Duration Tuning in the Mouse Auditory Midbrain

Antje Brand,1,2 Reas Urban,1 and Benedikt Grothe1,2

 1Zoologisches Institut, Universität München, 80333 Munich; and  2Max-Planck-Institute of Neurobiology, 82152 Martinsried, Germany


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Brand, Antje, Reas Urban, and Benedikt Grothe. Duration Tuning in the Mouse Auditory Midbrain. J. Neurophysiol. 84: 1790-1799, 2000. Temporal cues, including sound duration, are important for sound identification. Neurons tuned to the duration of pure tones were first discovered in the auditory system of frogs and bats and were discussed as specific adaptations in these animals. More recently duration sensitivity has also been described in the chinchilla midbrain and the cat auditory cortex, indicating that it might be a more general phenomenon than previously thought. However, it is unclear whether duration tuning in mammals is robust in face of changes of stimulus parameters other than duration. Using extracellular single-cell recordings in the mouse inferior colliculus, we found 55% of cells to be sensitive to stimulus duration showing long-pass, short-pass, or band-pass filter characteristics. For most neurons, a change in some other stimulus parameter, (e.g., intensity, frequency, binaural conditions, or using noise instead of pure tones) altered and sometimes abolished duration-tuning characteristics. Thus in many neurons duration tuning is interdependent with other stimulus parameters and, hence, might be context dependent. A small number of inferior colliculus neurons, in particular band-pass neurons, exhibited stable filter characteristics and could therefore be referred to as "duration selective." These findings support the idea that duration tuning is a general phenomenon in the mammalian auditory system.


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Temporal features of sounds are important for sound identification. These include amplitude or frequency modulation, the time interval between different elements of a complex sound or the duration of a specific element. The neural substrate for processing most of these temporal cues has been intensively studied, and neurons exhibiting specific tuning for these cues have been found throughout the auditory system. Moreover there is not much doubt that temporal cues contain information most relevant for terrestrial or flying vertebrates, including mammals. Tuning of single neurons to the duration of a stimulus, for example, has been described in bats (Casseday et al. 1994; Ehrlich et al. 1997) and frogs (Feng et al. 1990; Gooler and Feng 1992; Potter 1965). In bats, duration tuning has been discussed as a specific adaptation for echolocation, and in frogs, it has been discussed as an adaptation for mating behavior. The fact that duration tuning has also recently been found in the cat auditory cortex (He et al. 1997) and the chinchilla auditory midbrain (Chen 1998) suggests that duration tuning is a common phenomenon in vertebrate auditory systems. Nevertheless it might serve different behavioral needs in different species.

In addition to the question of the behavioral relevance of duration tuning in the auditory system, there are unresolved issues related to the problem of when a neuron should be defined as "duration tuned." Previous studies of duration tuning have not systematically investigated the robustness of duration tuning in the face of changes in stimulus parameters other than duration.

We, therefore tested whether there is duration tuning in the auditory midbrain of mice and to what extent this duration tuning can be considered as a major characteristic of a neuron's response. We took the approach of using stimuli that are clearly different from each other in one stimulus parameter (frequency, binaurality, amplitude, or spectral content). We chose this approach because it would more likely reveal differences than changing only one parameter in a systematic way. We present data showing that the mouse auditory system contains neurons that show band-pass filter characteristics for stimulus duration, thereby adding evidence that duration tuning is present in all mammals. Moreover, our data suggest that the duration tuning of at least some of these neurons is robust in the face of changes in other stimulus parameters including amplitude, binaural stimulus conditions, frequency, and spectral content. However, our data also indicate that it is important to analyze a neuron's response to a variety of stimuli to allow the classification of a neuron as duration selective.


    METHODS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Eighteen male outbred nonalbino mice (Mus musculus) were used in this study. Before surgery, the mouse was anesthetized with an initial intraperitoneal injection of ketamine (10 mg/100 g body wt) in a solution of Xylazinhydrochloride (0.2%). During the recording session, the animal received a continuous intramuscular infusion of the same anesthetic (0.1 ml/h). The skin was deflected from the upper part of the skull to allow a metal rod to be mounted using cyanoacrylate and dental cement. The rod was later used to secure the mouse's head during recordings. A small hole (0.5-1 mm diam) was cut into the skull above the inferior colliculus (IC) on one side according to coordinates from the stereotaxic atlas of the mouse brain (Franklin and Paxinos 1997). Recording started immediately after surgery in a sound-attenuated and heated chamber (30-32°C). Recording sessions generally lasted 8-12 h. At the end of the experiment, the mouse was killed by an overdose of pentobarbital. The skull was opened, and the marks of the electrode penetrations on the brain surface were evaluated to confirm that recordings were obtained from the IC.

