|
|
||||||||
Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403
Submitted 19 December 2003; accepted in final form 13 May 2004
| ABSTRACT |
|---|
|
|
|---|
| INTRODUCTION |
|---|
|
|
|---|
Behavioral studies have provided evidence of localization-dependent precedence phenomena in several animal species, including barn owls. Several animal studies have measured lateralization of sources placed symmetrically about the midline (Cranford 1982
; Keller and Takahashi 1996b
; Kelly 1974
; Wyttenbach and Hoy 1993
). At short delays, lateralization judgments correspond to the side of the leading sound. As the delay is increased, judgments become evenly distributed on the 2 sides, suggesting that the lagging sound becomes separately localizable. This conclusion is supported by results of a recent study measuring localization of paired sources using eye movements in cats (Tollin and Yin 2003
). At lead-lag delays from 400 µs to 10 ms, subjects oriented toward the leading sound. At longer delays, subjects localized the lagging sound on some trials. Finally, a recent study from our laboratory demonstrated spatial discrimination suppression in barn owls (Spitzer et al. 2003
). As in humans, leading sounds had a large effect on the ability to detect chances in the location of lagging sounds, and lagging sounds had a smaller effect on spatial acuity for leading sounds.
The neuronal basis of the PE is not well understood. Studies of central auditory structures in a variety of species have demonstrated that leading sounds suppress responses of spatially sensitive neurons to lagging sounds, providing a neuronal correlate of the PE (e.g., Fitzpatrick et al. 1995
; Keller and Takahashi 1996b
; Mickey and Middlebrooks 2001
; Yin 1994
). Although the PE occurs for a wide range of signals, including speech and continuous noise, most previous physiological studies, including that in the barn owl (Keller and Takahashi 1996b
), have focused primarily on neuronal responses to clicks or sounds with durations of a few ms. The use of transient stimuli potentially offers 2 major advantages: 1) the ability to separate neuronal responses to leading and lagging sounds, and 2) the ability to clearly visualize neuronal interactions in the absence of confounding effects of acoustic superposition of leading and lagging sounds. (In practice, these advantages may be compromised by the response times of the acoustic transducers and peripheral auditory filters.) In natural listening situations, however, the delay between the primary signal and its reflection will often be shorter than the signal duration, resulting in substantial temporal overlap of leading and lagging waveforms. The resulting acoustic superposition of leading and lagging sounds at the subject's ear causes degradation of the directional cues to each source. Consequently, it is expected that effects of the leading sound on responses of spatially sensitive neurons to the lagging sound will be confounded by additional masking effects when the sounds overlap. Such effects would not have been apparent in previous studies using shorter stimuli. To be generally applicable to the variety of sounds and reverberant conditions encountered in natural environments, an understanding of the neuronal mechanisms of the PE must therefore extend to situations in which the sound duration is longer than the lag delay. As a step in this direction, the present study documents neuronal responses to pairs of leading and lagging sounds with durations of 50 and 100 ms, and lead-lag delays ranging from 1 to 200 ms.
The physiological mechanisms of lead-evoked suppression remain controversial. Several authors have proposed inhibitory mechanisms to explain both behavioral (Harris et al. 1963
; Lindemann 1986
; Zurek 1987
) and neuronal (Fitzpatrick et al. 1995
; Yin 1994
) effects. In mammals, the spatial dependence of lead effects suggests that a substantial component of these interactions may be mediated by inhibitory processes in binaural brain stem nuclei (Litovsky and Delgutte 2002
). On the other hand, recent modeling studies have demonstrated that, particularly at low frequencies, both behavioral and neurophysiological effects occurring at delays of a few milliseconds could result from interactions of leading and lagging sounds at early stages of auditory processing that do not involve neuronal inhibition (Hartung and Trahiotis 2001
; Tollin 1998
; Trahiotis and Hartung 2002
). If such mechanisms were responsible for the suppression of neuronal responses to lagging sounds, this effect should be evident at the initial site of binaural interaction and at all subsequent processing stages. To elucidate the neuronal mechanisms of lead-evoked suppression it will be necessary to determine the site at which such interactions first become apparent within the ascending auditory pathways.
The lateral subdivisions of the barn owl's IC contain a neuronal map of auditory space. Within these structures, single-peaked auditory spatial receptive fields (SRFs) are generated through the combination of inputs from binaural neurons with highly ambiguous spatial tuning (Konishi 2003
). This process seems to involve a gradual series of processing stages (Mazer 1995
), resulting in a continuous distribution of spatial selectivity within the lateral shell subdivision of the IC core (ICc-ls) and the external nucleus of IC (ICx). In the present study, we examined the distribution of lead-dependent spatial masking effects, which are functionally analogous to the lead-evoked suppression observed in previous studies, among a population of IC neurons at varying levels of spatial processing. The results demonstrated an association between lead-dependent effects and spatial selectivity, suggesting that a neuronal correlate of the PE is generated in parallel with refinement of spatial selectivity within the barn owl's IC.
| METHODS |
|---|
|
|
|---|
All procedures conformed to National Institutes of Health guidelines for care and use of laboratory animals and were approved by the Institutional Animal Care and Use Committee of the University of Oregon. The subjects were 3 adult barn owls (Tyto alba) from a captive breeding colony at the University of Oregon. Experiments were conducted using a chronic preparation for recording in anesthetized owls that was described previously (Euston and Takahashi 2002
). Before use in experiments, each owl had a head plate and 2 recording wells attached to its skull under isofluorane anesthesia. After recovery from surgery, the 3 subjects were returned to a flight cage in an owl colony where they were housed together for the duration of their experimental use. For neurophysiological recording, anesthesia was induced by intramuscular injection of ketamine (22 mg/kg) and valium (5.6 mg/kg), and maintained with N2O/O2 (25 to 40%) supplemented by isofluorane (0.125 to 1%), as needed. Recording sessions had a maximum duration of 12 h. Each subject was used in several recording sessions (Owl 719: 21 sessions; Owl 883: 6 sessions; Owl 916: 8 sessions), with a minimum recovery period of 10 days between sessions.
Neurophysiological recordings were conducted in a sound-attenuating chamber (IAC). The owl's head was stabilized by a holder attached to the chronically implanted headplate and its body supported by a heating pad. Before each recording session, the lid of one recording well was removed and the interior of the well was cleaned with a 0.25% mixture of chlorhexidine in sterile saline. In the first session, the portion of the skull underlying each recording well was excised to permit introduction of recording electrodes. Single-unit recordings were obtained using glass-coated tungsten microelectrodes with impedances at 1 kHz from 1 to 12 M
and exposed tip lengths of 5 to 20 µm. Electrodes were introduced through the forebrain and advanced ventrally toward the stereotaxic coordinates of the auditory midbrain using a stepping motor microdrive (µD-500, Power Technologies). The signal recorded by the electrode was fed to an oscilloscope and audio monitor to permit detection of stimulus-evoked activity. An interactive graphical user interface (BCLab running in Matlab v. 5.3, The Mathworks) allowed the experimenters to select virtual stimulus locations while searching for responsive units. Single-unit action potentials were isolated either by level triggering or through the use of a template matching spike sorter (Alpha-Omega MSD). Typical recording sessions involved 1 to 3 electrode penetrations. At the end of the recording session the well was rinsed with sterile saline and the lid was replaced. After recording sessions the owl was kept in an isolated recovery chamber until it recovered from anesthesia, at which point it was returned to its flight cage.
Stimulus presentation
Virtual auditory space (VAS) stimuli were generated as described previously (Keller et al. 1998
) using each subject's own head related transfer functions (HRTFs). HRTFs were band-pass filtered between 2 and 12 kHz, converted from frequency to time domain representations by inverse Fourier transformation (30-kHz sampling rate), and stored digitally as 255-point (8.5-ms) finite impulse response filters. Two sets of binaural HRTF measurements were obtained for each subject. The first set sampled 617 locations spanning the frontal hemifield, at a spacing of 5° in azimuth and elevation in double polar coordinates. The second set sampled the following regions of space in 1° increments: 20 to 20° azimuth at elevations 20, 10, 10, and 20° at 0° elevation; 40 to 40° elevation at 0° azimuth.
