Hearing Research 193 (2004) 39–50
www.elsevier.com/locate/heares
Effects of an acute acoustic trauma on the representation of avoice onset time continuum in cat primary auditory cortex
Masahiko Tomita, Arnaud J. Nore~na, Jos J. Eggermont *
Departments of Physiology and Biophysics, and Psychology, Neuroscience Research Group, University of Calgary,
2500 University Drive N.W., Calgary, Alta., Canada T2N 1N4
Received 1 December 2003; accepted 2 March 2004
Available online 24 March 2004
Abstract
Here we show that hearing loss associated with an impairment of speech recognition causes a decrease in neural temporal
resolution. In order to assess central auditory system changes in temporal resolution, we investigated the effect of an acute hearing
loss on the representation of a voice onset time (VOT) and gap-duration continuum in primary auditory cortex (AI) of the ketamine-
anesthetized cat. Multiple single-unit activity related to the presentation of a /ba/–/pa/ continuum – in which VOT was varied in 5-ms
step from 0 to 70 ms – was recorded from the same sites before and after an acoustic trauma using two 8-electrode arrays. We also
obtained data for gaps, of duration equal to the VOT, embedded in noise 5 ms after the onset. We specifically analyzed the
maximum firing rate (FRmax), related to the presentation of the vowel or trailing noise burst, as a function of VOT and gap
duration. The changes in FRmax for /ba/–/pa/ continuum as a function of VOT match the psychometric function for categorical
perception of /ba/–/pa/ modeled by a sigmoid function. An acoustic trauma made the sigmoid fitting functions shallower, and shifted
them toward higher values of VOT. The less steep fitting function may be a neural correlate of an impaired psychoacoustic temporal
resolution, because the ambiguity between /ba/ and /pa/ should consequently be increased. The present study is the first one in
showing an impairment of the temporal resolution of neurons in AI caused by an acute acoustic trauma.
� 2004 Elsevier B.V. All rights reserved.
Keywords: Noise trauma; Hearing loss; Voice onset time; Speech perception; Temporal resolution
1. Introduction
Animal vocalizations and speech in humans, are
characterized by distinct amplitude fluctuations. It hasbeen demonstrated that the auditory system makes ef-
fective use of these temporal cues for perception. In this
context, Shannon et al. (1995) showed that noise-bands
modulated with the temporal envelope of speech, pro-
ducing an acoustical signal with strongly degraded
spectral information but with preserved temporal
envelope cues, was sufficient to allow a correct identifi-
cation of consonants, vowels and words. Moreover,
* Corresponding author. Tel.: +1-403-220-5214; fax: +1-403-282-
8249.
E-mail address: [email protected] (J.J. Eggermont).
0378-5955/$ - see front matter � 2004 Elsevier B.V. All rights reserved.doi:10.1016/j.heares.2004.03.002
amplitude fluctuation can be used by the auditory sys-
tem in auditory scene analysis. Indeed, different fre-
quency components coherently modulated may be
interpreted as being related to the same source or au-ditory object (Bregman et al., 1990).
Amplitude fluctuations can be defined as periodic (as
in vowels) or aperiodic. The voice onset time (VOT), the
interval with aspiration noise between the consonant re-
lease and voicing onset, is an aperiodic amplitude fluc-
tuation. The difference between /ba/ and /pa/ phonemes,
for instance, depends to a large extent on the difference in
VOT (Kuhl andMiller, 1978). A VOT of 0ms is generallyassociated with the perception of /ba/, whereas a VOT of
25 ms and higher results in the perception of /pa/. The
perception changes abruptly from voiced to voiceless at
this boundary (Abramson and Lisker, 1970). Interest-
ingly, this boundary does not depend on a specific human
mail to: [email protected]
40 M. Tomita et al. / Hearing Research 193 (2004) 39–50
speech mechanism and was reported in chinchillas (Kuhl
and Miller, 1978) and monkeys (Morse and Snowdon,
1975; Sinnott and Adams, 1987) at approximately the
same value. The fact that the perceptual boundary was
reported in other mammals than humans suggests thatevolution may have taken advantage of specific proper-
ties of the central nervous system to design speech-sounds
(Kuhl and Miller, 1978). VOT boundaries also shift
with place of articulation and the boundaries for /da/–/ta/
and /ga/–/ka/ are higher than for the /ba/–/pa/ distinction.
Neural correlates of these perceptual boundaries have
been investigated in the auditory nerve of chinchillas
(Sinex and McDonald, 1988, 1989), inferior colliculus ofchinchillas (Chen et al., 1996) and in the auditory cortex
of monkey (Steinschneider et al., 1995, 2003) and cat
(Eggermont, 1995a,b). Steinschneider et al. (1995) ex-
amined multi-unit activity elicited by the consonant
vowel syllable /da/ and /ta/ that varied in VOT (0, 20, 40
and 60 ms). They found responses time-locked to stim-
ulus onset and to the onset of voicing with 40 ms VOT.
The response to voicing onset was markedly diminishedwith 20 ms and was similar to that evoked by /da/ with
0 ms VOT. These results were seen in 59% penetrations,
which display the ‘‘double-on’’ response pattern.
Eggermont (1995b) studied the representation of VOT
for a /ba/–/pa/ continuum in which VOT was varied in 5-
ms steps from 0 to 70 ms. He found that the mean value
for the minimum detectable VOT, which was repre-
sented in onset responses to both the voiceless andvoiced parts of the sound, was 46 ms in adult cat.
Comparing the results obtained in awake monkeys
(Steinschneider et al., 1995, 2003) and anesthetized cats
(Eggermont, 1995a,b) suggests that the minimum VOT
is little affected by anesthesia.
The role of aperiodic amplitude fluctuations in the
understanding of speech has also been studied by using
gap-detection paradigms (Schneider and Hamstra, 1999;Snell and Frisina, 2000; Snell et al., 2002). Eggermont
(1995a, 1999, 2000) focused on the cortical representa-
tion of gaps embedded in noise. For short leading noise-
burst duration (5 ms), he found mean values for the
minimum neural gap threshold (MNGT) around 35 ms,
and similar to those obtained with /ba/–/pa/ continuum.
Hearing loss and aging, conditions known as being
associated with an impairment of speech understanding(CHABA, 1998; Humes, 1991; Abel et al., 1990), are
both linked to a decrease in temporal resolution (Moore,
1985, 1993; Gordon-Salant and Fitzgibbons, 1993; Snell
et al., 2002; Mazelova et al., 2003). Thus, impairment in
temporal resolution, as measured in a gap-detection task
(Walton et al., 1998) or evoked potentials by a VOT
continuum (Tremblay et al., 2003), may be related to the
decline in the understanding of speech. It has beendemonstrated that gap-detection thresholds were im-
paired in older subjects compared to those in younger
subjects (Snell, 1997). Consistent with this finding,
Walton et al. (1998) reported an age-related alteration of
temporal resolution of neurons in inferior colliculus. It
is suggested that the decline in temporal resolution
during aging may involve, in addition to a deficit in the
function of the cochlea, a central component. Numerousstudies have shown that a hearing loss is followed by
changes in central inhibition (Rajan, 1998, 2001; Wang
et al., 2002; Nore~na et al., 2003). However, there is noelectrophysiological study in the literature addressing
the effect of hearing loss on the cortical representation of
VOT, i.e., on the temporal resolution of the auditory
system.
