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Complex sound analysis (frequency resolution, filtering and spectral integration) by single units of the inferior colliculus of the cat
139
Brain Research Reviews, 13 (1988) 139-163 Elsevier BRR 90080
Complex sound analysis (frequency resolution, filtering and spectral integration) by single units of the inferior colliculus of the cat Giinter Ehret’ and Michael M. Merzenich2 ‘Fakultii:
fiir Biologie,
Universitiit Konstanz, Konstanz (F. R. G.) and ‘Coleman Laboratory, Department of Otolaryngology, University of California, San Francisco, CA 94143 (U.S.A.) (Accepted
Key words: Cat; Complex
19 January
1988)
sound analysis; Critical band; Filtering; Frequency Lateral inhibition; Masking; Spectral analysis
resolution;
Inferior
colliculus;
CONTENTS Introduction
.............................................................................................................................................
140
................................................................................................................................ Materials and Methods 2.1. Animals and surgery ............................................................................................................................. ............................................................................................................................. 2.2. Stimulus generation ....................................................................................................................... 2.3. Experimental procedure 2.4. Data analysis ......................................................................................................................................
140 140 141 141 142
Results .................................................................................................................................................... 3.1. Response thresholds andspontaneous activity ............................................................................................ .............................................................................................. 3.2. CF-tone responses, rate-intensity functions 3.3. Tuning curves ..................................................................................................................................... 3.4. Spectral integration bandwidths (effective bandwidths, CR-bands, CB,,,, CB,) ............................................. and CF .............................................................................................. 3.4.1. Relation between bandwidths and sound intensity 3.4.2. Relation between bandwidths .............................................................................. 3.4.3. Symmetry of critical bands ............................................................................................................ and other neural characteristics ...................................................................................... 3.4.4. Bandwidths
143 143 145 147 148 149 150 151 152
................................................................................................................................................ Discussion 4.1. General aspects ................................................................................................................................... 4.2. Principal findings ................................................................................................................................. 4.3. Frequency dependence of frequency resolution ........................................................................................... 4.4. Relationships among measures of frequency resolution in the ICC ................................................................... 4.4.1. CR-bands ................................................................................................................................. 4.4.2. Effective bandwidths ................................................................................................................... 4.4.3. Tuning curves ............................................................................................................................ 4.4.4. Critical bands ............................................................................................................................ 4.5. Symmetry of critical bands ..................................................................................................................... 4.6. Intensity dependence of bandwidths of spectral integration ............................................................................ ................................................................................................................................. 4.6.1. CR-bands 4.6.2. Critical bands ............................................................................................................................ 4.7. Mechanisms of frequency resolution and of critical bands ...............................................................................
153 153 153 153 154 155 156 156 157 157 157 157 158 159
_.
5. Summary
_. _.
Acknowledgements References
Correspondence:
0165-0173/88/$03.50
_. _.
_,_.
0
_. _.
_. _._.
G. Ehret,
Fakultat
1988 Elsevier
fur Biologie,
Universitat
Science Publishers
Konstanz,
B.V. (Biomedical
Postfach
Division)
160
5560, D-7750 Konstanz,
_.
F.R.G.
_,
_.
160 160
140 1. INTRODUCTION
nents (formants of vowels) in background noise measured by spike rates of auditory nerve fibers is de-
vocalizations and human speech have complex frequency spectra. The frequency-place transfor-
graded at higher sound intensities”~‘” although a spike-rate code seems to be sufficient for encoding tone responses in background noise5,93.
mations in the cochlea and cochlear filtering processes resolve the frequency spectrum and transfer it into the frequency-selective activity of cochlear nerve fibers. Filtering properties and dynamics of ac-
Thus, available data on frequency resolution, filtering and spectral integration in auditory nerve fibers cannot explain properties of critical band analysis and many psychophysical data on complex sound
tivity of cochlear nerve fibers in response to complex sounds like broadband noises27~~~51~b7~69, tone-noise combinations6,2~.31.58,63-65,83 speech sounds’-“. 7 and ‘r.‘s have been investigated. The results of these
perception.
Most naturally
studies
have been
occurring
related
sounds including
to psychophysical
animal
mea-
sures of auditory filtering and frequency resolution specifically to *critical bands’ and ‘critical ratio bands ~17.76.i?.Yb . Critical bands are perceptual units, within the bandwidths of which sound energy is integrated and evaluated. Thus, they constitute a measure in the terms of spectral distance of the ability to resolve frequency components in complex sounds by spectral integration. Whenever the ear is stimulated by a complex sound spectrum - and this is the case in the great majority of auditory perceptions - mechanisms of frequency resolution and critical band filtering are active in the auditory system. The comparison between auditory nerve data and perceptual frequency resolution and spectral integration lead to several important results. First, bandwidths of critical bands, critical ratio bands (CRbands) and effective bandwidths of cochlear nerve fibers show a frequency dependence similar to those measured psychophysically5.2*.27.65 although absolute bandwidths may differ substantially. Second, the peripheral filters represented in the response rates of auditory nerve fibers behave non-linearly. That is, spectral integration within these filters and/or the bandwidth themselves change with increasing sound On the other hand, in perception, critical bands and critical ratio bandwidths are largely independent of sound intensity up to about 80 dB sound pressure level (SPL)36,76-78.96. The constancy of psychophysical frequency resolution over a broad range of sound intensity is the reason for the perceptual constancy for the spectral contents of sound independent of its intensity. Third, in contrast to perception, the resolution of speech frequency compo-
It is suggested that the critical band anal-
ysis must arise in higher auditory brain centers. After substantial parallel processing in the brainstem, information about the frequency spectrum of a sound is conveyed
to the central nucleus of the infe-
rior colliculus
(ICC) by more than 10 separate projections’.35.““.8’,Yl. Th’ 1s convergence of input on a single map of frequency representation in the ICC can be expected to give rise to coding of critical band characteristics which lack an explanation by neuronal responses at lower levels. The first objective of our present study is to provide a broad and in depth quantification of properties of spectral resolution in single neurons of the ICC, i.e. to measure effective bandwidths, CR-bands (broadband masking), critical bands (narrowband masking and bandwidths of integration for two-tone stimuli) and tuning curves over a broad range of sound intensities from the unit’s response thresholds to above 100 dB SPL. On the basis of these data we shall evaluate: {a) whether the psychophysical measures of frequency resolution can be explained by response characteristics of neurons in the ICC; (b) whether conventional single-frequency tuning curves are predictive for their responses to complex sounds; (c) how distinctions between various specific response properties relate to ICC neurons’ frequency filtering and spectral integration; (d) what mechanisms underly and account for spectral sound analysis and critical band formation.
intensity20.51.62.
2. MATERIALS
AND METHODS
2.1. Animals and surgery Seven adult cats were anesthetized with an initial dose of 50 mgikg sodium pentobarbital (Nembutal) for surgery. They also received 0.2 mglkg atropine and 1 mglkg dexamethasone. During the recording session. an areflexic state of anesthesia was main-
141 tained by an iv. injection 5 mg/kg chlorprothixene
of 10 mg/kg Nembutal (Taractan)
and
about every 3-5
h. Besides some analgetic effect, Taractan induces slow-wave sleep and allows a substantial reduction of the barbiturate dose for sufficient anesthesia. This combination of anesthetics has been used successfully in studies of the mouse auditory and visual system13,21-22*g2. The rectal temperature and the animals’ core temperature
was monitored maintained at
sured in the closed system and was flat to + 5 dB between 1 and 26 kHz and flat to f 8 dB between 100 Hz and 33 kHz. The sound pressure level (SPL re. 20 PuPa) in the closed system was determined by a calibrated microphone (Bruel and Kjaer, 4133). At the maximum SPLs used, harmonic distortion products were at least 45 dB (mostly more than 60 dB) below the level of the fundamental frequency. All experiments were conducted in a double-walled sound-at-
37 “C. The inferior colliculus (IC) on one side was ap-
tenuated
proached dorsally by removal of the occipital part of the cerebral cortex and of the bony tentorium overly-
2.3. Expe~ime~ta~pr~ce~ure
ing part of the IC. Paralene insulated tungsten electrodes (impedances 1.5-4 MS2) were advanced in a
Reported data, unless otherwise obtained from the IC contralateral
dorsoventral orientation into the central sector of the IC by a remote controlled microdrive. Sampling did not include the anterior, posterior, medial and lateral thirds of the IC; and as only units recorded from a depth of 700 pm or more are included, this reported sample is believed to consist exclusively of neurons from the ICC47. Neural responses were amplified, bandpass filtered (500 Hz-5 kHz) and recorded on a TEAC four-channel tape recorder (together with stimulus synchronous timing pulses) for off-line computer analysis. An experiment typically lasted 24-30 h.
stimulation. Binaural stimuli were also used, principally to categorize the binaural response class of studied units. Tone bursts with SPLs up to 75 dB SPL were used as search stimuli. When a single unit was isolated, its characteristic frequency (CF) and lowest excitation threshold to tone bursts (the threshold at CF) were determined as that frequency and intensity at which an increase of activity above the spontaneous level was just noticeable. With the single unit’s best frequency thereby established, the response threshold to noise bursts was determined. The noise band was centered on the CF of the neuron and usually covered a minimum band~dth from two octaves below to one octave above CF (two octaves for units with CFs below 5 kHz). The lowest cutoff frequency of the noise was 80 Hz, the highest 40 kHz. Basic properties of binaural responses were then determined by simultaneous stimulation of both ears (excitatory/excitatory = E/E; excitatory/no influence ipsilaterally = E/O; excitatorylipsilaterally inhibitory = E/I) with tone bursts at CF, 10 dB above the unit’s threshold contralaterally and up to 75 dB above contralateral threshold ipsilaterally. After these basic data characterizing single units were derived, the measurement of spectral integration bandwidths and frequency resolution was undertaken. First, the masking of tone responses by broadband noise was studied. The CF tone was set at 3 dB above threshold and the responses to 20 tone bursts and 20 interburst intervals were recorded. Continuous broadband noise with the bandwidth as that used for the noise threshold dete~ination was then added at an SPL near the noise threshold, and the responses to 20 tone bursts again recorded. Noise intensity was
2.2. Stimuli generation Tones of known frequencies (Data Precision counter, 5740) were produced in generators (Philips PM 5107 and Exact 129), passed through attenuators (Hewlett-Packard, 350D) and shaped into bursts of 200 ms duration (10 ms trapezoidal rise and fall times). In most studies, stimuli were delivered at 500 ms intervals. Sinewaves in the tone bursts were initiated at zero phase. Two tones could be added together (phase-locked in the initiated cycle at zero phase) to generate either shaped bursts of two-tone complexes or tone bursts presented in the presence of a second, continuous tone. Noise was produced in a random noise generator (General Radio 1390-B), bandpass filtered (Rockland 852, 48 dB/octave slopes), attenuated (Hewlett-Packard, 350D) and could also be shaped into bursts as described above. Continuous noise of variable bandwidth could be added to the tone bursts. A closed speaker system84 with two identical electrostatic speakers was used. The frequency response of the speakers was mea-
room.
indicated, were to the acoustic
142 increased in 10 dB steps and the recording of responses to tones continued until: (a) the unit re-
which the formerly tonic response was reduced to a simple ‘on’ response to the excitatory tone; and (d)
sponded only to the continuous
total inhibition. In order to obtain this whole set of information, it was usually necessary to hold a single
noise; or (b) the re-
sponse was totally suppressed by the noise; or (c) tone-evoked responses or ‘off’ responses still occurred at the highest noise levels available. Using the same procedure, measurements were made for CFtone stimuli
at 10, 20, 40, 60 and 80 dB above the
unit’s response threshold at CF. Masking of tone responses by noise of variable bandwidth was then investigated for tonal stimuli at 20,40,60 and 80 dB above threshold. At a given tone intensity, the continuous broadband noise was presented at the level at which it had just masked the tone response in the previous broadband masking tests. The upper and lower cutoff frequencies of the noise band were then changed independently (while the spectrum level of the noise was constant) to create progressively narrower bandwidths around the tone frequency. Responses to 20 tone bursts and 20 intertone intervals were recorded for every noise bandwidth. The band narrowing was continued until a clear tone response again emerged. As still another measure of spectral integration. the response of the unit to bursts of two phase-locked tones of variable frequency separation was measured at 20,40,60 and $0 dB above the unit’s tone response threshold. By varying the frequency distance between the two tones (one below and the other above CF), the maximum bandwidth of frequency separation at which excitatory responses to the two-tone complex could be elicited, was determined. Beyond that bandwidth, either no excitatory response or a response to only one tone occurred. Again, at every frequency separation the responses to 20 stimuli and 20 interstimulus intervals were recorded. Finally, the excitatory tuning curve and the width of areas in which the excitatory tone responses (tone always IO dB above threshold at CF) could be inhibited by a second continuous tone, and the relative strengths of such inhibition, were determined at stimulus levels of the inhibitory tone up to 80 dB above the excitatory tone-response threshold. The strengths of inhibition were estimated by the reduction of the response rate ranging from (a) weak inhibition, in which the response rate was reduced by 113; (b) partial inhibition, in which the response rate was reduced by 213; (c) almost total inhibition in
neuron for more than 1 h. 2.4. Data analysis The difference between tone (Lrr) and noise (LrN) threshold expressed in SPL and spectrum measure of the ‘effective’ filter bandwidth ron, if the filter is linear and rectangularZ7. difference width L,-LrN
can be converted
= 10 log BW,,,
level is a of a neuThe level
into a frequency
band-
(Hz)
Thus, with the reservations mentioned, effective bandwidths (BW,,,) constitute a simple approximation of the filter characteristics of studied neurons. The recorded response to tone bursts in noise and two-tone complexes were analyzed in terms of: (1) spike rates in tone and intertone intervals; and (2) peristimulus-time histograms (PSTHs). From these analyses, masked tonal thresholds, which allow the calculation of CR-bands and bandwidths of spectral integration (critical bands from narrowband masking: CB,,,; critical bands from two-tone separation: CB,,) were derived. (a) Masked tonal thresholds in broadband noise: the masked response threshold to the tone for a given ICC neuron was considered to be reached at that stimulus noise level, for a given tone level, at which the spike rates in the tone interval and in the 200 ms intertone interval following the tone interval were within 20% of each other. This 20% criterion has been adapted in previous investigations to differentiate response categories of auditory units52*72. If the unit did not respond to noise, the noise level leaving 10 spikes in 20 tone intervals was considered to be at the masked threshold. The second criterion which had to be fulfiiled at the masked threshold was a flat PSTH, without peaks in the tone and intertone intervals. Thus, both response rate and overall temporal response patterns in tone and intertone intervals had to be approximately the same at the masked threshold. Two masking series are shown by examples in Fig. 1. In analogy to psychophysics, the ratio of the tone intensity
and the spectral intensity
of the noise at the
143 masked threshold can be used to determine the width of a filter which is proportional to one that filters out, 20 T
lS
26
68
4.83
CF
KHZ
UNIT
48
12
36
8
24
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12
R
0 8
l&30
200 msec
300
19
Lr-LN = CR-band (dB) = 10 Iog~~CR-band(Hz)
4eB
20
890 Hz 80 09
CF
mrec
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700 I-‘-* 500
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no -16
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spectrum level
dB
from the broadband spectrum presented, the noise band effective for masking the tone perception29176. This critical intensity ratio, representing a filter bandwidth (‘CR-band’), is equal to the difference of the tone level (Lr) and the spectrum level of the noise (LN) at the masked threshold
no
55
65
75
dB
spectrum level
Fig. 1. Series of PSTHs and rate intensity curves for two units, demonstrating the procedures for broadband masking. The tone level above threshold at which the noise was added is indicated in the topmost histogram, where no noise was present. Spectrum levels of the masking noise are indicated in each histogram, Asterisks mark histograms at which the tone response is totally masked. Note that -16 dB noise increases the tone response (unit 26) more than would be predicted by a linear summation of response rates in tone (closed circles) and intertone (open circles) intervals (see bottom diagram). Tone duration, marked by a horizontal bar: 200 ms (flat top). Bin width: 3.125 ms. The arrows in the rate intensity diagrams at the bottom of the figure indicate the noise level at which, according to our 20% criterion for rate differences in tone and intertone intervals, the tone response was masked.
(2)
Given this psychophysical definition of CR-bands, we used the masked thresholds to calculate ‘neural CR-bands’ for the ICC units of the cat. (b) bandwidth of spectral integration from narrowband masking (CBNaM): the band-narrowing procedure started with the tone response of a neuron masked by a broadband noise; band-narrowing continued until the tone response again emerged. We defined the critical band as that bandwidth of the noise at which the spike rate in the tone interval became more than 20% higher than that in a 200 ms intertone interval (graphical interpolation from rate-bandwidth curves). To accept a critical band measure, it was required that the tone response occurred for still smaller noise bandwidths. Fig. 2 shows two series of PSTHs and rate-bandwidth curves to demonstrate critical bandwidth estimation. (c) Bandwidths of spectral integration from twotone separation (CB,): we defined that bandwidth of frequency separation of the two tones as that critical band over which excitation was effectively integrated to create an excitatory response, at which either more than 10 spikes (in the summed response to 20 tone bursts) in case of a pure on-response or more than 40 spikes in case of a tonic response occurred in the tone interval, or the response rate in the tone interval was 20% higher than the spontaneous activity in the intertone interval (graphical interpolation from rate-bandwidth curves). Thus, for frequency distances narrower or wider than this critical frequency separation, the response in the tone interval was greater or ‘less, respectively. Fig. 3 shows two series of PSTHs and rate-bandwidth curves as examples for critical bandwidth estimation. 3. RESULTS
3.1 e Response t~res~~l~s and s~~nt~~e~~s activity These reported results include data from 91 quan-
20
,B IZ
UNIT
19
CF
890
Hz
60 oB 0.6 - 1.1 KHZ
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I
UNIT 32
CF
UNIT 53
8.7 KHZ 20 DB
6.0 - 11.0 KHZ
0.7 - 1.1 KHZ
B
2.1 - 3.0
12
19.0 - 25,0 KHZ
I
19,O - 24.5 KHZ
6
2.1 - 2.9 KHZ
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KHZ
7.0 - 11.0 KHZ
Ii!