During physiological recording, sounds were presented using a dichotic delivery system with foam insert earphones (model ER-1, Etymotic Research, Elk Grove Village, IL). Stimulus waveforms were generated digitally, and typically consisted of broadband noises with flat (±1 dB) spectra from 2 to 12 kHz, durations of 50 or 100 ms, and 2.5-ms cosine ON and OFF ramps. VAS stimuli were generated by real-time convolution of the stimulus waveform with the HRTFs for the appropriate ears and location (PD1 Power DAC, Tucker Davis Technologies, Gainesville, FL). To generate combinations of leading and lagging sounds, a sequence of zeros, with length corresponding to the lag delay, was concatenated to the end (leading sound) or beginning (lagging sound) of a single-noise waveform. The leading and lagging waveforms were then convolved with the HRTFs for the appropriate locations, and the filtered waveforms were added. Digitally processed waveforms were converted to analog voltage at 30-kHz sampling rate (PD1, Tucker Davis), attenuated (PA4, Tucker Davis) and amplified (HB6, Tucker Davis) before earphone presentation. All stimuli were presented at 52 dB SPLA, which was typically 25 to 35 dB above the response threshold of space-specific neurons, measured at their best locations.
An initial test was performed to characterize the auditory spatial tuning of each isolated unit. Sounds were presented from a set of 292 virtual locations, arranged in a checkerboard pattern to sample the entire frontal hemifield at a spacing of 10° in azimuth and elevation. Noise pips of 50 ms were presented with an interstimulus interval of 250 ms. The stimulus set was presented in 2 to 5 repetitions. In this, and all subsequent tests, the order of stimulus presentation was randomized for each repetition.
"Spatial response profiles" (SRPs) were generated by plotting the response (spikes per stimulus recorded in a time window equal to the stimulus duration, delayed by the unit's response latency), as a function of stimulus azimuth and elevation. Stimulus onset was delayed relative to the start of data collection by an amount equal to the stimulus duration to allow measurement of spontaneous discharge before stimulation. In addition, spike data were recorded during a silent interval equal to the total sound duration plus interstimulus interval at the start of each stimulus set repetition. The set of locations that evoked increases in discharge rate, relative to background firing, will be referred to as the "spatial receptive field" (SRF). The area within the SRF from which
75% of the maximal rate was obtained is termed the "best area." For units with SRFs containing a single dominant peak, the location within the best area that elicited the maximal average firing rate is termed the "best location." In off-line analysis (see SPATIAL TUNING INDEX), the best location was determined by calculating the weighted average of locations within the best area, using response magnitude as the weighting factor. (If the best area contained more than one region, the one that contained the most total spikes was used.) For on-line determination of target locations (see INTERACTION INDEX) the best location was estimated as the center of the dominant peak of the SRF.
Data analysis
SPATIAL TUNING INDEX.
Neuronal spatial selectivity was quantified by a spatial tuning index (STI), that measures the spatial dispersion of responses across the frontal hemifield. STI is calculated from the spatial response profile by computing a weighted sum of angles between the sampled locations and the unit's best location, with response magnitude as the weighting factor, normalized to sum of all angles
![]() | (1) |
i is the absolute value of the angle between location i and the unit's best location, Ri is the magnitude of the response to location i, and n is the number of locations tested. STI has a potential range from 1, if the spatial distribution of responses is uniform, to 0, if a unit responds to only a single location. The range of observed values was 0.003 to 0.471.
INTERACTION INDEX.
The effect of a leading or lagging sound on the response to a sound at a unit's best location was quantified using the interaction index (I; Eq. 2). The sound at best location is termed the target (t) and the other sound the masker (m). I is calculated as follows
![]() | (2) |
The time windows used to measure Rt+m and Rt are illustrated in Fig. 1. To quantify the effect of the masker on total spike output, the Rt+m window was set to include all spikes evoked by either the target or the masker. Thus the window began at the onset of the leading sound, delayed by the response latency, and had a duration equal to the lag delay plus either the duration of the response to the target-alone (measured from visual inspection of spike raster displays) or, alternatively, the duration of the stimulus duration plus 10 ms (Fig. 1, vertical lines), whichever was longer. The use of the alternative minimum duration insured inclusion of responses occurring after the offset of leading maskers at short delays in some units, that might otherwise be excluded (e.g., Fig. 1A, Masker Leads). The Rt measurement window began at stimulus onset, delayed the response latency, and had the same duration as that of the Rt+m window.
|
|
To quantify masking effects on responses to trailing segments, I was used to compare the response at masker offset in the target-lagging condition to the onset of the response in the target-alone condition (Fig. 2). Thus Rt+m was measured in a window starting at masker offset (Fig. 2, Masker Leads, shaded area). The duration of the Rt+m window was equal to the lag delay at delays
5 ms. At shorter delays, a duration of 5 ms was used because the responses to leading and lagging segments often continued for a few milliseconds beyond the lag delay, and because shorter windows yielded less reliable results. Rt was measured in a window with duration equal to that of the Rt+m window, starting at target onset. The reasons for choosing the onset segment of the target-alone response as a reference for comparison, in preference to the final segment, are detailed in the RESULTS section. For comparison, the response to leading segments of the target were analyzed in a similar manner. In this case, both Rt+m and Rt were measured in windows starting at target onset, with duration equal to the lag delay (Fig. 2, Target Leads).
TARGET DETECTION.
Neuronal detection of a target at best location in the presence of a masker was quantified by receiver operating characteristic (ROC) analysis, following methods applied in previous neurophysiological studies (e.g., Bradley et al. 1987
; Britten et al. 1992
; Mountcastle et al. 1969
). Responses were recorded during 20 repetitions of several target-plus-masker combinations with lead-lag delay varied from 200 to 200 ms. By convention, lag delay is measured between the onset of leading and lagging sounds, and is positive when the masker leads the target. The response to the target plus masker (Rt+m) was measured using the same procedures as in the initial I calculation, except that responses were not averaged across repetitions. The masker-alone response (Rm) was measured using the initial 200 ms of the +200 ms delay stimulus, in a window starting at stimulus onset, delayed by the unit's response latency, and with duration equal to the lag delay plus the longer of 110 ms or the duration of the response to the target alone. The minimum effective response duration of 110 ms was again used to prevent exclusion of spike bursts after the offset of leading maskers in units with short (<110 ms) target-alone responses. ROC curves were constructed using a set of response criterion values spanning the range of single-trial Rt+m and Rm values. The ROC curve was generated by plotting the proportion of "hits" (Rt+m > criterion), against the proportion of "false alarms" (Rm > criterion), for each criterion value. The criterion values included the maximum and minimum response values, as well as any value that resulted in a change in the proportion of both hits and false alarms. A criterion value greater than the maximum response and a value of one less than the minimum response were also included to define the endpoints of the curve. The area under the resulting curve, termed proportion correct [p(c)] provides an unbiased measure of target detection (Green and Swets 1966
), representing the performance of an ideal observer, using the neuron's responses as the decision variable. Values of 0.5 and 1 correspond to chance and perfect detection performance, respectively. Values <0.5 may occur if the average response to the masker-alone condition is greater than the response to the target-plus-masker condition.
HIGH-RESOLUTION AZIMUTH TUNING. High-resolution single-source azimuth tuning curves were obtained by recording neuronal responses to a set of virtual locations spanning the azimuthal extent (or a portion thereof) of the peak of the SRF in 1° increments at an elevation of 20, 10, 0, 10, or 20°. Because most space-specific units cannot reliably detect changes in elevation about their SRF peaks of <5° (unpublished observations), this sampling was sufficient to characterize the azimuth tuning at the SRF peak of units with best elevations between 25 and 25°. Azimuth tuning curves for leading and lagging targets were obtained in the same manner, but with the addition of a masker at a fixed location outside the SRF, at the same elevation as the loci sampled at high resolution. The average azimuthal separation between the masker and the units' best azimuths was 28.0 ± 6.8°. The lag delay was always 3 ms, and sound durations were 100 ms. The peaks of azimuth tuning curves for single, leading, and lagging targets were determined by fitting the tuning-curve data with either a Gaussian curve or, if the tuning-curve was clearly skewed, with a lognormal curve. To ensure that fitted peaks accurately reflected neuronal azimuth tuning, a curve fit was excluded from further analysis if it explained <75% of the response variance, or if the calculated peak was located at an endpoint of the range of sampled azimuths. Best azimuths for single, leading, and lagging targets were determined from the corresponding curve fits. Tuning-curve shifts were calculated by determining the change in best azimuths between the single source and either leading or lagging target conditions relative to the location of the masker. By convention, a positive shift value indicates that the best azimuth in the target+masker condition is further away from the masker than the best azimuth in the single source condition.