In the present study, we investigated the effect of anacute hearing loss on the representation of a voice onset
time continuum (/ba/–/pa/ phonemes) in primary audi-
tory cortex. Multiple single-unit (MU) activity related to
the presentation of the /ba/–/pa/ continuum – in which
VOT was varied in 5-ms step from 0 to 70 ms – was
recorded from the same recording sites before and after
an acoustic trauma. Moreover, MU activity related to
the presentation of gaps inserted 5 ms after the onset ofthe noise (‘‘early’’ gap) in a 1-s noise-burst was also
recorded. Gap duration was varied in 5-ms step from
0 to 70 ms. The goal of our study is to gain insight into
the effects of an acute hearing loss on the cortical rep-
resentation of VOT and gaps. More generally, our study
is aimed at pointing out potential central changes after a
hearing loss that are associated with a decline in speech
understanding in humans.
2. Method
2.1. Animal preparation
The care and the use of animals reported on in this
study were approved by the Life and EnvironmentalScience Animal Care Committee of the University of
Calgary (BI-2001-021). All cats were anesthetized with
administration of 25 mg/kg of ketamine (100 mg/ml)
injected intra-muscularly followed after approximately
10 min by 20 mg/kg of pentobarbital sodium (65 mg/ml)
intra-muscularly and 0.25 ml/kg body weight of a mix-
ture of 0.1 ml acepromazine (0.25 mg/ml) and 0.9 ml
of atropine methyl nitrate (5 mg/ml) subcutaneously.Lidocain (20 mg/ml) was injected subcutaneously and a
skin flap and muscle tissue overlying right temporal
bone was removed and the skull cleared. A large screw
was cemented upside down on the skull with dental
acrylic. Two 8 mm diameter holes were trephined over
the right temporal cortex so as to expose parts of pri-
mary auditory cortex. The holes were enlarged to expose
both anterior and posterior ectosylvian sulci if needed.The dura was left intact, and the brain was covered with
light mineral oil to prevent tissue drying. Then the cat
was placed in a sound-treated room on a vibration iso-
M. Tomita et al. / Hearing Research 193 (2004) 39–50 41
lation frame, and the head was secured with the screw.
Throughout the experiment, anesthesia at a level suffi-
cient to abolish pinna reflexes, was maintained with in-
tra-muscular injections of 2–5 mg/kg per hour of
ketamine, and additional acepromazine/atropine mix-ture was administered every 2 h. Body temperature was
maintained at 37 �C with use of a temperature-con-trolled heating pad. At the end of the experiment, the
animals were killed with an overdose of pentobarbital
sodium. During the recordings the ear contra-lateral
to the speaker was filled with an ear mold substance
(Dur-a-Sil, Insta Mold Products).
2.2. Peripheral threshold estimation
Prior to acute recordings and in one-third of the
cases after the end of experiment, approximately 6 h
after the exposure, peripheral hearing sensitivity was
determined from auditory brainstem response (ABR)
threshold. For this purpose, tone pips with frequencies
of 3, 4, 6, 12, 16, 24 and 32 kHz were presented at 10/sin an anechoic room from a speaker placed 45� fromthe midline and at 55 cm distance from the cat’s head.
The sound-treated room was made anechoic for fre-
quencies above 625 Hz by covering walls and ceiling
with acoustic wedges (Sonex 300) and by covering ex-posed parts of the vibration isolation frame, equipment
and floor with wedge material as well. Calibration and
monitoring of the sound field was done using a Br€ueland Kj€aer (type 4134) microphone placed above ani-mal’s head and facing the loud speaker. ABRs were
recorded, with needle electrodes in ipsi- and contralat-
eral muscles covering both mastoids, in response to
c-function shaped tone pips with an effective (50% frompeak) duration of 15 ms. In this recording montage, the
first negative–positive component representing the
compound action potential of the auditory nerve isfrequently the largest component. The signals were
amplified between 300 and 3000 Hz using a DAM 500
(World Precision Instruments) differential amplifier and
averaged with a Br€uel and Kj€aer (type 2034) dual signalanalyzer in the signal enhancement mode. Artifact re-
jection and local lidocaine infusion were used to avoid
contamination of the ABR by muscle action potentials.
At high intensity levels 20–50 averages sufficed but atnear threshold values 200 averages were obtained
and repeated once. Step size was 10 dB, except
around threshold where it was 5 dB. Threshold was
defined as the lowest intensity that yielded a repro-
ducible response.
2.3. Acoustic stimulus presentation
Stimuli were generated using MATLAB� and trans-
ferred to the DSP boards of a TDT (Tucker Davis
Technologies) sound delivery system. Acoustic stimuli
were presented in an anechoic room from a speaker
placed 45� from the midline 55 cm distance from thecat’s left ear. Characteristic frequency (CF) and tuning
properties of individual neuron were determined withc-shape envelope tone pips. These tone pips with a half-peak-amplitude duration of 15 ms and a c-function-shaped envelope, were presented at a rate of 1/s in a
pseudo-random frequency order at fixed intensity level.
The 81 different frequencies used were equally spaced
logarithmically between 625 Hz and 20 kHz (or between
1.25 and 40 kHz) so that 16 frequencies were present per
octave. Each recording session comprised of up to ninedifferent intensity series in 10 dB steps of these tone pip
stimuli.
After the frequency–tuning properties of the cells at
each electrode were determined, the /ba/–/pa/ continuum
with VOTs ranging from 0 to 70 ms in steps of 5 ms was
presented in random order as described previously
(Eggermont, 1995b). These phonemes were generated
with a parallel/cascade Klatt-synthesizer KLSYN88a,using a 20-kHz sampling frequency. The total duration
of the stimulus was 250 ms, regardless the duration of
the VOT, and the onset noise burst was 5 ms in duration
(leading noise burst). The dominant frequency ranges
for the vowel part were F 0 ¼ 120 Hz, F 1 ¼ 700 Hz, andF 2 ¼ 1200 Hz. The fundamental frequency started at120 Hz, remained at that value for 100 ms, and then
dropped from there to 100 Hz at the end of the vowel.F 1 started at 512 Hz and increased from 25 ms to700 Hz, F 2 started at 1019 Hz and increased from 25 msto 1200 Hz, and F 3 changed in the same time span from2153 to 2600 Hz. In order to match the CF of neurons to
the spectral content of the vowel, its spectrum was
transformed so that the upper edge of the F 2 band wasabove the CF of neurons. The phonemes were presented
once every 2 s. The only parameter that changed in thecontinuum was the VOT; formant transition durations
were not altered. Twenty repetitions were presented at
each VOT value so that the entire stimulus sequence
lasted 600 s.