Action potentials from single neurons were recorded extracellularly using glass pipettes filled with 2 M sodium acetate. The impedance of the recording electrodes ranged from 5 to 20 MOmega . The electrodes were advanced with a hydraulic drive (Trent Wells) controlled from outside the recording chamber. Spikes from single units were fed via a recording amplifier, a band-pass filter (0.5-3 kHz), and a window discriminator into a DSP-Board (Tucker-Davis-Technologies, System II) in a PC, which measured their time of occurrence to 2.5-µs accuracy. Hardware was controlled by custom-made software. If not stated differently, spike counts derive from >= 10 repetitions of each stimulus measured over a 120-ms time window starting with the stimulus-onset (the low rates of spontaneous activity allowed this approach; see RESULTS). Poststimulus time histograms (PSTHs) were constructed from 10 repeats with a binwidth of 1 ms. Acoustic stimuli were presented via custom-made earphones (Schlegel 1977; Schuller 1997) fitted to the ears with probe tubes (5 mm diam). The earphones were calibrated using a 1/4-in Brüel and Kjaer microphone and a Brüel and Kjaer 2610 measuring amplifier. As search stimuli, we used pure tones manually varied in frequency, duration, and amplitude. Search stimuli were presented to the contralateral ear. For recording single-neuron response properties, acoustic stimuli were digitally generated by using two DSP-boards, 16-bit D/A converters (sampling rate 250 Hz), anti-aliasing filters (cutoff at 100 kHz), and digital attenuators from Tucker Davis Technologies (System II). Stimuli were amplified (Toellner) and fed into the earphones.

For each neuron, a best frequency and best duration was determined audiovisually. Using that duration, a frequency tuning curve was measured to confirm the best frequency (BF), to obtain rate level functions, and to determine Q10dB values [best frequency/bandwidth of tuning curve at 10 dB above threshold (a.T.)] as a measure for the sharpness of frequency tuning. Next, duration sensitivity was tested using contralaterally presented pure tones at the neuron's BF, 20 dB a.T. ("standard stimulation"). Different ranges of stimulus durations (1-10, 10-30, 10-100 ms) were presented in 10 steps in a randomized sequence to obtain a measure of the neuron's response as a function of duration. This allows us to determine whether there was any range over which the spike count dropped <50% of that evoked by the optimal duration. Following this procedure, neurons could be classified as "untuned" (no 50% cutoff), "long-pass" (lower cutoff), "short-pass" (upper cutoff), or "band-pass" (lower and upper cutoff). Neurons have only been classified as long-pass if they responded with 0 spikes per 10 stimuli to short stimulus durations of up to at least several milliseconds. The latter criterion excludes neurons that responded with a sustained discharge throughout the duration of stimulus presention from being defined as long-pass when they, in fact, responded to all stimulus durations tested.

Additionally, duration tuning was tested using stimuli other than the "standard stimulus": contralateral stimulation 10 dB a.T. at BF; contralateral stimulation 30 dB a.T. at BF; binaural stimuli at an interaural intensity difference (IID) of 0, 20 dB a.T. at BF; binaural (IID = 0) white noise, 20 dB above noise threshold; contralateral tones off-BF (>= 1 kHz higher or lower than the neuron's BF, eliciting a response of >0.4 spikes per stimulus), 20 dB above BF threshold. The cutoffs for the different stimulus conditions were then compared. A cutoff has been considered as stable if it shifted <25% in relation to the cutoff for standard stimulation.

