steep portion of the static tuning curve (stimulus centered at
45°) resulted in a maximal response at 0°, whereas modulation through the peak and shallow slope of the tuning curve (stimulus centered at +45°) caused a cessation of response at 0°. Responses of NPL-SOC neurons to shallow depth IPM stimuli were generally similar to those of IC neurons (see Fig. 13).

View larger version (13K):
[in this window]
[in a new window]
| FIG. 13.
Distributions of DSSI values indicate the range of sensitivity to shifting the range of simulated motion within the 3 unit populations. Responses to the standard set of IPM stimuli were obtained from 86 IC units, 20 PL-SOC units, and 19 NPL-SOC units. Responses of each unit generated 2 values, calculated from negative-going and positive-going phases of IPD modulation. Most of the lowest values (e.g., DSSI <0.2) from the total sample were from PL-SOC units, and the distribution of values from this population was clearly biased to lower values than either of the other 2 distributions. The mean DSSI value for PL-SOC units (0.21) was lower than means for IC (0.40) and NPL-SOC units (0.36; P < 0.0001 Mann-Whitney U test). Means for IC and NPL-SOC units were not significantly different (P > 0.05).
|
|
In addition to comparisons of responses between successive stimuli, the cyclic nature of IPM stimuli enables comparison of responses to modulation in opposite directions through the same range of IPD within a single stimulus. In Fig. 9 the response profiles illustrated in the previous two figures are replotted together with responses to the negative-going portions of the modulation cycles (dashed lines) on common IPD axes to give full-cycle response profiles. For each stimulus, response profiles of the PL-SOC unit to the two half-cycles of modulation are nearly identical, as would be expected if responses reflect only instantaneous IPD. In contrast, responses of the IC unit to simulated motion in opposite directions through the same range of IPD form hysteresis loops, indicating additional sensitivity to the temporal context of stimulation.

View larger version (13K):
[in this window]
[in a new window]
| FIG. 9.
Comparison of responses to alternate half cycles of IPM stimuli, corresponding to simulated motion in opposite directions through the same range of azimuth, reveals additional differences between PL-SOC and IC units. Response profiles were obtained from the period histograms in Figs. 7 and 8. Dashed lines indicate responses during the negative-going half cycle of IPM, corresponding to motion toward ipsilateral space.
|
|
Responses to shallow depth IPM stimuli of representative samples of PL-SOC and IC units are shown in Figs. 10 and 11, respectively, to illustrate the range of effects of simulated motion within the two unit populations. Half-cycle (positive-going phase) response profiles were obtained with complete sets of semi-overlapping IPM stimuli with carrier frequencies and SPL chosen on-line to give an optimum combination of discharge rate and IPD-tuning (typically stimuli were near each unit's best frequency and >30 dB above response threshold). Most PL-SOC units were insensitive to simulated motion as assessed in this manner (Fig. 10). PL-SOC units exhibiting profound effects of simulated motion (e.g., Fig. 10I) were rare. IC neurons exhibited a wider range of sensitivity to simulated motion (Fig. 11). In sharp contrast to PL-SOC neurons, responses of most IC neurons were profoundly affected by small shifts in the range of simulated motion. The strongest effects were usually associated with the steepest portion of the static IPD-tuning function (e.g., Fig. 11 D-I). Units shown in Figs. 7-9 are indicated by asterisks.

View larger version (28K):
[in this window]
[in a new window]
| FIG. 10.
PL-SOC units were generally insensitive to simulated motion. Profiles were obtained from responses of 9 units to the positive-going portions of a standard set of semi-overlapping IPM stimuli (2-Hz triangular phase-modulating waveform, 45° depth, contralateral phase offsets: 135°, 90°, 45°, 0°, 45°, 90°, 135°, 180°). Carrier frequency and DSSI value ( , see Fig. 12) are shown for each unit. Stimuli were presented at each unit's best frequency and 30 dB above threshold. For most units (A-H) response profiles to successive stimuli were contiguous, with most discrepancies apparently reflecting random variation. In only 1 case (I) were systematic shifts in responses to successive stimuli observed. *Responses of unit in C were also shown in Fig. 7.
|
|

View larger version (28K):
[in this window]
[in a new window]
| FIG. 11.
