Adaptation effects on amplitude modulation detection: Behavioral and neurophysiological assessment in the goldfish auditory system

Hearing Research, Elsevier

19 (1985) 57-71

57

HRR 00623

Adaptation effects on amplitude modulation detection: Behavioral and neurophysiological assessment in the goldfish auditory system Sheryl Coombs

and Richard

R. Fay

Parmly Hearing Instrtute, Loyola Uniuersrty of Chicago, Chicago, IL 60626. U.S.A. (Received

22 April 1985; accepted

18 June 1985)

The ability of goldfish to detect the presence of amplitude modulations (AM) impressed on 200, 570 and 800 Hz tones was measured under stimulus conditions producing intermittent, short-term adaptation and continuous, long-term adaptation. Sensitivity to AM under intermittent conditions increased as a function of modulation rate, with thresholds of AM detection occurring between 10 and 25% modulation at 10 AZ and around 2% modulation at 100 Hz. AM sensitivity was independent of carrier frequency and did not change under randomly varying intensity changes. Under long-term adaptation, thresholds of AM detection ranged from 1.3% at 100 Hz to 2.1% at 10 Hz, showing increased sensitivity and less dependence on modulation rate. The effects of overall intensity on AM sensitivity were the same for both conditions, with sensitivity being relatively independent of overall signal level at 10 Hz modulation and dependent on level at 100 Hz. The responses of goldfish auditory neurons to modulated and unmodulated signals were measured under stimulus conditions similar to those for behavioral studies. Single saccular neurons responded to modulated signals with both an increase in average rate above that evoked by the unmodulated signal and with phase-locking to the AM envelope. Rate increments and phase-locking responses were observed in neurons showing significant short-term adaptation to the unmodulated signal, whereas neurons showing no increase in rate or synchronization to the AM envelope showed little or no adaptation to the unmodulated signal. The effects of overall intensity, modulation rate and adaptation duration on neural responses were similar to behaviorally measured effects. These results show that adaptation affects AM detection and that phase-locking to the AM envelope is the most likely basis for behavioral detection. adaptation,

amplitude

modulation,

eighth nerve, goldfish

Introduction Preliminary studies on the ability of goldfish to detect amplitude modulation (AM) impressed on pure tone bursts [2] showed a substantial decrease in sensitivity to AM relative to that previously measured under conditions in which the pure tone was on continuously [5]. Increased sensitivity under conditions which presumably caused long-term adaptation in the nervous system suggested to us that adaptation processes might have an effect on AM detection. Moreover, a number of neurophysiological studies on the response properties of central auditory neurons to amplitude-modulated signals have identified, on the basis of short-term adaptation patterns, cell types that are particularly responsive to amplitude modulation [20,12]. Cells showing rapid and complete adaptation are typically the most responsive to AM signals. It is not 0378-5955,‘85/$03.30

0 1985 Elsevier Science Publishers

unusual for these cells, noted in the mammalian cochlear nucleus [20,12], and catfish medullary and midbrain nuclei [21], to show neural enhancement of the AM envelope, with gains up to 20 dB. Such enhancement has not been observed at the level of eighth nerve fibers in mammals [12], but has been noted for goldfish saccular fibers [5]. Unlike mammalian eighth nerve fibers, saccular fibers in the goldfish show a variety of short-term adaptation patterns [5,3], including a phasic, onset type like that described as being very responsive to AM signals in the mammalian cochlear nucleus

WI. The experiments reported here were designed to examine the role of short- and long-term adaptation processes in the detection and encoding of AM signals by the goldfish auditory system. Behavioral measures of sensitivity to sinusoidally amplitude-modulated (SAM) tones of different over-

B.V. (Biomedical

Division)