All tests were carried out using a repetition rate of three stimuli per second and 10 repetitions for each stimulus. Stimuli were presented in a randomized order. Rise/fall times of all sounds were 0.5 ms. These short rise/fall times may have caused an increase in spectral bandwidth at frequencies <10 kHz and thereby may have influenced the response of a neuron. However, all neurons included in the present study had best frequencies above 6 kHz and only four of them had best frequencies <10 kHz (none of these were included in the test for stability of duration tuning). Additionally, spectral contents of the stimuli were measured using a 1/4-in Brüel and Kjaer microphone, a 1/4-in microphone amplifier (Reinstorp, VtS), and a SR 770 FFT Network Analyzer (Stanford Research Systems). For frequencies above 5 kHz, distortions were not detectable. Thus we can exclude effects on duration tuning caused by spectral artifacts.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

We recorded from 107 single neurons in the mouse IC. Best frequencies ranged from 6 to 41 kHz. In response to standard stimulation, the vast majority of cells (73%) showed phasic discharge patterns either to the onset (59%) or to the offset of the stimulus (14%). The remaining 27% of the neurons responded with a sustained discharge throughout the stimulus duration, 12% with a chopper-pattern. Seventy-three percent of these neurons exhibited monotonic, 27% nonmonotonic rate-level-functions (drop of spike rate >50% compared with the maximal response). Of 85 neurons tested for binaural response characteristics using different interaural level differences, 25% responded to both contralateral and ipsilateral stimulation (E/E). 13% of the neurons were excited by contralateral and inhibited by ipsilateral sounds (E/I), 62% showed no influence at all from the ipsilateral ear (E/O).

Duration tuning under standard stimulus conditions

Of the 107 neurons tested using standard stimulation (pure tone at BF, contralateral stimulation 20 dB a.T.), 48 were classified as "untuned" to the stimulus duration. These included two response types. The first (37 neurons) consisted of an ON response with approximately equal spike count across all of the stimulus durations, i.e., the spike count never dropped below 50% of maximum (Fig. 1A). The second group of neurons that we considered as untuned consisted of 11 sustained responders. As shown in Fig. 1B, these neurons responded with spike counts that increased as a function of stimulus duration. Applying the 50% cutoff criterion would---of course---define these neurons as long-pass. However, the increase in spike count was almost linearly related to the stimulus duration whereas the spike rate as a function of stimulus duration (Fig. 1B, - - -) decreased. Additionally, all but one of these neurons responded with >= 0.5 spikes per stimulus even at the shortest duration tested. One neuron responded with only 0.3 spikes per stimulus to the shortest duration but with 0.5 spikes/stimulus to the next longer stimulus duration (the neuron showed no spontaneous activity). Therefore we categorized these neurons as untuned. There seems to be nothing special about this group of untuned neurons in terms of rate-level functions, frequency tuning, and binaural properties: 25% had nonmonotonic rate-level functions and 75% had monotonic rate-level functions; 19% were E/E, 9% E/I, and 72% E/O. Q10dBs were equally distributed between 1.6 and 14. 



View larger version (17K):
[in this window]
[in a new window]
 
Fig. 1. The 2 response types of neurons considered as untuned for duration to standard stimulation shown as tuning functions (top). Bottom: selected poststimulus time histograms (PSTHs) showing the response patterns. A: neuron with a phasic ON response to pure tones independent of the stimulus duration. B: neuron with a sustained discharge to pure tones; response rate increases with stimulus duration in an almost linear and predictable way (---). By simply using a 50% threshold criteria for duration tuning, this neuron would have been categorized as long-pass. However, the neuron responded to any stimulus duration and the increase of response rate was almost constant (- - -). , the timing of stimuli that is also given in the top upper corner of the PSTHs. Binwidth of PSTHs: 1 ms.

Of all neurons, tested 41 neurons showed long-pass duration tuning in that they did not respond at all (=0 spikes) to the shortest stimulus and discharged with <0.5 spikes per stimuli in response to at least the shortest three durations tested. However, they responded vigorously to all stimuli longer than a specific threshold duration. After reaching this threshold, 15 of the 41 neurons had phasic discharge patterns (13 with ON response and 2 with OFF response; see Table 1). Their spike counts reached a plateau at stimulus durations slightly longer than the lower cutoff threshold (Fig. 2A). The spike count of 26 neurons increased with stimulus duration (Fig. 2B). For the latter, a 50% cutoff could not be determined, but since they did not respond at all to several short durations up to a criterion duration, we nevertheless considered them as long-pass. Long-pass neurons did not show any special characteristics in terms of their rate-level functions, frequency tuning or binaural properties: 44% nonmonotonic, 56% monotonic; 50% E/E; 17% E/I; 33% E/O; Q10dBs were equally distributed between 2 and 16.6. 