IPD tuning of most IC units was influenced by shifting the range of simulated motion. Profiles were obtained to responses of 9 IC units with same stimuli and conventions as in Fig. 10. Effects of simulated motion were more varied in IC; some units were relatively insensitive to simulated motion (A-C), like PL-SOC units, but for most units (D-I), shifting the range of simulated motion resulted in corresponding shifts of the response profiles. *Responses of unit in H were shown in Fig. 8.
|
|
The generality of findings illustrated thus far by individual examples was assessed by quantitative comparison of responses to a standard set of shallow depth IPM stimuli. Responses were recorded from 20 PL-SOC units, 19 NPL-SOC units, and 86 IC units by using a standard stimulus set consisting of semi-overlapping 90° peak-to-peak IPD excursions spanning 360° of IPD, such as those used in Figs. 10 and 11. Stimuli were generated with a 2-Hz, 45° amplitude triangular phase modulating waveform. The initial phase of the contralateral carrier signal was incremented in 45° steps between successive stimuli (8 in total). The extent of discontiguity of responses to overlapping portions of successive stimuli was quantified with an arbitrary numerical measure similar to that used in our previous study (Spitzer and Semple 1993
), referred to as the dynamic spatial sensitivity index (DSSI). The DSSI measures the amount of discontiguity at each IPD (histogram bin) between responses to successive stimuli, normalized to the maximum response at each IPD. Its calculation is illustrated in Fig. 12. Distributions of DSSI values for the three unit populations are shown in Fig. 13. The three distributions show considerable overlap at low values, indicating that all three unit populations contain substantial proportions of units that are relatively insensitive to simulated motion. However, the distribution for PL-SOC units is clearly biased to lower values than those of the other two populations. Furthermore, the distribution for IC units contained a substantial proportion of units with high DSSI values (>0.35), reflecting profound sensitivity to simulated motion, which was seldom evident in responses of PL-SOC units. The mean DSSI value for PL-SOC units was significantly lower than those for NPL-SOC and IC units (both comparisons P = 0.0001, Mann-Whitney U test). Mean values for NPL-SOC and IC units were not significantly different (P > 0.05).

View larger version (19K):
[in this window]
[in a new window]
| FIG. 12.
Illustration of the method used to quantify dynamic spatial sensitivity. Responses of each unit were obtained with a standard stimulus set consisting of 2-Hz triangular IPM (as in Figs. 7-10) with initial phase-offset of the contralateral carrier signal incremented in 45° steps (from 180° to +135°) between successive stimuli. Carrier frequency and binaural SPL were chosen to give an optimal combination of discharge rate and IPD sensitivity (typically stimuli were at best frequency and 30 dB above response threshold). A. Responses were expressed as period histograms (20 bins) binned relative to the modulation period (examples show responses to modulations centered at 45° and 0° from Fig. 8). Each histogram bin corresponds to a 9° range of IPD, and for each direction of phase modulation each 9° arc of IPD from 0° to 351° is represented in responses to 2 stimuli. B: corresponding portions of each pair of responses to semi-overlapping stimuli were aligned to permit comparison of corresponding histogram bins. C: for each pair of corresponding histogram bins the difference of the bin heights, |Y0 Y1|, and the maximum bin height, Ymax, were determined. The dynamic spatial sensitivity index (DSSI) was computed according to the equation
|
|
 |
DISCUSSION |
Previously we demonstrated that simulated motion could profoundly influence IPD tuning of units in IC. This finding was unexpected on the basis of established theories of IPD detection within the superior olive, suggesting either that temporal properties of IC units reflect a transformation of the representation of IPD within the ascending binaural pathway, or that binaural interactions occurring at the initial site of binaural convergence have unexpected temporal properties. Furthermore, the diversity of response properties within IC raised the possibility that more than one mechanism of IPD coding may be present within SOC. To address these issues, responses of SOC neurons to time-varying IPD were characterized and compared with those of IC units. The results indicated that the two populations of SOC neurons differed in their sensitivity to simulated motion. IPD tuning of PL-SOC units was uninfluenced by temporal variation, whereas NPL-SOC units exhibited effects similar to those seen in IC responses. Because PL-SOC units most likely correspond to MSO neurons, which provide the predominant source of IPD-tuned excitatory input to the midbrain, the current findings support the view that sensitivity to simulated motion arises at the level of IC and thus represents a fundamental transformation of the central representation of directional information. The following discussion reviews evidence concerning the identity of the different populations of IPD-sensitive neurons within SOC and considers both the mechanistic and functional implications of these findings.
Neuronal populations within SOC
Previously we demonstrated that SOC contains distinct populations of IPD-sensitive neurons that were primarily differentiated on the basis of PL (Spitzer and Semple 1995
). Several lines of evidence were cited supporting the view that PL units, and not NPL units, correspond to the primary binaural comparators responsible for the initial encoding of IPD and represent the major source of IPD-tuned input to the midbrain. Because this argument is crucial to interpretation of the current findings the supporting evidence is summarized below.