Gaps ranging from 5 to 70 ms in duration were placed
in two positions in wideband noise bursts of 1 s in du-
ration that were presented once per 3 s in random order.
The first position, the ‘‘early gap,’’ started 5 ms after thenoise burst onset, and the second position, the ‘‘late
gap,’’ was positioned 500 ms after noise burst onset. Only
results for the early gap will be presented as they relate to
the VOT results (Eggermont, 1999). Each gap stimulus
was presented 15 times. The noise burst used consisted of
‘‘frozen’’ noise, i.e., the pseudo-random noise sequence
was the same for all conditions. These stimuli (a con-
tinuum of /ba/–/pa/ phonemes and a stimulus detectingearly and late gap) were presented at peak intensities of
65 or 75 dB SPL and the intensity level was same before
and after the acoustic trauma.
Fig. 1. Changes in frequency tuning of MU responses recorded in one
cat. The frequency–tuning curves of each recording site obtained be-
fore and after the acoustic trauma are shown in panels (a) and (b),
respectively. Panel (c) shows the lower envelopes of all frequency–
tuning curves in panels (a) and (b). The difference of the value esti-
mated from contour lines in panel (c) are plotted at 3, 4, 6, 8, 12, 16, 24
and 32 kHz in panel (d). ABR threshold shifts obtained 5 h after the
trauma are shown as dot line in panel (d).
42 M. Tomita et al. / Hearing Research 193 (2004) 39–50
2.4. Acoustic trauma
The acoustic trauma was induced by a 1-h exposure
to a pure-tone at the maximum output level. The trauma
tone frequency (TF) was set at 5 or 6 kHz. The soundwas presented by a high-power amplifier (Samson Servo
240) and loudspeaker (Yorkville 120 W) placed 75 cm
away from the cat’s head. Measured at cat’s head, the
trauma tone fundamental frequency had a level of 115–
120 dB SPL; whereas the second and third harmonics
had a level of 25 and 38 dB lower than that of funda-
mental frequency, respectively. The pure tone exposure
was administered about 8 h after the start of the prep-aration, following typically 4 h of recording at the se-
lected recording sites. The post-exposure threshold at
CF was generally obtained with c-shape envelope tonepips between 1 and 1.5 h after the end of the exposure,
and just prior to recording responses to the VOT and
gap stimuli.
2.5. Recording and spike separation procedure
Two arrays of eight electrodes (Frederic Haer Corp.)
each with impedances between 1 and 2 MX were used.The electrodes were arranged in a 4 · 2 configurationwith inter-electrode distance within rows and columns
equal to 0.5 mm. Each electrode array was oriented with
the long axis parallel to the midline in primary auditory
cortex located in majority between anterior and pos-terior ectosylbian sulci. The arrays were manually and
independently advanced using Narishige M101 hydrau-
lic microdrives. The signals were amplified 10,000 times
using a Frederic Haer Corp. HiZx8 set of amplifiers with
filter cut-off frequencies set at 300 Hz and 5 kHz. The
amplified signals were processed by a DataWave multi-
channel data acquisition system. Spike sorting was done
off line using a semi-automated procedure based onprincipal component analysis (Eggermont, 1990) im-
plemented in MATLAB. The spike times and wave-
forms were stored. The data presented in this paper
represent only well separated single units that, because
of their regular spike wave form, likely are dominantly
from pyramidal cells, thereby minimizing potential
contributions from thalamocortical afferents or inter-
neurons (Eggermont, 1996). For statistical purposes, theseparated single-unit spike trains were added again to
form a multi-unit spike train. We have previously shown
that the CFs of neurons recorded from the same elec-
trode are similar (Eggermont, 1996).
2.6. Data analysis
To assess frequency–tuning properties, the peaknumber of action potentials in the post-stimulus time
histogram (PSTH, 5 ms bins) calculated over the first
100 ms after c-tone presentation was estimated. The
peak counts for three adjacent frequencies were then
combined, in order to reduce variability, and divided by
number of stimuli and presented as a firing rate per
stimulus. This resulted in 27 frequency bins covering 5
octaves so that the final frequency resolution for deter-mining the CF was approximately 0.2 octaves. The re-
sults were calculated per stimulus intensity, and were
combined into an intensity–frequency–rate profile from
which tuning curves, rate-intensity functions and
iso-intensity rate-frequency contours could be derived
(Eggermont, 1996) using routines implemented in
MATLAB. The frequency–tuning curve was defined for
a firing rate at 25% of the maximum peak-firing rate.This was about 10–20% above the background firing-
rate, but as the latter was dependent on the level of
stimulus-induced suppression, the tuning curve criterion
based on a percentage of peak firing rate was preferred
over that based on increase over background activity. In
order to calculate threshold shifts with the acoustic
trauma for each cat, all tuning curves for each cat were
drawn as the contour lines at 25% from maximum re-sponse as function of a frequency before and after the
acoustic trauma (Fig. 1(a) and (b)). The lower envelope
of the set of frequency–tuning curves was traced
(Fig. 1(c)) and the difference of the values at the lowest
threshold between before and after the noise exposure
was estimated as the cortical threshold shift as a func-
tion of frequency (Fig. 1(d)).
M. Tomita et al. / Hearing Research 193 (2004) 39–50 43
Post-stimulus time histograms with a 5-ms binwidth
were used to represent the recordings for the /ba/–/pa/
continuum and early stimuli. From these PSTHs both
the peak latency and the spike count were calculated.
The minimum neural VOT (MNVOT) was defined asthe minimum VOT at which neural responses are time-
locked to both the burst onset and the onset of voicing.
Similarly, the minimum neural gap threshold (MNGT)
for ‘‘early’’ gap was defined as the minimum gap du-
ration at which neural responses are time-locked to
both the leading and the trailing noise burst. The re-
sponses related to the vowel and the trailing noise
burst were analyzed only when an onset response tothe leading noise burst was clearly visible. The
MNVOT and MNGT were obtained from inspection
of the dot displays and depended on the number of
stimulus presentation and the firing rate of the neu-
rons. We presented 20 repetition for each VOT dura-
tion of a /ba/–/pa/ continuum and required at least four
time-locked spikes per 20 presentations to the onset of
voicing for assigning the MNVOT. Similarly, in gapstimuli 15 repetition for each gap duration were rep-
resented and three time-locked spikes per 15 presenta-
tions to the trailing noise burst were required to assign
the MNGT.