| RESULTS |
|---|
|
|
|---|
= 0.23; P = 0.0004) between spatial selectivity, quantified by STI, and unit response latency, indicating that the most spatially selective units had the longest latencies. There was no clear indication, however, that either distribution contained multiple modes. These findings are in agreement with those of a previous study (Mazer 1995
|
A previous study demonstrated that the responses of space-specific neurons to sounds at their best locations were reduced in the presence of leading sounds displaced by 40° in azimuth (Keller and Takahashi 1996b
). Thus the neuronal representation of the direction of the lagging sound within the space map is suppressed, providing a potential neuronal correlate of the behavioral PE. We now consider the spatial distribution of such effects in both azimuth and elevation. The spatial dependence of lead source effects was studied, quantitatively, in 26 units by recording responses to lagging sounds at the units best locations, combined with leading sounds at locations spanning the frontal hemifield. For simplicity, the lagging sound at best location will be referred to as the target (t), and leading sound as the masker (m). The delay between onset of the masker and the target was either 3 (22 units) or 5 (4 units) ms.
The usual patterns of lead-source effects are illustrated for 3 units with varying degrees of spatial selectivity in Fig. 4. The lead effect was quantified by the interaction index (I, see METHODS, Data analysis). For this analysis, the response to the target plus masker (Rt+m) was measured in a window set to capture all spikes evoked by either the target or masker, and compared with the response to the target-alone (Rt), measured in a window with equivalent duration (Fig. 1). The SRPs are shown in the left column (Fig. 4A) and the spatial distributions of I are shown in the middle column (Fig. 4B). The target locations (crosses) and best areas (dotted lines) are indicated in Fig. 4B to facilitate comparison of the spatial topographies of lead effects with the SRPs. In all 3 units, the lead-source effects ranged from suppression (I < 0) to values close to zero, indicating that the masker had little effect on the net response relative to the target-alone condition. Lead-evoked facilitation (Rt+m > Rt + response to masker-alone) was never observed in any of the units studied. For all 3 units in Fig. 4B, the masking effect was minimal at locations near the best area, or at far peripheral locations. In the most spatially selective unit (unit 883DC, top row), the masker was most suppressive when it was located lateral to or above the SRF. In the other 2 units, the SRF extends vertically, following the contour of locations with the same ITD as that of the best location. In such units, lead effects were usually minimal along the same iso-ITD contour as that of the best location, and maximal at laterally adjacent locations. The masking effect (I) is plotted against the normalized single-source response at each location in Fig. 4C. In all 3 cases, the strongest lead-evoked suppression occurred at locations that produced the weakest responses in the single-source condition. By contrast, leading sounds at locations that produced responses >40% of maximum in the single-source condition had minimal suppressive effects.
|
Because the sounds used in the preceding test were much longer than the lag delay, resulting in considerable temporal overlap of leading and lagging waveforms, the suppression of neuronal responses to the target caused by leading maskers located outside the SRF could reflect either acoustic or neuronal interactions, or a combination of the two. To better understand the cause of response suppression, we next compare the effects of leading and lagging maskers on responses to targets at the best location in a larger sample of IC units exhibiting varying levels of spatial selectivity.
When leading and lagging sound are presented from different locations at approximately equal levels, some reduction of the response to the best location sound is expected to result from degradation of the binaural cues caused by the acoustic superposition of waveforms from the 2 sources (Keller and Takahashi 1996a
; Takahashi and Keller 1994
). Specifically, the spectrum of interaural level difference cues will be altered, and the level of interaural correlation diminished, the latter resulting in a reduction of the effectiveness of ITD cues (Albeck and Konishi 1995
; Saberi et al. 1998
). Such effects are approximately equal, regardless of whether the masker or target leads. Therefore any difference in suppressive effects caused by leading and lagging maskers cannot be attributed to these acoustic interactions alone. Furthermore, any difference in effectiveness of suppression between leading and lagging maskers resulting from interactions within peripheral filters (Hartung and Trahiotis 2001
; Trahiotis and Hartung 2002
) or asymmetric temporal weighting at the initial site of binaural interaction (Tollin 1998
) should be exhibited by all IC neurons.
Effects of leading and lagging maskers on responses to targets at best location were compared in 59 units, including 6 presumptive OT units. For this test the masker was positioned outside the SRF, at a location that was found, on-line, to suppress responses to the target. In 58/59 units, the masker was positioned at the same elevation as the estimated best location. In one unit, the masker was positioned 30° above the best location. The azimuthal separations between targets and maskers ranged from 14 to 55° (median = 26°). Sounds were 100-ms broadband (212 kHz) noise bursts presented with lead-lag onset delays of ±1, 2, 5, 10, 20, 50, 100, and 200 ms, expressed relative to target onset. The target and masker waveforms were identical, before convolution with the head-related impulse responses (HRIRs).
Comparing effects of leading and lagging maskers revealed 2 types of suppressive effects. In many units, the amount of suppression was similar, regardless of whether the masker led or lagged. This type of effect, termed temporally symmetric, is illustrated by responses of unit 883CJ in Fig. 5. The response to a target leading the masker by 200 ms is the same as that evoked by the target alone, and consists of a robust, moderately adapting discharge, sustained throughout the stimulus duration. By contrast, when the masker leads by 200 ms, it elicits a single spike at onset on some trials, followed by suppression of spontaneous firing, suggesting lateral inhibition. As the delay is decreased, causing the sounds to overlap in time, the response to the target is clearly suppressed throughout the duration of the masker. At delays from 1 to 20 ms, the magnitude of suppression is approximately equal, whether the masker leads or lags. This symmetric suppression is consistent with the effects of acoustic superposition on the available binaural cues. It is also possible that the masker exerts an additional inhibitory effect. However, any contribution of lateral inhibition to suppression of the target response appears not to depend on the temporal order of the masker and target. Note that, at delays from 5 to 20 ms, there is a strong, transient burst of spikes at the offset of the masker. At 50 ms, suppression is stronger when the target leads. This effect may reflect an interaction of the degradation of binaural cues with the temporal dynamics of the response to the target. When the target leads, the masker coincides with the weaker, later portion of the response and is thus more effective than in the opposite configuration, when it coincides with the stronger initial portion of the response. At 100 and 200 ms the masker has little to no effect. As in this example, symmetric response suppression was most often observed in units with SRFs containing prominent lateral side-peaks and vertically elongated main peaks.
|
50 ms. This type of asymmetric interaction is analogous to the behavioral PE in that the neuronal representation of the location of a lagging sound is more effectively suppressed than is that of a leading sound.
|
|
The preceding conclusions were confirmed by statistical analysis (Table 1). At each delay value, IC units were classified as either symmetric or asymmetric by comparing responses to the target when the masker led or lagged. A unit was classified as symmetric if its responses with both leading and lagging maskers were significantly lower than the response to the target-alone, but not different from one another. A unit was classified as asymmetric if its response in the masker leading condition was significantly lower than half the magnitude of the response in the masker-lagging condition (all comparisons: t-test,
= 0.01). At delay values from 1 to 20 ms there was a substantial proportion of symmetric units. At each delay value in this range the mean STI value of asymmetric units was significantly lower than that for symmetric units, indicating the former units were more spatially selective.
|
|
The temporal overlap of leading and lagging sounds results in segments of stimuli during which only the leading or lagging waveform is present, flanking a segment in which both are present. The responses to such stimuli were often complex, with distinct components appearing to reflect differences in masking effects within different stimulus segments. Analysis of the segment-specific responses helped to pinpoint the differences between temporally symmetric and asymmetric suppression.
During the overlap segment, the mixing of the leading and lagging waveforms in each ear degrades the binaural cues. The degradation is the same, however, regardless of whether the target leads or lags and would not, by itself, contribute to a temporally asymmetric effect. Thus if suppression resulted entirely from these acoustic interactions, it is expected that masking of responses to the overlap segment would be the same, regardless of which sound led. This prediction was evaluated by comparing masking during the overlap segment in the masker-leading and masker lagging conditions (see METHODS, Data analysis).