Nearly all PL units were located in or immediately adjacent to the MSO cell column or within the hilus of LSO. These structures represent the primary sites of binaural convergence within SOC (Kil et al. 1995
; Spangler et al. 1985
; Warr 1966
, 1982
) and provide the major source of binaural input to the midbrain. Response properties of PL units were consistent with a role as primary binaural comparators. Specifically, PL units usually responded to monaural stimulation of either ear, and the preferred IPD of responses to binaural stimuli could be predicted from the phase difference of the monaural responses.
NPL units were more widely scattered throughout SOC but tended to be located in dorsal, rostral, and medial periolivary groups. These locations do not receive substantial convergent monaural input (Thompson and Thompson 1991a
,b
; Warr 1969
, 1982
) and do not provide a major source of input to IC (Adams 1979
; Brunso-Bechtold et al. 1981
; Henkel and Spangler 1983
; Roth et al. 1978
; Schofield and Cant 1992
). In rodents these sites are major targets of a descending input from IC (Caicedo and Herbert 1993
; Carey and Webster 1971
; Faye-Lund 1986
; Thompson and Thompson 1993
; Vetter et al. 1993
). NPL units lack the major physiological hallmarks expected of binaural comparators, such as responsiveness to bilateral monaural stimulation and PL. Given their physiological properties and location within SOC it is most likely that NPL units are tertiary binaural neurons that derive IPD sensitivity via input from IC. In support of this hypothesis, response latencies of NPL units were much longer than those of PL units and were comparable with, or even longer than, those of IC units (Spitzer and Semple 1995
).
Finally, it is important to note that differences in ease of isolating single units at different locations within SOC almost certainly resulted in an oversampling of NPL units. PL units were mainly encountered at sites near MSO, where isolation of single units is extremely difficult because of the presence of a large "neurophonic" field potential. Because NPL units were most often encountered at sites distant from MSO, where recording is less challenging, it is likely that the proportion of such units in our sample represents a gross overestimate of their relative abundance within SOC.
Neural mechanisms in IC
IPD-tuning evident in responses of most IC units to time-varying stimuli differed from that obtained with static stimuli in at least two basic respects. First, responses to time-varying stimuli were often more sharply tuned to IPD. Second, responses to shallow-depth IPM stimuli revealed that the level of discharge associated with a particular value of IPD was highly dependent on the spatiotemporal context of the specific stimulus in which it was encountered. Although little is known concerning the neuronal mechanism that generates sensitivity to simulated motion, at least two of its properties are readily apparent; it must involve some form of temporal integration and it must occur after MSO. Two candidate neural mechanisms will be discussed.
First, sensitivity of IC neurons to simulated motion could result from nonlinear interactions between IPD-tuned excitatory and inhibitory inputs. Low frequency regions of IC receive partially convergent input from MSO and the dorsal nucleus of the lateral lemniscus (DNLL) (Aitkin and Schuck 1985
; Brunso-Bechtold et al. 1981
; Roth et al. 1978
), which are thought to convey IPD-tuned excitation and inhibition, respectively. MSO neurons are predominantly tuned to ITDs/IPDs corresponding to positions in contralateral space (Spitzer and Semple 1995
; Yin and Chan 1990
) and send an excitatory projection to ipsilateral IC (Adams 1979
; Brunso-Bechtold et al. 1981
; Elverland 1978
; Henkel and Spangler 1983
; Kumoi et al. 1993
; Nordeen et al. 1983
; Oliver et al. 1995
). DNLL also contains neurons tuned to contralateral ITDs (Brugge et al. 1970
) but sends its major efferent projection to contralateral IC (Shneiderman and Oliver 1989
; Shneiderman et al. 1988
). As a result, neurons in the region of overlap of these projections within IC would be subject to spatially opponent excitatory and inhibitory influences, as illustrated in Fig. 14. This arrangement of synaptic inputs could generate sensitivity to simulated motion if stimulation of inhibitory inputs potentiates successively stimulated excitatory inputs as a result of postinhibitory rebound. To illustrate, responses of a hypothetical IC neuron to two shallow-depth IPM stimuli are shown in Fig. 14. Modulation through a range of IPD adjacent to the peak of the static tuning-curve (Fig. 14, open circles) results in successive stimulation of the inhibitory and excitatory inputs. Recruitment of the excitatory input thus coincides with a period of increased excitability caused by postinhibitory rebound e.g., (Jahnsen and Llinás 1984
; Spain et al. 1991
), resulting in potentiation of the excitatory effect. Modulation restricted to the peak of the static tuning curve stimulates only the excitatory input resulting in a less vigorous response. The sharper IPD tuning and greater modulation of discharge of IC neurons in response to time-varying stimuli could also result from the same mechanism.