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all intensities, carrier frequencies and modulation rates were made under conditions of intermittent and continuous adaptation. Neurophysiological measures were made under identical stimulus conditions to determine the neural response of single saccular nerve fibers to modulated and unmodulated signals. Methods Behavioral studies Classical conditioning techniques similar to those used in previous studies [7,10] were used to train goldfish to respond to the presence of amplitude-modulated tones. Briefly, fish were restrained underwater in a test tank and water movements created by the respiring fish were measured with a thermistor. Reflex inhibition of respiration was conditioned to a sound stimulus by pairing the stimulus and a mild electric shock. The respiration rate occurring during the 7 s interval preceding a sound stimulus (A) was compared to the rate during the stimulus (B) to yield a suppression ratio of B/A + B. Ratios of 0.4 or less were defined as detections or ‘yes’ responses which resulted in a computer adjustment of the next stimulus to be less detectable. Following a ‘no’ response ratio higher than 0.4, the stimulus was adjusted to be more detectable. The animal’s threshold of detection was computed by averaging the signal level mid-way between a ‘yes’ and ‘no’ response over 8 yes/no transitions. Absolute thresholds to unmodulated pure tones were obtained for each fish to determine sensation levels prior to measurement of AM sensitivity. The test tank was a 20 cm diameter and 25 cm high cylindrical jar made of 3 mm thick nalgene. An underwater sound speaker projected upward from the bottom of the tank and was embedded in gravel to produce a reasonably flat frequency response in the tank. The tank sat on a 5 cm thick slab of limestone which was isolated from substrate vibrations with industrial shock absorbers. The entire apparatus was housed in a sound-attenuating single-walled IAC chamber. AM signals were produced as previously [5] by electronically multiplying a sinusoidal carrier frequency (F,) by a sinusoidal modulator frequency (F,). A DC component added to the modulation signal was adjusted so that the output

of the multiplier was an AM signal having an envelope periodicity equal to the frequency of F,,. The modulation percentage (or modulation depth, m) was controlled with a programmable attenuator inserted between the F,, source and the multiplier. The resulting AM signal was then led to a manual attenuator which controlled the overall sound pressure level, to a power amplifier and finally to the underwater loudspeaker. The spectra of SAM signals consist of a major band at the carrier frequency and two side bands at F, + F, and F, - F,. Attenuating the modulator signal by 6 dB relative to that producing 100% modulation results in a 50% modulated signal with side bands 12 dB down from that of the carrier. To determine if the percent modulation of the acoustic signal was the same as the electronic signal, the relative amplitudes of the carrier frequency and the side bands were measured for the acoustic signal with a hydrophone and wave analyzer. AM sensitivity was determined under three stimulus conditions: continuous, continuouspulsed and pulsed (Fig. 1). The continuous case was identical to experimental conditions used previously by Fay [5] in which the carrier frequency was presented continuously during both intertrial and trial intervals. During an AM trial, the sinusoidal component of the modulation signal was gated on and off at zero crossings to produce 7 s of amplitude modulation impressed on the carrier signal. The ‘continuous-pulsed’ condition was identical to the continuous condition except that the modulation signal was gated on and off in 500 ms time intervals for the duration of the trial. The intertrial interval for the pulsed condition differed from the above in that the unmodulated carrier frequency was gated on and off (500 ms on/off time, 10 ms rise/fall times). During the trial, the modulator signal was gated on (always between bursts) in the same way as for previous conditions, resulting in 500 ms AM bursts that repeated for the duration of the trial. Animals were run on two intensity conditions with the pulsed stimulus. In one case, the overall signal level of each pulse was fixed at a given sensation level and in the other, it was randomly varied by f 10 dB around a mean sensation level of 40 dB.

59

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Fig. 1. Representation of the various stimulus conditions used in behavioral and physiological experiments relationship between the modulated and unm~ulated signal. (A) Continuous condition. (B) Continuous-pulsed condition.