The I values calculated from responses to the overlap segments (Fig. 2, between dashed lines) are plotted as a function of spatial selectivity for delays from 1 to 50 ms in the left column of Fig. 9. At all delays, responses of most units were moderately to heavily suppressed (I < 0) during the overlap segment, both when the masker led (circles) and when it lagged (triangles). This result is consistent with the expectation that acoustic interactions will have a major effect on responses of all units, regardless of the temporal order of masker and target. To compare effects of leading and lagging maskers, the difference between I values in the masker-leading and masker-lagging conditions (asymmetry = IM_leads IM_lags) is plotted against spatial selectivity in Fig. 9 (right column). At delays between 1 and 10 ms, most values were close to zero, indicating approximately equal suppression in the 2 conditions. Thus in most units temporally symmetric influences were sufficient to explain the masking effects within the overlap segment at these delays. This result is consistent with the expected acoustic masking effects, as well as with lateral inhibition, provided that the inhibitory mechanism is insensitive to the temporal order of masker and target. The major exceptions, at delays from 1 to 5 ms, were highly spatially selective units that exhibited greater suppression in the masker-leading condition. This form of temporally asymmetric suppression was also evident at 10- to 50-ms delays in responses of several highly selective units, and 2 less-selective units. Such asymmetric suppression is inconsistent with the predictions of acoustic masking, and indicates the contribution of an additional mechanism that is sensitive to the temporal order of masker and target.
|
A second prediction of simultaneous acoustical masking is that the suppressive effects should occur only during the overlap segment. Thus in the masker-leading condition, we would expect to see a strong response to the trailing stimulus segment, in which only the target is present. This prediction is consistent with the responses of the symmetric unit shown in Fig. 5, at delays >2 ms, but not with those of the asymmetric unit shown in Fig. 6. At delays from 5 to 50 ms, the symmetric unit fired a burst of spikes after the offset of leading maskers, which resembled the response to stimulus onset in the target-alone condition (Fig. 5, Fig. 2A, Masker Leads, shaded region). Such responses demonstrate a recovery from the masking effect almost immediately after termination of masker-target overlap. In the asymmetric unit (Fig. 6, Fig. 2B), by contrast, an onset-like response to the trailing segment does not emerge until the target delay is increased to 20 ms. In this case, the masker appears to exert a suppressive influence on the response to the trailing segment that persists well beyond masker offset. Such effects are consistent with a long-lasting inhibitory mechanism, but not with the degradation of binaural cues resulting from acoustic superposition.
Suppression beyond masker offset was evaluated in the entire IC unit sample by comparing the responses to the trailing stimulus segment, in the masker-leading condition, to the onset segments of the responses to the target alone (see METHODS, Data analysis and Fig. 2). The resulting I values are plotted as a function of spatial selectivity in Fig. 10 (left column, circles). To demonstrate how the suppression of responses to trailing segments contributes to overall response asymmetry, the responses to leading segments in the masker-lagging condition were analyzed in similar fashion (Fig. 10, left column, triangles). At delays of 1 and 2 ms, most units had little or no response to the trailing target-alone segment, resulting in negative values. As delay was increased, responses to the trailing segment emerged more quickly in less spatially selective units than in the more selective ones. Thus at a delay of 50 ms, I values for responses to trailing segments are close to 0 in the less-selective units (STI <0.13), but well below 0 for many of the more-selective units. The recovery of responses at short delays in the less spatially selective units indicates that masking effects are primarily limited to the overlap segment. This effect is consistent with the expectations for acoustic masking, as well as lateral inhibition with a short time constant. By contrast, the suppression of responses to the trailing segment at delays up to tens of milliseconds in the highly selective units is suggestive of long-acting lead-evoked inhibition. This effect is unlikely to have resulted from response adaptation because the strongest suppression of trailing segment responses usually occurred after overlap segments that evoked little or no response. A peripheral mechanism is equally unlikely because interactions within peripheral filters are limited to a few milliseconds.
|
In summary, separate analysis of responses to the overlap and trailing stimulus segments suggests that the observed masking effects reflect a combination of several factors. In the least spatially selective neurons, at delays >2 ms, a combination of temporally symmetric suppression of responses to the overlapping stimulus segment and robust responses to trailing target-alone segments resulted in approximately equal masking effects in the masker-leading and masker-lagging conditions. This type of masking is consistent with the expected effects of acoustic superposition on binaural cues, with possible additional contributions of temporally symmetric lateral inhibition. Such acoustic effects also appear to make a major contribution to the suppression of responses to the overlapping stimulus segment in the more selective units. However, this mechanism cannot account for the temporally asymmetric suppression in the more selective units that resulted from a combination of long-lasting suppression of responses to trailing segments of the target and, in some units, greater suppression during the overlap segment in the masker-leading condition. Such effects are consistent with a lead-evoked inhibitory mechanism. Finally, at delays of 1 and 2 ms nearly all units exhibited some level of temporally asymmetric suppression. In most units, this effect was primarily attributable to the masking of responses to trailing target-alone segments. This effect is consistent with a peripheral mechanism or with short-acting lateral inhibition.
Neuronal detection of leading and lagging sounds
The temporal asymmetry of suppressive effects results in a difference in the ability of the most spatially selective IC neurons to detect leading and lagging targets at their best locations. This effect was quantified by ROC analysis measuring the ability of neurons to signal the presence of the target through changes in discharge rate relative to the masker-alone condition (see METHODS, Data analysis for details). The methods used to generate ROC curves from neuronal spike data are based on those used in previous studies (e.g., Bradley et al. 1987
; Britten et al. 1992
; Mountcastle et al. 1969
) and are illustrated in Fig. 11. In this example, there was a small response to the masker, located on the edge of the SRF (Fig. 11B, masker alone), and a much larger response to the target at the best location (Fig. 11B, target alone). When the masker led the target by 1 ms (Fig. 11B, +1 ms), the response was slightly greater than that to the masker alone. When the target led by 1 ms (Fig. 11B, 1 ms), the response was much greater than that to the masker alone, but still less than that to the target alone. To construct ROC curves, spikes were counted on each stimulus repetition in a time window set to capture all spikes evoked by either sound (Fig. 11B, dashed vertical lines, same windowing as in Figs. 1 and 7). A set of response criteria was adopted that spanned the range of recorded spike counts. ROC curves were generated by plotting the proportion of trials on which Rt+m exceeded the criterion ("hits") against the proportion of trials on which Rm exceeded the criterion ("false alarms") for each criterion value. The areas under the resulting curves [proportion correct, p(c)] are equivalent to the performance of an ideal observer using the neuron's spike counts as a decision variable in a 2-alternative forced-choice task (Green and Swets 1966
). ROC curves obtained from the responses in Fig. 11B are shown in Fig. 11C. In this example, when the target led the masker by 1 ms (1 ms, triangles), the response on nearly every trial was greater than the maximum response in the masker-alone condition, resulting in nearly perfect detection performance [0.99 p(c)]. The smaller response when the masker led by the same amount (+1 ms) was reflected in lower target detectability [0.74 p(c)]. Increasing the target delay to +5 ms caused the response to increase (response not shown), improving detection performance to 0.92 p(c).
|
![]() | (3) |
|
|
|
Azimuth tuning of responses to leading and lagging targets
Results of recent modeling studies suggest that suppression of neuronal responses to lagging sounds may result from interactions within peripheral filters that give rise to new effective internal interaural time differences (ITDs) and interaural level differences (ILDs) that differ from those present in the stimuli (Hartung and Trahiotis 2001
; Trahiotis and Hartung 2002
). Consequently, a lead-lag sound pair, with the lagging sound at a unit's best binaural configuration and the leading sound at the worst configuration, may produce internal ITDs and/or ILDs, at the level of the auditory nerve, that are well outside the range of the unit's binaural tuning curve(s). If such mechanisms were responsible for the asymmetric suppression of responses to targets at best location observed in the present study, azimuth tuning of responses to leading and lagging targets should be substantially shifted relative to that for single sounds, and tuning of responses to lagging targets should be more affected than that for leading targets. These predictions were evaluated by examining high-resolution azimuth tuning curves for single, leading, and lagging targets obtained from a sample of 52 units. High-resolution tuning curves were obtained by recording responses to targets at a set of virtual locations spanning the peak of the SRF in 1° increments, either alone, or in the presence of a masker at a fixed location outside the SRF peak, and a lead-lag delay of 3 ms (see METHODS, Data analysis).