View larger version (13K):
[in this window]
[in a new window]
| FIG. 14.
A schematic illustration of how sensitivity of IC neurons to simulated motion could result from interactions between successively stimulated excitatory and inhibitory inputs. Open circles indicate responses to static IPDs. Top panel: response of an IC model neuron to IPD under static (open circles) and time-varying (lines) conditions. Simulated motion adjacent to the peak of the static IPD-tuning curve elicits a relative response enhancement. In this schema, the enhancement effect arises because the simulated motion successively activates inhibitory input from contralateral DNLL (shaded area) and excitatory input from ipsilateral MSO (open area), causing potentiation of the excitatory effect. Simulated motion through the peak of the static tuning curve only activates the excitatory input.
|
|
Second, sensitivity to simulated motion could reflect response adaptation resulting from intrinsic membrane properties of IC neurons. Results of a recent modeling study provide support for this mechanism (Cai et al. 1998a
,b
). Computer simulations were used to test responses of two IC neuron models to the same time-varying IPD stimuli employed in this study. A model incorporating IPD-tuned excitatory and inhibitory inputs, similar to that described above, replicated many previously documented aspects of IPD tuning in IC neurons but was unable to replicate responses to time-varying IPDs (Cai et al. 1998a
). Addition to the model IC neuron of a hyperpolarizing membrane conductance that was activated by spiking resulted in adaptation of neuronal responses to sustained stimuli, sharper IPD tuning in response to time-varying IPD, and discontiguous responses to semi-overlapping IPM stimuli (Cai et al. 1998b
). Although these results would seem to favor adaptation over excitatory-inhibitory interactions as the cause of sensitivity to simulated motion, it should be noted that the nonadapting model used in the simulation assumed linear summation of excitatory and inhibitory inputs. Furthermore, effects of simulated motion on responses of the model appear smaller in magnitude to those observed in vivo. Thus it remains to be determined whether nonlinear interactions between excitatory and inhibitory inputs might also result in similar or more realistic model responses. Finally, it should be noted that the two mechanisms are not mutually exclusive.
Central representation of time-varying IPD
Our results demonstrate a transformation of the neuronal representation of IPD within the ascending auditory pathway. At the site of initial binaural interaction in SOC, neural discharge rate is directly related to instantaneous IPD, irrespective of temporal context. At the IC, response properties are more diverse. A substantial proportion of IC neurons respond like SOC neurons, but discharge rates of many neurons are strongly influenced by temporal variation of IPD. These findings add to a growing body of evidence that neural coding of auditory spatial cues is influenced by motion at levels of the auditory pathway above the SOC. Nevertheless, the functional implications of these data for directional hearing remain unclear.
Several recent physiological studies reported effects of motion on the neural representation of spatial information that are similar to our observations in IC. Kleiser and Schuller (1995)
studied the effect of apparent motion on responses of neurons tuned to azimuth in IC of an echolocating bat. Typically, the range of azimuth to which a neuron responded shifted in a direction opposite to the direction of apparent motion. A similar effect of real motion on azimuth tuning was also demonstrated in cortical neurons of macaque monkeys (Ahissar et al. 1992
). Because azimuth is directly related to IPD, these findings are directly analogous to the shifts of response profiles that we observed in IC as a result of offsetting the range of IPM (Figs. 8 and 11). We also demonstrated that IPD tuning of IC neurons is sharper in response to time-varying than to static stimuli. The same effect was observed in the auditory midbrain of the barn owl (Takahashi and Keller 1992
). That species with a wide range of auditory specializations share similar forms of sensitivity to acoustic motion is highly suggestive of a common underlying mechanism that plays a fundamental role in directional hearing.
In normal listening situations the binaural cues for sound localization are likely to vary over time as a result of motion of sound sources relative to the head. The observed transformation may be indicative of a processing strategy adapted to the demands of sound localization in natural settings where both the head and sound sources are free to move. According to this view, motion sensitivity of IC neurons may represent a specialization for detection of small changes of IPD. As a consequence, position of a moving sound source would be encoded through larger modulations of discharge rate of a greater number of neurons than would be expected based on responses to static stimuli. Although this line of thought suggests that moving sounds might be more salient stimuli than static ones, there is currently no direct evidence to support this conjecture.
