Auditory Gap Detection, Perceptual Channels, and Temporal … · 2019. 12. 19. · pitch of an event in the stream of speech and the spatial property of the percept (i.e., the per-ceived

J Am Acad Audiol 10 : 343-354 (1999)

Auditory Gap Detection, Perceptual Channels, and Temporal Resolution in Speech Perception Dennis P. Phillips*

Abstract

This article overviews some recent advances in our understanding of temporal processes in auditory perception . It begins with the premise that hearing is the online perceptual elabo-ration of acoustic events distributed in time . It examines studies of gap detection for two reasons: first, to probe the temporal acuity of auditory perception in its own right and, second, to show how studies of gap detection have provided new insights into the processes involved in speech perception and into the architecture of auditory spatial perceptual mechanisms. The implications of these new data for our comprehension of some central auditory pro-cessing disorders are examined .

Key Words: Gap detection, perceptual channels, sound localization, speech perception, temporal resolution

Abbreviations : SLI = specific language impairment, VOT = voice onset time

S ounds are, by their very natures, physi-cal events distributed in time, and so it should come as no surprise that the basic

and clinical auditory sciences are devoting increasing effort to elucidating the temporal processes required for veridical auditory per-ception. "Hearing" is not simply about the detec-

tion of the presence of sound or even discrimination of its long-term spectral content; rather, it entails the successful online perceptual elaboration of the short-term content of the sig-nal (Stevens, 1980 ; Moore et al, 1988; Phillips, 1988, 1998 ; Viemeister and Wakefield, 1991). Construed in this way, there are probably many "temporal processes" in hearing. Thus, the voice pitch of an event in the stream of speech and the spatial property of the percept (i .e ., the per-ceived location of the source relative to the lis-tener) are both based in part on temporal processes-computation of interlaryngeal-pulse intervals in the first case and of interaural dis-parities in sound arrival time in the second . The ability to order two events, to segregate them in time, or even to know that there are two

*Hearing Research Laboratory, Department of Psychology, Dalhousie University, Halifax, Nova Scotia,

Canada Reprint requests : Dennis P. Phillips, Hearing Research

Laboratory, Department of Psychology, Dalhousie University, Halifax, NS, Canada B3H 4J1

events present contributes to another tier of temporal processes (Moore, 1989).

These are nontrivial distinctions, because, at least at the level of the brain's ability to estab-lish a sensory representation of the stimulus, quite different neural circuits may mediate the coding of different temporal stimulus features (Phillips, 1995, 1998). In turn, this means that those circuits may, in principle, be indepen-dently susceptible to pathology, and there is indeed some evidence of precisely this in the neurologic literature (Phillips, 1995, 1998). By the same token, this separability of mechanism

raises the possibility that those mechanisms (and the perceptual functions they mediate) have different developmental time courses and/or different susceptibilities to alteration as a result of experience.

The purpose of the present article is to sur-vey some experiments on auditory gap detection that have a direct bearing on the mechanisms involved in the detection and discrimination of changes in the stream of sound across time .

This general issue is an important one because a number of studies have pointed to distur-bances in the processes that mediate the per-ceptual elaboration of sequential auditory events in developmentally language-delayed children (Tallal et al, 1993). Indeed, a case can be made in some of these children that such perceptual defects lie at the root of the problem, that is, that the higher-level linguistic deficits might follow

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Journal of the American Academy of Audiology/Volume 10, Number 6, June 1999

as a kind of cascade error from a low-level per-ceptual defect (Tallal and Piercy, 1975 ; Elliott et al, 1989 ; Tallal et al, 1993, 1996 ; Bishop, 1997 ; Wright et al, 1997). For what follows, we empha-size that the perceptual operations involved in gap detection are only a subset of those used in the perception of sequential auditory events . Our rationale is simply that the gap detection paradigm has proved to offer more insights into auditory perception than might otherwise have been imagined, and that these insights may help us understand the nature of the speech perception process itself. Most generally, the presentation of convincing evidence on the diver-sity and properties of temporal auditory processes offers the possibility of prompting research into the developmental time courses of those processes and their differential suscepti-bility to pathology in childhood or adulthood.

We begin by sketching the temporal struc-ture of speech sounds . We turn then to a brief account of the traditional gap detection paradigm and some of the factors that influence gap detec-tion performance. We next consider some recent experiments using a modified gap detection par-adigm, which offer new insights into the tem-poral processes involved in gap detection per se and into temporal acuity in speech perception. We then show how the new gap detection para-digm has been used to study some general prop-erties of auditory perception and conclude with a brief description of where these observations fit in the context of our general comprehension of central auditory processing disorders and their management.

TIME STRUCTURE OF SPEECH SOUNDS

S peech sounds have a time structure that can be described at a number of levels . In the voiced speech components, there are periodic glottal pulses, and the temporal spacing of these pulses is a key factor in determining voice pitch. What we mean by this is that the time waveform of the sound contains nearly identical elements (glottal pulses) that are repeated in a relatively regular (periodic) fashion. Thus, adult male voices tend to have fundamental frequencies near 120 Hz, while female voices have pitches nearly twice that . Furthermore, note that changes in the glottal pulse rate over time con-stitute intonation contours (e.g., rising contours for interrogatives and rapidly declining ones for declaratives) . These changes are also the basis of the melodic contours produced by the singing

voice. In the unvoiced components of the speech signal (e.g., consonantal bursts ; whispered speech is also a fine example), the time waveform of the sound is much more random (noisy), and any pitch percept is more subtle and based on the spectral distribution of stimulus energy.

The phonetically important components of the speech signal are independent of voice pitch. The phonemes have relative unique acoustic signatures that result from the imposition of the upper vocal tract filter function at the time of articulation on the carrier source (glottal air flow waveform) passing through it ("source-fil-ter theory"; Lieberman and Blumstein, 1988). The steady vowels are the simplest case ; for each vowel, the vocal tract has a unique config-uration (and, therefore, filter function) that imposes distinct peaks on the laryngeal tone (or laryngeal noise, in the case of whispered speech), and these peaks constitute the formant frequencies that uniquely specify the vowel. The most complex case is probably that of the stop consonants . For them, the initial consonantal burst is very short (a few msec) and has a ran-dom time waveform ; if voiceless, its spectrum results from the imposition of the upper vocal tract filter function on the release and aspira-tion noise. As the vocal tract changes configu-ration for the production of the ensuing vowel, the peaks in the filter function shift accordingly (formant transitions), finally to settle as the defining formant frequencies of the steady vowel. Voicing, marked by the appearance of glottal pulses, typically begins either relatively soon after the consonantal burst (generally 5-25 msec, in our laboratory ; see also Lisker and Abramson, 1964 ; Stark and Tallal, 1979) or very much later (50-105 msec); indeed, there is very little overlap in the distributions of voice onset times NOW for the voiced (short VOT) and unvoiced (long VOT) stops.

For what follows, it is our assumption that just as identity of a steady vowel can be speci-fied by the conjunction of the first two formant frequencies (e.g., Peterson and Barney, 1952), the consonants also have relatively unique acoustic signatures (Stevens and Blumstein, 1978; Blum-stein and Stevens, 1979, 1980), that is, unique short-term spectra, as in the bursts of the stops. Certainly, in the case of phonemes whose defin-ing acoustic content is time varying, it is possi-ble that the acoustic signature actually is based on two or more samples of the sound (Lahiri et al, 1984), but this is a small point. The larger issue is that the existence of such signatures at all means that phoneme recognition may proceed

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through a template-matching ("bottom-up") process, doubtless aided by contextual infor-mation ("top-down" processing) when the stim-

ulus is acoustically ambiguous (Lahiri et al,

1984) .

TRADITIONAL GAP DETECTION

G ap detection is a measure of one form of auditory temporal acuity. Typically, the lis-

tener is presented with two relatively long (e.g ., hundreds of msec) bursts of sound, one of which (the "target") contains a brief silent period (gap) at its temporal midpoint . The task of the listener is to indicate which burst of sound contains the gap. An adaptive threshold tracking procedure is normally used to determine the shortest (threshold) detectable gap according to some criterion level of performance. Because the gap

is short relative to the length of the sound in

which it occurs, neither overall stimulus energy nor overall stimulus duration can easily be used

to perform the task . Moreover, the contribution

of gating transients to performance of the task is minimized either by using broadband carri-ers, by employing background noise maskers (Moore, 1993), or by inserting an extremely short (i .e ., known independently to be unde-tectable) gap bounded by the same transients into the comparison (or "reference") sound (Phillips et al, 1997). Figure 1A provides a schematic depiction of typical within-channel gap detection stimuli.

When the silent period is relatively long, the stimulus is easily perceptually parsed into a leading marker, a subsequent silent period, and

then the resumption of the carrier. Near gap threshold, this is not true, and the percept is of a single "glitch" or "hiccup" : a single discontinuity

in an otherwise homogeneous sound (Moore, 1993). With this in mind, the best gap detection performances (i .e ., the lowest gap thresholds) are

seen with carriers that are broadband and sig-nificantly above amplitude threshold (Eddins

et al, 1992 ; Moore et al, 1993). Under these con-ditions, gap thresholds can be as low as 2 to 3

msec (Plomp, 1964 ; Penner, 1977 ; Phillips et al, 1998). Using very narrow-band signals, one can show that the gap detection performance sup-

ported by the most apical cochlear sectors (those representing frequencies significantly less than

0.5-1 .0 kHz) is poorer than that seen at higher frequencies (Hall et al, 1996). There are at least two reasons for this (Moore, 1993). One is that very low center-frequency noise signals have low-frequency fluctuations in amplitude that

Temporal Processes in Hearing/Phillips

BETWEEN-CHANNEL

W

time in msec

B

Figure 1 Schematic depictions of typical gap detec-

tion stimuli are shown for within-channel (A) and

between-channel (B) designs. In the within-channel

design, the leading and trailing markers of the gap have

common acoustic features (e.g ., the same spectral content

or the same laterality) . In the between-channel design,

the leading and trailing markers of the gap differ along

one (Phillips et al, 1997) or more (Taylor et al, 1999)

dimensions . In the cases shown, the leading marker is shorter in duration than the trailing one. In practice, within-channel gap thresholds are independent of the loca-

tion of the gap, while between-channel thresholds are ele-

vated as the leading marker is made more brief.

the listener can confuse with the gap intended to be detected . The second is that the cochlear filter is relatively narrow for low center fre-quencies, and the attendant "ringing" at the off-

set of the leading marker consequently can obscure the gap that follows .

An important feature of the "processing" required to perform the traditional gap detection task is its within-channel nature . That is, because the leading and trailing markers are

acoustically similar (or identical), they stimulate the same set(s) of peripheral auditory neurons. The temporal operation to be executed by the lis-tener is, therefore, actually the detection of a dis-continuity in the activity aroused in the neural or perceptual channel(s) representing the stim-ulus content (Phillips et al, 1997). It is for this reason that one can record the activity of single cochlear nerve fibers to observe the represen-tation of the gap stimulus in the time course of spike discharges ; such studies reveal a corre-spondence between the shortest gaps clearly represented as a dip or discontinuity in the

ongoing discharge rate of cochlear nerve fibers

on the one hand and independently measured behavioral gap thresholds on the other (Zhang et al, 1990).

Ultimately, the behavioral detectability of a temporal gap must depend on the unequivocal-

ity or precision of that gap's representation in

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neural activity. One way to maximize this "salience" of the neural representation is to use a stimulus that activates more than one fre-quency channel of cochlear output . Thus, gap detection thresholds seen using very narrow-band noises improve with increasing noise band-width (Eddins et al, 1992). Grose (1991) and Hall et al (1996) have studied the detection of gaps bounded by multiple narrow bands of noise and confirmed that gap detection performance is indeed improved by dispersing the stimulus energy across more than one cochlear filter. Moreover, performance seemed to be relatively independent of the spectral separation of the markers (Hall et al, 1996). Presumably, the per-ceptual elaboration of the gap by more central regions of the auditory system exploits the inde-pendence and number of activated cochlear channels in some form of averaging or cross-cor-relation process executed on the outputs of the active channels (Viemeister, 1979 ; Grose, 1991). More generally, it is the independence with which the outputs of different cochlear channels are represented centrally that underlies such diverse phenomena as comodulation masking release (Hall et al, 1984) and profile analysis (Green, 1988). That is, it is the preservation of the frequency-specific processing that makes possible the analysis of differences or similari-ties in activity across those channels .

BETWEEN-CHANNEL GAP DETECTION AND VOICE ONSET TIMES

G ap detection as a perceptual operation takes on special importance from the fact that the

stream of speech sounds is broken by periods of relatively low amplitude sound or even com-plete silence. To be sure, some of these pauses are very long and are intended as points of emphasis or to parse speech output at changes in topic. However, for the present purposes, some of the most interesting "gaps" in the stream of speech are the phonetically important ones (viz ., VOTs). From the speech production stand-point, what makes VOTs of interest is their vir-tually nonoverlapping distributions for the voiced and voiceless stop consonants (Lisker and Abramson, 1964 ; Liberman et al, 1967). From the speech perception standpoint, VOTs are of spe-cial interest for two reasons. One is that the VOT cue is most often cited as being the (only) one that distinguishes stop consonants with the same place of articulation (Repp, 1979). The second is that the percepts evoked by elements drawn from synthetic VOT continua tend to be

labeled categorically, that is, elements from one end are uniformly labeled as exemplars of the prototypical short VOT sound, while elements from the opposite end of the continuum are labeled as exemplars of the prototypical long VOT sound-both of these over significant ranges of VOTs . The labeling function reverses quite abruptly at the so-called "phonetic bound-ary," which is typically associated with VDTs near 30 msec (Eimas and Corbit, 1973). The reasons for this are unclear, but the fact that the perceptual behavior extends to chinchillas (Kuhl and Miller, 1978) suggests that it is a very basic auditory phenomenon . In this regard, Kuhl and Miller (1978) argued that such categories in speech exploit "natural psychophysical bound-aries," even if the identity of those boundaries had not yet been worked out.

There are, arguably, two related difficulties with trying to model VOT perception with a tra-ditional gap detection paradigm . One is that in the speech sound, the leading marker (the con-sonantal burst) is very short, while this is almost never true in the traditional gap detection stim-ulus . The second is that in the speech sound, the "gap" is bounded by spectrally different mark-ers, while this is rarely true in traditional stud-ies of gap detection. This point is an important one. As mentioned above, the perceptual oper-ation required to perform traditional gap detec-tion is technically a discontinuity detection executed on the perceptual channel activated by the stimulus ; this is because the leading and trailing markers activate the same peripheral neurons, and so the gap to be detected is repre-sented as a discontinuity in the activity aroused in the activated channel. In contrast, when the leading and trailing markers are significantly dif-ferent (e.g., spectrally nonoverlapping), the per-ceptual operation necessarily becomes one of the relative timing of the offset of activity in the channel representing the leading marker and the onset of activity in the channel activated by the trailing marker. Phillips et al (1997, 1998) referred to such a paradigm as "between-chan-nel" gap detection for this reason, and they made clear that the "channels" here did not need to refer only to the classical critical bands (Scharf, 1970) but to the complete central neural "rep-resentation" of the stimulus elements . Phillips et al further argued that this relative timing operation must be performed by the central auditory system because the auditory periphery contains no neural machinery capable of medi-ating the operation. That is, the cochlear output lines are, for the most part, functionally

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independent, and there are no longitudinal

cochlear interconnections to mediate any cross-

correlation of activity in those lines . Figure 1B

presents a schematic depiction of typical between-channel gap detection stimuli . Note

that the temporal configuration of the markers

is the same as that in the within-channel case,

and that what distinguishes the between-chan-nel case is the acoustic differences between the markers that delimit the silent period .

There is agreement that gap thresholds are elevated by the existence of frequency dispari-ties between the leading and trailing markers for both narrow-band noise and tonal cases (Fitzgibbons et al, 1974 ; Neff et al, 1982 ; Formby

et al, 1996 ; Heinz et al, 1996 ; Phillips et al, 1997). Elevated gap thresholds are also seen when the leading and trailing markers are dif-ferent but specifically designed to resemble speech sounds (Formby et al, 1993 ; Nelson et al, 1995 ; Phillips et al, 1997). Moreover, in the same listeners, between-channel but not within-chan-nel, gap thresholds are sensitive to the duration of the leading marker and show increases for leading marker durations less than about 30 msec (Phillips et al, 1997). This latter find-ing provides support for the view that the two kinds of gap detection paradigms tap funda-mentally different timing mechanisms . Still fur-ther support comes from two other findings . One is that between-channel gap thresholds showed much larger individual differences than

did within-channel ones (Phillips et al, 1997, 1998). The second is that while one within-chan-nel gap threshold is a good predictor of gap threshold in a second within-channel task, within-channel gap thresholds are poor predic-tors of between-channel thresholds in the same listeners (Phillips and Smith, 1999).

To illustrate some of these points, Figure 2 shows gap threshold data for within- and between-channel tasks in a single group of six listeners with normal hearing. Gap threshold has been plotted as a function of leading marker duration . The two shaded areas in the plot are the envelopes of the within- and between-chan-nel gap threshold distributions, respectively (data are taken from the study of Phillips et al [1998] ; see below). The lower shaded area in Figure 2 shows the distribution of gap thresh-olds for a within-channel task . Note that, for each

leading marker duration, gap thresholds across the listeners had only a small range, centered on very low values (a few msec). It was also the case that, by and large, the spread of scores was independent of leading marker duration . The

70

60

50 _E -a40 0 L

T 30

n ca 20 ('3

10

0 50 100 150 200 250 Duration of leading marker (msec)

Figure 2 Distributions of gap detection thresholds in six normal listeners for a within-channel (lower shaded

area) and a between-channel task (upper shaded area).

The shaded areas represent the envelope of mean gap thresholds for each of the six listeners. Gap threshold has

been plotted as a function of leading marker duration .

Note that gap thresholds are short and largely indepen-

dent of leading marker duration for the within-channel but not the between-channel task . Data are post hoc

reanalyses of those presented by Phillips et al (1998) .

upper shaded area shows the distribution of gap thresholds in the same listeners, but for a between-channel task . All of the thresholds are higher, and there is greater variability in the data, expressed here as the vertical spread of scores for any specified leading marker duration. Note that, in contrast to the within-channel

data, the shaded area for the between-channel scores swings strongly upward at the extreme left of the plot, illustrating that between-chan-

nel gap thresholds are longer for very short durations of the leading marker.

The reasons for the poorer temporal acuity

of between-channel gap detection are not known with certainty. That is, it is not clear why a cross-correlation of the activity in two different channels need have a poorer acuity than dis-continuity detection in any single channel. Fitzgibbons et al (1974) took a cognitive approach

by describing the between-channel operation in

terms of the dwelling of attentional processes on the perceptual channel activated by the leading marker and the subsequent, presumably time-consuming, shifting of those processes to the channel representing the trailing one. Phillips

et al (1997) also advocated a role of attentional processes, but at a "lower" level. They suggested that the allocation of perceptual or attentive

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resources to any one channel (e.g ., that repre-senting the leading marker) impoverishes the time stamping of events in any other channel. Such an account is simply an extension of the precedent set earlier by Scharf et al (1987, 1994), namely, that allocation of attentive resources to one channel impairs the detection of threshold-level signals in other channels .

Irrespective of the reasons for the higher gap thresholds in the between-channel case, the absolute values of gap thresholds seen in it are of interest. The first reason for this concerns the mechanisms that determine the gap threshold. In general, it is likely that the extent to which between-channel gap thresholds are greater than within-channel ones depends on the extent to which the leading and trailing markers acti-vate different perceptual channels, that is, on the extent to which the temporal judgment relies on a cross-correlation of activity between channels rather than a discontinuity detection within a channel. Perceptual channels in any dimension (frequency, space, etc.) need not be narrowly tuned, and they may have sloping ("fuzzy") edges. This means that when the gap markers each activate more than one channel, both within- and between-channel processes can con-tribute to gap threshold. The further apart the markers are along the relevant stimulus dimen-sion, the more likely is the perceptual operation to rely exclusively on between-channel processes, and thus have a poor acuity (Phillips et al, 1997 ; Formby et al, 1998 ; Taylor et al, 1999).

The second reason for interest in absolute between-channel gap thresholds concerns the extent to which they offer insight into the ori-gins of the VOT phonetic boundary. Phillips et al (1997) studied gap thresholds for stimuli with different leading marker durations. They showed that if the leading marker in the between-chan-nel paradigm was only 5 to 10 msec in duration, then, notwithstanding considerable individual variation, grand mean gap thresholds were typ-ically near 25 to 35 msec . The 5- to 10-msec leading marker roughly approximates the dura-tion of the consonantal burst, so that the between-channel gap stimulus has some of the temporal properties of the speech sound, even though it has none of the phonetic ones . The grand mean gap thresholds so obtained are roughly those that distinguish the VOTs in voiced stop consonants from those of unvoiced stops (Lisker and Abramson, 1964; Eimas and Corbit, 1973 ; Kuhl and Miller, 1978). That is, the psychophysical boundary exploited by speech in this instance might be the distinction between

detectable and undetectable gaps for sounds that have the between-channel and temporal configuration of stop consonants .

Certainly, the between-channel gap thresh-old is not the only possible factor determining the VOT phonetic boundary. The temporal judg-ment of the onset simultaneity of sounds (Pisoni, 1977) and the temporal ordering of two differ-ent stimuli (Hirsh and Sherrick, 1961) appear to be subject to a 20-msec or so boundary effect, and this fits well with the location of the VOT boundary, too. Whether these nonspeech per-ceptual findings are all directly related is unclear, but even if they are not, it would perhaps be unsurprising to learn that the joint contributions of these phenomena might result in the emer-gence of a sharply demarcated VOT phonetic boundary.

Of still further interest is the fact that when the between-channel nature of the gap paradigm was defined by ear rather than by fre-quency (i .e ., the leading and trailing markers had the same spectral composition but were presented to different ears), the same grand mean gap threshold (about 35 msec) was seen for very short leading markers (Phillips et al, 1997). This similarity in acuity suggests that the same relative timing mechanism was accessed in the binaural experiment as in the foregoing monaural ones . If that is in fact the case, then the relative timing mechanism must of neces-sity be centrally located, because only central neurons have access to information from both ears .

BETWEEN-CHANNEL GAP DETECTION AND AUDITORY SPACE

n the preceding cases, the "between-chan-nel" nature of the gap detection task was

forced by using leading and trailing markers that selectively stimulated different populations of peripheral auditory neurons. Thus, in the Phillips et al (1997) studies, leading and trail-ing markers were designed to stimulate differ-ent frequency sectors of the cochlea in a single ear or the same frequency region but in differ-ent ears . It is possible, however, that the "chan-nels" upon which the relative timing mechanism operates extend beyond those defined by differ-ences in the identities of the peripheral neu-rons activated by the markers . That is, some perceptual channels arise from central neural computations, and the generality of the rela-tive timing mechanism can be assessed by whether between-channel phenomena are seen

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in cases where the markers activate similar populations of peripheral neurons but different central perceptual channels .

One obvious such case is spatial hearing, because broadband sources located on the left and right of the head in freefield space proba-bly activate comparable populations of neurons in the two ears; the spatial property of the per-cepts (and thus the perceptual channels acti-vated) arise from central computations of the relative timing and amplitudes of the signals at each ear for each marker. Phillips et al (1998) addressed this question directly by having lis-teners perform within- and between-channel gap detection tasks in which the markers were broadband noise sources located at the poles of the interaural axis in the freefield. As might have been expected, within-channel gap thresh-olds (i .e ., gap thresholds for markers originat-ing from a single locus) were low (a few msec) and largely independent of leading marker dura-tion . Between-channel gap thresholds (i .e ., gap thresholds for markers originating from differ-ent speakers) were considerably different in dif-ferent listeners, were always longer than within-channel gap thresholds, and were espe-cially so for short-duration leading markers. Indeed, the grand mean between-channel gap threshold for stimuli containing a 5-msec lead-ing marker was again close to 35 msec . Figure 2 was derived from these data .

These data suggest that stimuli located in the far left and right auditory hemifields acti-vate different spatial auditory channels . The fording is entirely compatible with a long history of auditory neuroscience (Phillips and Brugge, 1985). Recall that interaural disparities in the phase, arrival time, or amplitudes of the signals at the eardrums are the binaural cues for sound source location, and that binaural central neu-rons, especially those rostral to the olivary nuclei, can be sensitive to these disparities . One com-mon expression of sensitivity to these cues is a sigmoidal relation of response rate to disparity size, such that maximal excitatory responses are seen for disparities grossly favoring the con-tralateral ear, and inhibitory responses or very low excitatory firing rates are seen when the dis-parities favor the ipsilateral ear. The steep and informative portion of the sigmoidal function-that is, the part of the function in which there is a one-to-one relation between disparity size and neural firing rate-is usually associated with small disparities favoring the contralateral ear (Phillips and Irvine, 1981). This is one line of evidence that led to the view that each side

of the central auditory forebrain independently encodes or represents spatial information for the contralateral auditory hemifield (Phillips and Irvine, 1981 ; Phillips and Brugge, 1985). It is a view supported by behavior-lesion studies showing that unilateral forebrain auditory abla-tions result in sound localization deficits only for sources in the sound hemifield contralateral to the lesion (Jenkins and Masterton, 1982 ; Kavanagh and Kelly, 1987).

Now, it is possible, at least grossly, to pre-dict the effective spatial receptive fields of bin-aural neurons, based on their sensitivity to the cues for source azimuth. Since the neurons described above are inhibited by (or unrespon-sive to) stimuli simulating ipsilateral freefield locations and excited by ones simulating loca-tions in the contralateral hemifield, it follows that their receptive field boundaries, and thus the limits of their spatial tuning, also bound the contralateral auditory hemifield. Freefield studies in animals have indeed described the presence of "hemifield" neurons in the auditory midbrain and cortex (Middlebrooks and Petti-grew, 1981 ; Semple et al, 1983 ; Imig et al, 1990 ; Rajan et al, 1990 ; Brugge et al, 1996). Certainly, there are other forebrain (especially cortical) neurons whose patterns of binaural input and sensitivity to binaural sound location cues sug-gest that they would display spatial tuning for midline locations (i .e ., a preference for interau-ral disparities near zero : Kitzes et al, 1980 ; Phillips and Irvine, 1981; Irvine et al, 1996) . This, however, does not dispute the existence or independence of hemifield tuning in other neu-rons, and thus a neural basis for perceptual channels with hemifield tuning .

The spatial tuning of human auditory perceptual channels is still being worked out (Boehnke and Phillips, 1999). The published psychophysical evidence to date (e.g ., Phillips et al, 1998) suggests only that stimuli deep in the two lateral auditory hemifields activate differ-ent perceptual channels, and not necessarily that those channels have hemifield tuning. How-ever, the suspicion that human spatial chan-nels might include those with a hemifield architecture is bolstered by two other lines of independent evidence . One is that when auditory cortical trauma in man results in sound localization deficits, the deficits are distributed across the contralateral hemifield (Sanchez-Longo and Forster, 1958 ; Zatorre et al, 1995). The second is that neurologic patients with parietal lesions, who typically show an attentional "neglect" of the contralateral body surface and

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visual field, also can display an auditory neglect that is limited to the acoustic hemifield con-tralateral to the lesion (Heilman and Valen-stein, 1972).

Most recently, Boehnke and Phillips (1999) have provided psychophysical evidence, based on a between-channel gap detection paradigm, on the tuning of spatial channels in human listen-ers with normal hearing. By systematically vary-ing the freefield spatial locations of both the leading and trailing markers of gap detection stimuli, they were able to map the boundaries of auditory azimuth associated with low gap thresholds ("within-channelness") for each lead-ing marker location . Their data clearly indi-cated the existence of broadly tuned left and right auditory hemifield channels whose bor-ders probably extend some 30 degrees across the midline. These data appear to be a direct behav-ioral expression of the spatial receptive fields of central neurons (Rajan et al, 1990).

SOME IMPLICATIONS FOR CENTRAL AUDITORY PROCESSING DISORDERS

W e began with the premise that there is a host of temporal processes in hearing and that specification of the properties of these processes is a prelude to determining their devel-opmental time courses or their differential sen-sitivity to pathology or their contribution to a central auditory processing disorder. In the pre-ceding pages, we have taken the apparently simple (and single) perceptual skill of auditory gap detection and have shown that it is decom-posable into at least two different operations (discontinuity detection and relative timing). We have argued that the contribution of these two processes to a given gap threshold depends on the extent to which the gap's markers selec-tively activate different perceptual channels . The "between-channel" case of gap detection is of special interest for at least two reasons. One is that it might offer a new insight into the gen-esis of VOT perceptual phonetic boundaries (i .e ., it might offer a new insight into the perceptual mechanics of speech discrimination). The second is that the between-channel paradigm can be exploited to study other aspects of hearing (e.g., its spatial architecture). Research in this domain is only just beginning, but already it has provided new evidence suggestive of at least two spatial channels in human hearing (left and right hemi-fields) that map onto our independent knowledge of basic auditory neuroscience and clinical neu-rology quite nicely.

It is likely that some form of "disorder of rapid auditory temporal processing" is associ-ated with developmental language disorders in some children . Tallal has been one of the strongest advocates of this position, particu-larly for the case of specific language impair-ment (SLI ; Tallal and Piercy, 1975; Stark and Tallal, 1979 ; Tallal et al, 1993, 1996 ; but see also Elliott et al, 1989 ; Bishop, 1997). The percep-tual problem in this instance is usually revealed in an auditory sequencing task in which the child is required either to order, or to discrim-inate, two (or more) closely spaced, brief sounds . The "either" here is important, because affected children usually perform poorly at both tasks when the interstimulus intervals are relatively short (Tallal and Piercy, 1973). In any case, this is not simply a matter of the coexistence of the perceptual disorder and the SLI in the same children . Rather, the severity of the perceptual problem measured with nonverbal stimuli is strongly correlated with that of the language impairment (Tallal et al, 1985a), and its pres-ence is a potent predictor of whether the chil-dren are independently classified as normal or impaired on the basis of linguistic criteria (Tal-lal et al, 1985b) . Most recently, attempts specif-ically to train affected children in the compromised auditory perceptual tasks have led to some amelioration of the language deficit (Merzenich et al, 1996; Tallal et al, 1996); this perhaps represents the strongest evidence of a causal relation between the perceptual problem and the language one.

Note that, without disputing any of the fore-going findings, neither the demonstration of poor scores on the sequencing task nor the reme-diation of the language problem by auditory training specifies precisely what auditory tem-poral process(es) is (are) impaired in SLI chil-dren . The difficulty here is that there are a number of separable perceptual operations the compromise of which could result in poor per-formance on the sequencing task, and which could reasonably be expected to disturb per-ception sufficiently to be the seed of a SLI. Wright et al (1997) have very elegantly shown that a group of SLI children did not show a gen-eralized deficit in "the perception of rapidly pre-sented sounds" but rather one maximally visible in backward (as opposed to simultaneous or for-ward) masking paradigms. This is precisely the kind of defect that would impair performance in the brief-vowel and stop consonant experiments of Tallal and Piercy (1975) . The backward nature of the aberrant masking is likely to interfere with

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the perceptual elaboration of low-amplitude (or brief) early component of the sounds that impart the unique identity to the stimulus (Phillips,

1998) . By the same line of reasoning, it is also the kind of defect that could impair performance in gap detection tasks with short leading mark-

ers and, arguably through that route, the accu-rate perception of the stop consonants (Phillips

et al, 1997) . The general point is that it is the careful dissection of perceptual performance into its component building blocks that provides

a strong basis for intervention .

There have been other recent investigations of "low-level" auditory processes in adults and children with developmental language disor-ders, and each of these studies has revealed some form of temporal processing deficit (Ste-fanatos et al, 1989 ; Hari and Kiesila, 1996 ; McAnally and Stein, 1996 ; see also Galaburda et al, 1994). In these cases, the demonstrated dif-ficulties are somewhat harder to relate to the gen-esis of the language dysfunction than are those described above (Tallal and Piercy, 1975 ; Wright et al, 1997). It is thus uncertain whether some of these deficits are correlated with (i .e ., mark-ers for) the language disorder, as opposed to being causally related to it. It is, for example, clear that an impoverished ability of brainstem audi-tory neurons to phase-lock responses to stimu-lus periodicities constitutes a temporal "processing" problem (or perhaps "representa-tional" problem, Phillips, 1995), but it is unclear how, or if, this problem is related to the dyslexia in the listeners in whom it is observed (McAnally and Stein, 1996). These are important issues because they shape the way we should concep-tualize the underlying pathophysiology.

Our foregoing discussions of "temporal pro-cessing" and of "perceptual channels" are ger-mane to the management of listeners with central auditory processing problems in two further ways . One is that the strictly temporal properties of sensory neurons in the brain can be enhanced by behavioral training (Recan-zone et al, 1992) . It is, therefore, possible that if a central auditory processing disorder resides in a specifiable temporal processing problem, then directed training that targets the rele-vant perceptual operation might enhance the performance of that impaired perceptual machinery. It was, indeed, precisely this kind of argument that prompted the recent devel-opment of training strategies for SLI children (Merzenich et al, 1996 ; Tallal et al, 1996). The basic science of this line of work is still being elaborated (e.g ., the generality of benefits of a


specific training ; Wright, 1998), but it is not

unreasonable to suggest that the more pre-cisely a compromised perceptual mechanism is

described, the more specifically it can be tar-

geted for remediation. A second point concerns the issue of auditory

spatial channels . We have long known of the exis-tence of the "cocktail party effect," that is, the ability to attend selectively to one of a number of concurrent conversations, or, in principle, to one of a number of concurrent streams of any sound (Handel, 1989). Now, one of the bases available for parsing out the target conversation is the target's spatial location relative to the listener. In principle, this is not fundamentally different from the case of binaural (un)masking, wherein a low-frequency binaural signal "pops out of a binaural noise masker if the interau-ral phase relations of the signal and masker are different (Moore, 1989). The brain computes the spatial location of a sound separately for spectrally different sources (or for different spec-tral elements within a source ; Jenkins and Merzenich, 1984; Phillips and Brugge, 1985 ; Phillips, 1995), so that different populations of neurons are activated not only according to the spectral content of a sound but also according to the sound's locus. Data obtained using the between-channel gap detection paradigm seem to indicate the existence of perceptual channels based on source location (Phillips et al, 1998 ; Boehnke and Phillips, 1999), and we argued

above that the existence of such channels is con-sistent with a long history of neurophysiologic evidence on binaural sound localization . The further ramification of this research is that the perceptual disadvantage of noisy or difficult lis-tening environments might be moderated if the intended target sound (e.g., the teacher's voice) stimulates a different spatial channel to that occupied by the distracting sound (hallway noise) . This is probably true for all listeners, but it is especially important for those whose auditory streaming or attentive skills are chal-lenged .

The foregoing paragraphs provide bases for at least two general strategies for the manage-ment and remediation of the listener with a central auditory processing disorder. One is the explicit and targeted training of the listener in

the perceptual skill(s) identified as being at the root of the problem. The second is the manage-ment of the auditory environment so that the lis-tener's attentive resources are captured as easily as possible by the sound source of interest . In this regard, directed training of the impaired

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listener's attentive skills may be as helpful as the training of their perceptual ones .

Grose JH . (1991). Gap detection in multiple narrow bands of noise as a function of spectral configuration . JAcoust Soc Am 90:3061-3068 .

Acknowledgment . Some of the research described in this article was funded by grants from Natural Sciences and Engineering Research Council of Canada to the author. Special thanks are due to Susan Boehnke, Susan Hall, Dr. Chris Moore, and an anonymous reviewer for helpful comments on a previous version of the manuscript .

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