Although the peaks of the azimuth tuning-curves for leading and lagging targets were often shifted relative to the peak of the single source tuning-curve, the observed shifts were small. Examples are shown in Fig. 15, A and B. Units 719XQ (Fig. 15A) and 916CC (Fig. 15B) exhibited temporally symmetric and asymmetric masker effects, respectively. In both cases, the azimuth tuning curves for leading and lagging targets are shifted by 3 or 4 degrees, relative to the azimuth tuning curves for single sources, and in a direction opposite to that of the masker (+20° azimuth in both cases). Unit 719QF (Fig. 15C) exhibited pronounced temporally asymmetric suppression. Nevertheless, the weak responses to lagging targets had similar azimuth tuning to responses to single and leading targets, with the best azimuths differing by only 1°. Responses of this unit and unit 916CC suggest that asymmetric suppression does not result from a shift of the effective ITD, at the level of the auditory nerve, to values outside the range that drive neuronal responses to single sources.
|
|
| DISCUSSION |
|---|
|
|
|---|
Spatial dependence of lead source effects
Several previous studies have addressed the dependence of lead-source effects on spatial cues, using transient stimuli. In the IC and auditory cortex of awake rabbits, suppression of responses to lagging sounds was commonly observed in both ITD-sensitive and ITD-insensitive neurons (Fitzpatrick et al. 1995
, 1999
). In most ITD-sensitive neurons, leading sounds presented at either the best or worst ITD suppressed responses to a lagging sound at the best ITD. Approximately equal proportions of neurons in both structures exhibited stronger suppression when the leading sound was at the best ITD ("best/best" configuration) or at the worst ITD ("worst/best" configuration). Other studies have used either free-field presentation (Litovsky and Yin 1998b
) or VAS stimuli (Litovsky and Delgutte 2002
; Reale and Brugge 2000
), generated using a standard set of HRTFs, to examine the spatial dependence of lead-source effects in the same structures in anesthetized cats (barbiturates: Reale and Brugge 2000
; urethane: Litovsky and Delgutte 2002
). As in the rabbit, responses of spatially sensitive neurons to lagging sounds were usually suppressed by leading sounds at either the best or worst location. However, in cat IC and auditory cortex, large majorities of such units exhibited stronger lag-response suppression in the best/best configuration than when the leading and lagging sounds were at different locations. It is not clear to what extent the apparent differences in proportions of different types of spatial interactions observed in cats and rabbits reflect true species differences, or differences in anesthetic state or stimulus presentation methods.
All of the units tested for the spatial dependence of lead effects in the present study exhibited unequivocal suppression of responses when the leading sound was located outside of the SRF. This effect is analogous to worst/best suppression reported in previous studies using transient stimuli. Comparison of effects of leading and lagging maskers, located outside the SRF, on responses to targets at the best location revealed that the worst/best suppression observed in the least spatially selective neurons was temporally symmetric, and thus likely to result from the affects of acoustic superposition of leading and lagging waveforms on binaural cues. Because ITD and ILD in barn owls vary predominantly along the azimuthal and elevational dimensions, respectively, such interactions would be expected to have the greatest effects on ITD cues when masker and target differ in azimuth, and on ILD cues, when masker and target differ in elevation. In the more spatially selective neurons, worst/best suppression was often temporally asymmetric. This type of interaction requires an additional mechanism that is sensitive to the temporal order of masker and target. Regardless of the mechanism, temporally asymmetric suppression, occurring when a direct sound and reflection arrive from different locations, may be useful to reduce ambiguity about the location of the direct (leading) source.
In anesthetized cats, the strongest lead-evoked suppression is typically observed when the masker and target are both at a unit's best location (Litovsky and Delgutte 2002
; Litovsky and Yin 1998a, b
; Yin 1994
). It is not clear how such best/best suppression would be expected to affect responses to the stimuli used in the present study, given that the temporal overlap of leading and lagging noise bursts at the same location generates what is essentially a single sound with the same binaural cues as the target alone. The combination sound is slightly louder (1.5 dB) and longer than the single target and has a rippled spectrum throughout the overlap period. Our data demonstrate that these alterations have little effect on the response, relative to that in the target-alone condition.
Site of origin of temporally asymmetric suppression
The association with spatial selectivity suggests that temporally asymmetric masking results from processing within the lateral subdivisions of IC. The single-peaked SRFs of ICx neurons are generated by the combination of binaural inputs in the lateral subdivisions of IC. In the barn owl, neuronal and behavioral sensitivity to the location of sounds in azimuth and elevation depend on sensitivity to ITD and ILD, respectively (Euston and Takahashi 2002
; Knudsen and Konishi 1979
; Moiseff 1989
; Moiseff and Konishi 1983
, 1981
; Spezio and Takahashi 2003
). Inputs from neurons sensitive to ITD and ILD first converge in ICc-ls (Adolphs 1993
; Takahashi et al. 1989
), where nearly all units are sensitive to both cues (Mazer 1995
). The ITD-sensitive input originates exclusively from neurons in the ICc-core that are sensitive to ITD in narrow-frequency bands (Takahashi et al. 1989
; Wagner et al. 1987
). Because ITD tuning results from detection of ongoing interaural phase relationships (Carr and Konishi 1990
; Moiseff and Konishi 1981
), the ITD-sensitivity functions of ICc-core neurons are characterized by equal-amplitude peaks occurring at integer multiples of the period of the neurons' best frequencies (Wagner et al. 1987
). This form of ITD sensitivity gives rise to SRFs in which maximal firing is distributed along multiple vertical stripes, spaced approximately equally in azimuth (Euston and Takahashi 2002
). The generation of single-peaked SRFs thus requires the selective elimination of extraneous peaks from ITD-tuning functions. This process, termed "side-peak suppression," involves cross-frequency convergence of ITD-sensitive inputs (Takahashi and Konishi 1986
) and depends on GABAergic inhibitory mechanisms within ICc-ls and ICx (Fujita and Konishi 1991
). The transformation of ILD sensitivity required to generate SRFs with single peaks, restricted in elevation, is not as well understood. The major ILD-sensitive input to ICc-ls originates from neurons in nucleus ventralis lemnisci lateralis, pars posterior (VLVp) that have sharp frequency tuning and sigmoid ILD-sensitivity functions (Manley et al. 1988
). Unlike VLVp, many neurons in ICc-ls and ICx have peaked ILD-tuning functions (Moiseff and Konishi 1983
). However, recent findings suggest that the generation of selectivity for elevation within ICc-ls and ICx involves the selective combination of peaked and sigmoid ILD-sensitive inputs from different frequency bands (Euston and Takahashi 2002
; Spezio and Takahashi 2003
).
Available evidence suggests that spatial selectivity emerges gradually within ICc-ls and ICx, and not in discrete steps associated with each structure. A comprehensive mapping study demonstrated that several measures of binaural sensitivity, associated with refinement of spatial selectivity, vary systematically as functions of both lateral position within ICc-ls and ICx, and response latency (Mazer 1995
). Neurons in medial ICc-ls tended to have ITD-tuning functions with prominent side peaks, broad ILD tuning, sharp frequency tuning, and short latencies. As recordings were made more laterally, into the ICx, there was a progressive increase in ITD side-peak suppression, sharpness of ILD tuning, breadth of frequency tuning, and response latency. The spatial tuning characteristics and latency distributions of units from which detailed data sets were obtained in the present study are consistent with the properties of units in lateral ICc-ls and ICx reported by Mazer (1995)
. All of our units had SRFs containing a single dominant peak, although there was variation among units in the relative prominence of spatial side peaks and in the elevational extent of the main peak. Our observation that the least spatially selective units invariably exhibited symmetric masking, and that strong asymmetric suppression was evident only in more spatially selective units suggests that the latter property emerges, in parallel with the refinement of spatial selectivity, through processing within ICc-ls and ICx. This view is also consistent with the finding that, at delays >2 ms, the extent of response asymmetry is significantly correlated with response latency and by the observation that, among the more selective units, the extent of response asymmetry appears to increase systematically as a function of spatial selectivity.