Available psychophysical data do not provide a compelling case for special sensitivity to motion in the auditory modality. To the contrary, it has generally been concluded that the binaural system responds sluggishly to changing localization cues and that acoustic motion impairs localization performance (e.g., Blauert 1972
; Grantham 1986
; Grantham and Wightman 1978
; Licklider et al. 1950
). Certain aspects of responses of IC neurons are consistent with this view. A few neurons encountered in this and previous studies (Yin and Kuwada 1983
) showed selectively to direction or rate of change of IPD, which might appear to fulfill the criteria of a classical motion detector (Borst and Egelhaaf 1989
). However, most of these neurons were tuned to ecologically unrealistic velocities, casting doubt on their involvement in motion processing. More often, IC neurons exhibited IPD tuning but were also strongly influenced by simulated motion. As a result, the response associated with a particular IPD could vary widely, depending on the spatiotemporal context of the stimulus in which it was encountered. If the function of an IPD-tuned neuron is to signal the presence of a stimulus at its preferred IPD, these effects would seriously degrade the coding of spatial position by IC neurons for moving sound sources. Furthermore, because many IC neurons respond most vigorously to simulated motion approaching the peak of their IPD-tuning functions, the neuronal representation of instantaneous IPD would be erroneously displaced in the direction of simulated motion. These findings are in apparent agreement with psychophysical data demonstrating that absolute spatial resolution of the auditory system is greater for static than for moving sound sources (Chandler and Grantham 1992
; Grantham 1986
; Harris and Sergeant 1971
; Perrott and Musicant 1977
; Perrott and Tucker 1988
; Saberi and Perrott 1990
) and that listeners' judgments of instantaneous position of moving sound sources are consistently displaced in the direction of motion (Mateeff and Hohnsbein 1988
; Perrott and Musicant 1977
, 1981
).
A major problem with the preceding argument is that the auditory system has access to a representation of spatial position in SOC that is uninfluenced by motion. Preservation of this motion-invariant representation at the subsequent level of processing would only require the output of IC neurons to preserve the temporal pattern of their input from SOC with a level of precision on the order of tens of milliseconds. Considering that the initial encoding of IPD in MSO requires temporal resolution on the order of tens to hundreds of microseconds, the processing demands of preserving the initial representation of IPD in IC appear trivial by comparison. That the representation of spatial position established at the level of SOC is transformed in IC suggests that information about change of position is crucial to spatial processing at higher levels of the system. This argument is strengthened by the observation that auditory motion simulated by modulating the interaural level difference may induce conditioned enhancement and suppression in the IC comparable in many ways to that induced by time-varying IPD (Sanes et al. 1998
). Alternatively, degradation of the spatial code by motion may be a nonadaptive byproduct of neural mechanisms in IC specialized for other tasks. For example, the spatially opponent excitatory and inhibitory arrangement of inputs that we propose to account for responses of IC neurons may exist as a specialization to enhance spatial resolution in static localization tasks or for detection of behaviorally significant signals in the presence of noise (Caird et al. 1991
). Thus, despite compelling evidence that the representation of time-varying IPD is transformed between SOC and IC, further investigation will be required to clarify the functional significance of that transformation for mechanisms of directional hearing.
 |
ACKNOWLEDGEMENTS |
The authors are indebted to S. Kaiser for exceptional engineering support. We also thank L. M. Kitzes for many insightful comments on an earlier version of this manuscript. This research was supported by Grant DC-01767 from the National Institute of Deafness and Other Communicative Disorders.
Animal experiments described in this paper were performed in the Department of Anatomy and Neurobiology at the University of California, Irvine, with full approval from that institution's Animal Care and Use Committee. Analysis and writing were completed at the authors' current institutions.
Address for repint requests: M. N. Semple, Center for Neural Science, New York University, 4 Washington Place, Room 809, New York, NY 10003.
 |
FOOTNOTES |
Received 5 August 1998; accepted in final form 10 September 1998.
 |
REFERENCES |
-
ADAMS, J. C.
Ascending projections to the inferior colliculus.
J. Comp. Neurol.
183: 519-538, 1979.[Medline]
-
AHISSAR, M.,
AHISSAR, E.,
BERGMAN, H.,
VAADIA, E.
Encoding of sound-source location and movement: activity of single neurons and interactions between adjacent neurons in the monkey auditory cortex.
J. Neurophysiol.
67: 203-215, 1992.[Abstract/Free Full Text]
-
AITKIN, L. M.,
SCHUCK, D.
Low frequency neurons in the lateral central nucleus of the cat inferior colliculus receive their input predominantly from the medial superior olive.
Hear. Res.
17: 87-93, 1985.[Medline]
-
BATSCHELET, E.
In: Circular Statistics in Biology. London: Academic, 1981.
-
BLAUERT, J.
On the lag of lateralization caused by interaural time and intensity differences.
Audiology
11: 265-270, 1972.[Medline]
-
BORST, A.,
EGELHAAF, M.
Principles of visual motion detection.
Trends Neurosci.