                              
View this table:
[in this window]
[in a new window]
 
Table 1. Distribution of duration tuning characteristics as a function of discharge patterns



View larger version (21K):
[in this window]
[in a new window]
 
Fig. 2. Two basic response types of long-pass neurons in response to standard stimulation. A: neuron with a phasic ON discharge that only responded to stimuli >= 16 ms. The 50% cutoff was ~25 ms. B: response of a neuron with a sustained discharge that only responded to stimuli >= 20 ms. , the timing of stimuli.

The duration tuning of five neurons was classified as short-pass. These neurons responded to short stimuli but stopped responding when the stimulus exceeded a specific duration. Figure 3 shows a typical example of a short-pass neuron that consistently responded to pure tones <6 ms duration. At 6 ms stimulus duration, the spike count dropped below the 50% criterion. For longer stimuli (tested <= 100 ms), the response of this particular neuron was ~20-40% of that evoked by 1 to 4 ms pulses. All of the short-pass neurons exhibited phasic responses with only one spike per stimulus presentation (Table 1). Since the number of these neurons is small, we cannot make any statements about what might be special in terms of their rate-level functions, frequency tuning or binaural properties.



View larger version (11K):
[in this window]
[in a new window]
 
Fig. 3. Response of a short-pass duration-tuned neuron. This neuron only responded to pure tones with a duration of <= 16 ms. The 50% cutoff was ~6 ms when tested with standard stimuli. , the timing of stimuli.

Of the 107 neurons, 13 exhibited band-pass tuning for stimulus duration. These neurons only responded to a certain range of stimulus durations when tested with the standard stimulus. They failed to respond to shorter as well as longer stimuli. Figure 4 shows two representative examples of such band-pass neurons. The range of durations over which the spike rate met the >50% criterion varied considerably. The most sharply tuned neuron only responded to stimuli between 10 and 12 ms duration, whereas the most broadly tuned neuron responded to stimuli between 20- and 80-ms duration. The most important feature of these neurons was that all of them responded with an OFF response (Table 1). This can be seen in the PSTHs in Fig. 4. In both cases the response shifts to the right with increasing stimulus duration. Interestingly, 12 of the 13 neurons exhibited highly nonmonotonic rate-level functions, indicating a strong inhibitory influence. Only one of them showed a monotonic rate-level function. All of the band-pass neurons showed rather broad frequency tuning with Q10dB values <5. The number of binaurally tested band-pass neurons is too small to evaluate whether they have a typical binaural characteristic or not.



View larger version (21K):
[in this window]
[in a new window]
 
Fig. 4. Response of 2 neurons that showed band-pass filter characteristics for the duration of standard stimuli. The neuron in A only responded to pure tones with a duration of 6-64 ms. The 50% cutoffs were ~8 and 54 ms, respectively. The neuron in B only responded to pure tones with a duration of 4-14 ms with 50% cutoffs ~4.5 and 11 ms. , the timing of stimuli.

In summary, the long-pass tuned neurons represented the majority (70%) of duration-tuned neurons in the IC, whereas only few short-pass (8%) and band-pass neurons (22%) could be found. Neurons with band-pass filter characteristics always responded with OFF discharges. Long-pass neurons exhibited phasic responses as well as sustained responses. No relation of duration-tuning characteristics and best frequencies could be observed, and a relationship of monotonic/nonmonotonic rate level functions and duration tuning is only obvious for band-pass neurons. Another relationship exists between band-pass duration tuning and broad frequency tuning characteristics (low Q10dB values).

Stability of duration tuning

In the experiments using a standard stimulation paradigm, more than half (55%) of the neurons showed at least some kind of duration tuning. However, a crucial question for defining neurons as duration tuned is whether these duration-tuning characteristics persisted even when we presented stimuli that elicited prominent responses but that differed from the standard stimulation paradigm in amplitude, frequency, or spectral content. To test this, we recorded from 52 neurons not only using standard stimuli but also testing duration tuning to other stimuli as listed in METHODS.

For comparison with other studies, the duration filter characteristics of 52 neurons were obtained again at each neuron's BF, at 10 dB a.T., 29 of the 52 neurons were not tuned to stimulus duration, 18 responded only to long stimuli, 1 responded only to short stimuli, and 4 exhibited band-pass filter characteristics. Thus the distribution at 10 dB a.T. was approximately the same as that at 20 dB a.T.

Figure 5 compares the distribution of the different tuning characteristics depending on stimulus conditions. The overall distribution of tuning characteristics appears to be similar for all stimulus parameters. However, different populations of neurons account for the distribution for each stimulus type (Fig. 5). That is because some neurons changed their tuning characteristics in one way, but others did so in the opposite way. Again other neurons showed the same duration-tuning characteristics for all stimuli tested. Thus in contrast to the single-unit level the resulting population response is rather stable across stimulus conditions.



View larger version (67K):
[in this window]
[in a new window]
 
Fig. 5. Distribution of duration-tuning characteristics for standard stimulation and the stimuli used for testing stability of duration tuning. "20" = pure tone, contralateral, 20 dB above threshold (a.T.), at BF; "10" = pure tone, contralateral, 10 dB a.T., at BF; "30" = pure tone, contralateral, 30 dB a.T., at BF; "bin" = pure tone, binaural (IID = 0), 20 dB a.T., at BF; "noise" = binaural noise (IID = 0), 20 dB a.T. for noise; "off-BF" = pure tone, contralateral, 20 dB a.T. >=  1 kHz below or above BF.

Of the 52 neurons tested for all different stimulus types listed in the preceding text, 26 were classified as untuned for duration under standard stimulus conditions. Of these, 22 (85%) remained untuned to duration under all six stimulus conditions tested. Four of the 26 neurons classified as untuned showed some duration sensitivity under at least one stimulus condition. One neuron changed to band-pass when tested with noise and to long-pass when tested with an off-BF tone; three changed to long-pass when tested with an off-BF tone. One example of a neuron changing from untuned (standard stimulus) to long-pass (off-BF) is shown in Fig. 6A.



View larger version (18K):
[in this window]
[in a new window]
 
Fig. 6. Duration tuning of 4 neurons with different tuning characteristics in response to standard stimuli and to other stimulus conditions. A: neuron with an untuned filter characteristic for standard stimulation but with long-pass filter properties in response to off-BF. B: duration tuning of a neuron exhibiting long-pass filter characteristics for standard stimulation that, however, shows band-pass duration tuning in response to a pure tone 1 kHz below the BF. C: duration tuning of a neuron showing short-pass filter characteristics for standard stimulation but band-pass tuning in response to noise. D: responses of a neuron that shows band-pass filter properties for all stimulus conditions tested (shown for noise).

Eleven of 19 neurons classified as long-pass exhibited the same type of duration tuning for all stimulus conditions. Four long-pass neurons lost any kind of duration tuning under at least one stimulus condition. Three cells' duration-tuning characteristics changed to band-pass for noise, and one neuron's tuning changed to band-pass at BF, 10 dB a.T., and off-BF (see Fig. 6B) and short-pass for binaural stimulation.

Two of three short-pass neurons changed or lost their duration tuning under at least one stimulus condition other than the standard stimulus. For example, the neuron showed in Fig. 6C changed from short-pass to band-pass when tested with noise.

Only four band-pass neurons could be tested for all stimulus conditions. All of them retained their band-pass filter properties for all stimulus types (Fig. 6D).

Thus a significant population of duration sensitive neurons (16/26) showed the same type of duration tuning for all six conditions tested. However, despite the fact that many of these "stable" neurons retained their basic filter properties (long-pass etc.), the actual filter cutoffs shifted significantly (Fig. 7, A and B) except for band-pass neurons (Fig. 7C). Therefore we determined how many of the neurons with stable filter characteristics also had stable filter cutoffs. Figure 8 shows the actual shifts of the cutoffs for long-pass neurons when tested with stimuli other than standard stimuli. Only 2 of the 17 long-pass could be classified as stable (their cutoff shifted <25%), whereas none of the 3 short-pass showed stable duration tuning (Fig. 9) with regard to both, basic filter properties and cutoffs. In contrast, all of the four neurons showing band-pass filter characteristics had stable filter cutoffs.



View larger version (19K):
[in this window]
[in a new window]
 
Fig. 7. A and B: shift of cutoffs for neurons with stable tuning characteristics but unstable cutoffs while presenting a stimulus other than the standard stimulus. C: example for a band-pass neuron with stable filters and stable cutoffs.



View larger version (66K):
[in this window]
[in a new window]
 
Fig. 8. Percentage of shift of cutoffs for the long-pass duration-tuned neurons. A cutoff was characterized as stable if it shifted <25%.



View larger version (34K):
[in this window]
[in a new window]
 
Fig. 9. Distribution of neurons showing stable duration-tuning properties. Considered as "stable" are neurons with identical tuning characteristics for 6 different stimulus conditions and cutoffs that shifted less than 25%.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

There are two main conclusions that can be drawn from the present study. First, duration-tuned neurons are present in the mouse IC, supporting the idea that duration tuning is a common feature of vertebrate auditory midbrain neurons. Second, the neurons that exhibited duration tuning can be divided into different groups. 1) In some neurons, the duration-tuning characteristics and filter cutoffs are stable throughout all different stimulus conditions. These neurons might be referred to as duration selective. 2) Many neurons show a specific type of filter characteristic independent of stimulus condition. However, the cutoffs can vary as a function of amplitude or other parameters. 3) The last group of neurons exhibits filter characteristics that are interdependent with other stimulus parameters. In this group of neurons duration tuning might be context dependent.

Comparison to other studies

In the frog torus semicircularis, a midbrain structure homologous to the IC of mammals, duration tuning was characterized using pure tones as test stimuli. The tones were presented at each neuron's BF, 10 dB a.T. Gooler and Feng (1992) found that the vast majority of neurons show long-pass tuning characteristics, some were short-pass or band-pass. Only few neurons didn't show any kind of duration tuning. There is a much higher proportion of duration-tuned neurons in the frog torus semicircularis than the present study shows for the mouse IC. However, the most specific and also the most robust type of duration tuning in the present study was the band-pass type of duration tuning. In the mouse, 12% had this type of tuning, a proportion similar to that found in the frog (9%). Clearly the higher proportion of duration-tuned neurons in the frog torus semicircular is due in part to the much higher percentage of sustained responders in the frog (67%) compared with the mouse IC (35%). Since Gooler and Feng considered neurons with sustained responses that showed a continuous increase of spike count with stimulus duration as long-pass, even though they responded to all stimulus durations tested, the absolute number of neurons classified as long-pass is much higher.

Comparison of our results with those of Casseday et al. (1994) and Ehrlich et al. (1997), reporting ~36% duration-tuned neurons in the IC of the big brown bat, is rather difficult. Neurons in this species of bat are mainly tuned to very short stimulus durations that match those of the echolocation calls. These studies did not distinguish between short-pass and band-pass neurons, as this would be difficult at the very short durations that these neurons are tuned to. Tuning to very short stimulus durations (2-10 ms) in the IC of the big brown bat has also been found by Pinheiro et al. (1991).

Consistent in these studies of the bat IC is a clear indication that there are more short-pass neurons than in the mouse and that in general the neurons in the bat IC are tuned to shorter durations than are neurons in the frog torus semicircularis and the mouse IC.

Only one other study has dealt with duration tuning in the auditory midbrain of a nonecholocating mammal, the IC of the chinchilla (Chen 1998). In the chinchilla, 19 of 41 cells (46%) were untuned to duration, but only 3 neurons (7%) showed band-pass duration tuning. All of them had OFF discharge patterns. One of these neurons showed a band-reject tuning characteristic. In contrast to all other studies, no short-pass tuning was found in the chinchilla IC. Despite the small sampling size, the 7% band-pass seems to be comparable to that found in the present study, indicating that the findings described in the present study might well be representative for rodents and possibly for most mammals. It should be noted, however, that in the chinchilla study all OFF neurons showed band-pass or band-reject tuning characteristics, whereas in the present study, 2 of 15 OFF neurons showed long-pass, the remaining 13 showed band-pass filter characteristics. Furthermore Fuzessery and Hall (1999) found neurons in the pallid bat IC that have an OFF response but didn't show any kind of duration tuning.

A similar distribution of duration-tuned neurons has also been found in the dorsal zone (dorsal to AI and ventral to the suprasylvian sulcus) of the cat auditory cortex (He et al. 1997). In this study, ~10% of the neurons revealed band-pass characteristics for the duration of noise bursts and 30% showed short-pass tuning.

Behavioral relevance

Duration-tuned neurons have been described in the frog's auditory midbrain (Feng et al. 1990; Gooler and Feng 1992; Narins and Capranica 1980; Potter 1965). Because the observed duration tuning in the range of >= 100 ms corresponds to the durations of the frog's mating calls, it might be directly related to the frogs' mating behavior. Female frogs find and choose their partners via mating calls that are emitted by the males. The distinguishing features of these calls are patterns of amplitude modulations. Because different modulation frequencies are correlated with different durations of a single modulation cycle, duration sensitivity could significantly add to an effective temporal sound analysis.

Duration-tuned neurons have also been found in the midbrain of several bats, including the big brown bat, Eptesicus fuscus (Casseday et al. 1994; Ehrlich et al. 1997; Jen and Feng 1999; Pinheiro et al. 1991), the pallid bat, Antrozous pallidus (Fuzessery 1994; Fuzessery and Hall 1999), and the little brown bat, Myotis lucifugus (Galazyuk and Feng 1997). These bats systematically shorten the duration of the emitted sounds during the process of catching a flying insect prey. It seems that for the bat, an important task of the auditory system is to relate a specific echo to a specific echolocation call. Duration tuning might be crucial for this task.

More recently duration-tuned neurons have been found in the cat auditory cortex (He et al. 1997), the chinchilla IC (Chen 1998), and in the mouse IC (present study). The presence of duration-tuned neurons in these species indicates that duration tuning might be a fundamental feature of vertebrate auditory systems. This does not exclude the possibility that the range of durations to which neurons are tuned, i.e., very long durations in frogs, very short durations in bats and intermediate durations in mouse or chinchilla, is related to specific behavioral needs (Ehrlich et al. 1997; Jen and Feng 1999).

Duration tuning in the IC and its interaction with other parameters

Most studies testing duration tuning used pure tones, noise or, in the case of recording from the bat IC, recordings were performed using frequency modulated sweeps. To our knowledge, only two of these studies tested the effect of changing another stimulus parameter on duration tuning. Galazyuk and Feng (1997) measured the duration tuning of neurons in the auditory cortex of the echolocating bat M. lucifugus as a function of stimulus amplitude. They found that the best duration of 65% of the neurons shifted significantly as stimulus levels increased. Pinheiro et al. (1991) showed that many IC neurons in the big brown bat preferred a specific combination of duration and stimulus repetition rate.

In the present study, we varied a broader range of stimulus parameters and measured their influence on duration tuning. A small but significant number of cells showed stable tuning patterns and stable cutoffs. These neurons might be categorized as duration selective, whereas other neurons (22 of 26 cells; 85%) showed a clear shift of cutoffs with changes in one or more stimulus parameters. The latter can be categorized as duration tuned, but this duration tuning interacts with other stimulus parameters in much the same way that frequency tuning depends, for instance, on sound level. Interestingly, 10 of 26 (38%) neurons changed their general tuning characteristics when the stimulus type was changed from pure tone to noise or when the frequency of the stimulus was changed. One could argue that this rules out the definition duration tuning for these neurons since it is not a stable characteristic of these cells. However, we favor a different interpretation. It has been shown that binaural properties (e.g., EI vs. EO) of single cells might change depending on the stimulus presented. Such changes have been discussed as context dependent in the bat auditory midbrain (Park et al. 1998) and the bat primary auditory cortex (Razak et al. 1999). In both structures, neurons have been found that exhibit different binaural properties depending on whether they process stimuli that mimic the echolocation call or not. In the present study, neurons in the IC have been found that show different duration-tuning characteristics in response to different stimulus types. Therefore the kind of duration tuning to a stimulus and the way a single cell contributes to the temporal analysis within complex networks might also depend on the stimulus presented and may be even influenced by context or the behavioral state of an animal. Influences of modulatory acting transmitters that are related to the behavioral state of an animal like noradrenaline or serotonin have been shown to strongly influence temporal processing of single neurons in the auditory brain stem (Kössl and Vater 1989) and midbrain (Hurley and Pollak 1999).

Possible mechanism

There are at least two simple mechanisms that could explain long-pass duration tuning with no responses at all to stimuli below a certain duration. The first mechanism would simply be an intrinsic property of a neuron that requires a high degree of temporal summation to reach the threshold for producing an action potential like a high-input resistance (compare: Oertel 1997). In neurons with such properties, the lower cutoff should shift when stimuli with a different spectral content are presented, as it did in most of these neurons. Additionally, it should shift with stimulus amplitude. In both cases, a different numbers of excitatory inputs would be recruited and the synchrony of these inputs would be different as well.

An alternative explanation for long-pass duration tuning that might be most applicable to sustained responders would be the interaction of a sustained excitatory input with a transient onset inhibitory input. The latter would prevent the neuron from responding to short stimuli or to the initial part of a longer stimulus but would not affect the later part of the response provided the sound was long enough. The existence of such onset inhibition has been described in the free-tailed bat auditory midbrain (Bauer et al. 2000; Klug et al. 1999; Park et al. 1998).

Casseday et al. (1994) suggested a model of how band-pass or short-pass duration tuning could be created by a coincidence detector mechanism that includes a tonic inhibition, delayed onset excitation, and an offset excitation. The latter might be a rebound from inhibition produced by intrinsic properties of the duration-tuned neuron itself. However, it might also stem from a different source consisting of neurons with off-responses. Such neurons have been found in the superior olivary complex of the mustached bat (Grothe 1994), the free-tailed bat (Grothe et al. 1997), the big brown bat (Grothe and Casseday 1998), and the rabbit (Kuwada and Batra 1999). The sustained inhibitory input would be necessary to restrain the cell from responding to the onset or offset excitation alone. As a consequence, the neuron would only respond if the onset and the offset excitation arrived simultaneously. The fact that in some band-pass or short-pass neurons duration tuning could be eliminated by blocking GABAergic or glycinergic inhibition indicates that inhibition is important for producing duration tuning (Casseday et al. 1994; Fuzessery and Hall 1999; Jen and Feng 1999). In addition, Covey and colleagues (1996) presented data from a patch-clamp recording of a duration-tuned IC neuron that clearly indicated the existence of this input combination. Consistent with this model, all of the neurons that we found to be band-pass and that were all robust in their duration tuning responded with an OFF discharge. Differences in binaurality, amplitude, or spectral bandwidth could influence the temporal interaction of excitation and inhibition in general. Integration of multiple inputs could change response properties of neurons (Covey et al. 1996; Kuwada et al. 1997; Oliver and Huerta 1992) as well as an ongoing inhibition. The fact that many neurons changed their tuning to band-pass characteristics when noise was presented instead of the "standard stimulus" is consistent with this notion. Broad-band stimuli might simply be more effective in causing OFF responses due to rebound from inhibition.

Conclusions

A careful analysis of the duration-tuning behavior of single IC neurons indicates that a significant minority of the neurons shows the same kind of duration-tuning characteristics for a variety of stimuli and can therefore be characterized as duration selective. The majority of neurons shows some kind of duration tuning. In many neurons, the tuning characteristics, however, change as a function of stimulus parameters other than duration. This might indicate a context dependent temporal processing in these neurons. The present study adds evidence to the notion that duration tuning is a general phenomenon in the vertebrate auditory system and should be considered as an important aspect of temporal processing.


    ACKNOWLEDGMENTS

We thank Drs. J. H. Casseday, E. Covey, and A. S. Feng for helpful comments on an earlier version of the manuscript. The software used for controlling stimulus presentation and recording was programmed by D. Molter (Zoological Institute, University of Munich). The experiments were performed in accordance with the German Tierschutz-Gesetz.

This work was supported by the German Research Foundation (DFG), Forschergruppe Hörobjekte-TP3/Grothe.

Present address of A. Brand: Max-Planck-Institute of Neurobiology, Am Klopferspitz 18A, 82152 Martinsried, Germany.


    FOOTNOTES

Present address and address for reprint requests: B. Grothe, Max-Planck-Institute of Neurobiology, Am Klopferspitz 18A, 82152 Martinsried, Germany (E-mail: bgrothe{at}neuro.mpg.de).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 23 September 1999; accepted in final form 6 June 2000.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

0022-3077/00 $5.00 Copyright © 2000 The American Physiological Society