Moreover, the maximum firing rate (FRmax) related
to the responses for the voicing or the trailing noise
burst for each VOT or gap duration were derived from
PSTHs. In order to avoid the increase in firing rate re-lated to a late rebound response, only spikes that oc-
curred within a time window of 30 ms starting at a time
equal to the peak latency of the leading noise burst plus
VOT or gap duration were included in the analysis.
All statistical analyses were performed using Statview
5�. Illustrations and figures were prepared with MAT-
LAB� and SigmaPlot�.
3. Results
Recordings were made from the right auditory cortex
in 13 cats. For a total of 46 recording sites out of 103
that showed reliable frequency–tuning curves before and
after the noise trauma, we recorded clear MU responses
to the VOT or gap stimuli approximately 1–1.5 h beforeand approximately 1.5–2 h after the acoustic trauma.
The consonant–vowel stimuli were frequency trans-
formed so that the upper edge of the F2 band was above
the neuron’s pre-trauma CF. The study presented here
includes data collected in the same animals as those in
two other studies. Namely, the effects of an acoustic
trauma on the neural responses related to frequency
response properties were reported in Nore~na et al.(2003). Moreover, the effects of an acoustic trauma on
spontaneous activity and neural synchrony were de-
scribed in Nore~na and Eggermont (2003).
3.1. Effects of the acoustic trauma on thresholds
As described in Section 2, the cortical threshold shift
after the trauma was estimated by comparing the CFs of
103 MU recordings before and after the trauma.Fig. 1(d) shows the threshold shift after the acoustic
trauma in one cat. The solid line indicates the estimated
hearing loss from cortical MU recordings and dotted
line indicates the ABR threshold. ABR thresholds were
measured before the trauma in all the cats studied.
However, ABR thresholds measured before and after
the acoustic trauma were obtained in only five cats and
were on average 40 dB for frequencies above the traumatone (reported in Nore~na et al., 2003). In these cats, theABR threshold shift was generally larger than cortical
threshold shift, however, the shape of the threshold shift
according to frequency was similar in both ABR and
cortical data. The reason for this underestimation of the
peripheral hearing loss by CF thresholds is due to cor-
tical reorganization.
As reported before, after an acoustic trauma un-masking of new excitatory connections occurs resulting
in considerable CF shifts with little threshold increase
(Nore~na et al., 2003). This is illustrated in Fig. 2showing a response area for a particular electrode site
just before the acoustic trauma induced with a 5 kHz
tone and about 3 h after the trauma. Shown are contour
lines for the percentage of maximum response in the
PSTH obtained in a 5 ms bin in the time window of10–60 ms following tone pip onset. Contour lines are
shown for 75%, 50% and 35%, whereby the lower con-
tour is considered here as the neuron’s frequency–tuning
curve. The pre-trauma tuning curve (top) has a CF
around 10 kHz and threshold below 15 dB SPL (the
lowest sound level used). At 3 h 40 min after the expo-
sure (bottom), the CF is now about 7 kHz and the
threshold about 25 dB SPL. The response area above8 kHz that was initially present has completely disap-
peared and a new response area between 4 and 8 kHz,
and thus largely outside the original response area,
emerged. Tuning curves were also obtained at regular
intervals spanning the 4.5-h time range between those
recordings but are not shown here (for details see
Nore~na et al., 2003). Thus, the estimated hearing lossfrom cortical CFs will always be less than that estimatedfrom ABR thresholds.
Fig. 3(a) shows the ABR threshold shift in five cats as
a function of the difference between the frequency at
which ABR thresholds have been measured and the TF.
One notes that ABR threshold shift is around 40 dB in
average above the TF. Fig. 3(b) shows the cortical CF-
threshold shifts, for the recording sites that yielded re-
sponses to the /ba/–/pa/ and gap stimuli, as a function ofthe difference between the pre-trauma CF and the TF.
The cortical threshold shift is around 20 dB above the
TF and is larger for the frequency band above TF than
Fig. 3. Threshold shift after the acoustic trauma. Panel (a) shows pe-
ripheral threshold shift based on auditory brainstem response (ABR)
in five cats. Panel (b) shows the cortical threshold shift at the char-
acteristic frequency (CF) as a function of the difference between the
pre-exposure CF and trauma tone frequency (TF), respectively. The
black solid line in panel (a) shows the averaged peripheral threshold
shift. The black line in panel (b) shows the average CF-threshold shift
for those units that showed responses to the VOT or gap stimuli.Fig. 2. Pre- and post-acoustic trauma frequency response areas. The
contour lines separate response at 75% of maximum (black), 50% of
maximum (gray) and 35% of maximum. The latter contour line is
considered as the frequency–tuning curve. One observes that the post-
trauma tuning curve barely overlaps with the pre-trauma tuning curve.
44 M. Tomita et al. / Hearing Research 193 (2004) 39–50
below TF. The average threshold elevation is 13.1 dB for
MUs with CF below and above TF and significantly
different from 0 (tð43Þ ¼ 5:287, p < 0:001). As notedabove, these threshold shifts were calculated at the CFs,
which typically changed dramatically after the noise
trauma and thus do not represent the peripheral hearingloss at particular frequencies. The increase in the
thresholds at CF in the subset of 46 recordings analyzed
here was nearly identical to that in the overall set of 124
neurons analyzed previously (Nore~na et al., 2003).
3.2. Individual example
Fig. 4 shows neural responses obtained at the samerecording site for presentation of the /ba/–/pa/ contin-
uum ((a)–(c)) and the ‘‘early’’ gap stimuli ((d)–(f)) (see
Section 2). Left-hand panels ((a) and (d)) show dot
displays: each dot corresponds to a spike. The dot dis-
plays are organized vertically according to gap duration
or VOT and horizontally for time since leading noise
burst onset. Middle panels ((b) and (e)) represents the
PSTHs (the bin size is 5 ms) of the data shown in panels
(a) and (d), respectively. The oblique dotted lines indi-cate the time windows (30-ms duration) in which the
FRmax, for each gap duration or VOT, is derived.
Right-hand panels ((c) and (f)) show the FRmax, for
each gap duration or VOT, related to the presentation of
the trailing noise or the vowel.
One notes first that the responses related to the pre-
sentation of the /ba/–/pa/ continuum are similar to those
related to the presentation of the ‘‘early’’ gap stimuli. Inboth cases, neural responses are evoked at the onset of
the stimuli. Moreover, neurons are activated by the
trailing stimulus only if it is presented at more than
Fig. 4. A comparison of the responses to a /ba/–/pa/ continuum (a)–(c) and early gap (d)–(f) conditions from the same recording site. Dot displays
(left column) and PSTH (middle column) are organized vertically according to VOT or gap duration and horizontally for time since the onset of the
leading noise burst. Time windows for evaluation of the PSTHs to the trailing stimulus are selected (between dot lines) according to VOT or gap
duration and the latency of peak response for the leading noise burst. The maximum firing rate in a 5 ms bin (FRmax) in these time windows is called
the peak responses to the vowel or trailing noise burst, and plotted as a function of VOT or gap duration (right column). The fit curves in panels (c)
and (f) are calculated according to Eq. (1): Y ¼ y0 þ a=ð1þ ekðX�x50ÞÞ (see text).