Neurophysiological studies Neurophysiological experiments were designed to determine the response of single eighth nerve fibers to various SAM signais under continuous and bursting conditions similar to those used in psychophysical studies. SAM signals varied in terms of carrier frequency, modulation frequency, percent modulation and overall sound pressure level and were generated as described above for behavioral studies. Single units in the goldfish saccular nerve were recorded in response to modulated and unmodulated tones using standard methods [7,10]. Fish were immobilized with intramuscular injections of Flaxedit, anesthetized with MS-222 and clamped onto a respiratory tube. The fish were then lowered into a vibration-isolated, water-filled test tank nearly identical in design and dimensions to the behavioral tank and the saccular nerve was exposed by simple surgery. Micropipettes filled with

showing the temporal condition. (C) Pulsed

3 M KC1 were advanced through the nerve with a motorized microdrive. The output of the electrode was amplified between 300 and 3000 Hz, and single unit spikes were converted into TTL pulses of 0.5 ms duration by a voltage discriminator. Stimulus conditions were nearly identical to those used in psychophysical experiments. For pulsed conditions, both the carrier and modulator were gated on and off (400 ms on, 600 ms off, 10 ms rise/fall times). For continuous conditions, unmodulated signals were presented continuously and only the F, signal was gated on and off at zero crossings. Spike data were collected in the form of PST histograms from which measures of average rate, adaptation, and modulation synchronization were extracted. IO-sweep PST histograms were triggered 200 ms before the onset of the modulator signal and continued 100 ms after the end of modulation. For synchronization measures, histogram intervals

corresponding to a single cycle of amplitude modulation were added together to yield a folded period histogram. This distribution was used to calculate the coefficient of synchronization (R) a measure of the histogram’s dispersion or the precision with which spikes are phase-locked to the modulation envelope [5,1]. Spike rates were averaged over the entire duration of amplitude modulation (400 ms) and also over the 200 ms preceding and the 100 ms following the AM signal to yield ‘average rate’ measures of neural response. Short-term adaptation was quantified as a ratio between the maximum rate for the first and second 50 ms intervals of the neural response evoked after the onset of amplitude modulation. Maximum rate within each 50 ms interval was determined by selecting the highest rate from among 41 rates, each averaged over a sliding 10 ms window (i.e. from bins O-9, l-10, 2-11...40-49, bin widths = 1 ms). This method was chosen to capture accurate onset rates in rapidly adapting neurons and to avoid problems of changing response latencies.

Results Behavioral results Behavioral data were averaged across four fish, with at least 6 threshold determinations from each fish under each condition. AM sensitivity as a function of modulation rate for three carrier frequencies is plotted in Fig. 2 for the various stimulus conditions. AM sensitivity in the pulsed condition is similar for all carrier frequencies with threshold levels of detection occurring at modulation percentages as low as 1.75-3% for modulation rates between 50 and 100 Hz. Sensitivity falls off rapidly below modulation rates of 25-50 Hz. In contrast, AM sensitivity under continuous stimulus conditions changes very little as a function of modulation rate for an 800 Hz carrier and only moderately for a 200 Hz carrier. Continuous conditions produce better SAM sensitivity than pulsed conditions, especially at lower modulation rates. Under the intermediate condition (continuouspulsed), sensitivity was slightly poorer than under the continuous condition, but similar to the continuous condition in that it changed very little as a function of modulation rate. The effects of sensation level on sensitivity to an 800 Hz signal amplitude-modulated at 10 and

Fig. 2. AM sensitivity for different carrier frequencies as a function of modulation rate for various stimulus conditions. Sensitivity is expressed as % modulation at threshold levels of detection. - - - -, thresholds obtained under pulsed condicontinuous conditions; - - - -, continuoustions; -, pulsed conditions. S.E. bars have been eliminated for clarity, but substantial overlap of SE. bars occurred (1) between different carrier frequencies for each modulation rate in the pulsed condition, (2) between the continuous and continuouspulsed condition at both 10 and 100 Hz modulation (F, = 800 Hz) and (3) for pulsed, continuous-pulsed and continuous condition at 100 Hz modulation (F, = 800 Hz). S.E. bars did not overlap between the pulsed and continuous conditions, nor between puked and continuous-pulsed when the modulation rate was 10 Hz (F, = 800 Hz).

100 Hz tinuous tinuous ulation above a

are shown in Fig. 3 for pulsed conditions. For both the pulsed case, sensitivity in detecting 10 changes little as a function of 20 dB sensation level. In contrast,

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Fig. 3. AM sensitivity as a function of sensation level (dB above threshold) under pulsed (dashed lines) and continuous (solid lines) conditions. 0 and X represent the AM threshold under randomly varying (40 dB SLklO dB) intensity conditions. S.E. bars showed substantial overlap between fixed and random intensity data points at both modutation rates.