12: 297-306, 1989.[Medline]
-
BRUGGE, J. F.,
ANDERSON, D. J.,
AITKIN, L. M.
Responses of neurons in the dorsal nucleus of the lateral lemniscus of cat to binaural tonal stimulation.
J. Neurophysiol.
33: 441-458, 1970.[Free Full Text]
-
BRUNSO-BECHTOLD, J. K.,
THOMPSON, G. C.,
MASTERTON, R. B.
HRP study of the organization of auditory afferents ascending to central nucleus of inferior colliculus in cat.
J. Comp. Neurol.
197: 705-722, 1981.[Medline]
-
CAI, H.,
CARNEY, L. H.,
COLBURN, H. S. A
model for binaural properties of inferior colliculus neurons. I. A model with ITD-sensitive excitatory and inhibitory inputs.
J. Acoust. Soc. Am.
103: 475-493, 1998a.[Medline]
-
CAI, H.,
CARNEY, L. H.,
COLBURN, H. S. A
model for binaural properties of inferior colliculus neurons. II. A model with ITD-sensitive excitatory and inhibitory inputs and an adaptation mechanism.
J. Acoust. Soc. Am.
103: 494-506, 1998b.[Medline]
-
CAICEDO, A.,
HERBERT, H.
Topography of descending projections from the inferior colliculus to auditory brainstem nuclei in the rat.
J. Comp. Neurol.
328: 377-392, 1993.[Medline]
-
CAIRD, D. M.,
PALMER, A. R.,
REES, A.
Binaural masking level difference effects in single units of the guinea pig inferior colliculus.
Hear. Res.
57: 91-106, 1991.[Medline]
-
CAREY, C. L.,
WEBSTER, D. B.
Ascending and descending projections of the inferior colliculus in the kangaroo rat (Dipodomys merriami).
Brain Behav. Evol.
4: 401-412, 1971.[Medline]
-
CHANDLER, D. W.,
GRANTHAM, D. W.
Minimum audible movement angle in the horizontal plane as a function of stimulus frequency and bandwidth, source azimuth, and velocity.
J. Acoust. Soc. Am.
91: 1624-1636, 1992.[Medline]
-
ELVERLAND, H. H.
Ascending and intrinsic projections of the superior olivary complex in the cat.
Exp. Brain Res.
32: 117-134, 1978.[Medline]
-
FAYE-LUND, H.
Projection from the inferior colliculus to the superior olivary complex in the albino rat.
Anat. Embryol.
175: 35-52, 1986.[Medline]
-
GOLDBERG, J.,
BROWN, P.
Response of binaural neurons of dog superior olivary complex to dichotic tonal stimuli: some physiological mechanisms of sound localization.
J. Neurophysiol.
32: 613-636, 1969.[Free Full Text]
-
GRANTHAM, D. W.
Detection and discrimination of simulated motion of auditory targets in the horizontal plane.
J. Acoust. Soc. Am.
79: 1939-1949, 1986.[Medline]
-
GRANTHAM, D. W.,
WIGHTMAN, F. L.
Detectability of varying interaural temporal differences.
J. Acoust. Soc. Am.
63: 511-523, 1978.[Medline]
-
HARRIS, J. D.,
SERGEANT, R. L.
Monaural/binaural minimum audible angles for a moving sound source.
J. Speech Hearing Res.
14: 618-629, 1971.[Medline]
-
HENKEL, C. K.,
SPANGLER, K. M.
Organization of the efferent projections of the medial superior olivary nucleus in the cat as revealed by HRP and autoradiographic tracing methods.
J. Comp. Neurol.
221: 416-428, 1983.[Medline]
-
HIRSH, I. J.
The relation between localization and intelligibility.
J. Acoust. Soc. Am.
22: 196-200, 1950.
-
JAHNSEN, H.,
LLINÁS, R.
Electrophysiological properties of guinea-pig thalamic neurones: an in vitro study.
J. Physiol. (Lond.)
349: 205-226, 1984.[Abstract]
-
KIL, J.,
KAGEYAMA, G. H.,
SEMPLE, M. N.,
KITZES, L. M.
Development of ventral cochlear nucleus projections to the superior olivary complex in gerbil.
J. Comp. Neurol.
353: 317-340, 1995.[Medline]
-
KLEISER, A.,
SCHULLER, G.
Responses of collicular neurons to acoustic motion in the horseshoe bat rhinolophus rouxi.
Naturwissenschaften
82: 337-340, 1995.
-
KUMOI, K.,
SAITO, N.,
TANAKA, C.
Immunohistochemical localization of gamma-aminobutyric acid- and aspartate-containing neurons in the guinea pig superior olivary complex.
Hear. Res.