M. Tomita et al. / Hearing Research 193 (2004) 39–50 45
40 ms after the leading stimulus. Namely, the MNVOT
and MNGT have similar values, around 40 ms. In thisexample, the background firing rate is very low; neurons
do not respond to the second stimulus (vowel or trailing
noise) for VOT below 40 ms.
The data were fitted by a sigmoid function
Y ¼ y0 þ a 1��
þ ekðX�x50Þ�; ð1Þ
where Y is the FRmax, X is VOT or gap duration in ms,x50 is the VOT or gap duration corresponding to the
50% point of the function, y0 is the background activity,a is the difference between maximum and minimum ofthe sigmoid function, and k is a factor defining the slopeof the function. The middle (50%) points between min-
imum value and maximum value of FRmax from the
fitting curves to obtained data (panels (c) and (f)) are
very close to the value of the minimum VOT or gap
duration compared to that derived from visual inspec-
tion in the left (dot displays) and middle panels (PSTH).Namely, MNVOT as estimated from x50 is 42 ms for
/ba/–/pa/ stimulus continuum and the MNGT is esti-
mated at 37 ms.
3.3. Group data for the /ba/–/pa/ continuum and the
‘‘early’’ gap condition
As shown in Fig. 3, the average CF-threshold shiftis larger for the frequency band above TF than that
below TF. Consequently, we divided the data of the MU
recordings into two groups based on the CF and TF.
However, we found no significantly difference (with re-spect to onset response, FRmax, MNVOT and MNGT)
between the groups with CF above and below TF, and
thus pooled the data into a single group. All the fol-
lowing results then concern the entire group.
Fig. 5 shows the distribution of MNVOT and MNGT
values before and after the acoustic trauma. One notes
that the distribution in MNVOT and MNGT values
presents a peak around 40 ms before the acoustic trau-ma. After the acoustic trauma, the distribution is more
uniform and the number of MUs with MNVOT and
MNGT above 40 ms is increased. The averaged
MNVOT is 31 ms (SD¼ 13 ms) and 35 ms (SD¼ 17 ms)before and after the acoustic trauma, respectively. The
averaged MNGT is 36 ms (SD¼ 17 ms) and 38 ms(SD¼ 18 ms) before and after the acoustic trauma, re-spectively. The right-hand panels show the distributionin changes of MNVOT and MNGT with the acoustic
trauma. The number of MUs with difference of
MNVOT and MNGT above 0 ms is larger than that
below 0 ms, although the increase of MNVOT and
MNGT with the acoustic trauma was not significantly
different using one sample t-test hypothesized mean of
zero (/ba/–/pa/: p ¼ 0:11; early gap: p ¼ 0:17).Fig. 6 shows the changes in MNVOT and MNGT as
a function of the threshold shift at CF for the /ba/–/pa/
continuum (a) and the ‘‘early’’ gap condition (c). And
panels (b) and (d) show the changes in MNVOT and
Fig. 6. Differences of MNVOT ((a) and (b)) and MNGT ((c) and (d))
before and after the acoustic trauma as a function of threshold shift at
CF (left column) and as a function of the difference between CF and
TF (right column).
Fig. 5. Distribution of MNVOT (top row) and MNGT (bottom row) values for MU recording before (left column) and after (middle
column) acoustic trauma. Note that modal values of MNVOT and MNGT are around 40 ms. After the trauma, the number of MNVOT and
MNGT values of more than 40 ms is increased. Right column shows the difference of MNVOT and MNGT between before and after
acoustic trauma. Note that the number of MUs with an increase of MNVOT and MNGT after the acoustic trauma is larger than that
showing a decrease.
46 M. Tomita et al. / Hearing Research 193 (2004) 39–50
MNGT as a function of the difference between the pre-
trauma CF and the TF for the /ba/–/pa/ continuum (b)
and the ‘‘early’’ gap condition (d). One observes a ten-
dency for the MNVOT or the MNGT to be dependent
on threshold shift, but this was only significant for
MNVOT (R2 ¼ 0:206, p ¼ 0:013). Changes in MNVOTor MNGT were not significantly correlated with the
difference between the pre-trauma CF and TF.
Fig. 7 shows the averaged PSTHs in response to the
leading noise burst. We averaged the PSTHs obtained
fromMU recordings of stimulus representation with 25–
45 ms of VOT or gap duration. For each bin, the
changes in PSTH (before vs. after the trauma) were
statistically tested (paired t test). There was no signifi-cant difference between firing rates before and after the
acoustic trauma in both the /ba/–/pa/ continuum and
‘‘early’’ gap conditions.
Fig. 8 shows the average of the normalized FRmax as
a function of VOT or (‘‘early’’) gap duration. The nor-
malized FRmax were obtained by dividing the FRmax
obtained at each VOT- or gap-duration by the highest
FRmax to the trailing stimuli over all VOTs or gapdurations. As shown for individual recordings in Fig. 4,
the largest FRmax were usually obtained for highest
values of VOT or gap duration, namely around 70 ms.
An ANOVA showed that the data were very well fitted
by a sigmoid function (Eq. (1)); pre-trauma /ba/–/pa/:
R2 ¼ 0:96, p < 0:001, post-trauma /ba/–/pa/: R2 ¼ 0:98,p < 0:001, pre-trauma early gap: R2 ¼ 0:97, p < 0:001,and post-trauma early gap: R2 ¼ 0:97, p < 0:001.
Fig. 7. Averaged PSTHs for leading noise burst before and after
acoustic trauma in /ba/–/pa/ continuum and early gap condition (±SE).
Binwidth is 5 ms. Note that PSTH after the trauma is similar to the
PSTH before the trauma for the /ba/–/pa/ continuum and early gap
conditions.
Fig. 8. Average normalized maximum firing rate for the vowel (top)
and trailing noise burst after the early gap (bottom) obtained before
(filled circles) and after (open circles) the acoustic trauma (±SE). The
sigmoid curves shown provide the best statistical fit to the data. Note
that fitted curves for both the /ba/–/pa/ continuum and the early gap
condition are shifted toward longer VOT or gap duration.
M. Tomita et al. / Hearing Research 193 (2004) 39–50 47
One notices that the shape of the fitting curves before
the trauma is similar for /ba/–/pa/ and ‘‘early’’ gap
stimuli. Below a VOT or gap duration of 20 ms, the
FRmax is low and constant and corresponds to thebackground activity (the trailing stimulus does not
evoke stimulus-locked responses). Between 30 and
50 ms, the FRmax increases abruptly as a function of
VOT and gap duration. Finally, the FRmax reaches a
plateau from values of VOT or gap duration around 50
ms. The middle point (x50: the 50% detectable point)
from minimum to maximum value of FRmax gives
similar values for MNVOT and MNGT, namely 35 and38 ms, respectively.
After the trauma, the shape of the fitting curves for
both /ba/–/pa/ continuum and ‘‘early’’ gap condition is
changed. The most striking difference compared to the
pre-trauma condition is that the fitting curves are shifted
toward longer values of VOT or gap duration for both
conditions. And the slope of the fitting function is also
less steep for /ba/–/pa/ continuum. Indeed, slope valuesderived from the fitted data were 0.017 and 0.014 for
/ba/–/pa/ continuum in the pre and post-trauma condi-
tion, respectively. For the gap condition the slope stayed
the same at 0.019. As a consequence, the estimated
MNVOT and MNGT from the fit functions are in-
creased after the trauma compared to the pre-trauma
condition: MNVOT and MNGT derived from the fitted
data for post-trauma condition were 46 and 51 ms, re-spectively. Moreover, FRmax does not reach a plateau
at high values of VOT or gap duration after the trauma.
Again, after the trauma, the shape of the fitting curves
was similar between /ba/–/pa/ and ‘‘early’’ gap stimuli.
As we described above, the shape of the fitting curve
to data obtained before the trauma consists of three
parts divided by VOT or gap duration, a short VOT or
gap duration part with mostly background activity, amoderate duration part with abrupt changes of FRmax
and a long duration plateau. In order to estimate the
change of these FRmax values with the acoustic trauma,
we divided the data into three groups by VOT or gap
duration, namely short (0–20 ms) duration group, bor-
der (25–45 ms) duration group around MNVOT or
MNGT and long (50–70 ms) duration group. The
change of FRmax was statistically tested using a re-peated measures ANOVA with repeated factor of time
of recording (before and after the acoustic trauma). For
/ba/–/pa/ continuum, there was a significant decrease of
FRmax with the acoustic trauma for the border group
(F ¼ 9:829, p ¼ 0:002) and no significant change in theother two groups. For the early gap condition, the
FRmax in the short duration group and border group
48 M. Tomita et al. / Hearing Research 193 (2004) 39–50
were also significantly decreased with the acoustic
trauma (F ¼ 12:48, p ¼ 0:0005, F ¼ 27:18, p < 0:0001,respectively).
4. Discussion
The results of the present study can be summarized as
follows. There were no significant differences in the
mean MNVOT and MNGT to the /ba/–/pa/ and gap-in-
noise stimuli. The mean MNVOT and MNGT values as
estimated from the dot-displays were not significantly
affected by the trauma. However, the acoustic traumasignificantly shifted the sigmoid functions used to fit the
average data toward higher values of VOT or gap du-
ration, and the VOT fit curve became less steep. Before
the trauma, the mean 50% points of the fit curves were
35 and 38 ms for /ba/–/pa/ and gap stimuli, respectively.
After the trauma, the mean 50% points were in-
creased to 46 and 51 ms for /ba/–/pa/ and gap stimuli,
respectively.For the pre-trauma condition, our results are the
same as those from the previous studies of Eggermont
(1995a,b, 1999): MNGT and MNVOT presented similar
mean values around 35–40 ms. Moreover, these results
have been corroborated by another study where authors
have recorded auditory evoked potentials elicited by
stop consonant–vowel syllables directly from Heschl’s
gyrus and temporal gyrus in awake humans (Steins-chneider et al., 1999). This once more underlines the
minor effect that anesthesia has on our findings. Fur-
thermore, the recordings of the gap and /ba/–/pa/ stimuli
were at most 4 h apart, the earlier recording typically
occurring at least 5 h after the pentobarbital injection.
At this time one does not expect any change resulting
from lingering barbiturate effects. We have previously
reported about the lack of changes in temporal responseproperties as a function of time after anesthesia onset
(Eggermont, 1991), and we have extensive recordings of
VOT studies in animals (Tomita et al., unpublished)
with a permanent noise trauma where we did not ob-
serve any changes that could be attributed to time after
the single pentobarbital injection at the start of the ex-
periment. Thus we conclude that the changes that we
observe are due to the intervening noise trauma.Syllables with a relatively long VOT – above 30 ms,
were associated with a clear ‘‘double-onset’’ response,
namely a neural response time-locked to the consonant
release and one to voicing onset. On the other hand,
syllables with a VOT below 30 ms generally elicited a
reduced response – if any – to voicing onset. The latter
results suggest ‘‘that the perceptual category boundary
could reflect an average of the temporal activity patternsin auditory cortex (AI) that showed a double-on re-
sponse’’ (Eggermont and Ponton, 2002). In addition, the
fact that noise stimuli and different syllables are asso-
ciated with similar MNGT or MNVOT around 35 ms in
cortex suggests that these values reflect intrinsic cortical
neural properties and are not directly related to per-
ceptual boundaries. These points are developed below.
4.1. Neurophysiological mechanisms
Eggermont (1999, 2000) argued that cortical post-
activation suppression might be the main neurophysio-
logical mechanism accounting for the MNVOT and
MNGT. Post-activation suppression may result from
after hyperpolarization as well as from feed-back or
feed-forward inhibition (Eggermont, 2000). As men-tioned by Eggermont (1999), inhibition resulting from
the involvement of GABAA receptor activation is diffi-
cult to distinguish from after hyperpolarization. They
have approximately the same time constants and both
start a few ms after the excitatory on-response of the
neurons. Regardless the mechanism, post-activation
suppression limits the temporal resolution of the audi-
tory system in preventing the occurrence of locked re-sponses to the trailing or voicing stimulus when gap
duration or VOT are short. As modeled by Eggermont
(2000), the post-activation suppression is expected to be
prominent immediately after the onset of the leading
stimulus or consonant release. This hypothesis is con-
sistent with electrophysiological data showing that
MNGT decreases as a function of leading stimulus du-
ration (Eggermont, 2000).Post-activation suppression, in constraining temporal
neural responses, may then be responsible for the be-
havioral performances, namely for the categorical per-
ceptual boundary of a speech continuum, for instance of
/ba/–/pa/ phonemes. In this context, it is noted that the
perceptual boundary – around 25 ms (Kuhl and Miller,
1978) – is about 10 ms shorter the middle point of our
normal data fitted with a sigmoid function (Fig. 8). Thisdifference could be due to the anesthesia used as it in-
creases inhibition and after hyperpolarization effects.
Moreover, gap thresholds measured by Phillips et al.
(1997) corroborate this. Namely, in a condition where
the silent gap was marked by a wide-band noise (leading
stimulus, intended to simulate a consonantal burst) and
a low frequency narrow-band noise (trailing stimulus,
intended to simulate the vowel), gap thresholds werefound to match MNGTs found in Eggermont’s (1999,
2000) and in the present study. In addition, perceptual
gap thresholds and MNGT present similar values as a
function of leading burst duration (Eggermont, 2000).
However, the broad distribution of minimum gap and
VOT thresholds also suggests that the perceptual deci-
sion is likely made on basis of the population firing
activity as reflected in Fig. 8 and not on the distributionof the threshold values. In this respect, the activity in AI
likely only provides a basis on which to set perceptual
boundaries. If the activity produced by the consonant–
M. Tomita et al. / Hearing Research 193 (2004) 39–50 49
vowel phonemes in AI is affected so will be ability to
discriminate between them.
4.2. Neural changes induced by the acoustic trauma
We have shown that the acoustic trauma impairs
temporal resolution in AI: the sigmoidal fitting function
shifted toward higher values of gap duration or VOT.
Specifically, the middle points derived from these func-
tions increased by about 10 ms (Fig. 8). Because the
acoustic trauma induced a hearing loss (Figs. 1 and 3), it
is important to separate the potential effect of the ef-
fective intensity level of stimulation on the neural re-sponses from that of changes in temporal acuity. A
decrease in the effective intensity level may have induced
the impairment in temporal resolution we observed. For
instance, Fig. 6 shows that the increase in MNVOT and
MNGT is slightly dependent on the threshold shift.
However, the unaffected FRmax values for large VOTs
suggest that the changes in temporal resolution of cor-
tical neurons after the acoustic trauma are not related tothe effective intensity level. Fig. 8 shows that the FRmax
(for gap durations or VOTs above 55 ms) is not de-
creased after the trauma; to the contrary, the largest
FRmax values are even increased. This result suggests
that, on average, neurons have roughly conserved the
same responsiveness to the trailing stimulus. Eggermont
(1995b, 1999) showed that MNGT or MNVOT could
depend on the strength of the onset response related tothe presentation of the leading stimulus or the conso-
nant release. A decrease in the onset response related to
the onset of the leading stimulus was associated with a
decrease in MNGT and MNVOT. A decrease in effec-
tive level due to hearing loss may have decreased the
neural responsiveness to the leading stimulus and con-
sequently decreased the MNGT and MNVOT. This
explanation is not corroborated by our results: the av-eraged onset responses related to the leading stimulus
are not changed after the acoustic trauma compared to
before (Fig. 7). This is likely due to the elevated sound
level (65 or 75 dB SPL) used in these experiments.
In our previous paper (Nore~na et al., 2003), weshowed that neural activity was more strongly sup-
pressed following the presentation of the tone burst for
the post-noise trauma condition than for the pre-traumacondition. This suggests that the acoustic trauma may
result in an increase of post-activation suppression, and
hence longer MNVOT and MNGT values.
4.3. Potential perceptual correlates of the central changes
that follow an acoustic trauma
Glasberg et al. (1987) showed that hearing loss wasassociated with a slower rate of recovery from forward
masking. The authors suggested that larger gap thresh-
olds in hearing-impaired subjects might be associated
with this. This result is consistent with the hypothesis,
suggested by our results (described above), that hearing
loss increases the strength of the post-activation sup-
pression. Namely, in preventing the occurrence of the
second ‘‘on-response’’ related to the presentation of thetrailing stimulus or voicing, the increased post-activa-
tion suppression could alter the temporal resolution.
We showed that the acoustic trauma changed the slope
of the fitting function (Fig. 8). Indeed, for a /ba/–/pa/
continuum, the slopes were shallower in the post-trauma
condition. Then, if the presence of the VOT in the /ba/–
/pa/ continuum is actually encoded through a population
average of the FRmax related to the presentation of thetrailing stimulus, the ambiguity between /ba/ and /pa/
should consequently be increased. It is important to note
that the slope derived from the psychometric function
(Kuhl and Miller, 1978; Strouse et al., 1998) defines the
accuracy of the categorical perception or, in other words,
the ambiguity between the two extremes. It is indispens-
able for accurate coding of a signal-like speech to mini-
mize these ambiguities. That may be the reason why theslope in the psychometric function is relatively steep. The
decreased slopes of the fitting function of our data in
the post-trauma conditionmay be a neural correlate of an
impaired psychoacoustic temporal resolution. In addi-
tion, in low signal-to-noise ratio conditions, this decrease
in temporal resolutionmay even aggravate the perceptual
performances.
This study shows for the first time that a hearing lossinduced by an acute acoustic trauma decreases the
temporal resolution of cortical neurons, both in the re-
gion of the hearing loss and up to 1.5 octave below it.
We suggest that this impairment in the ability to code
VOT might be related to an increase in the post-acti-
vation suppression.
Acknowledgements
This work was supported by the Alberta Heritage
Foundation for Medical Research, the National Sci-
ences and Engineering Research Council, the Canadian
Language and Literacy Research Network, and the
Campbell McLaurin Chair for Hearing Deficiencies.
References
Abel, S.M., Krever, E.M., Alberti, P.W., 1990. Auditory detection,
discrimination and speech processing in ageing, noise-sensitive and
hearing-impaired listeners. Scand. Audiol. 19, 43–54.
Abramson, A., Lisker, L., 1970. Discrimination along the voicing
continuum: cross-language tests. In: Proceedings of the 6th
International Congress of Phonetic Science, Prague, 1967. Aca-
demic Press, Prague, pp. 569–573.
50 M. Tomita et al. / Hearing Research 193 (2004) 39–50
Bregman, A.S., Levitan, R., Liao, C., 1990. Fusion of auditory
components: effects of the frequency of amplitude modulation.
Percept. Psychophys. 47, 68–73.
Chen, G.D., Nuding, S.C., Narayan, S.S., Sinex, D.G., 1996.
Responses of single neurons in the chinchilla inferior coliculus to
consonant–vowel syllables differing in voice-onset time. Aud.
Neurosci. 3, 179–198.
Committee on Hearing, Bioacoustics, and Biomechanics, Commission
on Behavioral and Social Sciences and Education, National
Research Council (CHABA) 1998. Speech understanding and
aging. Working Group on Speech Understanding and Aging.
J. Acoust. Soc. Am. 83, 859–895.
Eggermont, J.J., 1990. The Correlative Brain: Theory and Experience
in Neural Interaction. Springer, Berlin.
Eggermont, J.J., 1991. Rate and synchronization measures of
periodicity coding in cat primary auditory cortex. Hear. Res.
56, 153–167.
Eggermont, J.J., 1995a. Neural correlates of gap detection and
auditory fusion in cat auditory cortex. Neuroreport 6, 1645–1648.
Eggermont, J.J., 1995b. Representation of a voice onset time contin-
uum in primary auditory cortex of the cat. J. Acoust. Soc. Am. 98,
911–920.
Eggermont, J.J., 1996. How homogeneous is cat primary cortex.
Evidence from simultaneous single-unit recordings. Aud. Neurosci.
2, 76–96.
Eggermont, J.J., 1999. Neural correlates of gap detection in three
auditory cortical fields in the cat. J. Neurophysiol. 81, 2570–2581.
Eggermont, J.J., 2000. Neural responses in primary auditory cortex
mimic psychophysical, across-frequency-channel, gap-detection
thresholds. J. Neurophysiol. 84, 1453–1463.
Eggermont, J.J., Ponton, C.W., 2002. The neurophysiology of audi-
tory perception: from single units to evoked potentials. Audiol.
Neurootol. 7, 71–99.
Glasberg, B.R., Moore, B.C., Bacon, S.P., 1987. Gap detection
and masking in hearing-impaired and normal-hearing subjects.
J. Acoust. Soc. Am. 81, 1546–1556.
Gordon-Salant, S., Fitzgibbons, P.J., 1993. Temporal factors
and speech recognition performance in young and elderly listeners.
J. Speech Hear. Res. 36, 1276–1285.
Humes, L.E., 1991. Understanding the speech-understanding problems
of the hearing impaired. J. Am. Acad. Audiol. 2, 59–69.
Kuhl, P.K., Miller, J.D., 1978. Speech perception by the chinchilla:
identification function for synthetic VOT stimuli. J. Acoust. Soc.
Am. 63, 905–917.
Mazelova, J., Popelar, J., Syka, J., 2003. Auditory function in presby-
cusis: peripheral vs. central changes. Exp. Gerontol. 38, 87–94.
Moore, B.C., 1985. Frequency selectivity and temporal resolution in
normal and hearing-impaired listeners. Br. J. Audiol. 19, 189–201.
Moore, B.C., 1993. Temporal analysis in normal and impaired hearing.
Ann. N.Y. Acad. Sci. 682, 119–136.
Morse, P.A., Snowdon, C.T., 1975. An investigation of categorical
speech discrimination by rhesus monkeys. Percept. Psychophys. 17,
9–16.
Nore~na, A.J., Eggermont, J.J., 2003. Changes in spontaneous neural
activity immediately after an acoustic trauma: implications for
neural correlates of tinnitus. Hear. Res. 183, 137–153.
Nore~na, A.J., Tomita, M., Eggermont, J.J., 2003. Neural changes in
cat auditory cortex after a transient pure-tone trauma. J. Neuro-
physiol. 90, 2387–2401.
Phillips, D.P., Taylor, T.L., Hall, S.E., Carr, M.M., Mossop, J.E.,
1997. Detection of silent intervals between noises activating
different perceptual channels: some properties of ‘‘central audi-
tory’’ gap detection. J. Acoust. Soc. Am. 101, 3694–3705.
Rajan, R., 1998. Receptor organ damage causes loss of cortical
surround inhibition without topographic map plasticity. Nat.
Neurosci. 1, 138–143.
Rajan, R., 2001. Plasticity of excitation and inhibition in the receptive
field of primary auditory cortical neurons after limited receptor
organ damage. Cereb. Cortex 11, 171–182.
Schneider, B.A., Hamstra, S.J., 1999. Gap detection thresholds as a
function of tonal duration for younger and older listeners.
J. Acoust. Soc. Am. 106, 371–380.
Shannon, R.V., Zeng, F.G., Kamath, V., Wygonski, J., Ekelid, M.,
1995. Speech recognition with primarily temporal cues. Science 270,
303–304.
Sinnott, J.M., Adams, F.S., 1987. Differences in human and monkey
sensitivity to acoustic cues underlying voicing contrasts. J. Acoust.
Soc. Am. 82, 1539–1547.
Sinex, D.G., McDonald, L.P., 1988. Average discharge rate represen-
tation of voice onset time in the chinchilla auditory nerve.
J. Acoust. Soc. Am. 83, 1817–1827.
Sinex, D.G., McDonald, L.P., 1989. Synchronized discharge rate
representation of voice-onset time in the chinchilla auditory nerve.
J. Acoust. Soc. Am. 85, 1995–2004.
Snell, K.B., 1997. Age-related changes in temporal gap detection.
J. Acoust. Soc. Am. 101, 2214–2220.
Snell, K.B, Frisina, D.R., 2000. Relationships among age-related
differences in gap detection and word recognition. J. Acoust. Soc.
Am. 107, 1615–1626.
Snell, K.B., Mapes, F.M., Hickman, E.D., Frisina, D.R., 2002. Word
recognition in competing babble and the effects of age, temporal
processing, and absolute sensitivity. J. Acoust. Soc. Am. 112, 720–
727.
Steinschneider, M., Fishman, Y.I., Arezzo, J.C., 2003. Representation
of the voice onset time (VOT) speech parameter in population
responses within primary auditory cortex of the awake monkey.
J. Acoust. Soc. Am. 114, 307–321.
Steinschneider, M., Schroeder, C.E., Arezzo, J.C., Vaughan Jr., H.G.,
1995. Physiologic correlates of the voice onset time boundary in
primary auditory cortex (A1) of the awake monkey: temporal
response patterns. Brain Lang. 48, 326–340.
Steinschneider, M., Volkov, I.O., Noh, M.D., Garell, P.C.,
Howard 3rd, M.A, 1999. Temporal encoding of the voice
onset time phonetic parameter by field potentials recorded
directly from human auditory cortex. J. Neurophysiol. 82,
2346–2357.
Strouse, A., Ashmead, D.H., Ohde, R.N., Grantham, D.W., 1998.
Temporal processing in the aging auditory system. J. Acoust. Soc.
Am. 104, 2385–2399.
Tremblay, K.L., Piskosz, M., Souza, P., 2003. Effects of age and age-
related hearing loss on the neural representation of speech cues.
Clin. Neurophysiol. 114, 1332–1343.
Walton, J.P., Frisina, R.D., O’Neill, W.E., 1998. Age-related alter-
ation in processing of temporal sound features in the auditory
midbrain of the CBA mouse. J. Neurosci. 18, 2764–2776.
Wang, J., Ding, D., Salvi, R.J., 2002. Functional reorganization in
chinchilla inferior colliculus associated with chronic and acute
cochlear damage. Hear. Res. 168, 238–249.
Effects of an acute acoustic trauma on the representation of a voice onset time continuum in cat primary auditory cortexIntroductionMethodAnimal preparationPeripheral threshold estimationAcoustic stimulus presentationAcoustic traumaRecording and spike separation procedureData analysis
ResultsEffects of the acoustic trauma on thresholdsIndividual exampleGroup data for the /ba/-/pa/ continuum and the ``early'' gap condition
DiscussionNeurophysiological mechanismsNeural changes induced by the acoustic traumaPotential perceptual correlates of the central changes that follow an acoustic trauma
AcknowledgementsReferences
Top Related