8
60 DB
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CF 2284 KHZ
6
4
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7,0 - 10.0 KHZ*
12
2.15 - 2,85 K#2*
12
2.2 - 2.85 KHZ*
16
19.5
-
24.5 KHZ*
8
mrec I0 B
8.0 - 10.0 KHz*
16 12
spike
rate
spike
210 _I
I
bandwidth
Fig. 2. Band-narrowing series for two units, demonstrating how a tone response emerged from the masked condition when the bandwidth of the noise was progressively narrowed (from top to bottom of the PSTHs, see also rate-bandwidth curves). In the top histogram, the tone level above threshold is indicated. Bandlimits of the noise are shown in all histograms. Asterisks indicate bandwidths at which a clear tone response has emerged. Other symbols as in Fig. 1. Again, discharge rates during tonal stimulation (closed circles) and during intertone intervals (open circles) are plotted at the bottom. Arrows in these rate-bandwidth diagrams indicate the critical bandwidths according to our criterion.
titatively studied single units from the ICC. AH units responded to tone bursts. All but 8 responded to broadband noise bursts. In Fig. 4A,B response
/ .
0 =Jo 900
bandwidth
rate
.
150 L 90
30
20.0 - 24.0 KHZ*
I2
800
frequ.
700
650
separation
HZ
6.0
5.5
fraqu.
5.0
4.0
kHz
separation
Fig. 3. Two-tone separation series (PSTHs and respective rate-frequency separation curves) for two units, demonstrating how a response to the two-tone complex changed as the separation between tone frequencies was successively narrowed (from top to bottom). Tone level above threshold is indicated in the top histogram. In all histograms the frequencies of the two tones are presented. Asterisks mark examples in which the neurons responded to the two-tone complex. Unit 12 was spontaneously active with a resting discharge of 5 spikes/s, unit 53 did not show any spontaneous activity. Other symbols as in Fig.
1.Discharge rates during tonal stimulations (closed circles) and during intertone intervals (open circles) are shown at the bottom. Arrows in these rate-frequency separation diagrams indicate the critical bandwidths according to our criterion.
thresholds to tone and broadband noise bursts are shown. Lowest tone thresholds were seen for neu-
145 defined by PSTH patterns. Class 1: tonic or phasictonic response; class 2: phasic (‘on’) response, which
E/E . El0 ’ E/I l
could have a minor tonic component;
class 3: pauser
response including chopper responses; class 4: longlatency response (latency longer than 20 ms); class 5: spontaneous activity inhibited; class 6: no response. Table I presents
the percentages
of units in these re-
sponse classes for CF-tone responses between 3 and 80 dB above threshold. Tonic responses were predominant at 3 and 10 dB above threshold, while pausspectrum dB . LO -t J
‘L-
30-
.
20-O
l
la’
loo-
-LO-501 0.1
. .
l
8
.
.
:
.
l
- 30-
er responses were most frequently recorded at higher sound intensities. Only a small number of neurons with phasic and long latency responses were seen. In combination with these responses in the tone inter-
level
:. B
___-_------_-~_.-___-__ 0.2
0.5 1 2 characteristic
5 IO frequency
20
COkHz
Fig. 4. A: tone response threshold plotted as a function of unit characteristic frequency (CF). Different symbols indicate the binaural response properties of the single units. B: response thresholds to broadband noise bursts as a function of unit CF. Open circles and dashed lines show the behavioral thresholds of the cat’9g.
rons with CFs between about 5 and 13 kHz. By contrast, lowest noise thresholds occurred for neurons with CFs between 8 and 22 kHz. The maximum tonethreshold range for units with similar CFs in an individual cat was almost 43 dB. This is close to the maximum threshold difference for units with similar CFs in the whole sample of 7 cats. Units with excitatory input from both ears (E/E) in this sample all had CFs below about 2.2 kHz. Monaural units (E/O) in this sample all had CFs higher than 900 Hz. All units with ipsilateral inhibitory input (E/I neurons) in this sample had CFs higher than 320 Hz (Fig. 4A). Spontaneous activity ranged between zero and 95 spikes/s. Of all units, 31% had spontaneous activities below 0.5 spikes/s; 32% had rates between 0.5 and 3.5 spikes/s; 19% had rates between 4 and 7.5 spikes/s; and 18% had rates higher than 7.5 spikes/s. 3.2. CF-tone responses, rate-intensity ~u~ctio~ We discriminated between 6 tone-response classes
vals, additional tone intervals, curred in 15% above threshold Rate-intensity divided into 3
‘off’ responses (higher rates in intercompared with tone intervals) ocof the units at tone levels of 40 dB and higher. functions to tone bursts at CF were classes. Class A comprised 20 units
with steadily increasing spike rates, or rate saturation at any tone level. These units did not show a rate decrease of more than 20% at the highest level tested (at least 60 dB above threshold). Class B units (25 units) had rate-intensity functions with a single peak at a certain tone level, and more than 20% lower dischange rates at higher and lower tone levels. Class C units (27 units) had either one or several peaks and one or several valleys separated by at least 20% rate difference in their rate-intensity functions.
TABLE I Percentages of units showing different types of CF tone responses (PSTH patterns, 1-6) at 3-W dB above their tone threshold
1, tonic, phasic-tonic; 2, mainly phasic; 3, pauser and chopper; 4, long latency; 5, spontaneous activity inhibited; 6, no tone response (compare text). Total numbers of units (n) are also indicated. PS TH pattern
Tone level above threshold (dB) ._ _._._ ____-.__-_ 3 10 20 40 60
2 3 4 5 6
62 24 4 10 0 0
52 22 20 6 0 0
25 22 35 13 4 1
21 25 39 9 5
1
4
4
n
79
81
82
76
83
51
1
25 25 37 7 2
80 25 22 43 6 0
146
I30 70 60 5
unit L9
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unit 66
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Figs. 5 and 6. Representative examples of units with different shapes of excitatory tuning curves and inhibitory areas (hatched). The widths of effective bandwidths (thin horizontal lines at the lips of rhe tuning curves), CR-bands (dotted horizontal lines), critical hands,,, (thick, solid horizonal lines and critical bands. rrs (thick, dashed horizontal lines) are also indicated for each neuron. Effective bandwidths and CR-bands are always placed symmetrically around the CFs. The bandlimits of CB,U, and CB.,,, are measured as described in the text. Some other response features characterizing these representative neurons are also indicated in each figure.
147 3.3. Tuning curves
1.
inhlbnlon
Figs. 5 and 6 present typical examples of excitatory
belmv
CF
InhibItIon
above
CF
tuning curves (TCs) and inhibitory areas. TCs had various shapes including those with a widening of the frequency response area on both flanks (Figs. 5A,B and 6A) as sound intensity was increased (23%; percentages are related to n = 65 TCs measured at least up to 60 dB above CF threshold), broadening of the frequency response area only towards the low-frequency side (15%;.Fig. 5D), very steep slopes on both sides (15%; Fig. 6C), closed response area (5%; Fig. 6D), tilted response area so that at high SPLs an excitatory response at CF was absent (7%), and other complex shapes, e.g. large inhibitory areas within the excitatory area and/or more than one continuous excitatory area (35%; Figs. 5C and 6B). In Fig. 7 the Q iMa-values (CF divided by the 10 dB bandwidth of the excitatory TC) are shown as a function of CF. Despite the scatter of the data, QIOdBvalues are significantly correlated to CF (regression analysis, r = 0.415, P < 0.001); on the average, Qioda-values (the sharpness of the peaks of TCs) in this sample increase with increasing CF. Figs. 5 and 6 demonstrate the variety of shapes of inhibitor areas observed in ICC neurons. In 6 (9%) low-frequency units, no inhibitory areas could be detected. Eight units (12%) had inhibitory areas only below the CF. Fifteen units (23%) had inhibitory ranges only above the CF. The majority of units (55%) had areas of inhibition flanking the excitatory
%d6
20 18 16
I) . .
IL
Fig. 7. Q,,,-values ot excitatory tuning curves (CF divided by the bandwidth 10 dB above threshold) as a function of CF. The regression (dashed line) indicates that the average Qlods increases with increasing CF.
o’, <1
11,
1-3 3-8
,:,
11,
8-16.16
,=-
8-16>16
kHz
Fig. 8. Diagrams showing the average relative strength of inhibition in inhibitory fields below and above characteristic frequency (CF) of the neurons as a function of CF ranges. Parameter is tone intensity above the neurons’ thresholds (circles: 3, 10, 20 dB above; squares: 30, 40, 50 dB above; triangles: 60, 70,SO dB above threshold). The strength of inhibition has been measured as 0 = no inhibition; 1 = some inhibition (reduction of response rate by about 113); 2 = partial inhibition (reduction of response rate by about Z/3); 3 = almost total inhibition (the formerly tonic response is reduced to an on-response); 4 = total inhibition of tone evoked activity.
TC on both high and low sides. Within these inhibitory areas, the strength of inhibition exerted on the CFtone was also variable. Typically, inhibitory strength (defined in the Methods section) was higher above the CF than below it. Average relative strength of inhibition below and above the CF is shown in Fig. 8 for units with CFs below 1 kHz, between 1 and 3 kHz, 3 and 8 kHz, 8 and 16 kHz, and above 16 kHz in 3 intensity ranges above tone response threshold. Clearly, inhibitory strength is weaker (P < 0.01, U-test) if the inhibitory tone is below CF than if it is above CF. If the inhibitory tone is below CF. strength of inhibition generally remains rather constant with changing sound intensity or increases only somewhat for high CF units. If the inhibitory tone is above the CF, inhibitory strength increases, on the average, for units with CFs in the whole frequency range. Least inhibition is seen below the CF in units with CFs below 8 kHz and above the CF in units with CFs below 1 kHz. In addition to excitatory and inhibitory areas, a number of neurons had response areas over which tone bursts induced off-responses; or over which continuous tones induced off-responses to CF-tone bursts (Fig. 6D); or over which a continuous tone facilitated responses to CF-tone bursts (Figs. 5C and 6C).
148 3.4.
Spectral
widths,
integration
CR-bands,
bandu~idths
(effective
band-
CRNBM, CB,,,)
Statistical comparison of bandwidth
Effective bandwidths, bandwidths of critical ratios (CR-bands) and critical bands estimated from narrowband masking (CB,& and two-tone separation (CB,,) procedures - and their relations to excitatory and inhibitory
TCs -
TABLE II
are shown for a number
of
representative units in Figs. 5 and 6. As is evident from the figures, the relationships between bandwidths and band limits are rather variable
among the
spectral integration bands and in comparison to the TCs. On the average, however, the bandwidths of
Bandwidths of excitatory tuning curves (TC), critical ratio bands (CR-bands), and critical bands from narrowband masking (NBM) and two-tone separation (‘ITS) are compared at every sound intensity for every neuron investigated. Then the number of cases in which one of the bandwidths of the above kinds was larger than one of another kind was summed up over all intensities and units. The resulting sums are shown in the table. For example, in 132 cases, TCs had larger bandwidths than CR-bands, while in 78 cases CR-bands were larger. Statistically significant differences (sign-test) are indicated. ***P < 0.001: **p< 0.01; *P < 0.02.
TCs (BW,,), CR-bands and critical bands (CBNBM and CBrrs), taken at the same above-threshold levels, correlate with high statistical significance among each other, as expressed by the following functions:
CR-band
log CBrrs = 0.816 log CB,,, P
Ti-s
log CR-band P< 0.001)
(3)
= 0.956 log CB,,,-0.171
(Y = 0.473; (4)
+ 0.505 (r = 0.743;
log BW,, = 0.940 log CB, P < 0.001)
+ 0.165 (r = 0.918;
(5)
(6)
= 1.08 log CB,,-0.554
log CR-band = 0.958 log SW,, P< 0.001)
(r = 0.585; (7)
+ 0.025 (r = 0.621; (8)
The values of the correlation coefficient (T) indicate closest relation between BWr, and CB, and comparably weak relations between CR-bands and the other bandwidth measures. We compared the widths of TCs, CR-bands, CB NBMand CB,, of each neuron separately at each tone level and summed up for a11neurons the cases in which one or the other bandwidth was larger. Table II shows the results. A statistical comparison of the pairs of numbers in Table II (sign-test) revealed the following relations: CR-band band,,,
78
TC
TTS
132***
17j***
67
NBM 133***
52 91***
TC
so
107*** fis
+ 0.548 (r = 0.759:
log BWTc = 0.821 log CB,u, P < 0.001)
log CR-band P
relationships
< tuning curve < critical band,,
< critical
93* 61
It is evident that, on the average, CR-bands are the smallest followed by the widths of excitatory TCs. Critical bands from two-tone separation measurements are wider than CR-bands and TCs, and critical bands from narrowband masking have the largest bandwidths of all. Table II, however, indicates that a considerable number of units do not fit into the average bandwidth relationships derived above. For example, CR-bands of some units were wider than TCs and critical bands at some tone levels. Such a deviation from the average was typically found (SO-85% of the cases) in units not responding to noise (Fig. 6A) and in units with no inhibitory areas or some or partial inhibition only at one side of the excitatory TC (Fig. 5A). Effective bandwidths, which are CR-bands at the response threshold of a neuron, have bandwidths wider than CR-bands 3 dB above threshold in 72% of the neurons and wider than TC bandwidths in 85% of the neurons (Figs. .5A-C and 6C,D). Since critical bands have not been measured close to response threshold, a comparison of their widths with the effective bandwidths is not meaningful. Figs. 5 and 6 demonstrate that the extension of critical bands (CB,*, and CBrrs) is stopped by areas of total inhibition. In other words, critical bands never crossed fields of total inhibition and in most cases there was only little overlap of critical bandwidths and side bands of total inhibition of the excitatory
149 TCs. On the other hand, critical bands could extend
shown in Figs. 5 and 6. Single-frequency
into or even beyond fields of subtotal inhibition (Figs. 5A-C and 6B,C). In 6 cases in which CBNBM
sound TCs for 4 further neurons are shown in Fig. 9. Obviously, filter curves based on a single tone and on
crossed
a complex sound can show remarkable differences. Single frequency TCs obviously do not adequately
an area of some or partial
inhibition,
they
reached into a field characterized as facilitating a response in the excitatory TC (Figs. .5C and 6C). Critiand CB,,) never extended from cal bands (CB,,, one excitatory area beyond an inhibitory area into another range within which excitatory tone responses could be elicited (Fig. 6B). Spectral integration determined by critical band measurements was restricted to the excitatory area that is directly connected with the CF of a unit. This restriction of spectral integration was also seen in units with marked low-frequency tails extending more than 3 octaves below the CF. Only two neurons had CBNBM reaching substantially into the tail region while 12 other neurons with low-frequency tails of TCs formed their spectral integration bandwidths closely around the CFs (Fig. 9, unit 43). Conventional frequency TCs are determined as comprising that areas in which single-frequency tones can elicit excitatory neural responses. By connecting the low-side and high-side cutoff frequencies of critical bands, measured at various intensities, we obtain a different type of TC, namely one in response to a complex sound spectrum. Such TCs which become relevant when a neuron responds to a complex sound can be derived from the critical bandwidths
characterize the frequency filtering of a neuron in the central nervous system for complex sound stimuli. Eqns. 5 and 6 indicate that, on the average, the bandwidths of single-tone TCs and of critical bands are strongly correlated. Figs. 5, 6 and 9 demonstrate, however, that on the single unit level there are often large differences between frequency resolution measured for a single-tone sound spectrum.
stimulus
Figs. 10-14. On the average, TC bandwidths and all spectral integration bandwidths increase signi~cantly with increasing CF for CFs above 500 Hz and are rather constant for lower CFs. This can be expressed by the following functions (CF above 500 Hz): (Fig.
10) log BW,,
= 0.710
0.5 1
2
510”
,
CF4.8kHz ’ 02
* 0.5
log CF
(I = 0.581; P < 0.001)
+ 0.804 (9)
(Ag. 11A) log BW,, (r=0.791;P<0.001)
.
1;
and for a complex
3.4.1. Relation between bandwidths and CF. The effective bandwidths (BWnrr), bandwidths of excitatory tuning curves (BW,&, CR-bands, and critical bands (CB,,, and CB,) are shown at various SPLs above the units’ tone thresholds as a function of CF in
=
0.835
log
CF-0.106
00)
(Fig. 11B) log SW,, = 0.732 (I = 0.676; P c 0.001)
CF 10.0kHr
and complex
log CF
+ 0.751 (11)
l
l.
l . l
2 ” 1
2
?5’ ktiz
Fig. 9. Comparison of single-tone excitatory tuning curves (dashed lines) with tuning curves for complex sounds, determined by the bandwidths of the critical bands from narrowband masking (solid lines). Obviously, frequency filtering measured by single-tone and complex-tone responses can differ substantially.
a1 0.2
0.5
1
2
5
10 20
Fig. 10. Effective bandwidths (BW,,,) of the neurons calculated from Eqn. 1, as a function of the neurons’ CFs. The regression line (dashed line) follows Eqn. 9. Open symbols and solid lines show behavioral CR-bandwidths from Watsons’ (circles), Pickle@’ (triangles) and Costalupes4 (squares).
The regression
BWTC k.Fj
tone
IO:
w 3dB A IOdB
level
above
threshold
coefficients
in the functions
of ef-
fective bandwidths, TCs and critical bands are similar, suggesting a common basis for their relation to CF. CR-bands show the largest scatter of the data
S, . +
points (Fig. 12) and the largest deviations of the coefficients from those of the other functions. All correlations are significant on a high statistical level. 3.4.2. Relation between bu~dwidt~s and sound inte~sity. Figs. 15 and 16 summarize how bandwidths depend on sound intensity. The average bandwidths of excitatory TCs and CR-bands increase with increasing SPL (Fig. 15). This is indicated by significantly larger bandwidths 60 or 80 dB above tone threshold,
compared
with those 3, 10 or 20 dB above
tone threshold (P < 0.05 at least; U-test) and by a regression analysis revealing significant correlations
CR-bandwidth tone
0.1
0.2
0.5
1
2
5
IO
level above
threshold
. 3dB .lOdB VOdB
20 kHz
nAA itA&:
. ” l
Fig. 11.bandwidths of excitatory tuning curves measured 3. IO and 20 dB (A) and 40. 60 and X0 dB (B) above tone response threshold as a function of CF. Bandwidths represent :hc distances between lowest and highest frequencies evoking an excitatory response at a given intensity irrespective of inhibitory areas that might intervene. The dashed lines indicate regressions after Eqns. 10 and 11. Solid lines and open symbols show behavioral CR-bandwidths (see Fig. 10).
(Fig. GA) log CR-band (r = 0.618; PtO.OO1) (Fig. 12B) log CR-band (r = 0.407; P< 0.001)
= 0.966
log CF-0.703 (12)
ktiz 100
lLOd;
:
.
. 4”
‘:. .
50
.6OdB
20
.8OdB
.
0.2
0.5
T 4
: A.. 0).
... :Lu. il’f . 3;
= 0.628 log CF + 1.13 (33)
(Fig. 13A) log CB,a,$ (r = 0.839: P
= 0.748 log CF -I- 0.664
(Fig. 13B) log CB,n, (Y= 0.770; P < 0.001)
= 0.634 log CF +
(Fig. 14A) log CBrrS (r = 0.782; P< 0.001)
= 0.693
(Fig. 14B) log CBrrs (r = 0.683; P < 0.001)
= 0.679
04) 1.226 (15) 0.1
log CF
+ 0.734 (16)
log CF +
1.115 (17)
1
2
5
10
20 kHz
Fig. 12. Bandwidths of critical ratio bands (CR-bands) sured 3, 10 and 20 dB (A) and 40,60 and 80 dB (B) above response threshold as a function of CF. The dashed lines cate regressions after Eqns. 12 and 13. Solid lines and symbols show behaviorai CR-bandwidths of the cat (see 10).
meatone indiopen Fig.
151 are, on the average,
For lower CFs, CB,
CBNBM
tone level .20dl3
20-
above
threshold
independent. Intensity independence
. LOd3
is a characteristic
intensity of criti-
cal bands from narrowband masking both, on the average (Fig. 16A) and for 62% of the single units studied (compare Figs. 5,6 and 9). Narrowband masking yields linearity of spectral filtering up to 80 dB above the units’ tone response thresholds, all the other measures show and/or non-linear
a widening of filter bandwidths spectral integration with increasing
tone level at least in some frequency ranges. 3.4.3. Symmetry of critical bands. Critical bandwidths from narrowband masking and two-tone sepa-
kHz-I 20-
ration were investigated for the symmetry of band limits with reference to the CF. We averaged the upper and lower band limits at each tone level above threshold separately for units with CFs below 1 kHz, between 1 and 4 kHz, between 4 and 8 kHz, between 8 and 16 kHz. The average upper and lower band lim-
IO= 53 2-
0.2,:,:
0.1-. B, 0.1
0.2
,,,, 0.5
1
, , 2
, ,,,,,,, 5
1 r 10
, ,CFL
CBTTS
20 kHz
Fig. 13. Bandwidths of critical bands from narrowband masking (CB,,,) measured 20 and 40 dB (A) and 60 and 80 dB (B) above tone response threshold as a function of CF. Regression lines (dashed lines) following Eqns. 14 and 15 are shown as well as behavioral critical bandwidths from narrowband masking by Pickles6’,6” (open circles) and Nienhuys and Clarks6 (open squares).
between
bandwidths
tone level l 20dB ACOdB
above
threshold
. t A%
c--
and tone level above threshold
(SL) CF < 3 kHz: log BW,, PC 0.001)
= 0.014 SL f 2.24 (r = 0.631;
CF > 3 kHz: log SW,, (~
= 0.009 St + 3.08 (r = 0.366;
(18)
(19)
CF < 3 kHz: log CR-band 0.335; P < 0.001)
= 0.012 SL f 2.15 (r =
CF > 3 kHz: log CR-band 0.215; P < 0.001)
= 0.006 SL + 3.01 (r =
(20)
(21)
A tone level dependence of CBTTS occurs only for CFs > 3 kHz: log CB,, = 0.008 SL + 3.25 (r = 0.488; P < 0.001) (22)
Fig. 14. Bandwidths of critical bands from two-tone separation (CB,) measured 20 and 40 dB (A) and 60 and 80 dB (B) above tone response threshold as a function of CF: regression lines (dashed lines) following Eqns. 16 and 17 are indicated and behavioral critical bands from narrowband rnasking~~.~‘.~~are also shown.
CF >3kHz CFc3kWz
.
.
;
0.1 ’
CF>3kHz
1
20
204
CF<3kHz,
I
:
LO
1
1
I-
I1
8OdB 20
60
40
60
80dB
3kHz
.
i
;-
z8 :
i CF 23kHz
‘
1,
3 tone Fig.
15. Bandwidths
(B) as a function
above
level
of tuning of tone level
10 20 LO 69
curves above
average increase
of bandwidth
Fig for units with
lines indicate
with increasing
$0 -LO 60 above threshold
tone level
and CR-bandwidths
threshold
CFs below and above 3 kHz. The regression nificant
80dB
threshold
(A)
Ii*
$O
,I-
I,
a sig-
level.
16. Critical
bandwidths
from
narrowband
separation
threshold
for units with CFs below and above 3 kHz. CFs above
as a function
3 kHz
digm (B), the bandwidths the tone levef
of
masking
two-tone units with
(B)
60dE
tone
in the two-tone
(A) and
level
above
Except
separation
are, on the average,
for
para-
independent
of
its are placed around an average CF at each frequency range and are plotted in Fig. 17. They show that critical bands are formed asymmetrically around center frequencies below 1 kHz and above 4 kHz. For neurons with CFs below 1 kHz the above-CF part of and CBrrs) is wider than the critical band (CB,,, that below CF. For neurons
with CFs above 4 kHz
the below-CF part of the CB is wider than that above CF. For units with CFs between 1 and 4 kWz the critical bandwidths are formed symmetrically around CF. 3.4.4. Bandwidths and other neural characteristics. We tested whether widths of TCs, CR-bands and critical bands are related to spontaneous activity, tone response latency (measured 40 dF3 above tone response thr~shoid), tone response threshold, the type of tone response (PSTH pattern) and type of binaural response. Tone response latency and threshold were compensated for CF-dependence. Statistically significant relationships - either ?-test (PSTH pattern and binaural response type) or re-
Fig.
17.
hands,,,, above center
Average (A)
upper
and critical
thresholds. frequency
and
lower
bands,,,
bandlimits (B)
of
critical
at the 4 tone
levels
Bandwidths are placed around the average (f,-) for units in 5 CF classes as indicated. On
the linear frequency
scale (abscissa)
above
4 kHz
asymmetrical
around branch
CF. For units with CFs below 1 kHz the above CF is wider than that below CF. while units with CFs above
have
units with CFs below critical
band
filters
4 kHz have wider branches below CF. Symmetry bands is seen in units with CFs between 1and 4 kHz.
1 and
formed
of critical
153 gression analysis (spontaneous activity, tone response latency and threshold) - did blot occur between any of the bandwidth measures and any of these other neural response characteristics. That is, the neural bandwidths of frequency resolution, filtering and spectral integration do not depend on and are not related to spontaneous activity, tone response latency and threshold and tone response and binaural response type. There occurred, .however, relationships between the bandwidths of CR-bands and critical bands (CBNBMand CBrrs) and rate-intensity functions of the same units. Units with single-peak functions in response to tone bursts (class B) had larger critical bands,aM than units with other rate-intensity functions (P < 0.01, U-test). They had larger critical bandsrrs than units with multi-peak functions (class C; P < 0.02) and larger CR-bands than units with increasing or saturating functions (class A; P < 0.05). It seems that, on the average, units with single-peak rate-intensity functions to tone bursts have larger bandwidths of spectral integration than units with other spike-rate functions. 4. DISCUSSION
4.1. General aspects
The placement of electrodes allowed us to selectively record from units in the core of the ICC. The range of characteristic frequencies of the neurons (132 Hz-33 kHz) indicates that our sample covered the whole hearing range of the cat. The most sensitive units in our sample had tone response thresholds comparable with behavioral thresholds in the cat (Fig. 4A)4g. The threshold variance in the order of 30-40 dB for units with similar CFs can be explained by threshold differences of auditory nerve fibers”3. These threshold data together with a relatively low occurrence rate of units with purely phasic tone responses (Table I), with most units changing their frequency response patterns to pauser patterns with increasing tone intensity (Table I), and occurrence of units with complicated inhibitory fields and off-response areas (Figs. 5 and 6), which all are properties of ICC or dorsal cochlear nucleus units in unanesthetized animals’**“, indicate that the response properties of our present sample of neurons may not be severely influenced by the anesthetics used,
4.2. Pri~~ipal~~di~gs The further discussion shall be structured according to the following list of our principal findings: (1) The frequency dependencies of the filter bandwidths derived from the 5 different measures of frequency resolution in ICC neurons (effective bandwidth, singIe-frequency tuning curve, CR-bands and critical bands from narrowband masking and twotone separation measurements) are similar to those found in behavioral tests of frequency resolution. (2) biggie-frequency tuning curves (the conventional tuning curves) are often inadequate to describe frequency resolution for complex sound spectra although the bandwidths of these tuning curves correlate, on the average, with the bandwidths of spectral frequency resolution (CR-bands and critical bands). (3) Areas of luferul inhibition, if exerting a total suppression of tone evoked activity, strictly confine the extension of critical bandwidths. (4) Shapes of neural critical bandwidths are arymmetric on a linear frequency scale relative to the CF in most of the frequency range of hearing. (5) Average neural critical bands (CBNBM)have constant, intensity-independent bandwidths (at least between 20 and 80 dB above the neurons’ response thresholds or between about 5 and 110 dB SPL). Bandwidths of tuning curves, CR-bands and of CB.ns (only for units with CFs > 3 kHz) increase, on the average, with increasing sound intensity. (6) Critical bandwidths are encoded by changes of response rates in neurons of the ICC. (7) Frequency resolution, spectral filtering and integration are neural properties of the ICC that are independent of tone response threshold, response latency, spontaneous activity, tone response type, and binaural response type. 4.3. frequency dependence ~ffrequency resolution The frequency dependence of frequency resolution measured in psychophysical tests (critical bands and CR-bands) is well documented for man and many mammals including the cat”7*61.76.g6. All available data for man and mammals (except for one bat44) can be described by functions of the form shown by Eqns. 9-17. If we take the available behavioral data on critical bands55*61*63 and CR-bands4.6’.89 of the cat and calculate the average bandwidth-frequency relationship we obtain Eqns. 23 and 24:
154 log
CB,,,
=
0.655
f
+
0.606
(r
=
P < 0.001) log
CR-band
P< 0.001)
0.950; (23)
=
0.882
f -
0.496
(r
=
0.941; (24)
The regression coefficients of these behavioral data are not significantly different from each other. The regression coefficient of the behavioral critical band function (0.655) does not differ significantly from those of the neural measurements (Eqns. 14-17). This is also the case if Eqns. 24 and 12 (CR-bands) are compared. We can conclude, therefore, that our measurements of neural bandwidths of frequency resolution in the ICC of the cat demonstrate the same average frequency dependence of bandwidths as found in behavioral tests. This frequency dependence of filter bandwidths is of cochlear origin as relations between critical bandwidths, frequency and dependence of cochlear place’s*33 and frequency critical bands5.65 and CR-bands” in auditory nerve fibers indicate. If we compare the absolute values of critical bands from behavioral narrowband masking tests5h,h’*” with the critical bands of ICC units measured under similar narrowband masking conditions, we find that average neural bandwidths are larger than the behavioral values (Fig. 13). This discrepancy may have its origin in the difference between tone and noise levels at which the band narrowing procedure for critical band measurement started. In the behavioral tests this difference was average 6 dB smaller (the noise was 6 dB louder) compared to that required for masking ICC units. In other words, the average ICC neuron in the behavioral test was overmasked by 6 dB. This 6 dB difference is equal to a factor of 4 for bandwidth for which behavioral and neural means differ in Fig. 13. If this explanation is true, the cats used the neurons least sensitive to masking (those with the smallest filter bandwidths) in the behavioral masking tests, for detecting the tone bursts in noise. Our criterion of the response-rate difference between tone and intertone intervals for assessing the critical bandwidth could have also caused neural bandwidths larger than behavioral ones. Neural critical bandwidths become smaller when the percent rate difference used as criterion is increased. Thus, in perception, a more than 20% rate difference (our
present criterion) may be necessary for detecting differences between spectral energy inside and outside a critical bandwidth. The comparison of behavioral and neural CRbands (Fig. 12) yields similar average values if neural bandwidths derived 3-20 dB above tone response threshold are compared with the behavioral data (Fig. 12A). At higher tone levels, average neural CR-bands deviate from the behavioral measurements (mainly for rather low-frequency neurons~, that is, signal detection in broadband noise stays constant when measured behaviorally but worsens markedly in neural measurements when the sound intensity is increased.
Some suggestions
about how in-
tensity dependence of neural filtering could be compensated for in the behavioral detection test will be made later. 4.4. Relationships among measures of frequency
re-
solution in ihe ICC
On the one hand, statistically
significant
relations
among the widths of spectral integration bands and single-frequency tuning curves are obvious from Eqns. 3-8. On the other hand, the single neuron data shown in Figs. 5 and 6 indicate that great differences of widths can occur among all measures of frequency resolution if related to an individual neuron. This seeming contradiction originates in the data evaluation. The first evaluation tells that if one sort of filter bandwidth is wide (narrow) all the others are likely to be wide (narrow) too. These relations among filters can be predicted from and are caused by their similar frequency dependence (Eqns. 10-17). Figs. 5 and 6. however, demonstrate how peripheral filtering is qualified in single unit responses depending on the kind of sound to be processed. The conventional single-frequency excitatory tuning curves can be regarded as a framework in which spectral integration might be expected. Substantial deviations of shapes from those of auditory nerve fibers4” occurred in 62% of the tuning curves measured in the present study. This high proportion of higher order shapes in the ICC, which is very similar to the 64% found in the IC of the mouseZ’ and the occurrence of inhibitory areas in 91% of the units studied manifests the fact that peripheral frequency resolution has been modified by various kinds of excitatory and inhibitory interactions in the pathway to the IC
155 or in the IC itself. Our results show that excitatory and inhibitory interactions and other mechanisms in-
CR-bandwidth
fluencing the response rates of ICC neurons are determinants for the adjustment of the bandwidths of spectral integration (effective bandwidths, CRbands, critical bands). This shall be evaluated in the following. 4.4.1. CR-bands. Areas the extension
of total
inhibition
of critical bands and excitatory
limit tuning
curves but not of CR-bands. This shows that tuning curves and CBS are directly related to frequency selective filtering coupled with excitatory tone response areas. CR-bands, per definition, reflect the strength of a response to noise compared to that to a tone within the noise bandwidth. If the masked threshold of that tone is seen as the point of stimulus dominance by the broadband noise through a ‘swamping’ of the signal activity53 then the difference of tone level and noise spectrum level (critical intensity ratio) is an indicator for the noise bandwidth that contributes to masking the tone and thus might be regarded as an, although indirect, measure of a filter bandwidth (CR-band). This CR-band concept derived from psychophysics of broadband masking29,36 seems to be applicable to auditory nerve fibers18,20* 25,83;however, as the present results show, it is not generally applicable to neurons in the ICC of the midbrain. Masked thresholds cannot be defined in neurons with off-responses, tone-response dominance even at highest noise levels, absence of a tone response, and equality of responses in tone+noise and noise intervals at several noise levels (at a given tone level). These response types made it impossible to determine CR-bands in 41 of 443 measurements. Further three interactions of tone and noise responses and of excitation and inhibition are found, which systematically influence CR-bandwidths as demonstrated in Fig. 18. (a) Units in which noise enhances the tone response at least by 20% of the response rate without noise at some combination of tone and noise level (an example is unit 26 in Fig. l), generally have smaller than average CR-bands (Fig. 18). Obviously, there is a higher noise level necessary to mask an increased tone response, although the increase is due to the noise. Enhancement of tone-burst responses by continuous noise has been described for the auditory nerve20*67, however only in about 8% of the mea-
0.1
ci.2
05
1
2
5
XI
20
Wz
Fig. 18. CR-bands plotted as a function of CF of neurons which showed certain response conditions at any of the tone levels at which tests have been conducted. Circles: units in which noise enhanced the tone response. Triangies: units without inhibitory fields below or above or on both sides of the CF. Upside down triangles: units which did not respond to noise. (Further explanations in the text.)
sured masking sequences. In the ICC, this non-linear interaction of excitatory tone and noise responses occurred in 23% of all masking sequences and led to the many cases of small CR-bands shown in Fig. 18. Continuous noise does not only mask tone responses in ICC neurons (at high noise levels) but can, at certain combinations of tone and noise levels, improve the responses to tone bursts in a considerable number of units. (b) Units without an excitatory response to noise generally have extremely broad CR-bands (e.g. Fig. 6A) which, if regarded as filter bandwidths would be meaningless because they would often cover more than the audible frequency range of the cat (Fig. 18). Noise, if not producing an excitatory response, obviously exerts a powerful inhibition on the tone response so that at the masked threshold, total inhibition of sound evoked responses is reached at large signal-to-noise ratios. Total inhibition of a tone response by noise has not been observed in the auditory nerve and ventral cochlear nucleus*‘. (c) Units without inhibitory areas or with inhibition only on one side of the excitatory tuning curve often have larger than average CR-bandwidths (Fig. 181, especially if masked thresholds are determined at higher sound intensities. This suggests that an influence of inhibitory areas, induced by the broadband noise itself, suppresses the masking effect of the noise on the tone response. A’ differential ef-
156 feet of inhibitory side bands on the excitatory area of ICC neurons of awake rhesus monkeys has already been demonstrated’“. Inhibition was stronger at the
bandwidths from effective bandwidths can be explained by non-linear interactions of tone and noise responses in CR-bands as discussed before. These in-
edges of the excitatory area compared with the center. If this effect was working in our present measurements it could explain a relatively strong inhibition
teractions are not present in measurements of effective bandwidths. We can only speculate about reasons why effective bandwidths in most of the units are
on the masking noise within the CR-band by noise outside while the tone in the center of the band would
larger than 3 dB bandwidths of the tuning curves. Close to the units’ response thresholds, off-CF tones
be less affected. The consequence is that signal-tonoise ratios at the masked thresholds and thus CRbands should become narrow for units with strong in-
seem to be less effective than broadband noise in eliciting an excitatory response possibly because excitation by noise is centered at CF while tone excitation
hibition on both sides of the CF, or wide for units with only weak inhibitory areas. Lack of or only comparatively weak inhibition, without substantial increase
in tuning curve measurements is not. 4.4.3. Tuning curves. With a few exceptions Fig. 5D) critical bands (CB,,, and CB,)
with increasing sound intensity, as seen mainly in frequency areas below CF and for units with CFs below 8 kHz (Fig. 8) thus can be regarded as a major reason for the marked increase of the CR-bandwidths of these neurons with increasing sound intensity (Figs. 12 and 15B). Lateral inhibition as seen in most ICC neurons obviously contributes to a reduction of the masking effect of a broadband signal on a narrowband signal, i.e. it reduces the probability of a tone response to be masked (or ‘swamped’) by the response to a broadband stimulus like noise. This conclusion is in harmony with psychophysical tests of signal-masker discrimination in which, by a non-simultaneous presentation of the stimuli, lateral inhibition has been shown to influence both signal and maskAll these systematic effects on CR-bandwidths demonstrate that CR-bands of ICC neurons cannot simply be regarded as equivalents of frequency filters. 4.4.2. Effective bandwidths. Effective bandwidths of auditory units should correspond to the 3 dB bandwidths of the excitatory tuning curves and to the 3 dB CR-bandwidths if all three measures arise from the same linear. rectangular filter26.27. In our sample of ICC neurons, however, these bandwidths differ. Effective bandwidths are often larger than the 3 dB
not reach into low-frequency tails and they never reached into excitatory areas of tuning curves separated from the area around the CF (e.g. Figs. 6B and 9). This result points to an important difference between tuning and filtering in response to single-frequency and multi-frequency sounds. In ICC neurons, the frequency range in which excitatory responses can be elicited is not necessarily congruent with that range over which excitation (measured via discharge rate) can be integrated. This statement has to be qualified in so far as in the present experiments integration has been studied only for frequency ranges centered around CFs of the units. Further investigations have to clarify whether spectral integration is possible around frequencies located, for example, in the tails of tuning curves. Nevertheless, the present data clearly demonstrate a sound stimuius-dependent separation of the status of frequency filtering in ICC neurons: single-tone filtering is defined by the frequency response area; complex sound filtering is defined by the bandwidths of spectral integration. One obvious implication of this result is that on the basis of single-frequency tuning curves the responses of ICC neurons to complex sound spectra cannot be predicted. Experimental demonstrations for that can already be found in the literature22.““.7’. There are two further indicators in our present
bandwidths of tuning curves and larger than the 3 dB CR-bands (P < 0.01, U-test, in both cases). A difference is not seen if widths of tuning curves and CRbands both 3 dB above tone response threshold are compared. We may suggest, therefore, that ICC neurons close to their tone threshold at CF do not behave like linear rectangular filters. Deviations of CR-
data showing that excitatory tuning curves of neurons in the IC may not adequately predict responses to complex sound. First, we observed areas around excitatory tuning curves in which sound has a faciiitating effect on responses caused by stimuli at the units‘ CFs (e.g. Figs. 5C, 6C and Fig. 9. unit 26). Facihtation can become relevant only by stimulation with
er37.38
(e.g. did
157 complex sound and may function responses
as an amplifier
for
to certain
frequency components in the CBNBM extend well into facilitation
sound. Since areas (Figs. 5C and K), these areas constitute an essential part of spectral integration. Second, areas of off-response induction to tone bursts in noise are found within or outside excitatory tuning curves, mainly at higher sound intensities (e.g. Fig. 6D). Although off-responses can occur in response to CFtones within the excitatory tuning curve, off-response areas indicate an interaction of frequency components
over considerable
bandwidths
and thus
relate to complex sound processing and spectral integration. Unit 36 (Fig. 6D) is an example of the possibility of spectral integration within an off-response area. 4.4.4. Critical bands. Critical bandwidths from integration of two-tone responses (CBrrs) show some features which are intermediate between single-tone filtering and critical bands from narrowband masking. First, CB,, are, on the average, wider than tuning curve bandwidths but narrower than CB,a, (Table II). Second, CB,, (in neurons with CFs > 3 kHz) increase less with increasing sound intensity than bandwidths of tuning curves (Figs. 15 and 16B; Eqns. 19 and 22), while CB,,, do not, on the average, increase at all (Fig. 16A). At 60 and 80 dB above tone threshold, average widths of CBrrs and CB,a, are very similar (Fig. 16). This means that for lower tone intensities (mainly 20 dB above tone response threshold) there is a ‘deficit’ of integration ability for two-tone excitation within the spectral integration bandwidths defined by the narrowband masking paradigm. In the low-intensity range, phase-locking to the envelope of the two phase-locked tones may have to be considered as one factor influencing spectral integration as measured by response rate. The determinateness of the response and the response strength (spike rate) to the amplitude modulation of a tone increases in IC units up to about 35 dB super-threshold tone level@’ (G. Langner, personal communication). Depending on the frequency separation, two phaselocked tones can produce low-frequency amplitude modulation to which ICC units could lock the more consistently and with higher discharge rate at 60-80 dB compared with 20 dB super-threshold tone level. Thus, the frequency separation between the two tones for reaching a constant spike-rate increase (our
criterion) intensity,
could become larger with increasing so that we measure larger CBrrs.
tone
4.5. Symmetry of critical bands Except for the frequency range of CFs between 1 and 4 kHz, average critical bands (CBNBM and CB,) are asymmetrical on a linear frequency scale with regard to CF (Fig. 17). In units with CFs below 1 kHz, above-CF branches are wider, in units with CFs above 4 kHz above-CF branches are narrower than below-CF branches. A similar kind of asymmetry is found already in tuning curves of cochlear nerve fibers24,40. The only difference is in the range of symmetry which seems to be wider in the colliculus (l-4 kHz) than in the auditory nerve (l-2 kHz). Obviously, bandwidths of spectral integration in ICC units follow the basic asymmetries of excitation patterns within the cochlea’,7, however, without displaying low-frequency ‘tails’ as single-frequency tuning curves do. Data from psychophysical measurements in man are non-conclusive with regard to the symmetry of critical bands. They depend very much on the proposed hypothesis about the filter shape and on the method of filterband determination. Basically symmetric filters were found by Schafer et al.74, Pattersons9, Margolis and Small46 and Fidel1 et al.28 for center frequencies between about 100 Hz and 8 Hz. On the other hand, asymmetries of the kind reported in the present study have been shown in other studies for center frequencies between 2 and 8 kHz (aboveCF branch of the filter narrower than the below-CF branch)3.3~.~ and for a CF of 400 Hz (above-CF branch wider)14. Thus, in cases where asymmetries of critical bands with regard to center frequency have been found psychophysically in man, they are in agreement with our neural data from the IC of the cat (Fig. 17).
of bu~d~idt~s of spectral integration 4.6.1. CR-bands. On the average, signal-to-noise
4.6. Znte~sity dependence
ratios at the masked tonal threshold in broadband noise increase and, as a consequence, CR-bands widen with increasing sound intensity (Fig. 15B). As already discussed, this non-linearity can be interpreted, at least in part, on the basis of our data on inhibitory fields around excitatory tuning curves and
158
their influence
on interactions
of tone and noise re-
sponses. Here we have to discuss the intensity dependent neural coding of tone signals in noise with regard to the available psychophysical results of the caf”.s”. Watson’s data indicate intensity independence of CR-bands measured close to absolute threshold up to about 50 dB above that threshold over the whole frequency range tested (0.125-16 kHz). CostaiupesJ extended these data for tone ieveis of about 70-85 dB above absolute threshold and found intensity independence of CR-bandwidths for center frequencies
below about 4 kHz. At 8 and 16
signal-to-noise ratio (increasing CR-bandwidth) with increasing sound intensity. The combination of the worsening of the signal-to-noise ratio at the neuronai level in the IC (constant criterion employed) with the improvement of the psychophysical tone detection in noise (criterion change on the basis of the neural response) may lead to a mutual compensation of both non-linearities. The result then could be the observed overall linearity of CR-bands in the behavioral test&s”. This hypothesis will be tested by comparison of the intensity dependence of neural CR-bands in the ICC with that of intensity difference limens
kHz, however. bandwidths increased with increasing level for tone levels higher than about 60 dB above
from behavioral
absolute threshold. Our present single unit data show an increase of CR-bandwidths with increasing level from tone levels 3 dB to 80 dB above the units’ response thresholds. This increase is. on the average. larger for units with CFs below 3 kHz than for those with CFs above 3 kHz (Eqns. 20 and 21; Fig. 15B). Obviously, there are marked differences with regard to intensity dependence between neural data on CRbandwidths from the ICC and psychophysical measurements. In order to explain the psychophysical intensity independence of tone-signal detection in broadband noise on the basis of intensity-dependent neural behavior. the following has to be considered. If we suggest that tone detection in noise depends on a neural increment response of neurons responding to the tone on the background of their response to the noise, similar to our rate criterion used to assess the masked threshold (Fig. 1). then the subject evaluates
4.6.2. Criticul buds. One important result of the present and a previous study”’ is the intensity independence of average neural critical bandwidths determined in narrowband masking tests (Fig. 16A). As described in the Method section, the intensity independence of CB,,, follows from the same criterion for masked threshold assessment as used in the CR-band measurements. Does this mean that spectral filtering as directly measured by bandwidth variations in the critical-band tests is intensity independent, whereas spectral ~ff~e~~ff~i~~ within the filter bandwidths (CR-band measurement) changes with changing sound intensity? This question can be answered by the calculation of the ratio between tone intensity and the total noise intensity at the masked threshold within critical bandwidths from narrowband masking tests. ‘The calculation runs according to Eqn. 2 with the only difference that instead of the spectrum level of the broadband noise the total level of the noise within the critical bandwidth is inserted. The resulting level differences between tone and total noise levels at the masked thresholds are plotted in Fig. 19 as a function of the characteristic frequency of the neurons (A) and as a function of the sound pressure level of the tone (B). Apparently, these ievcl differences are independent of frequency and sound intensity over the remarkable range from 5 to 110 dB SPL. Statistically significant relations between the level difference and CF or SPL do not exist. Thus Fig. 19 presents a clear answer to the question in that spectral integration within critical band filters turns out to be intensity independent. This is an important result since it demonstrates that frequency resolution - spectral filtering and in-
a difference iimen of intensity between tone+noise and noise. i.e. a difference iimen of response rate between the tone-t-noise and the noise response. Sound intensity discrimination in psychophysical tests has been shown to improve with increasing intensity”ih.3Y.This means that the neural increment response to the tone above the noise background necessary for tone detection in psychophysical tests can become smaller with increasing sound intensity. In other words. behavioral tests indicate a change of the criterion or a change of the available information for tone detection with regard to a constant neural increment response. Our criterion for defining the masked threshold at the neural level was constant (20% rate difference), and on that basis we measured an increasing
measurements
(Ehret.
in prepara-
tion).
1.59 determined
on the basis of bandwidth
variations
of a
filter-centered sound stimulus (e.g. narrowband loudness summation in multitone masking 34+46*i4*88, they are of concomplexes 3**75.97,lateralization78) stant width over a broad intensity range. If they are determined by methods which include a stimulus with sound energy outside the critical band filter (e.g. masking by comb-filtered and notch-filtered noise45*60.82.90,or single-tone or two-tone maskit@) critical bandwidths have been shown to increase with increasing sound intensity. 4.7. mechanisms offrequenc~ resoIutiofl and .
I
0
t
,
I
I,,
10 20
f
30
,
/
I
I,,
LO SO 80
l
I,,
70
,
80
I,
I
I
t
90 100 llOd6
Fig. 19. Signal-to-noise ratios at the masked tonal thresholds (critical ratios) calculated (see Eqn. 2) by using noise bandwidths equal to the critical bandwidths measured in the narrowband masking paradigm (CBIURM)and plotted as a function of characteristic frequency (A) and sound pressure level of the tones (B). Both plots show that the critical ratios of the neural critical bandwidths are largely independent of frequency and sound intensity. That is, spectral integration within critical bandwidths is a system-inherent constant feature at the level of the ICC.
tegration - on the single neuron level in the ICC is virtually independent of sound intensity. This conclusion holds if sound energy is concentrated within a single critical bandwidth. If, as in the broadband masking tests (critical ratio measurements) spectral components outside a critical band filter can influence processing within the filter, spectral integration becomes intensity dependent probably by non-linear interactions of excitatory and inhibitory influences of the masker on the tone signal. These physiological results from single neurons in the IC of the cat have parallels in psychophysical measurements on humans. If critical bandwidths are
of criti-
cal bands In all measurements of frequency resolution of neurons in the ICC described in this study, dischargerate changes of the neurons were the decisive parameter which lead to the determination of filter bandwidths. Since the neural critical bandwidths agreed well in all their features with the psychophysical ones, we suggest that auditory frequency resolution with relevance to perception is accomplished through a spike-rate code in single neurons of the ICC. Thus, the ICC may mark the endpoint of the process of frequency resolution in the auditory system which starts with the spatial resolution in the cochlea., Recent measurements of critical bandwidths in collicular (wave V) evoked potentials in ma@ support this conclusion, because the bandwidths determined by wave V amplitude changes agreed well with those derived psychophysically. We showed that the filter bandwidths of singfe neurons in the ICC were strongly influenced by areas of inhibition and facilitation next to the excitatory area of a neuron’s single-frequency tin&g curve. These lateral inhibitory and facilitative “inmuences might have their origin in the regularity of the layered structure of the ICC which is parafleled functionally by the layers of the isofrequency planes4’* 54,57. Connections between the isofrequency planes which have been demonstrated anatomically5’ could convey the inhibitory and facilitating influences. It is interesting to note that high resolution electrophysiological measurements of the bandwidths of isofrequency planes in the cat42 showed that our neural criticat bands derived from the n~rr~wba~d maskin paradigm were just twice as wide as the frequency bandwidth of one isofrequenc?y:plane (at agiven cen-
160 ter frequency
of the CB,,,
That is, a critical bandwidth
and frequency
plane).
would extend from the
curves, effective bandwidths, critical critical bands derived using narrowband
ratio bands, masking and
center of a given isofrequency plane to the neighboring planes both at higher and lower frequencies. The
two-tone separation paradigms) have been obtained from the responses of these neurons at sound pres-
critical bandwidth, of which in 1970 J.V. Tobias said in the foreword to Scharf’s chapter on critical bands74 ‘ the other senses lack the mysteriousness of this
sure levels (SPL) up to 80 dB above the units’ response thresholds (nearly 110 dB SPL). Among our
unseen - perhaps nonexistent - but pervasive auditory filter’, would exist in the functional anatomy of the central nucleus of the IC. One important finding of our present study was that frequency resolution, including bandwidths of tuning curves critical ratios and critical bands are properties of neural coding in the ICC that do not depend on spontaneous activity, tone response threshold and latency, tone response (PSTH pattern) and binaural response type. Frequency resolution is a largely independent feature of information processing in the IC. Thus, we can infer that different sorts of information about a sound signal are processed simultaneously by every ICC neuron. A neuron can 1at the same time, be in the modes of, for example, spectral filtering, binaural processing and rhythm or modulation coding. Such a parallel processing of different features of a sound stimulus by different aspects of a neuron’s response could be a general property of higher order auditory neurons and may give rise to maps beyond tonotopicity on the neuronal substrate in higher auditory centers of the brain41~48~8”~85-X7~
results are the following: (1) Narrowband masking measures of critical bands from ICC neurons closely parallel behavioral measures using the same stimulus paradigm. (2) Frequency resolution power as measured by critical bandwidths varies little as a function of stimulus
intensity.
(3) Tuning
curves of ICC neu-
rons provide no simple basis for predicting the frequency filtering of the same neurons excited by complex sound spectra. (4) There is a frequency dependence of all measures of frequency resolution similar to that found in psychophysical determinations of critical bandwidths. That is. spatial frequency resolution in the cochlea is the origin for the resolution found in the ICC and in behavioral tests. (5) Lateral inhibition at the level of the ICC clearly plays a role in frequency resolution. (6) Frequency resolution is encoded by response rate changes of ICC neurons and is independent of tone response threshold, response latency, spontaneous activity, tone response type. binaural response type. It is concluded that spectral analysis of sound is established by processes, including lateral inhibition, independent of other basic response properties of neurons at the level of the ICC.
5. SUMMARY ACKNOWLEDGEMENTS
The central nucleus of the inferior colliculus (ICC) is a center of convergence of brainstem input and is critical for auditory information processing. Here, the analysis of complex sound spectra by single neurons in the ICC is investigated. Several measures of frequency resolution (excitatory/inhibitory tuning
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This study has been supported by the Deutsche Forschungsgemeinschaft (Eh 53/7-l), by NS-10414, and by HRI and the Coleman Fund. We thank Drs. Jenkins, Schreiner, and Snyder for helpful discussions and technical support.
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163 87 Suga, N., Functional organization of the auditory cortex: Representation beyond tonatopy in the bat. In C.N. Woolsey (Ed.), Cortical Sensory Organization, Vol. 3, Multiple Auditory Areas, Humana, Clifton, NJ, 1982, pp. 1.57-218. 88 Swets, J.A., Green, D.M. and Tanner, W.T., On the width of critical bands, J. Acoust. Sot. Am., 34 (1962) 108-l 13. 89 Watson, C.S., Masking of tones by noise for the cat, 1. Acoust. Sot. Am., 35 (1963) 167- 172. 90 Weber, D.L., Growth of masking and the auditory filter, J. Acoust. Sot. Am., 62 (1977) 424-429. 91 Willard, F.H. and Ryugo. D.K., Anatomy of the central auditory system. In J.F. Willott (Ed.), The Aud~t~r~JPqchobiology of the Mouse, Thomas, Springfield, 1983, pp. 201-304. 92 Willott, J.F. and Urban, G.P., Response properties of neurons in nuclei of the mouse inferior colliculus, J. Cump.
Pl~ysiol., 127 (1978) 175-184. 93 Young, E.D. and Barta, P.E., Rate responses of auditory nerve fibers to tones in noise near masked threshold, J. Acoust. Sot. Am., 79 (1986) 426-442. 94 Young, E.D. and Brownell, WE., Responses to tones and noise of single cells in dorsal cochlear nucleus of unanesthesized cats, 1. Neuroph_ysiol., 39 (1976) 282-300. 95 Zerlin, S., Electrophysiologic~l evidence for the critical band in humans, J. Acoust. Sot. Am., 79 (1986) 1612-1616. 96 Zwicker, E. and Feldtkellcr, R., Das Ohr als ~achr~c~te~ern~f~~ger, Hirzel, Stuttgart, 1967. 47 Zwicker. E.. Flottorp, G. and Stevens, S.S., Critical band width in loudness summation. J. Acousf. Sot. Am., 29 (1957) 548-557.
Brain Research Reviews, 13 (1988) 139-163 Elsevier BRR 90080
Complex sound analysis (frequency resolution, filtering and spectral integration) by single units of the inferior colliculus of the cat Giinter Ehret’ and Michael M. Merzenich2 ‘Fakultii:
fiir Biologie,
Universitiit Konstanz, Konstanz (F. R. G.) and ‘Coleman Laboratory, Department of Otolaryngology, University of California, San Francisco, CA 94143 (U.S.A.) (Accepted
Key words: Cat; Complex
19 January
1988)
sound analysis; Critical band; Filtering; Frequency Lateral inhibition; Masking; Spectral analysis
resolution;
Inferior
colliculus;
CONTENTS Introduction
.............................................................................................................................................
140
................................................................................................................................ Materials and Methods 2.1. Animals and surgery ............................................................................................................................. ............................................................................................................................. 2.2. Stimulus generation ....................................................................................................................... 2.3. Experimental procedure 2.4. Data analysis ......................................................................................................................................
140 140 141 141 142
Results .................................................................................................................................................... 3.1. Response thresholds andspontaneous activity ............................................................................................ .............................................................................................. 3.2. CF-tone responses, rate-intensity functions 3.3. Tuning curves ..................................................................................................................................... 3.4. Spectral integration bandwidths (effective bandwidths, CR-bands, CB,,,, CB,) ............................................. and CF .............................................................................................. 3.4.1. Relation between bandwidths and sound intensity 3.4.2. Relation between bandwidths .............................................................................. 3.4.3. Symmetry of critical bands ............................................................................................................ and other neural characteristics ...................................................................................... 3.4.4. Bandwidths
143 143 145 147 148 149 150 151 152
................................................................................................................................................ Discussion 4.1. General aspects ................................................................................................................................... 4.2. Principal findings ................................................................................................................................. 4.3. Frequency dependence of frequency resolution ........................................................................................... 4.4. Relationships among measures of frequency resolution in the ICC ................................................................... 4.4.1. CR-bands ................................................................................................................................. 4.4.2. Effective bandwidths ................................................................................................................... 4.4.3. Tuning curves ............................................................................................................................ 4.4.4. Critical bands ............................................................................................................................ 4.5. Symmetry of critical bands ..................................................................................................................... 4.6. Intensity dependence of bandwidths of spectral integration ............................................................................ ................................................................................................................................. 4.6.1. CR-bands 4.6.2. Critical bands ............................................................................................................................ 4.7. Mechanisms of frequency resolution and of critical bands ...............................................................................
153 153 153 153 154 155 156 156 157 157 157 157 158 159
_.
5. Summary
_. _.
Acknowledgements References
Correspondence:
0165-0173/88/$03.50
_. _.
_,_.
0
_. _.
_. _._.
G. Ehret,
Fakultat
1988 Elsevier
fur Biologie,
Universitat
Science Publishers
Konstanz,
B.V. (Biomedical
Postfach
Division)
160
5560, D-7750 Konstanz,
_.
F.R.G.
_,
_.
160 160
140 1. INTRODUCTION
nents (formants of vowels) in background noise measured by spike rates of auditory nerve fibers is de-
vocalizations and human speech have complex frequency spectra. The frequency-place transfor-
graded at higher sound intensities”~‘” although a spike-rate code seems to be sufficient for encoding tone responses in background noise5,93.
mations in the cochlea and cochlear filtering processes resolve the frequency spectrum and transfer it into the frequency-selective activity of cochlear nerve fibers. Filtering properties and dynamics of ac-
Thus, available data on frequency resolution, filtering and spectral integration in auditory nerve fibers cannot explain properties of critical band analysis and many psychophysical data on complex sound
tivity of cochlear nerve fibers in response to complex sounds like broadband noises27~~~51~b7~69, tone-noise combinations6,2~.31.58,63-65,83 speech sounds’-“. 7 and ‘r.‘s have been investigated. The results of these
perception.
Most naturally
studies
have been
occurring
related
sounds including
to psychophysical
animal
mea-
sures of auditory filtering and frequency resolution specifically to *critical bands’ and ‘critical ratio bands ~17.76.i?.Yb . Critical bands are perceptual units, within the bandwidths of which sound energy is integrated and evaluated. Thus, they constitute a measure in the terms of spectral distance of the ability to resolve frequency components in complex sounds by spectral integration. Whenever the ear is stimulated by a complex sound spectrum - and this is the case in the great majority of auditory perceptions - mechanisms of frequency resolution and critical band filtering are active in the auditory system. The comparison between auditory nerve data and perceptual frequency resolution and spectral integration lead to several important results. First, bandwidths of critical bands, critical ratio bands (CRbands) and effective bandwidths of cochlear nerve fibers show a frequency dependence similar to those measured psychophysically5.2*.27.65 although absolute bandwidths may differ substantially. Second, the peripheral filters represented in the response rates of auditory nerve fibers behave non-linearly. That is, spectral integration within these filters and/or the bandwidth themselves change with increasing sound On the other hand, in perception, critical bands and critical ratio bandwidths are largely independent of sound intensity up to about 80 dB sound pressure level (SPL)36,76-78.96. The constancy of psychophysical frequency resolution over a broad range of sound intensity is the reason for the perceptual constancy for the spectral contents of sound independent of its intensity. Third, in contrast to perception, the resolution of speech frequency compo-
It is suggested that the critical band anal-
ysis must arise in higher auditory brain centers. After substantial parallel processing in the brainstem, information about the frequency spectrum of a sound is conveyed
to the central nucleus of the infe-
rior colliculus
(ICC) by more than 10 separate projections’.35.““.8’,Yl. Th’ 1s convergence of input on a single map of frequency representation in the ICC can be expected to give rise to coding of critical band characteristics which lack an explanation by neuronal responses at lower levels. The first objective of our present study is to provide a broad and in depth quantification of properties of spectral resolution in single neurons of the ICC, i.e. to measure effective bandwidths, CR-bands (broadband masking), critical bands (narrowband masking and bandwidths of integration for two-tone stimuli) and tuning curves over a broad range of sound intensities from the unit’s response thresholds to above 100 dB SPL. On the basis of these data we shall evaluate: {a) whether the psychophysical measures of frequency resolution can be explained by response characteristics of neurons in the ICC; (b) whether conventional single-frequency tuning curves are predictive for their responses to complex sounds; (c) how distinctions between various specific response properties relate to ICC neurons’ frequency filtering and spectral integration; (d) what mechanisms underly and account for spectral sound analysis and critical band formation.
intensity20.51.62.
2. MATERIALS
AND METHODS
2.1. Animals and surgery Seven adult cats were anesthetized with an initial dose of 50 mgikg sodium pentobarbital (Nembutal) for surgery. They also received 0.2 mglkg atropine and 1 mglkg dexamethasone. During the recording session. an areflexic state of anesthesia was main-
141 tained by an iv. injection 5 mg/kg chlorprothixene
of 10 mg/kg Nembutal (Taractan)
and
about every 3-5
h. Besides some analgetic effect, Taractan induces slow-wave sleep and allows a substantial reduction of the barbiturate dose for sufficient anesthesia. This combination of anesthetics has been used successfully in studies of the mouse auditory and visual system13,21-22*g2. The rectal temperature and the animals’ core temperature
was monitored maintained at
sured in the closed system and was flat to + 5 dB between 1 and 26 kHz and flat to f 8 dB between 100 Hz and 33 kHz. The sound pressure level (SPL re. 20 PuPa) in the closed system was determined by a calibrated microphone (Bruel and Kjaer, 4133). At the maximum SPLs used, harmonic distortion products were at least 45 dB (mostly more than 60 dB) below the level of the fundamental frequency. All experiments were conducted in a double-walled sound-at-
37 “C. The inferior colliculus (IC) on one side was ap-
tenuated
proached dorsally by removal of the occipital part of the cerebral cortex and of the bony tentorium overly-
2.3. Expe~ime~ta~pr~ce~ure
ing part of the IC. Paralene insulated tungsten electrodes (impedances 1.5-4 MS2) were advanced in a
Reported data, unless otherwise obtained from the IC contralateral
dorsoventral orientation into the central sector of the IC by a remote controlled microdrive. Sampling did not include the anterior, posterior, medial and lateral thirds of the IC; and as only units recorded from a depth of 700 pm or more are included, this reported sample is believed to consist exclusively of neurons from the ICC47. Neural responses were amplified, bandpass filtered (500 Hz-5 kHz) and recorded on a TEAC four-channel tape recorder (together with stimulus synchronous timing pulses) for off-line computer analysis. An experiment typically lasted 24-30 h.
stimulation. Binaural stimuli were also used, principally to categorize the binaural response class of studied units. Tone bursts with SPLs up to 75 dB SPL were used as search stimuli. When a single unit was isolated, its characteristic frequency (CF) and lowest excitation threshold to tone bursts (the threshold at CF) were determined as that frequency and intensity at which an increase of activity above the spontaneous level was just noticeable. With the single unit’s best frequency thereby established, the response threshold to noise bursts was determined. The noise band was centered on the CF of the neuron and usually covered a minimum band~dth from two octaves below to one octave above CF (two octaves for units with CFs below 5 kHz). The lowest cutoff frequency of the noise was 80 Hz, the highest 40 kHz. Basic properties of binaural responses were then determined by simultaneous stimulation of both ears (excitatory/excitatory = E/E; excitatory/no influence ipsilaterally = E/O; excitatorylipsilaterally inhibitory = E/I) with tone bursts at CF, 10 dB above the unit’s threshold contralaterally and up to 75 dB above contralateral threshold ipsilaterally. After these basic data characterizing single units were derived, the measurement of spectral integration bandwidths and frequency resolution was undertaken. First, the masking of tone responses by broadband noise was studied. The CF tone was set at 3 dB above threshold and the responses to 20 tone bursts and 20 interburst intervals were recorded. Continuous broadband noise with the bandwidth as that used for the noise threshold dete~ination was then added at an SPL near the noise threshold, and the responses to 20 tone bursts again recorded. Noise intensity was
2.2. Stimuli generation Tones of known frequencies (Data Precision counter, 5740) were produced in generators (Philips PM 5107 and Exact 129), passed through attenuators (Hewlett-Packard, 350D) and shaped into bursts of 200 ms duration (10 ms trapezoidal rise and fall times). In most studies, stimuli were delivered at 500 ms intervals. Sinewaves in the tone bursts were initiated at zero phase. Two tones could be added together (phase-locked in the initiated cycle at zero phase) to generate either shaped bursts of two-tone complexes or tone bursts presented in the presence of a second, continuous tone. Noise was produced in a random noise generator (General Radio 1390-B), bandpass filtered (Rockland 852, 48 dB/octave slopes), attenuated (Hewlett-Packard, 350D) and could also be shaped into bursts as described above. Continuous noise of variable bandwidth could be added to the tone bursts. A closed speaker system84 with two identical electrostatic speakers was used. The frequency response of the speakers was mea-
room.
indicated, were to the acoustic
142 increased in 10 dB steps and the recording of responses to tones continued until: (a) the unit re-
which the formerly tonic response was reduced to a simple ‘on’ response to the excitatory tone; and (d)
sponded only to the continuous
total inhibition. In order to obtain this whole set of information, it was usually necessary to hold a single
noise; or (b) the re-
sponse was totally suppressed by the noise; or (c) tone-evoked responses or ‘off’ responses still occurred at the highest noise levels available. Using the same procedure, measurements were made for CFtone stimuli
at 10, 20, 40, 60 and 80 dB above the
unit’s response threshold at CF. Masking of tone responses by noise of variable bandwidth was then investigated for tonal stimuli at 20,40,60 and 80 dB above threshold. At a given tone intensity, the continuous broadband noise was presented at the level at which it had just masked the tone response in the previous broadband masking tests. The upper and lower cutoff frequencies of the noise band were then changed independently (while the spectrum level of the noise was constant) to create progressively narrower bandwidths around the tone frequency. Responses to 20 tone bursts and 20 intertone intervals were recorded for every noise bandwidth. The band narrowing was continued until a clear tone response again emerged. As still another measure of spectral integration. the response of the unit to bursts of two phase-locked tones of variable frequency separation was measured at 20,40,60 and $0 dB above the unit’s tone response threshold. By varying the frequency distance between the two tones (one below and the other above CF), the maximum bandwidth of frequency separation at which excitatory responses to the two-tone complex could be elicited, was determined. Beyond that bandwidth, either no excitatory response or a response to only one tone occurred. Again, at every frequency separation the responses to 20 stimuli and 20 interstimulus intervals were recorded. Finally, the excitatory tuning curve and the width of areas in which the excitatory tone responses (tone always IO dB above threshold at CF) could be inhibited by a second continuous tone, and the relative strengths of such inhibition, were determined at stimulus levels of the inhibitory tone up to 80 dB above the excitatory tone-response threshold. The strengths of inhibition were estimated by the reduction of the response rate ranging from (a) weak inhibition, in which the response rate was reduced by 113; (b) partial inhibition, in which the response rate was reduced by 213; (c) almost total inhibition in
neuron for more than 1 h. 2.4. Data analysis The difference between tone (Lrr) and noise (LrN) threshold expressed in SPL and spectrum measure of the ‘effective’ filter bandwidth ron, if the filter is linear and rectangularZ7. difference width L,-LrN
can be converted
= 10 log BW,,,
level is a of a neuThe level
into a frequency
band-
(Hz)
Thus, with the reservations mentioned, effective bandwidths (BW,,,) constitute a simple approximation of the filter characteristics of studied neurons. The recorded response to tone bursts in noise and two-tone complexes were analyzed in terms of: (1) spike rates in tone and intertone intervals; and (2) peristimulus-time histograms (PSTHs). From these analyses, masked tonal thresholds, which allow the calculation of CR-bands and bandwidths of spectral integration (critical bands from narrowband masking: CB,,,; critical bands from two-tone separation: CB,,) were derived. (a) Masked tonal thresholds in broadband noise: the masked response threshold to the tone for a given ICC neuron was considered to be reached at that stimulus noise level, for a given tone level, at which the spike rates in the tone interval and in the 200 ms intertone interval following the tone interval were within 20% of each other. This 20% criterion has been adapted in previous investigations to differentiate response categories of auditory units52*72. If the unit did not respond to noise, the noise level leaving 10 spikes in 20 tone intervals was considered to be at the masked threshold. The second criterion which had to be fulfiiled at the masked threshold was a flat PSTH, without peaks in the tone and intertone intervals. Thus, both response rate and overall temporal response patterns in tone and intertone intervals had to be approximately the same at the masked threshold. Two masking series are shown by examples in Fig. 1. In analogy to psychophysics, the ratio of the tone intensity
and the spectral intensity
of the noise at the
143 masked threshold can be used to determine the width of a filter which is proportional to one that filters out, 20 T
lS
26
68
4.83
CF
KHZ
UNIT
48
12
36
8
24
4
12
R
0 8
l&30
200 msec
300
19
Lr-LN = CR-band (dB) = 10 Iog~~CR-band(Hz)
4eB
20
890 Hz 80 09
CF
mrec
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16
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spike rate
700 I-‘-* 500
500
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100
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2
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no -16
-6
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14
spectrum level
dB
from the broadband spectrum presented, the noise band effective for masking the tone perception29176. This critical intensity ratio, representing a filter bandwidth (‘CR-band’), is equal to the difference of the tone level (Lr) and the spectrum level of the noise (LN) at the masked threshold
no
55
65
75
dB
spectrum level
Fig. 1. Series of PSTHs and rate intensity curves for two units, demonstrating the procedures for broadband masking. The tone level above threshold at which the noise was added is indicated in the topmost histogram, where no noise was present. Spectrum levels of the masking noise are indicated in each histogram, Asterisks mark histograms at which the tone response is totally masked. Note that -16 dB noise increases the tone response (unit 26) more than would be predicted by a linear summation of response rates in tone (closed circles) and intertone (open circles) intervals (see bottom diagram). Tone duration, marked by a horizontal bar: 200 ms (flat top). Bin width: 3.125 ms. The arrows in the rate intensity diagrams at the bottom of the figure indicate the noise level at which, according to our 20% criterion for rate differences in tone and intertone intervals, the tone response was masked.
(2)
Given this psychophysical definition of CR-bands, we used the masked thresholds to calculate ‘neural CR-bands’ for the ICC units of the cat. (b) bandwidth of spectral integration from narrowband masking (CBNaM): the band-narrowing procedure started with the tone response of a neuron masked by a broadband noise; band-narrowing continued until the tone response again emerged. We defined the critical band as that bandwidth of the noise at which the spike rate in the tone interval became more than 20% higher than that in a 200 ms intertone interval (graphical interpolation from rate-bandwidth curves). To accept a critical band measure, it was required that the tone response occurred for still smaller noise bandwidths. Fig. 2 shows two series of PSTHs and rate-bandwidth curves to demonstrate critical bandwidth estimation. (c) Bandwidths of spectral integration from twotone separation (CB,): we defined that bandwidth of frequency separation of the two tones as that critical band over which excitation was effectively integrated to create an excitatory response, at which either more than 10 spikes (in the summed response to 20 tone bursts) in case of a pure on-response or more than 40 spikes in case of a tonic response occurred in the tone interval, or the response rate in the tone interval was 20% higher than the spontaneous activity in the intertone interval (graphical interpolation from rate-bandwidth curves). Thus, for frequency distances narrower or wider than this critical frequency separation, the response in the tone interval was greater or ‘less, respectively. Fig. 3 shows two series of PSTHs and rate-bandwidth curves as examples for critical bandwidth estimation. 3. RESULTS
3.1 e Response t~res~~l~s and s~~nt~~e~~s activity These reported results include data from 91 quan-
20
,B IZ
UNIT
19
CF
890
Hz
60 oB 0.6 - 1.1 KHZ
I0 6 6
I
UNIT 32
CF
UNIT 53
8.7 KHZ 20 DB
6.0 - 11.0 KHZ
0.7 - 1.1 KHZ
B
2.1 - 3.0
12
19.0 - 25,0 KHZ
I
19,O - 24.5 KHZ
6
2.1 - 2.9 KHZ
8
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7.0 - 11.0 KHZ
Ii!