Because recordings were obtained only from lateral subdivisions of IC, however, these data do not rule out the alternative possibility, that asymmetric suppression is generated before ICc-ls and ICx and passed on, selectively, to the more spatially selective neurons. However, this possibility seems less likely because, to bypass neurons with SRFs containing partially suppressed side peaks, there would need to be direct projections from IC-core and/or VLVp to the ICx, for which there is currently no evidence (Adolphs 1993
; Takahashi and Keller 1992
; Takahashi et al. 1989
). In fact, ICx appears to receive input exclusively from ICc-ls (Knudsen 1983
). Nevertheless, to establish conclusively whether asymmetric suppression originates within these structures, it will be necessary to record from ICc-core and VLVp.
Physiological basis of temporally asymmetric masking
Previous studies have demonstrated lead-evoked suppression of responses to lagging sounds in binaural or spatially sensitive neurons within a variety of central auditory structures (Fitzpatrick et al. 1995
, 1999
; Keller and Takahashi 1996b
; Yin 1994
). Several authors have proposed neuronal inhibitory mechanisms to account for these results (e.g., Fitzpatrick et al. 1995
; Yin 1994
), and for psychophysical PE phenomena (Harris et al. 1963
; Lindemann 1986
; Zurek 1987
). Recent modeling studies, however, have demonstrated that many of the neuronal and psychophysical effects observed in previous studies could result from interactions of leading and lagging sounds within peripheral filters (Hartung and Trahiotis 2001
; Trahiotis and Hartung 2002
), or through asymmetric temporal weighting of inputs by neurons at the initial site of binaural interaction (Tollin 1998
). The use of sounds with durations longer than the lag delay in the present study introduced an additional source of masking effects: the degradation of binaural cues resulting from acoustic superposition of leading and lagging sounds. Such acoustic effects are likely to cause temporally symmetric masking in all units. However, additional mechanisms are required to explain the temporally asymmetric masking observed at long delays in the most spatially selective units, and at the shortest delays in nearly all units.
Interactions within peripheral filters are unlikely to have made a major contribution to the suppression of responses to lagging targets at delays >2 ms in the present study. At frequencies above 4 kHz, which provide the basis for sound localization (Knudsen and Konishi 1979
; Konishi 1973
) and neuronal spatial selectivity (Knudsen and Konishi 1978b
; Moiseff and Konishi 1983
) in barn owls, the ringing response is largely attenuated within a few milliseconds after its peak. Mechanisms based on either peripheral interactions or temporal weighting at the initial site of binaural interaction are also inconsistent with the observed relation between asymmetric suppression and spatial selectivity. Such interactions may, however, explain the temporally asymmetric suppression exhibited by all neurons at delays of 1 and 2 ms. Although response adaptation may have contributed to the asymmetric suppression observed in the most spatially selective neurons, this mechanism cannot account for the suppression of the responses to the trailing segments of lagging targets at delays from 5 to 50 ms. Finally, the fact that the small shifts of azimuth tuning were equal for leading and lagging targets (Figs. 15 and 16) provides further evidence that peripheral interactions do not play a major role in asymmetric suppression at delays
3 ms.
The asymmetric masking observed at delays >2 ms is consistent with long-acting inhibition evoked by the leading sound. GABAergic inhibitory neurons and terminals are abundant throughout the brain stem pathways involved in coding ITD and ILD, including the ICc-ls and ICx (Carr et al. 1989
). ITD side-peak suppression in space-specific neurons can be selectively counteracted by local application of GABA antagonists (Fujita and Konishi 1991
), providing direct evidence that spatial selectivity is shaped by lateral inhibition within the ICx. Furthermore, side-peak suppression develops over the first few milliseconds of neuronal responses in ICx (Wagner 1990
), suggesting that lateral inhibitory inputs act with a delay relative to excitatory inputs. Delayed lateral inhibition would be expected to cause greater suppression of responses to lagging targets, if the inhibitory neurons are located within ICx, and are themselves subject to lateral inhibition. In this case, the first arriving sound would excite neurons at the appropriate space map location and inhibit responses to later-arriving sounds at other locations, including inhibitory neurons that would otherwise inhibit responses to the first sound.
Relation to behavioral precedence phenomena
Human psychophysical studies have typically used one of 3 measures to quantify the PE: perceptual fusion, lateralization/localization dominance, and discrimination suppression (reviewed in Blauert 1997
; Litovsky et al. 1999
). A recent study measured all 3 phenomena as a function of lag delay using the same stimuli and subjects (Litovsky and Shinn-Cunningham 2001
). The results demonstrated that, for transient stimuli, a single source is perceived at delays from 1 to 5 ms. Between 5 and 10 ms, subjects perceived the lagging sound as a separate event, but mislocalized it to a lateral position nearest to the leading source. The impairment of spatial discrimination ability for lagging sounds followed the same time course as the effects on perceived lateral position. These findings suggest that different mechanisms underlie perceptual fusion and the localization-dependent precedence phenomena (localization dominance and discrimination suppression).
Neuronal precedence phenomena, such as those documented in the present study, may contribute to both categories of behavioral phenomena. Previous neurophysiological studies have addressed fusion by attempting to relate human thresholds for resolving lagging sounds, referred to as "echo threshold," to neuronal recovery thresholds determined using a 50% recovery criterion. Measured in this way, the echo thresholds of most neurons in the IC of anesthetized cats (Yin 1994
) and auditory cortex of awake rabbits (Fitzpatrick et al. 1999
) exceeded human echo thresholds. Putting aside, for the moment, the issue of species differences, such findings could be interpreted to suggest that echo thresholds are determined by the small proportion of neurons with the shortest thresholds. Results of the signal-detection analysis in the present study suggest an alternative interpretation. In this case, neuronal detection was quantified by measuring the ability to signal the presence of the target through a reliable increase in firing rate relative to the response to the masker alone. In most neurons, partially recovered responses were sufficient to support high levels of detection performance. Thus neuronal detection thresholds calculated using signal detection metrics in this study were shorter than those obtained using a 50% recovery criterion. If the same is true in mammals, the level of correspondence between neuronal and behavioral echo thresholds may be greater than was previously suspected. In the barn owl, there was a substantial difference in the proportion of highly selective units exhibiting suprathreshold detection performance [0.75 p(c) criterion] for leading and lagging targets at the shortest delays. As the delay was increased, the proportion of units that could detect lagging targets increased. At delays of 10 to 20 ms, the proportion of suprathreshold units was equal to that for leading sounds at a delay of 1 ms. This finding suggests that the lagging sound can be resolved as a separate event when a substantial proportion of units are capable of signaling its presence through reliable increases in firing rate. Of course, because the time course of lead-evoked suppression in anesthetized preparations (e.g., Reale and Brugge 2000
; Yin 1994
) appears to be longer than that in awake animals (Fitzpatrick et al. 1995
, 1999
), it may not be possible to relate the delay dependence of suppression observed in the present study directly to that of behavioral PE measures. Establishing a more conclusive link between neuronal responses and echo thresholds will require comparable neuronal and behavioral measures obtained using the same stimuli in the same species. Such a comparison will require development of a behavioral measure of fusion, suitable for animal studies, that is not dependent on localization/lateralization judgments.
The effect of leading sounds on the perceived location of lagging sounds may be related to the reduction in the magnitude of neuronal responses, which extends to longer delays than do the effects on neuronal detection ability. Explanations of localization-based PE phenomena have been proposed within the context of binaural models in which perceived location is based on a "position" variable derived from the pattern of activity across an array of binaural coincidence detectors (Colburn 1973
, 1977
; Stern and Colburn 1978
). Although recent physiological studies (McAlpine and Grothe 2003
; McAlpine et al. 2001
) have questioned the general applicability of this model in mammals, there is abundant evidence for the proposed topographic representations of ITD (Carr and Konishi 1990
; Wagner et al. 1987
) and auditory space (Knudsen and Konishi 1978a
) in the owl's central auditory pathways. If the position variable is computed as the centroid of activity along the ITD/azimuth dimension (Hartung and Trahiotis 2001
; Stern and Colburn 1978
; Trahiotis and Stern 1994
), localization dominance will result from any mechanism producing greater effective activity on the array near the ITD of the leading source. Potential mechanisms include preferential weighting of earlier evoked activity by the decision process (Shinn-Cunningham et al. 1993
), lateral inhibition (Lindemann 1986
), or interactions of responses to leading and lagging sounds at early stages of peripheral (Hartung and Trahiotis 2001
) or central (Tollin 1998
) auditory processing. Whatever the physiological mechanism, localization dominance results from an effective weighted averaging of ITDs from the 2 sources, favoring the leading source. Discrimination suppression reflects the fact that a greater change in the location of a lagging source is required to change the perceived location by a just-detectable amount than is the case for leading or single sources. This model is supported by the finding that relative weighting factors, calculated from performance of human listeners in lateralization experiments with precedence stimuli, predict performance in ITD discrimination tasks using the same stimuli (Shinn-Cunningham et al. 1993
).