61

ity to a 100 Hz modulated signal increases with overall signal level throughout the range of sensation levels tested. When plotted in log-log coordinates, sensitivity (measured as 20 log,,M, where M is the modulation depth or 5%modulation/lOO) increases by 10 dB for nearly every 10 dB increment in overall level. This rate of growth begins to decline at the highest sensation levels. Results obtained with randomly varying pulse intensities are also shown in Fig. 3 for signals modulated at 10 and 100 Hz. Randomly varying the overall signal level from 30 to 50 dB above threshold failed to produce any significant changes in AM sensitivity relative to that measured at a fixed sensation level of 40 dB.

Neurul responses to AM signals under pulsed conditions. Data were collected from a total of 62 single saccular neurons in 14 fish. The responses of a unit with moderately high spontaneous activity to modulated and unmodulated tones are illustrated in the PST histograms and overall intensity functions of Fig. 4: The histograms show clear differences in the pattern and average rate evoked by the modulated carrier relative to that evoked by an unmodulated carrier. Corresponding intensity functions show how the fiber responds to SAM signals with both an increase in average spike rate and synchronization above that produced by the

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Fig. 4. The response of unit S6 to modulated and unmodulated signals. PST histograms on the left panel from top to bottom show spike activity over time for increasing intensities (in dB attenuation). Stimulus trace at bottom. Input/output functions on the panel at right show the synchronization coefficients and average spike rates evoked by the unmodulated () and modulated (- - - -) signal for different signal intensities and modulation percentages: 0 50%; A. 25%; 0, 12.5%: X, 6.35%: *, 3.12%; 0. 1.6%.

unmodulated signal. Both synchronization and rate increments decrease with decreasing modulation depths until at some modulation depth the intensity functions for the modulated and unmodulated signal are nearly the same. Fig. 5 shows the same representation of neural responses from a unit with low spontaneous activity. Rate responses are essentially similar to those of unit S6 in Fig. 4, whereas synchronization responses do not appear to decline with modulation depth in as regular a fashion as do those of unit S6. This may in part reflect the way in which synchronization measures are obtained, since the total number of spikes used in determining synchronization coefficients is dependent on evoked rate. Thus, synchronization measures for nonspontaneous units are least reliable under conditions which evoke few spikes. Sample size is not as great a problem for rate measures or synchronization measures for highly spontaneous units.

In general, most neurons encountered responded best to higher rates of modulation, with response gains (% modulation of spike rate/% modulation of stimulus envelope) as high as 30 dB. Fig. 6 demonstrates this trend with PST histograms from a single unit. Fig. 7 shows the same phenomenon for several units for which rate and synchronization criteria were used to obtain neural measures of AM sensitivity as a function of modulation rate. Rate functions are nearly identical to those obtained with synchronization criteria and similar to synchronization functions obtained earlier for the goldfish by Fay [5]. In general, units show either low-pass or high-pass filter characteristics, with high-pass units being encountered most frequently. These functions are qualitatively similar to the behavioral functions (Figs. 2 and 7) and show similarities between the neural response of high pass saccular units and the response of the whole system as measured behaviorally. 180 ,

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synchronization criteria were met are plotted for different modulation rates. Rate criteria were lo-20 spikes/s above that evoked by an unmodulated signal and synchronization criteria were the degree of phase locking to the modulation envelope that produced a coefficient of synchronization between 0.4 and 0.5. A 600 Hz carrier frequency was used for units S2, S4 and S6; 800 Hz for unit S25 and 400 Hz for 539. Behavioral data for a 570 Hz carrier (from Fig. 2) are plotted as heavy dashed lines for comparison.

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tion. This is alsd the case for behavioral measures of modulation sensitivity (Fig. 3). Neurons did not show evidence of AM responsiveness under all conditions. The PST histogram inset in Fig. 10 shows that when an unmodulated tone burst causes little or no adaptation, there is little change in the time pattern of responses evoked by the modulated carrier. Corresponding intensity functions in Fig. 10 show that this finding essentially holds over the dynamic range of the neuron. The relations~p between short-term adaptation and AM responsiveness is shown in Fig. 11 for over 40 units. The data points in this figure were generated by first obtaining a measure of adaptation (based on the ratio between the spike rates evoked during the first and second 50 ms of an unmodulated signal - see Meth~s) and then by obtaining rate and synchronization measures of the unit’s response to a 50% modulated signal. The ratio between the average rate evoked by the modulated signal and that evoked by the unmodulated signal was used as a measure of the unit’s rate response to modulation, whereas the degree of phase locking to the modulation envelope was used as a measure of the unit’s synchronization response to modulation. These plots show that rate responsiveness tends to grow with increasing degrees of adaptation independently of carrier frequency. The rate of growth for a 100 Hz modulated signal appears to be slightly greater than that for 10 Hz modulation. Synchronization responsiveness, on the other hand, tends to remain constant over a wide range of adaptation ratios, falling abruptly as adaptation ratios approach 1. At large modulation depths, neurons showing high degrees of adaptation tend to respond more robustly than neurons with less adaptation (Fig. 11). However, AM sensitivity of highly adapting units tends to fall off more rapidly. For example, moderately adapting, spontaneously active neurons, like S6 in Fig. 4, respond to lower modulation depths than do rapidly adapting, silent neurons, like S25 in Fig. 5. Fig. 7 also shows that the sensitivity of neurons like S6 is much better than that of unit S25 and approaches levels of behavioral sensitivity.

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Fig. 11. The relationship between short-term adaptation and neural measures of AM responsiveness. The degree of short-term adaptation was measured by the ratio between a maximum rate (averaged over a 10 ms sliding time window) evoked during the first and second 50 ms intervals of an unmodulated pure tone signal (see Methods for further details). The neural response to the SAM signal was measured for 50% modulated signals of various carrier frequencies modulated at 10 and 100 Hz. The degree of phase-locking to the modulation envelope (the coefficient of synchronization, R) is plotted on the bottom two figures, and the ratio between the average spike rate evoked by the modulated signal and that evoked by the unmodulated signal at intensities 10 dB above the neuron’s threshold is plotted for the top two figures.

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Neurons which do not respond with short-term adaptation to modulated signals in the pulsed condition, also show no significant longterm adaptation and little AM responsiveness under continuous conditions. Neurons which adapt, however, respond to AM signals under conditions of continuous adaptation in a way that is different from the response under intermittent (pulsed) conditions. Figs. 12 and 13 illustrate some of these differences. For the pulsed condition, it is clear that as modulation depth is decreased, the neural representation of the modulated signal becomes more and more like that of the unmodulated signal

in nearly all dimensions. These include the profile of the PST histogram, average rate and degree of synchronization to the modulation envelope. When the nervous system is continuously adapted to an unmodulated signal, however, the responses evoked by the modulated and unmodulated signals differ from those evoked under conditions of intermittent adaptation in two significant ways. Long-term adaptation can cause the rate response evoked by the unmodulated tone to drop dramatically relative to that evoked by the unmodulated signal in the pulsed case. Secondly, although the rate response to the modulated signal is also diminished relative to the pulsed condition,

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it shows little or no adaptation. The consequence of these two effects is that the ratio of spike rates between that evoked by the modulated and unmodulated signal (rate contrast) is enhanced for the continuous case. This effect can be seen more clearly in the accompanying intensity functions of Figs. 12 and 13. For both units S62 and S25, the rate-intensity function for a 6% modulated signal becomes almost indistinguishable from that for the unrnodulated signal in the pulsed case. In the continuous case, however, the modulation percentage at which the two functions become indistinguishable is much lower. This effect appears to be greatest when intensity functions for the unmodulated signal are steep (Fig. 12). Fig. 14 (bottom panel) demonstrates this effect for several units at different

modulation depths with a plot of rate contrast ratio for pulsed vs. continuous conditions. This figure also contains a similar plot of synchronization measures, indicating that there is also enhancement in the ability of neurons to phase-lock to the modulation envelope. Di!%XWioIl The role of adaptation in AM detection In this study, short-term adaptation is used to refer to the decline with time in the number of spikes evoked by a 400-500 ms intermittent signal, as measured by the PST histogram. Similarly, long-term adaptation is used to refer to the decline in rate that occurs over several minutes when the signal is on continuously. These experiments dem-

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onstrate that behavioral detection and neural responsiveness of saccular nerve fibers to SAM signals are affected by processes which govern both short- and long-term adaptation. When saccular neurons respond to an unmodulated signal with any degree of short-term adaptation, subsequent responses to the modulated signal differ significantly from those to the unmodulated signal along several neural dimensions, including average rate, temporal pattern of discharge and adaptation profile (Figs. 4-13). Conversely, when neurons respond tonically to unmodulated signals, there is no appreciable change in the neural response to modulated signals. This finding is similar to findings on catfish midbrain [21] and mammalian cochlear nucleus cells [20,12] in the sense that certain short-term adaptation patterns predict good AM Thus, it appears that whatever responsiveness. neural representation the nervous system uses for

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discriminating between modulated and unmodulated signals, information coming from channels showing significant short-term adaptation is most useful. Psychophysical results showing enhanced sensitivity to AM signals under continuous stimulus conditions suggest that long-term adaptation may have further effects on the ability of goldfish to detect amplitude modulations. These results are consistent with suggestions that such enhancement may also occur for humans [22]. However, there are a number of alternative explanations for these data. One possibility is that the continuous case, allowing a longer ‘look’ (one continuous look for 7 s), provides a larger sample size of amplitude fluctuations than does the pulsed case (seven looks of 500 ms each), especially at low modulation rates where behavioral differences are greatest. To dem-

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Fig. 14. The relationship between AM responsiveness under pulsed and continuous conditions. Rate and synchronization measures of AM responsiveness identical to those used in Fig. 11 are plotted for several units stimulated at various carrier frequencies modulated at 10 and 100 Hz. Where arrows appear, the rate evoked by the continuous unmodulated signal is 0 s/s and the rate ratio is plotted as the rate evoked by the modulated signal. Solid fine indicates where neural measures of AM responsiveness for pulsed and continuous conditions would be CXpld.

onstrate that differences between pulsed and continuous conditions could not be accounted for strictly on the basis of sample time, AM sensitivity was tested in an intermediate condition (continuous-pulsed in Fig. 1) which kept the nervous system in a continuous state of adaptation, but only allowed 500 ms ‘looks’ at the AM signal. The

results from this control (Fig. 2) show that under continuous adaptation, sensitivity to a 10 Hz-modulated signal is reduced by only a small percentage when sample time is identical to that in the pulsed case.

Another possibility is that the strategy used by the nervous system in comparing modulated and unmodulated signals is different under the two conditions. For the pulsed case, the nervous system must presumably store a neural representation of the unmodulated pulse for later comparison with the modulated pulse, In the continuous case, the nervous system need only detect a change between the ongoing nervous activity evoked by the continuous unmodulated signal and that evoked by the onset of amplitude modulation. Comparisons between the modulated and unmodulated signals would be facilitated in the continuous case because there is no time, and thus potential memory lapse, between the two signals as there is in the pulsed case. While this possibility cannot be ruled out, the apparent convergence of sensitivity functions for the two conditions at higher modulation rates (Fig. 2) argues against it. Moreover, there is evidence for a sensory mechanism at the level of single saccular fibers. That is, the neural response to AM signals appears to be enhanced under conditions of continuous adaptation. This enhancement involves a relative increase in the ratio between spike rates evoked by the modulated and unmodulated signals and in the degree of synchronization to the AM envelope (Fig. 14). The precise mechanism by which adaptation processes govern neural responsiveness to AM signals is unclear, but the way in which synaptic transmitters are replenished and depleted at the synapse between hair cells and saccular nerve fibers may play a major role. Work by Furukawa and his colleagues on the synaptic dynamics at the hair cell/nerve interface in the goldfish saccule suggests that (1) adaptation is due to neurotransmitter depletion at presynaptic sites, (2) changes in stimulus intensity cause changes in the number of active hypothetical release sites, (3) release sites have different threshold sensitivities, and (4) replenishment occurs serially, from high threshold sites first to low threshold sites last 113-15,17-191. According to Furukawa’s model, the response of the hair cell to the onset of a pure tone signal would be to activate an increasing number of transmitter release sites at its presynaptic base resulting in an increase in eighth nerve discharge. Sustained signals which caused a number of sites

to become depleted would result in response adaptation in the afferent nerve. Since only sites with relatively high thresholds would respond to periodic amplitude increments in the signal, these sites. when depleted, would be the first to be replenished. Lower-threshold release sites responsible for neural discharge to the lower-intensity ‘ valleys’ of the AM signal would be replenished last. In essence, this organization accomplishes two things: (1) a decrease in activity evoked at signal levels corresponding to AM valleys due to slower transmitter replenishment, and (2) an increase in activity to AM peaks through the maintenance of a rapidly rejuvenating pool of high threshold release sites. A system like this could explain the kind of contour enhancement noted in this and previous studies [5] for goldfish saccular fibers, for catfish midbrain cells [21] and for some mammalian cochlear nucleus cells [20,12]. This enhancement is greatest under conditions of continuous adaptation when lower threshold sites would presumably be under a constant state of depletion and the neuronal response to the unmodulated portion of the signal would approach zero at high intensities. The ultimate effect of this scheme is an enhanced signal/noise ratio where the ‘noise’ is equivalent to the neural response evoked by the unmodulated signal and the ‘signal’ is represented by activity evoked by periodic amplitude increments. In contrast, a less adapted system responding to intermittent stimuli would have to activate a series of release sites from low to high thresholds at the onset of each pulsed stimulus, in addition to those sites responding to periodic amplitude increments during the duration of the stimulus. This would mean more spikes in general for the pulsed case relative to the continuous case at any given intensity (see Figs. 12 and 13) but in essence, a lower signal/noise ratio, especially during the first few ms of the signal when most sites have not yet been depleted. Neural basis for AM detection A second question raised by these studies is precisely what information is used by the nervous system for making behavioral decisions. In general, it is presumed that behavioral discrimination between modulated and unmodulated signals could be based on long-term spectral differences (with

the spectrum of unmodulated signal dominated by the carrier frequency and that of the modulated signal having additional power in the sidebands at FC f F,) or on differences in temporal patterns of the AM envelope. Both spectral and temporal analyses are presumed to occur for humans, with detection at low modulation rates based on a temporal analysis and detection at higher modulation rates based on a spectral analysis [16]. Prior studies on AM detection by the goldfish point to a temporal solution [5] in which synchronization of neural discharge to the AM envelope encodes modulation rates in the range of 10-400 Hz. The evidence for the ability of goldfish to discriminate between changing AM rates is strongly in favor of a temporal mechanism [6,9], but somewhat weaker for the simple detection of AM impressed upon a pure tone carrier. The primary evidence for temporally-mediated AM detection relies on the close correspondence between behaviorally-measured sensitivity functions and neural functions derived from synchronization criteria. Results from the current study confirm this correspondence, but also show that it is very difficult to distinguish between average rate and synchronization responses to AM signals, especially in neurons responding at levels of behavioral sensitivity (Fig. 4). Average rate information could also be used by the nervous system for the detection of modulation. The nervous system could simply ‘listen’ for an increase in spike rate evoked by the modulated signal over that evoked by the unmodulated signal across many neural channels. This is a very simple mechanism which seems to account for signal detection [7] and intensity increment detection [8]. AM detection clearly has elements of an intensity increment task, and intensity difference limens (A I) measured with an 800 Hz signal modulated at 10 Hz are remarkably similar to Al’s obtained for an 800 Hz signal with single, pulsed intensity increments ([8], Fig. 15). Moreover, several features of AM detection are consistent with both average rate and synchronization hypotheses, including (1) an increase in AM sensitivity with increasing modulation rates (Fig. 7) (2) a growth in AM sensitivity with increasing intensity levels that is greater for a 100 Hz modulation rate than a 10 Hz rate (Figs. 3 and 9), and (3) differences

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Fig. 15. Intensity difference limens as a function of sensation level measured with SAM signals and single-step intensity increments under continuous and pulsed conditions.

between AM sensitivity under pulsed and continuous conditions (Figs. 2 and 14). Arguing against a simple rate mechanism, however, are results from experiments in which varying overall signal intensities failed to shift thresholds above those’ obtained under a fixed intensity. This conclusion relies on the assumption that the rate response of. neurons becomes more variable when overall signal level is varied. A neuron with a steep intensity function like S6 (Fig. 4), for example, would respond to different overall levels of the unmodulated signal with a wide range of rates, making the discrimination between modulated and unm~ulated signals more difficult on the basis of average rate. This assumption would not be true for neurons like S25 with shallow intensity functions (Fig. 5), but our data indicate that these neurons are generally less sensitive to AM signals and are unlikely to account for behavioral sensitivity. The ability of neurons to respond to AM signals with phase-locking to the AM envelope and with an increase in average rate may be related to spread of spectral energy into the tuning curve of the neuron. It is unhkely that the spectrum of the AM signal can be completely resolved by saccular fibers in the goldfish as is hypothesized for the narrowly tuned, band-pass bank of filters in man. Saccular fibers are very broadly tuned ( QIOdB= 0.8) and do not fit into a continuum of best frequencies [4,11] that would be needed to perform a place analysis of the AM spectrum. However, it is con-

ceivable that the detection of AM signals could be based on the spread of spectral energy within or across neurons. The majority of saccular fibers show low-pass filtering, with high-frequency cut-offs ranging from 200 to 600 Hz and high-frequency slopes varying between 3 and 50 dB/octave. The effect of such filters on a m~ulated 800 Hz signal would be essentially to reject the upper side band and to attenuate the carrier relative to the lower side band. Thus, the signal out relative to the,signal in would have an enhanced AM contour - a prediction that is consistent with neurophysiological observations of large gains in the m~ulation response of saccular fibers (Fig. 6). Low-pass filtering would also predict that sensitivity to an AM signal would increase as the side band separation became wider, or as the lower side band fell into progressively more sensitive regions of the tuning curve. Once the lower side band reached the high frequency cut-off, however, further side band separation would produce no gain in sensitivity. These two predictions are consistent with both neurophysiological and behavioral data showing that modulation sensitivity increases with mutation rate until it approaches asymptote at higher rates (Fig. 7). __ Arguing against the spectral spread hypothesis, however, are preliminary data which indicate that similarly tuned, low-pass units may vary drastically in their AM sensit~~ty, independent of absolute sensitivity. Furthermore, there are some saccular units which show a decrease in sensitivity with higher modulation rates (Unit S39, Fig. 7; [S]) - a finding, according to the spectral spread hypothesis, that would only be predicted for units narrowly tuned at the carrier frequency. Since saccular units are broadly tuned, it is unlikely that these results can be accounted for by spectral spread. Further studies examining the relationship between tuning, adaptation and AM responsiveness in saccular fibers are currently underway in our lab to evaluate the spectral spread hypothesis. Summaryand Conclusions

These studies demonstrate that behavioral detection and the response of single saccular fibers to SAM signals are affected by processes which

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govern both short-term and long-term adaptation. The ability of neurons to show short-term adaptation to a pure tone signal is related to their ability to respond to time-varying amplitude changes in that signal. Long-term adaptation may enhance behavioral detection and the ability of neurons to respond to amplitude fluctuations. Both phaselocking to the AM envelope and average rate information are available to the central nervous system for the detection of AM signals. Neither average rate changes nor the spread of spectral energy appear to be the sole basis upon which behavioral detection is based. Temporal patterns of discharge remain a viable source of information for AM detection at the level of the eighth nerve in goldfish.

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