68: 173-179, 1993.[Medline]
-
KUWADA, S.,
BATRA, R.,
YIN, T. C.,
OLIVER, D. L.,
HABERLY, L. B.,
STANFORD, T. R.
Intracellular recordings in response to monaural and binaural stimulation of neurons in the inferior colliculus of the cat.
J Neurosci.
17: 7565-7581, 1997.[Abstract/Free Full Text]
-
LI, L.,
KELLY, J. B.
Inhibitory influence of the dorsal nucleus of the lateral lemniscus on binaural responses in the rat's inferior colliculus.
J Neurosci.
12: 4530-4539, 1992.[Abstract]
-
LICKLIDER, J.C.R.
The influence of interaural phase relations upon the masking of speech by white noise.
J. Acoust. Soc. Am.
20: 150-159, 1948.
-
LICKLIDER, J.C.R.,
WEBSTER, J. C.,
HEDLUN, J. M.
On the frequency limits of binaural beats.
J. Acoust. Soc. Am.
22: 468-473, 1950.
-
MATEEFF, S.,
HOHNSBEIN, J.
Dynamic auditory localization: perceived position of a moving sound source.
Acta. Physiol. Pharmacol. Bulg.
14: 8-32, 1988.
-
NORDEEN, K. W.,
KILLACKEY, H. P.,
KITZES, L. M.
Ascending auditory projections to the inferior colliculus in the adult gerbil. Meriones unguiculatus.
J. Comp. Neurol.
214: 131-143, 1983.[Medline]
-
OLIVER, D. L.,
BECKIUS, G. E.,
SHNEIDERMAN, A.
Axonal projections from the lateral and medial superior olive to the inferior colliculus of the cat: a study using electron microscopic autoradiography.
J. Comp. Neurol.
360: 17-32, 1995.[Medline]
-
PERROTT, D. R.,
MUSICANT, A. D.
Minimum auditory movement angle: binaural localization of moving sound sources.
J. Acoust. Soc. Am.
62: 1463-1466, 1977.[Medline]
-
PERROTT, D. R.,
MUSICANT, A. D.
Dynamic minimum audible angle: binaural spatial acuity with moving sound sources.
J. Aud. Res.
21: 287-295, 1981.[Medline]
-
PERROTT, D. R.,
TUCKER, J.
Minimum audible movement angle as a function of signal frequency and the velocity of the source.
J. Acoust. Soc. Am.
83: 1522-1527, 1988.[Medline]
-
RAYLEIGH, L.
On our perception of sound direction.
Phil. Mag.
13: 214-232, 1907.
-
REALE, R.,
BRUGGE, J.
Auditory cortical neurons are sensitive to static and continuously changing interaural phase cues.
J. Neurophysiol.
64: 1247-1260, 1990.[Abstract/Free Full Text]
-
REES, A.,
MØLLER, A. R.
Stimulus properties influencing the responses of inferior colliculus neurons to amplitude-modulated sounds.
Hear. Res.
27: 129-143, 1987.[Medline]
-
ROTH, G. L.,
AITKIN, L. M.,
ANDERSEN, R. A.,
MERZENICH, M. M.
Some features of the spatial organization of the central nucleus of the inferior colliculus of the cat.
J. Comp. Neurol.
182: 661-680, 1978.[Medline]
-
SABERI, K.,
PERROTT, D. R.
Minimum audible movement angles as a function of sound source trajectory.
J. Acoust. Soc. Am.
88: 2639-2644, 1990.[Medline]
-
SANES, D. H.,
MALONE, B. J.,
SEMPLE, M. N.
Role of synaptic inhibition in processing of dynamic binaural level stimuli.
J. Neurosci.
18: 794-803, 1998.[Abstract/Free Full Text]
-
SCHOFIELD, B. R.,
CANT, N. B.
Organization of the superior olivary complex in the guinea pig. II. Patterns of projection from the periolivary nuclei to the inferior colliculus.
J. Comp. Neurol.
317: 438-455, 1992.[Medline]
-
SEMPLE, M. N.,
KITZES, L. M.
Single-unit responses in the inferior colliculus: Different consequences of contralateral and ipsilateral auditory stimulation.
J. Neurophysiol.
53: 1467-1482, 1985.[Abstract/Free Full Text]
-
SEMPLE, M. N.,
KITZES, L. M.
Binaural processing of sound pressure level in the inferior colliculus.
J. Neurophysiol.
57: 1130-1147, 1987.[Abstract/Free Full Text]
-
SHNEIDERMAN, A.,
OLIVER, D. L.
EM autoradiographic study of the projections from the dorsal nucleus of the lateral lemniscus: a possible source of inhibitory input to the inferior colliculus.
J. Comp. Neurol.
286: 28-47, 1989.[Medline]
-
SHNEIDERMAN, A.,
OLIVER, D. L.,
HENKEL, C. K.
Connections of the dorsal nucleus of the lateral lemniscus: an inhibitory parallel pathway in the ascending auditory system?
J. Comp. Neurol.
257: 188-208, 1988.
-
SPAIN, W. J.,
SCHWINDT, P. C.,
CRILL, W. E.
Post-inhibitory excitation and inhibition in layer V pyramidal neurons from cat sensorimotor cortex.
J. Physiol. (Lond.)
434: 609-626, 1991.[Abstract]
-
SPANGLER, K. M.,
WARR, W. B.,
HENKEL, C. K.
The projections of principal cells of the medial nucleus of the trapezoid body in the cat.
J. Comp. Neurol.
238: 249-262, 1985.[Medline]
-
SPITZER, M. W.,
SEMPLE, M. N.
Interaural phase coding in auditory midbrain: Influence of dynamic stimulus features.
Science
254: 721-724, 1991.[Medline]
-
SPITZER, M. W.,
SEMPLE, M. N.
Responses of inferior colliculus neurons to time-varying interaural phase disparity: effects of shifting the locus of virtual motion.
J. Neurophysiol.
69: 1245-1263, 1993.[Abstract/Free Full Text]
-
SPITZER, M. W.,
SEMPLE, M. N.
Neurons sensitive to interaural phase disparity in gerbil superior olive: diverse monaural and temporal response properties.
J. Neurophysiol.
73: 1668-1690, 1995.[Abstract/Free Full Text]
-
STANFORD, T. R.,
KUWADA, S.,
BATRA, R. A
comparison of the interaural time sensitivity of neurons in the inferior colliculus and thalamus of the unanesthetized rabbit.
J Neurosci.
12: 3200-3216, 1992.[Abstract]
-
STEVENS, S. S.,
NEWMAN, E. B.
The localization of actual sources of sound.
Am. J. Psychol.
48: 297-306, 1936.
-
TAKAHASHI, T. T.,
KELLER, C. H.
Simulated motion enhances neuronal selectivity for a sound localization cue in background noise.
J. Neurosci.
12: 4381-4390, 1992.[Abstract]
-
THOMPSON, A. M.,
THOMPSON, G. C.
Posteroventral cochlear nucleus projections to olivocochlear neurons.
J. Comp. Neurol.
303: 267-285, 1991a.[Medline]
-
THOMPSON, A. M.,
THOMPSON, G. C.
Projections from the posteroventral cochlear nucleus to the superior olivary complex in guinea pig: light and EM observations with the PHA-L method.
J. Comp. Neurol.
311: 495-508, 1991b.[Medline]
-
THOMPSON, A. M.,
THOMPSON, G. C.
Relationship of descending inferior colliculus projections to olivocochlear neurons.
J. Comp. Neurol.
335: 402-412, 1993.[Medline]
-
VETTER, D. E.,
SALDAÑA, E.,
MUGNAINI, E.
Input from the inferior colliculus to medial olivocochlear neurons in the rat: a double label study with PHA-L and cholera toxin.
Hear. Res.
70: 173-186, 1993.[Medline]
-
WAKEFORD, O. S.,
ROBINSON, D. E.
Lateralization of tonal stimuli by the cat.
J. Acoust. Soc. Am.
55: 649-652, 1974a.[Medline]
-
WAKEFORD, O. S.,
ROBINSON, D. E.
Detection of binaurally masked tones by the cat.
J. Acoust. Soc. Am.
56: 952-956, 1974b.[Medline]
-
WARR, W. B.
Fiber degeneration following lesions in the anterior ventral cochlear nucleus of the cat.
Exp. Neurol.
14: 453-474, 1966.[Medline]
-
WARR, W. B.
Fiber degeneration following lesions in the posteroventral cochlear nucleus of the cat.
Exp. Neurol.
23: 140-155, 1969.[Medline]
-
WARR, W. B.
Parallel ascending pathways from the cochlear nucleus: neuroanatomical evidence of functional specialization.
Contrib. Sens. Physiol.
7: 1-37, 1982.
-
YIN, T.C.T.,
CHAN, J. C. K.
Interaural time sensitivity in medial superior olive of cat.
J. Neurophysiol.
64: 465-488, 1990.[Abstract/Free Full Text]
-
YIN, T.C.T.,
KUWADA, S.
Binaural interaction in low frequency neurons in inferior colliculus of the cat. II. Effects of changing rate and direction of interaural phase.
J. Neurophysiol.
50: 1000-1019, 1983.[Abstract/Free Full Text]