The same conceptual framework can be applied to the barn owl by substituting the auditory space map for the binaural array (Saberi et al. 1998
). The present results demonstrate that, among the more spatially selective units in IC, activity evoked by a leading source is either equal to or greater than that evoked by a lagging source. The centroid of space-map activity will thus correspond to a location near the leading source, but displaced in the direction of the lagging source, resulting in localization dominance. Both the reduction in the magnitude and the reliability of lag-evoked responses may contribute to lag-discrimination suppression. In addition, the smaller impairment of azimuth discrimination for leading sounds, observed with 25- and 100-ms stimuli (Spitzer et al. 2003
), may result from the reduction of lead-evoked activity caused by acoustic superposition and the corresponding reduction of response reliability at short delays.
Recent findings demonstrating close agreement between behavioral and average neuronal performance suggest an alternative model of spatial discrimination in barn owls, based on point-by-point comparison of the neurophysiological images on the space map (Bala et al. 2003
). In this case, the relative reductions in reliability of lead- and lag-evoked activity could produce the observed pattern of discrimination impairments by reducing the reliability of differences in the map images of test stimuli that differ in location of either leading or lagging sources. Because resolution of both image comparison and position variable models ultimately depend on the spatial resolution of space-specific neurons, both models might be expected to generate similar discrimination results. Whichever model is used, neither precedence phenomenon would be predicted from the symmetric responses of the less spatially selective IC neurons. Thus the asymmetric suppression of responses to lagging sounds, which appears to develop in parallel with the refinement of spatial selectivity within ICx, may provide the basis for localization-based precedence phenomena in barn owls. To determine whether such neuronal effects are sufficient to account for localization-based precedence phenomena will require further experiments to enable comparison of behavioral measures of the PE with neuronal responses to the same stimuli recorded from awake subjects.
| GRANTS |
|---|
|
|
|---|
| ACKNOWLEDGMENTS |
|---|
|
|
|---|
| FOOTNOTES |
|---|
Address for reprint requests and other correspondence: M. W. Spitzer, Department of Psychology, Monash University, Clayton, Victoria 3800, Australia (E-mail: matt.spitzer{at}med.monash.edu.au).
| REFERENCES |
|---|
|
|
|---|
Albeck Y and Konishi M. Responses of neurons in the auditory pathway of the barn owl to partially correlated binaural signals. J Neurophysiol 74: 16891700, 1995.
Bala AD, Spitzer MW, and Takahashi TT. Prediction of auditory spatial acuity from neural images on the owl's auditory space map. Nature 424: 771774, 2003.[CrossRef][Medline]
Blauert J. Spatial Hearing. Cambridge, MA: MIT Press, 1997.
Bradley A, Skottun BC, Ohzawa I, Sclar G, and Freeman RD. Visual orientation and spatial frequency discrimination: a comparison of single neurons and behavior. J Neurophysiol 57: 755772, 1987.
Britten KH, Shadlen MN, Newsome WT, and Movshon JA. The analysis of visual motion: a comparison of neuronal and psychophysical performance. J Neurosci 12: 47454765, 1992.[Abstract]
Carr CE, Fujita I, and Konishi M. Distribution of GABAergic neurons and terminals in the auditory system of the barn owl. J Comp Neurol 286: 190207, 1989.[CrossRef][Web of Science][Medline]
Carr CE and Konishi M. A circuit for detection of interaural time differences in the brain stem of the barn owl. J Neurosci 10: 32273246, 1990.[Abstract]
Colburn HS. Theory of binaural interaction based on auditory-nerve data. I. General strategy and preliminary results on interaural discrimination. J Acoust Soc Am 54: 14581470, 1973.[CrossRef][Web of Science][Medline]
Colburn HS. Theory of binaural interaction based on auditory-nerve data. II. Detection of tones in noise. J Acoust Soc Am 61: 525533, 1977.[CrossRef][Web of Science][Medline]
Cranford JL. Localization of paired sound sources in cats: effects of variable arrival times. J Acoust Soc Am 72: 13091311, 1982.[CrossRef][Web of Science][Medline]
Euston DR and Takahashi TT. From spectrum to space: the contribution of level difference cues to spatial receptive fields in the barn owl inferior colliculus. J Neurosci 22: 284293, 2002.
Fitzpatrick DC, Kuwada S, Batra R, and Trahiotis C. Neural responses to simple simulated echoes in the auditory brain stem of the unanesthetized rabbit. J Neurophysiol 74: 24692486, 1995.
Fitzpatrick DC, Kuwada S, Kim DO, Parham K, and Batra R. Responses of neurons to click-pairs as simulated echoes: auditory nerve to auditory cortex. J Acoust Soc Am 106: 34603472, 1999.[CrossRef][Web of Science][Medline]
Fujita I and Konishi M. The role of GABAergic inhibition in processing of interaural time difference in the owl's auditory system. J Neurosci 11: 722739, 1991.[Abstract]
Green DM and Swets JA. Signal Detection Theory and Psychophysics. New York: Wiley, 1966.
Haas H. Über den einfluss eines einfachechos auf die hörsamkeit von sprache [On the influence of a single echo on the intelligibility of speech]. Acustica 1: 4958, 1951.
Harris GG, Flanagan JL, and Watson BJ. Binaural interaction of a click with a click pair. J Acoust Soc Am 35: 672678, 1963.
Hartmann WM. Localization of sound in rooms. J Acoust Soc Am 74: 13801391, 1983.[CrossRef][Web of Science][Medline]
Hartung K and Trahiotis C. Peripheral auditory processing and investigations of the "precedence effect" which utilize successive transient stimuli. J Acoust Soc Am 110: 15051513, 2001.[CrossRef][Web of Science][Medline]
Keller CH, Hartung K, and Takahashi TT. Head-related transfer functions of the barn owl: measurement and neural responses. Hear Res 118: 1334, 1998.[CrossRef][Web of Science][Medline]
Keller CH and Takahashi TT. Binaural cross-correlation predicts the responses of neurons in the owl's auditory space map under conditions simulating summing localization. J Neurosci 16: 43004309, 1996a.
Keller CH and Takahashi TT. Responses to simulated echoes by neurons in the barn owl's auditory space map. J Comp Physiol A Sens Neural Behav Physiol 178: 499512, 1996b.[Medline]
Kelly JB. Localization of paired sound sources in the rat: small time differences. J Acoust Soc Am 55: 12771284, 1974.[CrossRef][Web of Science][Medline]
Knudsen EI. Subdivisions of the inferior colliculus in the barn owl (Tyto alba). J Comp Neurol 218: 174186, 1983.[CrossRef][Web of Science][Medline]
Knudsen EI and Konishi M. A neural map of auditory space in the owl. Science 200: 795797, 1978a.
Knudsen EI and Konishi M. Space and frequency are represented separately in auditory midbrain of the owl. J Neurophysiol 41: 870884, 1978b.
Knudsen EI and Konishi M. Mechanisms of sound localization by the barn owl (Tyto alba). J Comp Physiol A Sens Neural Behav Physiol 133: 1321, 1979.[CrossRef]
Konishi M. Locatable and nonlocatable acoustic signals for barn owls. Am Naturalist 107: 775785, 1973.[CrossRef][Web of Science]
Konishi M. Coding of auditory space. Annu Rev Neurosci 26: 3155, 2003.[CrossRef][Web of Science][Medline]
Lindemann W. Extension of a binaural cross-correlation model by contralateral inhibition. II. The law of the first wave front. J Acoust Soc Am 80: 16231630, 1986.[CrossRef][Web of Science][Medline]
Litovsky RY, Colburn HS, Yost WA, and Guzman SJ. The precedence effect. J Acoust Soc Am 106: 16331654, 1999.[CrossRef][Web of Science][Medline]
Litovsky RY and Delgutte B. Neural correlates of the precedence effect in the inferior colliculus: effect of localization cues. J Neurophysiol 87: 976994, 2002.