8
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16
CF 2284 KHZ
6
4
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2.2 - 2.85 KHZ*
16
19.5
-
24.5 KHZ*
8
mrec I0 B
8.0 - 10.0 KHz*
16 12
spike
rate
spike
210 _I
I
bandwidth
Fig. 2. Band-narrowing series for two units, demonstrating how a tone response emerged from the masked condition when the bandwidth of the noise was progressively narrowed (from top to bottom of the PSTHs, see also rate-bandwidth curves). In the top histogram, the tone level above threshold is indicated. Bandlimits of the noise are shown in all histograms. Asterisks indicate bandwidths at which a clear tone response has emerged. Other symbols as in Fig. 1. Again, discharge rates during tonal stimulation (closed circles) and during intertone intervals (open circles) are plotted at the bottom. Arrows in these rate-bandwidth diagrams indicate the critical bandwidths according to our criterion.
titatively studied single units from the ICC. AH units responded to tone bursts. All but 8 responded to broadband noise bursts. In Fig. 4A,B response
/ .
0 =Jo 900
bandwidth
rate
.
150 L 90
30
20.0 - 24.0 KHZ*
I2
800
frequ.
700
650
separation
HZ
6.0
5.5
fraqu.
5.0
4.0
kHz
separation
Fig. 3. Two-tone separation series (PSTHs and respective rate-frequency separation curves) for two units, demonstrating how a response to the two-tone complex changed as the separation between tone frequencies was successively narrowed (from top to bottom). Tone level above threshold is indicated in the top histogram. In all histograms the frequencies of the two tones are presented. Asterisks mark examples in which the neurons responded to the two-tone complex. Unit 12 was spontaneously active with a resting discharge of 5 spikes/s, unit 53 did not show any spontaneous activity. Other symbols as in Fig.
1.Discharge rates during tonal stimulations (closed circles) and during intertone intervals (open circles) are shown at the bottom. Arrows in these rate-frequency separation diagrams indicate the critical bandwidths according to our criterion.
thresholds to tone and broadband noise bursts are shown. Lowest tone thresholds were seen for neu-
145 defined by PSTH patterns. Class 1: tonic or phasictonic response; class 2: phasic (‘on’) response, which
E/E . El0 ’ E/I l
could have a minor tonic component;
class 3: pauser
response including chopper responses; class 4: longlatency response (latency longer than 20 ms); class 5: spontaneous activity inhibited; class 6: no response. Table I presents
the percentages
of units in these re-
sponse classes for CF-tone responses between 3 and 80 dB above threshold. Tonic responses were predominant at 3 and 10 dB above threshold, while pausspectrum dB . LO -t J
‘L-
30-
.
20-O
l
la’
loo-
-LO-501 0.1
. .
l
8
.
.
:
.
l
- 30-
er responses were most frequently recorded at higher sound intensities. Only a small number of neurons with phasic and long latency responses were seen. In combination with these responses in the tone inter-
level
:. B
___-_------_-~_.-___-__ 0.2
0.5 1 2 characteristic
5 IO frequency
20
COkHz
Fig. 4. A: tone response threshold plotted as a function of unit characteristic frequency (CF). Different symbols indicate the binaural response properties of the single units. B: response thresholds to broadband noise bursts as a function of unit CF. Open circles and dashed lines show the behavioral thresholds of the cat’9g.
rons with CFs between about 5 and 13 kHz. By contrast, lowest noise thresholds occurred for neurons with CFs between 8 and 22 kHz. The maximum tonethreshold range for units with similar CFs in an individual cat was almost 43 dB. This is close to the maximum threshold difference for units with similar CFs in the whole sample of 7 cats. Units with excitatory input from both ears (E/E) in this sample all had CFs below about 2.2 kHz. Monaural units (E/O) in this sample all had CFs higher than 900 Hz. All units with ipsilateral inhibitory input (E/I neurons) in this sample had CFs higher than 320 Hz (Fig. 4A). Spontaneous activity ranged between zero and 95 spikes/s. Of all units, 31% had spontaneous activities below 0.5 spikes/s; 32% had rates between 0.5 and 3.5 spikes/s; 19% had rates between 4 and 7.5 spikes/s; and 18% had rates higher than 7.5 spikes/s. 3.2. CF-tone responses, rate-intensity ~u~ctio~ We discriminated between 6 tone-response classes
vals, additional tone intervals, curred in 15% above threshold Rate-intensity divided into 3
‘off’ responses (higher rates in intercompared with tone intervals) ocof the units at tone levels of 40 dB and higher. functions to tone bursts at CF were classes. Class A comprised 20 units
with steadily increasing spike rates, or rate saturation at any tone level. These units did not show a rate decrease of more than 20% at the highest level tested (at least 60 dB above threshold). Class B units (25 units) had rate-intensity functions with a single peak at a certain tone level, and more than 20% lower dischange rates at higher and lower tone levels. Class C units (27 units) had either one or several peaks and one or several valleys separated by at least 20% rate difference in their rate-intensity functions.
TABLE I Percentages of units showing different types of CF tone responses (PSTH patterns, 1-6) at 3-W dB above their tone threshold
1, tonic, phasic-tonic; 2, mainly phasic; 3, pauser and chopper; 4, long latency; 5, spontaneous activity inhibited; 6, no tone response (compare text). Total numbers of units (n) are also indicated. PS TH pattern
Tone level above threshold (dB) ._ _._._ ____-.__-_ 3 10 20 40 60
2 3 4 5 6
62 24 4 10 0 0
52 22 20 6 0 0
25 22 35 13 4 1
21 25 39 9 5
1
4
4
n
79
81
82
76
83
51
1
25 25 37 7 2
80 25 22 43 6 0
146
I30 70 60 5
unit L9
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2k
5kHz
unit 2.4 CF 2137th
50 UC) SJL e...... 1
0.5A0
L1r-n,
2
30
100 200
500
lk
2k
...............(
1 9
A
Yfi,
7
_._.'--".!.. '!'( t/ 1 I4 : :.i; / ir' :// _.............:::x&! \Ji.l’l. 5;
3
CFl%OkHz~_,.__........._~.~............._ \ I
E/I
”
..* f
unit 66
CF 11.66kWz EfO
Figs. 5 and 6. Representative examples of units with different shapes of excitatory tuning curves and inhibitory areas (hatched). The widths of effective bandwidths (thin horizontal lines at the lips of rhe tuning curves), CR-bands (dotted horizontal lines), critical hands,,, (thick, solid horizonal lines and critical bands. rrs (thick, dashed horizontal lines) are also indicated for each neuron. Effective bandwidths and CR-bands are always placed symmetrically around the CFs. The bandlimits of CB,U, and CB.,,, are measured as described in the text. Some other response features characterizing these representative neurons are also indicated in each figure.
147 3.3. Tuning curves
1.
inhlbnlon
Figs. 5 and 6 present typical examples of excitatory
belmv
CF
InhibItIon
above
CF
tuning curves (TCs) and inhibitory areas. TCs had various shapes including those with a widening of the frequency response area on both flanks (Figs. 5A,B and 6A) as sound intensity was increased (23%; percentages are related to n = 65 TCs measured at least up to 60 dB above CF threshold), broadening of the frequency response area only towards the low-frequency side (15%;.Fig. 5D), very steep slopes on both sides (15%; Fig. 6C), closed response area (5%; Fig. 6D), tilted response area so that at high SPLs an excitatory response at CF was absent (7%), and other complex shapes, e.g. large inhibitory areas within the excitatory area and/or more than one continuous excitatory area (35%; Figs. 5C and 6B). In Fig. 7 the Q iMa-values (CF divided by the 10 dB bandwidth of the excitatory TC) are shown as a function of CF. Despite the scatter of the data, QIOdBvalues are significantly correlated to CF (regression analysis, r = 0.415, P < 0.001); on the average, Qioda-values (the sharpness of the peaks of TCs) in this sample increase with increasing CF. Figs. 5 and 6 demonstrate the variety of shapes of inhibitor areas observed in ICC neurons. In 6 (9%) low-frequency units, no inhibitory areas could be detected. Eight units (12%) had inhibitory areas only below the CF. Fifteen units (23%) had inhibitory ranges only above the CF. The majority of units (55%) had areas of inhibition flanking the excitatory
%d6
20 18 16
I) . .
IL
Fig. 7. Q,,,-values ot excitatory tuning curves (CF divided by the bandwidth 10 dB above threshold) as a function of CF. The regression (dashed line) indicates that the average Qlods increases with increasing CF.
o’, <1
11,
1-3 3-8
,:,
11,
8-16.16
,=-
8-16>16
kHz
Fig. 8. Diagrams showing the average relative strength of inhibition in inhibitory fields below and above characteristic frequency (CF) of the neurons as a function of CF ranges. Parameter is tone intensity above the neurons’ thresholds (circles: 3, 10, 20 dB above; squares: 30, 40, 50 dB above; triangles: 60, 70,SO dB above threshold). The strength of inhibition has been measured as 0 = no inhibition; 1 = some inhibition (reduction of response rate by about 113); 2 = partial inhibition (reduction of response rate by about Z/3); 3 = almost total inhibition (the formerly tonic response is reduced to an on-response); 4 = total inhibition of tone evoked activity.
TC on both high and low sides. Within these inhibitory areas, the strength of inhibition exerted on the CFtone was also variable. Typically, inhibitory strength (defined in the Methods section) was higher above the CF than below it. Average relative strength of inhibition below and above the CF is shown in Fig. 8 for units with CFs below 1 kHz, between 1 and 3 kHz, 3 and 8 kHz, 8 and 16 kHz, and above 16 kHz in 3 intensity ranges above tone response threshold. Clearly, inhibitory strength is weaker (P < 0.01, U-test) if the inhibitory tone is below CF than if it is above CF. If the inhibitory tone is below CF. strength of inhibition generally remains rather constant with changing sound intensity or increases only somewhat for high CF units. If the inhibitory tone is above the CF, inhibitory strength increases, on the average, for units with CFs in the whole frequency range. Least inhibition is seen below the CF in units with CFs below 8 kHz and above the CF in units with CFs below 1 kHz. In addition to excitatory and inhibitory areas, a number of neurons had response areas over which tone bursts induced off-responses; or over which continuous tones induced off-responses to CF-tone bursts (Fig. 6D); or over which a continuous tone facilitated responses to CF-tone bursts (Figs. 5C and 6C).
148 3.4.
Spectral
widths,
integration
CR-bands,
bandu~idths
(effective
band-
CRNBM, CB,,,)
Statistical comparison of bandwidth
Effective bandwidths, bandwidths of critical ratios (CR-bands) and critical bands estimated from narrowband masking (CB,& and two-tone separation (CB,,) procedures - and their relations to excitatory and inhibitory
TCs -
TABLE II
are shown for a number
of
representative units in Figs. 5 and 6. As is evident from the figures, the relationships between bandwidths and band limits are rather variable
among the
spectral integration bands and in comparison to the TCs. On the average, however, the bandwidths of
Bandwidths of excitatory tuning curves (TC), critical ratio bands (CR-bands), and critical bands from narrowband masking (NBM) and two-tone separation (‘ITS) are compared at every sound intensity for every neuron investigated. Then the number of cases in which one of the bandwidths of the above kinds was larger than one of another kind was summed up over all intensities and units. The resulting sums are shown in the table. For example, in 132 cases, TCs had larger bandwidths than CR-bands, while in 78 cases CR-bands were larger. Statistically significant differences (sign-test) are indicated. ***P < 0.001: **p< 0.01; *P < 0.02.
TCs (BW,,), CR-bands and critical bands (CBNBM and CBrrs), taken at the same above-threshold levels, correlate with high statistical significance among each other, as expressed by the following functions:
CR-band
log CBrrs = 0.816 log CB,,, P
Ti-s
log CR-band P< 0.001)
(3)
= 0.956 log CB,,,-0.171
(Y = 0.473; (4)
+ 0.505 (r = 0.743;
log BW,, = 0.940 log CB, P < 0.001)
+ 0.165 (r = 0.918;
(5)
(6)
= 1.08 log CB,,-0.554
log CR-band = 0.958 log SW,, P< 0.001)
(r = 0.585; (7)
+ 0.025 (r = 0.621; (8)
The values of the correlation coefficient (T) indicate closest relation between BWr, and CB, and comparably weak relations between CR-bands and the other bandwidth measures. We compared the widths of TCs, CR-bands, CB NBMand CB,, of each neuron separately at each tone level and summed up for a11neurons the cases in which one or the other bandwidth was larger. Table II shows the results. A statistical comparison of the pairs of numbers in Table II (sign-test) revealed the following relations: CR-band band,,,
78
TC
TTS
132***
17j***
67
NBM 133***
52 91***
TC
so
107*** fis
+ 0.548 (r = 0.759:
log BWTc = 0.821 log CB,u, P < 0.001)
log CR-band P
relationships
< tuning curve < critical band,,
< critical
93* 61
It is evident that, on the average, CR-bands are the smallest followed by the widths of excitatory TCs. Critical bands from two-tone separation measurements are wider than CR-bands and TCs, and critical bands from narrowband masking have the largest bandwidths of all. Table II, however, indicates that a considerable number of units do not fit into the average bandwidth relationships derived above. For example, CR-bands of some units were wider than TCs and critical bands at some tone levels. Such a deviation from the average was typically found (SO-85% of the cases) in units not responding to noise (Fig. 6A) and in units with no inhibitory areas or some or partial inhibition only at one side of the excitatory TC (Fig. 5A). Effective bandwidths, which are CR-bands at the response threshold of a neuron, have bandwidths wider than CR-bands 3 dB above threshold in 72% of the neurons and wider than TC bandwidths in 85% of the neurons (Figs. .5A-C and 6C,D). Since critical bands have not been measured close to response threshold, a comparison of their widths with the effective bandwidths is not meaningful. Figs. 5 and 6 demonstrate that the extension of critical bands (CB,*, and CBrrs) is stopped by areas of total inhibition. In other words, critical bands never crossed fields of total inhibition and in most cases there was only little overlap of critical bandwidths and side bands of total inhibition of the excitatory
149 TCs. On the other hand, critical bands could extend
shown in Figs. 5 and 6. Single-frequency
into or even beyond fields of subtotal inhibition (Figs. 5A-C and 6B,C). In 6 cases in which CBNBM
sound TCs for 4 further neurons are shown in Fig. 9. Obviously, filter curves based on a single tone and on
crossed
a complex sound can show remarkable differences. Single frequency TCs obviously do not adequately
an area of some or partial
inhibition,
they
reached into a field characterized as facilitating a response in the excitatory TC (Figs. .5C and 6C). Critiand CB,,) never extended from cal bands (CB,,, one excitatory area beyond an inhibitory area into another range within which excitatory tone responses could be elicited (Fig. 6B). Spectral integration determined by critical band measurements was restricted to the excitatory area that is directly connected with the CF of a unit. This restriction of spectral integration was also seen in units with marked low-frequency tails extending more than 3 octaves below the CF. Only two neurons had CBNBM reaching substantially into the tail region while 12 other neurons with low-frequency tails of TCs formed their spectral integration bandwidths closely around the CFs (Fig. 9, unit 43). Conventional frequency TCs are determined as comprising that areas in which single-frequency tones can elicit excitatory neural responses. By connecting the low-side and high-side cutoff frequencies of critical bands, measured at various intensities, we obtain a different type of TC, namely one in response to a complex sound spectrum. Such TCs which become relevant when a neuron responds to a complex sound can be derived from the critical bandwidths
characterize the frequency filtering of a neuron in the central nervous system for complex sound stimuli. Eqns. 5 and 6 indicate that, on the average, the bandwidths of single-tone TCs and of critical bands are strongly correlated. Figs. 5, 6 and 9 demonstrate, however, that on the single unit level there are often large differences between frequency resolution measured for a single-tone sound spectrum.
stimulus
Figs. 10-14. On the average, TC bandwidths and all spectral integration bandwidths increase signi~cantly with increasing CF for CFs above 500 Hz and are rather constant for lower CFs. This can be expressed by the following functions (CF above 500 Hz): (Fig.
10) log BW,,
= 0.710
0.5 1
2
510”
,
CF4.8kHz ’ 02
* 0.5
log CF
(I = 0.581; P < 0.001)
+ 0.804 (9)
(Ag. 11A) log BW,, (r=0.791;P<0.001)
.
1;
and for a complex
3.4.1. Relation between bandwidths and CF. The effective bandwidths (BWnrr), bandwidths of excitatory tuning curves (BW,&, CR-bands, and critical bands (CB,,, and CB,) are shown at various SPLs above the units’ tone thresholds as a function of CF in
=
0.835
log
CF-0.106
00)
(Fig. 11B) log SW,, = 0.732 (I = 0.676; P c 0.001)
CF 10.0kHr
and complex
log CF
+ 0.751 (11)
l
l.
l . l
2 ” 1
2
?5’ ktiz
Fig. 9. Comparison of single-tone excitatory tuning curves (dashed lines) with tuning curves for complex sounds, determined by the bandwidths of the critical bands from narrowband masking (solid lines). Obviously, frequency filtering measured by single-tone and complex-tone responses can differ substantially.
a1 0.2
0.5
1
2
5
10 20
Fig. 10. Effective bandwidths (BW,,,) of the neurons calculated from Eqn. 1, as a function of the neurons’ CFs. The regression line (dashed line) follows Eqn. 9. Open symbols and solid lines show behavioral CR-bandwidths from Watsons’ (circles), Pickle@’ (triangles) and Costalupes4 (squares).
The regression
BWTC k.Fj
tone
IO:
w 3dB A IOdB
level
above
threshold
coefficients
in the functions
of ef-
fective bandwidths, TCs and critical bands are similar, suggesting a common basis for their relation to CF. CR-bands show the largest scatter of the data
S, . +
points (Fig. 12) and the largest deviations of the coefficients from those of the other functions. All correlations are significant on a high statistical level. 3.4.2. Relation between bu~dwidt~s and sound inte~sity. Figs. 15 and 16 summarize how bandwidths depend on sound intensity. The average bandwidths of excitatory TCs and CR-bands increase with increasing SPL (Fig. 15). This is indicated by significantly larger bandwidths 60 or 80 dB above tone threshold,
compared
with those 3, 10 or 20 dB above
tone threshold (P < 0.05 at least; U-test) and by a regression analysis revealing significant correlations
CR-bandwidth tone
0.1
0.2
0.5
1
2
5
IO
level above
threshold
. 3dB .lOdB VOdB
20 kHz
nAA itA&:
. ” l
Fig. 11.bandwidths of excitatory tuning curves measured 3. IO and 20 dB (A) and 40. 60 and X0 dB (B) above tone response threshold as a function of CF. Bandwidths represent :hc distances between lowest and highest frequencies evoking an excitatory response at a given intensity irrespective of inhibitory areas that might intervene. The dashed lines indicate regressions after Eqns. 10 and 11. Solid lines and open symbols show behavioral CR-bandwidths (see Fig. 10).
(Fig. GA) log CR-band (r = 0.618; PtO.OO1) (Fig. 12B) log CR-band (r = 0.407; P< 0.001)
= 0.966
log CF-0.703 (12)
ktiz 100
lLOd;
:
.
. 4”
‘:. .
50
.6OdB
20
.8OdB
.
0.2
0.5
T 4
: A.. 0).
... :Lu. il’f . 3;
= 0.628 log CF + 1.13 (33)
(Fig. 13A) log CB,a,$ (r = 0.839: P
= 0.748 log CF -I- 0.664
(Fig. 13B) log CB,n, (Y= 0.770; P < 0.001)
= 0.634 log CF +
(Fig. 14A) log CBrrS (r = 0.782; P< 0.001)
= 0.693
(Fig. 14B) log CBrrs (r = 0.683; P < 0.001)
= 0.679
04) 1.226 (15) 0.1
log CF
+ 0.734 (16)
log CF +
1.115 (17)
1
2
5
10
20 kHz
Fig. 12. Bandwidths of critical ratio bands (CR-bands) sured 3, 10 and 20 dB (A) and 40,60 and 80 dB (B) above response threshold as a function of CF. The dashed lines cate regressions after Eqns. 12 and 13. Solid lines and symbols show behaviorai CR-bandwidths of the cat (see 10).
meatone indiopen Fig.
151 are, on the average,
For lower CFs, CB,
CBNBM
tone level .20dl3
20-
above
threshold
independent. Intensity independence
. LOd3
is a characteristic
intensity of criti-
cal bands from narrowband masking both, on the average (Fig. 16A) and for 62% of the single units studied (compare Figs. 5,6 and 9). Narrowband masking yields linearity of spectral filtering up to 80 dB above the units’ tone response thresholds, all the other measures show and/or non-linear
a widening of filter bandwidths spectral integration with increasing
tone level at least in some frequency ranges. 3.4.3. Symmetry of critical bands. Critical bandwidths from narrowband masking and two-tone sepa-
kHz-I 20-
ration were investigated for the symmetry of band limits with reference to the CF. We averaged the upper and lower band limits at each tone level above threshold separately for units with CFs below 1 kHz, between 1 and 4 kHz, between 4 and 8 kHz, between 8 and 16 kHz. The average upper and lower band lim-
IO= 53 2-
0.2,:,:
0.1-. B, 0.1
0.2
,,,, 0.5
1
, , 2
, ,,,,,,, 5
1 r 10
, ,CFL
CBTTS
20 kHz
Fig. 13. Bandwidths of critical bands from narrowband masking (CB,,,) measured 20 and 40 dB (A) and 60 and 80 dB (B) above tone response threshold as a function of CF. Regression lines (dashed lines) following Eqns. 14 and 15 are shown as well as behavioral critical bandwidths from narrowband masking by Pickles6’,6” (open circles) and Nienhuys and Clarks6 (open squares).
between
bandwidths
tone level l 20dB ACOdB
above
threshold
. t A%
c--
and tone level above threshold
(SL) CF < 3 kHz: log BW,, PC 0.001)
= 0.014 SL f 2.24 (r = 0.631;
CF > 3 kHz: log SW,, (~
= 0.009 St + 3.08 (r = 0.366;
(18)
(19)
CF < 3 kHz: log CR-band 0.335; P < 0.001)
= 0.012 SL f 2.15 (r =
CF > 3 kHz: log CR-band 0.215; P < 0.001)
= 0.006 SL + 3.01 (r =
(20)
(21)
A tone level dependence of CBTTS occurs only for CFs > 3 kHz: log CB,, = 0.008 SL + 3.25 (r = 0.488; P < 0.001) (22)
Fig. 14. Bandwidths of critical bands from two-tone separation (CB,) measured 20 and 40 dB (A) and 60 and 80 dB (B) above tone response threshold as a function of CF: regression lines (dashed lines) following Eqns. 16 and 17 are indicated and behavioral critical bands from narrowband rnasking~~.~‘.~~are also shown.
CF >3kHz CFc3kWz
.
.
;
0.1 ’
CF>3kHz
1
20
204
CF<3kHz,
I
:
LO
1
1
I-
I1
8OdB 20
60
40
60
80dB
3kHz
.
i
;-
z8 :
i CF 23kHz
‘
1,
3 tone Fig.
15. Bandwidths
(B) as a function
above
level
of tuning of tone level
10 20 LO 69
curves above
average increase
of bandwidth
Fig for units with
lines indicate
with increasing
$0 -LO 60 above threshold
tone level
and CR-bandwidths
threshold
CFs below and above 3 kHz. The regression nificant
80dB
threshold
(A)
Ii*
$O
,I-
I,
a sig-
level.
16. Critical
bandwidths
from
narrowband
separation
threshold
for units with CFs below and above 3 kHz. CFs above
as a function
3 kHz
digm (B), the bandwidths the tone levef
of
masking
two-tone units with
(B)
60dE
tone
in the two-tone
(A) and
level
above
Except
separation
are, on the average,
for
para-
independent
of
its are placed around an average CF at each frequency range and are plotted in Fig. 17. They show that critical bands are formed asymmetrically around center frequencies below 1 kHz and above 4 kHz. For neurons with CFs below 1 kHz the above-CF part of and CBrrs) is wider than the critical band (CB,,, that below CF. For neurons
with CFs above 4 kHz
the below-CF part of the CB is wider than that above CF. For units with CFs between 1 and 4 kWz the critical bandwidths are formed symmetrically around CF. 3.4.4. Bandwidths and other neural characteristics. We tested whether widths of TCs, CR-bands and critical bands are related to spontaneous activity, tone response latency (measured 40 dF3 above tone response thr~shoid), tone response threshold, the type of tone response (PSTH pattern) and type of binaural response. Tone response latency and threshold were compensated for CF-dependence. Statistically significant relationships - either ?-test (PSTH pattern and binaural response type) or re-
Fig.
17.
hands,,,, above center
Average (A)
upper
and critical
thresholds. frequency
and
lower
bands,,,
bandlimits (B)
of
critical
at the 4 tone
levels
Bandwidths are placed around the average (f,-) for units in 5 CF classes as indicated. On
the linear frequency
scale (abscissa)
above
4 kHz
asymmetrical
around branch
CF. For units with CFs below 1 kHz the above CF is wider than that below CF. while units with CFs above
have
units with CFs below critical
band
filters
4 kHz have wider branches below CF. Symmetry bands is seen in units with CFs between 1and 4 kHz.
1 and
formed
of critical
153 gression analysis (spontaneous activity, tone response latency and threshold) - did blot occur between any of the bandwidth measures and any of these other neural response characteristics. That is, the neural bandwidths of frequency resolution, filtering and spectral integration do not depend on and are not related to spontaneous activity, tone response latency and threshold and tone response and binaural response type. There occurred, .however, relationships between the bandwidths of CR-bands and critical bands (CBNBMand CBrrs) and rate-intensity functions of the same units. Units with single-peak functions in response to tone bursts (class B) had larger critical bands,aM than units with other rate-intensity functions (P < 0.01, U-test). They had larger critical bandsrrs than units with multi-peak functions (class C; P < 0.02) and larger CR-bands than units with increasing or saturating functions (class A; P < 0.05). It seems that, on the average, units with single-peak rate-intensity functions to tone bursts have larger bandwidths of spectral integration than units with other spike-rate functions. 4. DISCUSSION
4.1. General aspects
The placement of electrodes allowed us to selectively record from units in the core of the ICC. The range of characteristic frequencies of the neurons (132 Hz-33 kHz) indicates that our sample covered the whole hearing range of the cat. The most sensitive units in our sample had tone response thresholds comparable with behavioral thresholds in the cat (Fig. 4A)4g. The threshold variance in the order of 30-40 dB for units with similar CFs can be explained by threshold differences of auditory nerve fibers”3. These threshold data together with a relatively low occurrence rate of units with purely phasic tone responses (Table I), with most units changing their frequency response patterns to pauser patterns with increasing tone intensity (Table I), and occurrence of units with complicated inhibitory fields and off-response areas (Figs. 5 and 6), which all are properties of ICC or dorsal cochlear nucleus units in unanesthetized animals’**“, indicate that the response properties of our present sample of neurons may not be severely influenced by the anesthetics used,
4.2. Pri~~ipal~~di~gs The further discussion shall be structured according to the following list of our principal findings: (1) The frequency dependencies of the filter bandwidths derived from the 5 different measures of frequency resolution in ICC neurons (effective bandwidth, singIe-frequency tuning curve, CR-bands and critical bands from narrowband masking and twotone separation measurements) are similar to those found in behavioral tests of frequency resolution. (2) biggie-frequency tuning curves (the conventional tuning curves) are often inadequate to describe frequency resolution for complex sound spectra although the bandwidths of these tuning curves correlate, on the average, with the bandwidths of spectral frequency resolution (CR-bands and critical bands). (3) Areas of luferul inhibition, if exerting a total suppression of tone evoked activity, strictly confine the extension of critical bandwidths. (4) Shapes of neural critical bandwidths are arymmetric on a linear frequency scale relative to the CF in most of the frequency range of hearing. (5) Average neural critical bands (CBNBM)have constant, intensity-independent bandwidths (at least between 20 and 80 dB above the neurons’ response thresholds or between about 5 and 110 dB SPL). Bandwidths of tuning curves, CR-bands and of CB.ns (only for units with CFs > 3 kHz) increase, on the average, with increasing sound intensity. (6) Critical bandwidths are encoded by changes of response rates in neurons of the ICC. (7) Frequency resolution, spectral filtering and integration are neural properties of the ICC that are independent of tone response threshold, response latency, spontaneous activity, tone response type, and binaural response type. 4.3. frequency dependence ~ffrequency resolution The frequency dependence of frequency resolution measured in psychophysical tests (critical bands and CR-bands) is well documented for man and many mammals including the cat”7*61.76.g6. All available data for man and mammals (except for one bat44) can be described by functions of the form shown by Eqns. 9-17. If we take the available behavioral data on critical bands55*61*63 and CR-bands4.6’.89 of the cat and calculate the average bandwidth-frequency relationship we obtain Eqns. 23 and 24:
154 log
CB,,,
=
0.655
f
+
0.606
(r
=
P < 0.001) log
CR-band
P< 0.001)
0.950; (23)
=
0.882
f -
0.496
(r
=
0.941; (24)
The regression coefficients of these behavioral data are not significantly different from each other. The regression coefficient of the behavioral critical band function (0.655) does not differ significantly from those of the neural measurements (Eqns. 14-17). This is also the case if Eqns. 24 and 12 (CR-bands) are compared. We can conclude, therefore, that our measurements of neural bandwidths of frequency resolution in the ICC of the cat demonstrate the same average frequency dependence of bandwidths as found in behavioral tests. This frequency dependence of filter bandwidths is of cochlear origin as relations between critical bandwidths, frequency and dependence of cochlear place’s*33 and frequency critical bands5.65 and CR-bands” in auditory nerve fibers indicate. If we compare the absolute values of critical bands from behavioral narrowband masking tests5h,h’*” with the critical bands of ICC units measured under similar narrowband masking conditions, we find that average neural bandwidths are larger than the behavioral values (Fig. 13). This discrepancy may have its origin in the difference between tone and noise levels at which the band narrowing procedure for critical band measurement started. In the behavioral tests this difference was average 6 dB smaller (the noise was 6 dB louder) compared to that required for masking ICC units. In other words, the average ICC neuron in the behavioral test was overmasked by 6 dB. This 6 dB difference is equal to a factor of 4 for bandwidth for which behavioral and neural means differ in Fig. 13. If this explanation is true, the cats used the neurons least sensitive to masking (those with the smallest filter bandwidths) in the behavioral masking tests, for detecting the tone bursts in noise. Our criterion of the response-rate difference between tone and intertone intervals for assessing the critical bandwidth could have also caused neural bandwidths larger than behavioral ones. Neural critical bandwidths become smaller when the percent rate difference used as criterion is increased. Thus, in perception, a more than 20% rate difference (our
present criterion) may be necessary for detecting differences between spectral energy inside and outside a critical bandwidth. The comparison of behavioral and neural CRbands (Fig. 12) yields similar average values if neural bandwidths derived 3-20 dB above tone response threshold are compared with the behavioral data (Fig. 12A). At higher tone levels, average neural CR-bands deviate from the behavioral measurements (mainly for rather low-frequency neurons~, that is, signal detection in broadband noise stays constant when measured behaviorally but worsens markedly in neural measurements when the sound intensity is increased.
Some suggestions
about how in-
tensity dependence of neural filtering could be compensated for in the behavioral detection test will be made later. 4.4. Relationships among measures of frequency
re-
solution in ihe ICC
On the one hand, statistically
significant
relations
among the widths of spectral integration bands and single-frequency tuning curves are obvious from Eqns. 3-8. On the other hand, the single neuron data shown in Figs. 5 and 6 indicate that great differences of widths can occur among all measures of frequency resolution if related to an individual neuron. This seeming contradiction originates in the data evaluation. The first evaluation tells that if one sort of filter bandwidth is wide (narrow) all the others are likely to be wide (narrow) too. These relations among filters can be predicted from and are caused by their similar frequency dependence (Eqns. 10-17). Figs. 5 and 6. however, demonstrate how peripheral filtering is qualified in single unit responses depending on the kind of sound to be processed. The conventional single-frequency excitatory tuning curves can be regarded as a framework in which spectral integration might be expected. Substantial deviations of shapes from those of auditory nerve fibers4” occurred in 62% of the tuning curves measured in the present study. This high proportion of higher order shapes in the ICC, which is very similar to the 64% found in the IC of the mouseZ’ and the occurrence of inhibitory areas in 91% of the units studied manifests the fact that peripheral frequency resolution has been modified by various kinds of excitatory and inhibitory interactions in the pathway to the IC
155 or in the IC itself. Our results show that excitatory and inhibitory interactions and other mechanisms in-
CR-bandwidth
fluencing the response rates of ICC neurons are determinants for the adjustment of the bandwidths of spectral integration (effective bandwidths, CRbands, critical bands). This shall be evaluated in the following. 4.4.1. CR-bands. Areas the extension
of total
inhibition
of critical bands and excitatory
limit tuning
curves but not of CR-bands. This shows that tuning curves and CBS are directly related to frequency selective filtering coupled with excitatory tone response areas. CR-bands, per definition, reflect the strength of a response to noise compared to that to a tone within the noise bandwidth. If the masked threshold of that tone is seen as the point of stimulus dominance by the broadband noise through a ‘swamping’ of the signal activity53 then the difference of tone level and noise spectrum level (critical intensity ratio) is an indicator for the noise bandwidth that contributes to masking the tone and thus might be regarded as an, although indirect, measure of a filter bandwidth (CR-band). This CR-band concept derived from psychophysics of broadband masking29,36 seems to be applicable to auditory nerve fibers18,20* 25,83;however, as the present results show, it is not generally applicable to neurons in the ICC of the midbrain. Masked thresholds cannot be defined in neurons with off-responses, tone-response dominance even at highest noise levels, absence of a tone response, and equality of responses in tone+noise and noise intervals at several noise levels (at a given tone level). These response types made it impossible to determine CR-bands in 41 of 443 measurements. Further three interactions of tone and noise responses and of excitation and inhibition are found, which systematically influence CR-bandwidths as demonstrated in Fig. 18. (a) Units in which noise enhances the tone response at least by 20% of the response rate without noise at some combination of tone and noise level (an example is unit 26 in Fig. l), generally have smaller than average CR-bands (Fig. 18). Obviously, there is a higher noise level necessary to mask an increased tone response, although the increase is due to the noise. Enhancement of tone-burst responses by continuous noise has been described for the auditory nerve20*67, however only in about 8% of the mea-
0.1
ci.2
05
1
2
5
XI
20
Wz
Fig. 18. CR-bands plotted as a function of CF of neurons which showed certain response conditions at any of the tone levels at which tests have been conducted. Circles: units in which noise enhanced the tone response. Triangies: units without inhibitory fields below or above or on both sides of the CF. Upside down triangles: units which did not respond to noise. (Further explanations in the text.)
sured masking sequences. In the ICC, this non-linear interaction of excitatory tone and noise responses occurred in 23% of all masking sequences and led to the many cases of small CR-bands shown in Fig. 18. Continuous noise does not only mask tone responses in ICC neurons (at high noise levels) but can, at certain combinations of tone and noise levels, improve the responses to tone bursts in a considerable number of units. (b) Units without an excitatory response to noise generally have extremely broad CR-bands (e.g. Fig. 6A) which, if regarded as filter bandwidths would be meaningless because they would often cover more than the audible frequency range of the cat (Fig. 18). Noise, if not producing an excitatory response, obviously exerts a powerful inhibition on the tone response so that at the masked threshold, total inhibition of sound evoked responses is reached at large signal-to-noise ratios. Total inhibition of a tone response by noise has not been observed in the auditory nerve and ventral cochlear nucleus*‘. (c) Units without inhibitory areas or with inhibition only on one side of the excitatory tuning curve often have larger than average CR-bandwidths (Fig. 181, especially if masked thresholds are determined at higher sound intensities. This suggests that an influence of inhibitory areas, induced by the broadband noise itself, suppresses the masking effect of the noise on the tone response. A’ differential ef-
156 feet of inhibitory side bands on the excitatory area of ICC neurons of awake rhesus monkeys has already been demonstrated’“. Inhibition was stronger at the
bandwidths from effective bandwidths can be explained by non-linear interactions of tone and noise responses in CR-bands as discussed before. These in-
edges of the excitatory area compared with the center. If this effect was working in our present measurements it could explain a relatively strong inhibition
teractions are not present in measurements of effective bandwidths. We can only speculate about reasons why effective bandwidths in most of the units are
on the masking noise within the CR-band by noise outside while the tone in the center of the band would
larger than 3 dB bandwidths of the tuning curves. Close to the units’ response thresholds, off-CF tones
be less affected. The consequence is that signal-tonoise ratios at the masked thresholds and thus CRbands should become narrow for units with strong in-
seem to be less effective than broadband noise in eliciting an excitatory response possibly because excitation by noise is centered at CF while tone excitation
hibition on both sides of the CF, or wide for units with only weak inhibitory areas. Lack of or only comparatively weak inhibition, without substantial increase
in tuning curve measurements is not. 4.4.3. Tuning curves. With a few exceptions Fig. 5D) critical bands (CB,,, and CB,)
with increasing sound intensity, as seen mainly in frequency areas below CF and for units with CFs below 8 kHz (Fig. 8) thus can be regarded as a major reason for the marked increase of the CR-bandwidths of these neurons with increasing sound intensity (Figs. 12 and 15B). Lateral inhibition as seen in most ICC neurons obviously contributes to a reduction of the masking effect of a broadband signal on a narrowband signal, i.e. it reduces the probability of a tone response to be masked (or ‘swamped’) by the response to a broadband stimulus like noise. This conclusion is in harmony with psychophysical tests of signal-masker discrimination in which, by a non-simultaneous presentation of the stimuli, lateral inhibition has been shown to influence both signal and maskAll these systematic effects on CR-bandwidths demonstrate that CR-bands of ICC neurons cannot simply be regarded as equivalents of frequency filters. 4.4.2. Effective bandwidths. Effective bandwidths of auditory units should correspond to the 3 dB bandwidths of the excitatory tuning curves and to the 3 dB CR-bandwidths if all three measures arise from the same linear. rectangular filter26.27. In our sample of ICC neurons, however, these bandwidths differ. Effective bandwidths are often larger than the 3 dB
not reach into low-frequency tails and they never reached into excitatory areas of tuning curves separated from the area around the CF (e.g. Figs. 6B and 9). This result points to an important difference between tuning and filtering in response to single-frequency and multi-frequency sounds. In ICC neurons, the frequency range in which excitatory responses can be elicited is not necessarily congruent with that range over which excitation (measured via discharge rate) can be integrated. This statement has to be qualified in so far as in the present experiments integration has been studied only for frequency ranges centered around CFs of the units. Further investigations have to clarify whether spectral integration is possible around frequencies located, for example, in the tails of tuning curves. Nevertheless, the present data clearly demonstrate a sound stimuius-dependent separation of the status of frequency filtering in ICC neurons: single-tone filtering is defined by the frequency response area; complex sound filtering is defined by the bandwidths of spectral integration. One obvious implication of this result is that on the basis of single-frequency tuning curves the responses of ICC neurons to complex sound spectra cannot be predicted. Experimental demonstrations for that can already be found in the literature22.““.7’. There are two further indicators in our present
bandwidths of tuning curves and larger than the 3 dB CR-bands (P < 0.01, U-test, in both cases). A difference is not seen if widths of tuning curves and CRbands both 3 dB above tone response threshold are compared. We may suggest, therefore, that ICC neurons close to their tone threshold at CF do not behave like linear rectangular filters. Deviations of CR-
data showing that excitatory tuning curves of neurons in the IC may not adequately predict responses to complex sound. First, we observed areas around excitatory tuning curves in which sound has a faciiitating effect on responses caused by stimuli at the units‘ CFs (e.g. Figs. 5C, 6C and Fig. 9. unit 26). Facihtation can become relevant only by stimulation with
er37.38
(e.g. did
157 complex sound and may function responses
as an amplifier
for
to certain
frequency components in the CBNBM extend well into facilitation
sound. Since areas (Figs. 5C and K), these areas constitute an essential part of spectral integration. Second, areas of off-response induction to tone bursts in noise are found within or outside excitatory tuning curves, mainly at higher sound intensities (e.g. Fig. 6D). Although off-responses can occur in response to CFtones within the excitatory tuning curve, off-response areas indicate an interaction of frequency components
over considerable
bandwidths
and thus
relate to complex sound processing and spectral integration. Unit 36 (Fig. 6D) is an example of the possibility of spectral integration within an off-response area. 4.4.4. Critical bands. Critical bandwidths from integration of two-tone responses (CBrrs) show some features which are intermediate between single-tone filtering and critical bands from narrowband masking. First, CB,, are, on the average, wider than tuning curve bandwidths but narrower than CB,a, (Table II). Second, CB,, (in neurons with CFs > 3 kHz) increase less with increasing sound intensity than bandwidths of tuning curves (Figs. 15 and 16B; Eqns. 19 and 22), while CB,,, do not, on the average, increase at all (Fig. 16A). At 60 and 80 dB above tone threshold, average widths of CBrrs and CB,a, are very similar (Fig. 16). This means that for lower tone intensities (mainly 20 dB above tone response threshold) there is a ‘deficit’ of integration ability for two-tone excitation within the spectral integration bandwidths defined by the narrowband masking paradigm. In the low-intensity range, phase-locking to the envelope of the two phase-locked tones may have to be considered as one factor influencing spectral integration as measured by response rate. The determinateness of the response and the response strength (spike rate) to the amplitude modulation of a tone increases in IC units up to about 35 dB super-threshold tone level@’ (G. Langner, personal communication). Depending on the frequency separation, two phaselocked tones can produce low-frequency amplitude modulation to which ICC units could lock the more consistently and with higher discharge rate at 60-80 dB compared with 20 dB super-threshold tone level. Thus, the frequency separation between the two tones for reaching a constant spike-rate increase (our
criterion) intensity,
could become larger with increasing so that we measure larger CBrrs.
tone
4.5. Symmetry of critical bands Except for the frequency range of CFs between 1 and 4 kHz, average critical bands (CBNBM and CB,) are asymmetrical on a linear frequency scale with regard to CF (Fig. 17). In units with CFs below 1 kHz, above-CF branches are wider, in units with CFs above 4 kHz above-CF branches are narrower than below-CF branches. A similar kind of asymmetry is found already in tuning curves of cochlear nerve fibers24,40. The only difference is in the range of symmetry which seems to be wider in the colliculus (l-4 kHz) than in the auditory nerve (l-2 kHz). Obviously, bandwidths of spectral integration in ICC units follow the basic asymmetries of excitation patterns within the cochlea’,7, however, without displaying low-frequency ‘tails’ as single-frequency tuning curves do. Data from psychophysical measurements in man are non-conclusive with regard to the symmetry of critical bands. They depend very much on the proposed hypothesis about the filter shape and on the method of filterband determination. Basically symmetric filters were found by Schafer et al.74, Pattersons9, Margolis and Small46 and Fidel1 et al.28 for center frequencies between about 100 Hz and 8 Hz. On the other hand, asymmetries of the kind reported in the present study have been shown in other studies for center frequencies between 2 and 8 kHz (aboveCF branch of the filter narrower than the below-CF branch)3.3~.~ and for a CF of 400 Hz (above-CF branch wider)14. Thus, in cases where asymmetries of critical bands with regard to center frequency have been found psychophysically in man, they are in agreement with our neural data from the IC of the cat (Fig. 17).
of bu~d~idt~s of spectral integration 4.6.1. CR-bands. On the average, signal-to-noise
4.6. Znte~sity dependence
ratios at the masked tonal threshold in broadband noise increase and, as a consequence, CR-bands widen with increasing sound intensity (Fig. 15B). As already discussed, this non-linearity can be interpreted, at least in part, on the basis of our data on inhibitory fields around excitatory tuning curves and
158
their influence
on interactions
of tone and noise re-
sponses. Here we have to discuss the intensity dependent neural coding of tone signals in noise with regard to the available psychophysical results of the caf”.s”. Watson’s data indicate intensity independence of CR-bands measured close to absolute threshold up to about 50 dB above that threshold over the whole frequency range tested (0.125-16 kHz). CostaiupesJ extended these data for tone ieveis of about 70-85 dB above absolute threshold and found intensity independence of CR-bandwidths for center frequencies
below about 4 kHz. At 8 and 16
signal-to-noise ratio (increasing CR-bandwidth) with increasing sound intensity. The combination of the worsening of the signal-to-noise ratio at the neuronai level in the IC (constant criterion employed) with the improvement of the psychophysical tone detection in noise (criterion change on the basis of the neural response) may lead to a mutual compensation of both non-linearities. The result then could be the observed overall linearity of CR-bands in the behavioral test&s”. This hypothesis will be tested by comparison of the intensity dependence of neural CR-bands in the ICC with that of intensity difference limens
kHz, however. bandwidths increased with increasing level for tone levels higher than about 60 dB above
from behavioral
absolute threshold. Our present single unit data show an increase of CR-bandwidths with increasing level from tone levels 3 dB to 80 dB above the units’ response thresholds. This increase is. on the average. larger for units with CFs below 3 kHz than for those with CFs above 3 kHz (Eqns. 20 and 21; Fig. 15B). Obviously, there are marked differences with regard to intensity dependence between neural data on CRbandwidths from the ICC and psychophysical measurements. In order to explain the psychophysical intensity independence of tone-signal detection in broadband noise on the basis of intensity-dependent neural behavior. the following has to be considered. If we suggest that tone detection in noise depends on a neural increment response of neurons responding to the tone on the background of their response to the noise, similar to our rate criterion used to assess the masked threshold (Fig. 1). then the subject evaluates
4.6.2. Criticul buds. One important result of the present and a previous study”’ is the intensity independence of average neural critical bandwidths determined in narrowband masking tests (Fig. 16A). As described in the Method section, the intensity independence of CB,,, follows from the same criterion for masked threshold assessment as used in the CR-band measurements. Does this mean that spectral filtering as directly measured by bandwidth variations in the critical-band tests is intensity independent, whereas spectral ~ff~e~~ff~i~~ within the filter bandwidths (CR-band measurement) changes with changing sound intensity? This question can be answered by the calculation of the ratio between tone intensity and the total noise intensity at the masked threshold within critical bandwidths from narrowband masking tests. ‘The calculation runs according to Eqn. 2 with the only difference that instead of the spectrum level of the broadband noise the total level of the noise within the critical bandwidth is inserted. The resulting level differences between tone and total noise levels at the masked thresholds are plotted in Fig. 19 as a function of the characteristic frequency of the neurons (A) and as a function of the sound pressure level of the tone (B). Apparently, these ievcl differences are independent of frequency and sound intensity over the remarkable range from 5 to 110 dB SPL. Statistically significant relations between the level difference and CF or SPL do not exist. Thus Fig. 19 presents a clear answer to the question in that spectral integration within critical band filters turns out to be intensity independent. This is an important result since it demonstrates that frequency resolution - spectral filtering and in-
a difference iimen of intensity between tone+noise and noise. i.e. a difference iimen of response rate between the tone-t-noise and the noise response. Sound intensity discrimination in psychophysical tests has been shown to improve with increasing intensity”ih.3Y.This means that the neural increment response to the tone above the noise background necessary for tone detection in psychophysical tests can become smaller with increasing sound intensity. In other words. behavioral tests indicate a change of the criterion or a change of the available information for tone detection with regard to a constant neural increment response. Our criterion for defining the masked threshold at the neural level was constant (20% rate difference), and on that basis we measured an increasing
measurements
(Ehret.
in prepara-
tion).
1.59 determined
on the basis of bandwidth
variations
of a
filter-centered sound stimulus (e.g. narrowband loudness summation in multitone masking 34+46*i4*88, they are of concomplexes 3**75.97,lateralization78) stant width over a broad intensity range. If they are determined by methods which include a stimulus with sound energy outside the critical band filter (e.g. masking by comb-filtered and notch-filtered noise45*60.82.90,or single-tone or two-tone maskit@) critical bandwidths have been shown to increase with increasing sound intensity. 4.7. mechanisms offrequenc~ resoIutiofl and .
I
0
t
,
I
I,,
10 20
f
30
,
/
I
I,,
LO SO 80
l
I,,
70
,
80
I,
I
I
t
90 100 llOd6
Fig. 19. Signal-to-noise ratios at the masked tonal thresholds (critical ratios) calculated (see Eqn. 2) by using noise bandwidths equal to the critical bandwidths measured in the narrowband masking paradigm (CBIURM)and plotted as a function of characteristic frequency (A) and sound pressure level of the tones (B). Both plots show that the critical ratios of the neural critical bandwidths are largely independent of frequency and sound intensity. That is, spectral integration within critical bandwidths is a system-inherent constant feature at the level of the ICC.
tegration - on the single neuron level in the ICC is virtually independent of sound intensity. This conclusion holds if sound energy is concentrated within a single critical bandwidth. If, as in the broadband masking tests (critical ratio measurements) spectral components outside a critical band filter can influence processing within the filter, spectral integration becomes intensity dependent probably by non-linear interactions of excitatory and inhibitory influences of the masker on the tone signal. These physiological results from single neurons in the IC of the cat have parallels in psychophysical measurements on humans. If critical bandwidths are
of criti-
cal bands In all measurements of frequency resolution of neurons in the ICC described in this study, dischargerate changes of the neurons were the decisive parameter which lead to the determination of filter bandwidths. Since the neural critical bandwidths agreed well in all their features with the psychophysical ones, we suggest that auditory frequency resolution with relevance to perception is accomplished through a spike-rate code in single neurons of the ICC. Thus, the ICC may mark the endpoint of the process of frequency resolution in the auditory system which starts with the spatial resolution in the cochlea., Recent measurements of critical bandwidths in collicular (wave V) evoked potentials in ma@ support this conclusion, because the bandwidths determined by wave V amplitude changes agreed well with those derived psychophysically. We showed that the filter bandwidths of singfe neurons in the ICC were strongly influenced by areas of inhibition and facilitation next to the excitatory area of a neuron’s single-frequency tin&g curve. These lateral inhibitory and facilitative “inmuences might have their origin in the regularity of the layered structure of the ICC which is parafleled functionally by the layers of the isofrequency planes4’* 54,57. Connections between the isofrequency planes which have been demonstrated anatomically5’ could convey the inhibitory and facilitating influences. It is interesting to note that high resolution electrophysiological measurements of the bandwidths of isofrequency planes in the cat42 showed that our neural criticat bands derived from the n~rr~wba~d maskin paradigm were just twice as wide as the frequency bandwidth of one isofrequenc?y:plane (at agiven cen-
160 ter frequency
of the CB,,,
That is, a critical bandwidth
and frequency
plane).
would extend from the
curves, effective bandwidths, critical critical bands derived using narrowband
ratio bands, masking and
center of a given isofrequency plane to the neighboring planes both at higher and lower frequencies. The
two-tone separation paradigms) have been obtained from the responses of these neurons at sound pres-
critical bandwidth, of which in 1970 J.V. Tobias said in the foreword to Scharf’s chapter on critical bands74 ‘ the other senses lack the mysteriousness of this
sure levels (SPL) up to 80 dB above the units’ response thresholds (nearly 110 dB SPL). Among our
unseen - perhaps nonexistent - but pervasive auditory filter’, would exist in the functional anatomy of the central nucleus of the IC. One important finding of our present study was that frequency resolution, including bandwidths of tuning curves critical ratios and critical bands are properties of neural coding in the ICC that do not depend on spontaneous activity, tone response threshold and latency, tone response (PSTH pattern) and binaural response type. Frequency resolution is a largely independent feature of information processing in the IC. Thus, we can infer that different sorts of information about a sound signal are processed simultaneously by every ICC neuron. A neuron can 1at the same time, be in the modes of, for example, spectral filtering, binaural processing and rhythm or modulation coding. Such a parallel processing of different features of a sound stimulus by different aspects of a neuron’s response could be a general property of higher order auditory neurons and may give rise to maps beyond tonotopicity on the neuronal substrate in higher auditory centers of the brain41~48~8”~85-X7~
results are the following: (1) Narrowband masking measures of critical bands from ICC neurons closely parallel behavioral measures using the same stimulus paradigm. (2) Frequency resolution power as measured by critical bandwidths varies little as a function of stimulus
intensity.
(3) Tuning
curves of ICC neu-
rons provide no simple basis for predicting the frequency filtering of the same neurons excited by complex sound spectra. (4) There is a frequency dependence of all measures of frequency resolution similar to that found in psychophysical determinations of critical bandwidths. That is. spatial frequency resolution in the cochlea is the origin for the resolution found in the ICC and in behavioral tests. (5) Lateral inhibition at the level of the ICC clearly plays a role in frequency resolution. (6) Frequency resolution is encoded by response rate changes of ICC neurons and is independent of tone response threshold, response latency, spontaneous activity, tone response type. binaural response type. It is concluded that spectral analysis of sound is established by processes, including lateral inhibition, independent of other basic response properties of neurons at the level of the ICC.
5. SUMMARY ACKNOWLEDGEMENTS
The central nucleus of the inferior colliculus (ICC) is a center of convergence of brainstem input and is critical for auditory information processing. Here, the analysis of complex sound spectra by single neurons in the ICC is investigated. Several measures of frequency resolution (excitatory/inhibitory tuning
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This study has been supported by the Deutsche Forschungsgemeinschaft (Eh 53/7-l), by NS-10414, and by HRI and the Coleman Fund. We thank Drs. Jenkins, Schreiner, and Snyder for helpful discussions and technical support.
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