Litovsky RY and Macmillan NA. Sound localization precision under conditions of the precedence effect: effects of azimuth and standard stimuli. J Acoust Soc Am 96: 752758, 1994.[CrossRef][Web of Science][Medline]
Litovsky RY and Shinn-Cunningham BG. Investigation of the relationship among three common measures of precedence: fusion, localization dominance, and discrimination suppression. J Acoust Soc Am 109: 346358, 2001.[CrossRef][Web of Science][Medline]
Litovsky RY and Yin TC. Physiological studies of the precedence effect in the inferior colliculus of the cat. I. Correlates of psychophysics. J Neurophysiol 80: 12851301, 1998a.
Litovsky RY and Yin TC. Physiological studies of the precedence effect in the inferior colliculus of the cat. II. Neural mechanisms. J Neurophysiol 80: 13021316, 1998b.
Manley GA, Koppl C, and Konishi M. A neural map of interaural intensity differences in the brain stem of the barn owl. J Neurosci 8: 26652676, 1988.[Abstract]
Mazer JA. Integration of Parallel Processing Streams in the Inferior Colliculus of the Barn Owl (PhD Dissertation). Pasadena, CA: California Institute of Technology, 1995.
McAlpine D and Grothe B. Sound localization and delay linesdo mammals fit the model? Trends Neurosci 26: 347350, 2003.[CrossRef][Web of Science][Medline]
McAlpine D, Jiang D, and Palmer AR. A neural code for low-frequency sound localization in mammals. Nat Neurosci 4: 396401, 2001.[CrossRef][Web of Science][Medline]
Mickey BJ and Middlebrooks JC. Responses of auditory cortical neurons to pairs of sounds: correlates of fusion and localization. J Neurophysiol 86: 13331350, 2001.
Moiseff A. Bi-coordinate sound localization by the barn owl. J Comp Physiol A Sens Neural Behav Physiol 164: 637644, 1989.[CrossRef][Medline]
Moiseff A and Konishi M. Neuronal and behavioral sensitivity to binaural time differences in the owl. J Neurosci 1: 4048, 1981.[Abstract]
Moiseff A and Konishi M. Binaural characteristics of units in the owl's brainstem auditory pathway: precursors of restricted spatial receptive fields. J Neurosci 3: 25532562, 1983.[Abstract]
Mountcastle VB, Talbot WH, Sakata H, and Hyvarinen J. Cortical neuronal mechanisms in flutter-vibration studied in unanesthetized monkeys. Neuronal periodicity and frequency discrimination. J Neurophysiol 32: 452484, 1969.
Perrott DR, Marlborough K, Merrill P, and Strybel TZ. Minimum audible angle thresholds obtained under conditions in which the precedence effect is assumed to operate. J Acoust Soc Am 85: 282288, 1989.[CrossRef][Web of Science][Medline]
Reale RA and Brugge JF. Directional sensitivity of neurons in the primary auditory (AI) cortex of the cat to successive sounds ordered in time and space. J Neurophysiol 84: 435450, 2000.
Saberi K, Takahashi Y, Konishi M, Albeck Y, Arthur BJ, and Farahbod H. Effects of interaural decorrelation on neural and behavioral detection of spatial cues. Neuron 21: 789798, 1998.[CrossRef][Web of Science][Medline]
Shinn-Cunningham BG, Zurek PM, and Durlach NI. Adjustment and discrimination measurements of the precedence effect. J Acoust Soc Am 93: 29232932, 1993.[CrossRef][Web of Science][Medline]
Spezio ML and Takahashi TT. Frequency-specific interaural level difference tuning predicts spatial response patterns of space-specific neurons in the barn owl inferior colliculus. J Neurosci 23: 46774688, 2003.
Spitzer MW, Bala ADS, and Takahashi TT. Auditory spatial discrimination by barn owls in simulated echoic conditions. J Acoust Soc Am 113: 16311645, 2003.[CrossRef][Web of Science][Medline]
Stern RM Jr and Colburn HS. Theory of binaural interaction based in auditory-nerve data. IV. A model for subjective lateral position. J Acoust Soc Am 64: 127140, 1978.[CrossRef][Web of Science][Medline]
Takahashi T and Konishi M. Selectivity for interaural time difference in the owl's midbrain. J Neurosci 6: 34133422, 1986.[Abstract]
Takahashi TT and Keller CH. Commissural connections mediate inhibition for the computation of interaural level difference in the barn owl. J Comp Physiol A Sens Neural Behav Physiol 170: 161169, 1992.[Medline]
Takahashi TT and Keller CH. Representation of multiple sound sources in the owl's auditory space map. J Neurosci 14: 47804793, 1994.[Abstract]
Takahashi TT, Wagner H, and Konishi M. Role of commissural projections in the representation of bilateral auditory space in the barn owl's inferior colliculus. J Comp Neurol 281: 545554, 1989.[CrossRef][Web of Science][Medline]
Tollin DJ. Computational model of the lateralization of clicks and their echoes. In: NATO Advanced Study Institute on Computational Hearing, edited by Greenberg S and Slaney M. Brussels, Belgium: NATO Scientific and Environmental Affairs Division, 1998, p. 7782.
Tollin DJ and Yin TC. Psychophysical investigation of an auditory spatial illusion in cats: the precedence effect. J Neurophysiol 90: 21492162, 2003.
Trahiotis C and Hartung K. Peripheral auditory processing, the precedence effect and responses of single units in the inferior colliculus. Hear Res 168: 5559, 2002.[CrossRef][Web of Science][Medline]
Trahiotis C and Stern RM. Across-frequency interaction in lateralization of complex binaural stimuli. J Acoust Soc Am 96: 38043806, 1994.[CrossRef][Web of Science][Medline]
Wagner H. Receptive fields of neurons in the owl's auditory brainstem change dynamically. Eur J Neurosci 2: 949959, 1990.[CrossRef][Web of Science][Medline]
Wagner H, Takahashi T, and Konishi M. Representation of interaural time difference in the central nucleus of the barn owl's inferior colliculus. J Neurosci 7: 31053116, 1987.[Abstract]
Wallach H, Newman EB, and Rosenzweig MR. The precedence effect in sound localization. Am J Psychol 57: 315336, 1949.[CrossRef]
Wyttenbach RA and Hoy RR. Demonstration of the precedence effect in an insect. J Acoust Soc Am 94: 777784, 1993.[CrossRef][Web of Science][Medline]
Yin TC. Physiological correlates of the precedence effect and summing localization in the inferior colliculus of the cat. J Neurosci 14: 51705186, 1994.[Abstract]
Zurek PM. The precedence effect and its possible role in the avoidance of interaural ambiguities. J Acoust Soc Am 67: 953964, 1980.[Medline]
Zurek PM. The precedence effect. In: Directional Hearing, edited by Yost WA and Gourevitch G. New York: Springer Verlag, 1987, p. 85105.
This article has been cited by other articles:
![]() |
L. D. SANDERS, A. S. JOH, R. E. KEEN, and R. L. FREYMAN One sound or two? Object-related negativity indexes echo perception Atten Percept Psychophys, November 1, 2008; 70(8): 1558 - 1570. [Abstract] [PDF] |
||||
![]() |
A. Reches and Y. Gutfreund Stimulus-Specific Adaptations in the Gaze Control System of the Barn Owl J. Neurosci., February 6, 2008; 28(6): 1523 - 1533. [Abstract] [Full Text] [PDF] |
||||
![]() |
Y. Gutfreund and E. I. Knudsen Adaptation in the Auditory Space Map of the Barn Owl J Neurophysiol, August 1, 2006; 96(2): 813 - 825. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. W. Spitzer and T. T. Takahashi Sound Localization by Barn Owls in a Simulated Echoic Environment J Neurophysiol, June 1, 2006; 95(6): 3571 - 3584. [Abstract] [Full Text] [PDF] |
||||
![]() |
G. C. Stecker Parallel Emergence of Spatial Tuning and Echo Suppression in the Auditory Midbrain? Focus on "A Neuronal Correlate of the Precedence Effect Is Associated With Spatial Selectivity in the Barn Owl's Auditory Midbrain" J Neurophysiol, October 1, 2004; 92(4): 1965 - 1966. [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |