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J Neurophysiol 91: 2215-2226, 2004. First published January 7, 2004; doi:10.1152/jn.01127.2003
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Ambiguities in Sound-Duration Selectivity by Neurons in the Inferior Colliculus of the Bat Molossus molossus From Cuba

Emanuel C. Mora1 and Manfred Kössl2

1Department of Animal and Human Biology, Faculty of Biology, Havana University, CP10 400, Ciudad de La Habana, Cuba; and 2Zoologisches Institut der Universität J. W. Goethe, D-60054, Frankfurt am Main, Germany

Submitted 21 November 2003; accepted in final form 29 December 2003


 ABSTRACT
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
This study examines duration selectivity in auditory neurons of the inferior colliculus of the bat Molossus molossus (Molossidae, Chiroptera) from Cuba. Three main types of duration selectivity, short-, band-, and long-pass, as previously described in other species, are present in M. molossus. The range of best durations in the inferior colliculus of this species approximates the durations of their echolocation calls, suggesting that, as has been shown in other species of bats and frogs, the filter mechanism that produces duration tuning is selective for species-specific sounds relevant to behavior. Duration coding in M. molossus is not unambiguous because ~30% of the short- and band-pass neurons respond best to two different stimulus durations. This bimodal duration selectivity could be explained by time delayed excitatory inputs that coincide with an inhibitory rebound. In addition, the effect of stimulus intensity on duration selectivity was tested. For most of the neurons (78%), duration selectivity was affected by absolute sound pressure level and/or small changes of sound pressure. In this respect, the processing of stimulus duration by collicular neurons seems to be more complex in M. molossus than in other species studied so far.


 INTRODUCTION
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
For several species of bats, it has been found that most auditory neurons respond best to frequencies and sound pressure levels (SPL) that closely match their own species-specific echolocation calls (Casseday and Covey 1992Go; Jen and Suthers 1982Go; Pollak and Bodenhamer 1981Go; Pollak et al. 1978Go; Schuller and Pollak 1979Go). More recently, it has been demonstrated that neurons in the inferior colliculus (IC) and auditory cortex of bats selectively respond to sound duration, one of the simplest temporal features (Casseday et al. 1994Go; Ehrlich et al. 1997Go; Fuzessery 1994Go; Fuzessery and Hall 1999Go; Galazyuk and Feng 1997Go; Pinheiro et al. 1991Go). Because the observed neuronal duration selectivity in each of the three species of bats studied so far approximates the durations of their own echolocation calls, it is suggested that the filter mechanism that produces duration tuning could supplement the filters for sound frequency and intensity (Ehrlich et al. 1997Go; Fuzessery and Hall 1999Go; Galazyuk and Feng 1997Go).

Two different models could explain duration selectivity: coincidence (Casseday et al. 1994Go; Ehrlich et al. 1997Go) and anti-coincidence mechanisms (Fuzessery and Hall 1999Go). Basically the same components are involved in both of them: a short-latency inhibitory input that persists for the duration of the stimulus, a delayed excitation triggered at stimulus onset, and an excitatory rebound from inhibition. In the coincidence model, the response appears only when the rebound from the inhibitory component coincides and summates with the delayed excitation, and this model could effectively explain short- and band-pass duration selectivity. The second model differs from the first one in that the early inhibition does not contribute to excitation (the 3rd component is not present). At short stimulus durations, inhibition (1st component) is over before the arrival of the excitatory input (2nd component), and the neuron responds maximally. Because increases in stimulus duration reduce or abolish the response due to the coincidence of inhibitory and excitatory events, this model provides a simple mechanism for creating short-pass duration selectivity. Most, if not all duration-selective neurons studied in the IC and auditory cortex of bats could derive their selectivity through one of these models, which are not mutually exclusive (Casseday et al. 1994Go, 2000Go; Ehrlich et al. 1997Go; Faure et al. 2003Go; Fuzessery and Hall 1999Go; Galazyuk and Feng 1997Go; Zhou and Jen 2001Go).

The existence of duration-tuned neurons could allow bats to identify by duration, at least partially, their own echolocation calls. However, other acoustic parameters relevant for echolocation need to be processed in parallel and therefore could affect duration selectivity. Such effects have been shown for repetition rate and FM (Fuzessery 1994Go; Jen and Zhou 1999Go; Pinheiro et al. 1991Go), but not in a systematic way for SPL of the stimulus. Only recently, changes produced in duration selectivity by varying the SPL were described for a population of neurons in the IC of Eptesicus fuscus (Faure et al. 2003Go; Zhou and Jen 2001Go) and the house mouse (Brand et al. 2000Go) as also previously observed in the auditory cortex of Myotis lucifugus (Galazyuk and Feng 1997Go). Those results strongly indicate that the consistency of duration selectivity needs to be proven by varying other acoustic parameters to come to conclusions on the significance of duration-selective neurons in a species' behavior. The SPL of echoes, for example, can vary considerably in relation with the distance to a reflecting surface, whereas their duration will remain constant. Echoes coming back from an insect at a distance of 3 m will be >60 dB attenuated at the bat's ears (Lawrence and Simmons 1982Go) (30-kHz call frequency). That is why SPL is one of the most important parameters to be tested to assess the consistency in duration selectivity.

Duration-selective neurons have been found in the IC or the cortex of bats (Ehrlich et al. 1997Go; Fuzessery and Hall 1999Go; Galazyuk and Feng 1997Go), frogs (Hall and Feng 1986Go; Narins and Capranica 1980Go; Penna et al. 2001Go; Potter 1965Go), cats (He et al. 1997Go), mouse (Brand et al. 2000Go), and chinchillas (Chen 1998Go). However, most of the results concerning the physiological basis and properties of this process have been described in bats.

The three species of bats studied to date—E. fuscus (Casseday et al. 1994Go; Faure et al. 2003Go; Pinheiro et al. 1991Go), M. lucifugus (Galazyuk and Feng 1997Go), and Antrozous pallidus (Fuzessery and Hall 1999Go)—all belong to the family Vespertilionidae. It is known that molossid bats show a more complex echolocation behavior than that observed in vespertilionid bats, i.e., search calls alternating in frequency, approach calls of longer durations and higher frequencies than search calls, and different designs of calls emitted in the surroundings of the colonies (Kössl et al. 1999Go; Simmons et al. 1979). This complexity could have physiological correlates at the level of the IC. The aim of this study was to determine whether the population of duration-selective neurons in the IC of a bat from the family Molossidae, Molossus molossus, selectively responds to species-specific calls durations. We also evaluated the effects of stimulus intensity on duration selectivity over a wide range of intensities to study the consistency of duration selectivity. The results are discussed in relation to the possible mechanisms underlying duration coding and the echolocation behavior of this bat species.


 METHODS
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Animals

The study was conducted on the IC of 13 female bats, M. molossus tropidorhynchus (Gray 1839Go) (Molossidae, Chiroptera). The animals were captured at the entrance to one of their colonies located in a building in the city of Havana and kept in captivity in a room with temperature, humidity, and photoperiod conditions similar to those of the bat's natural environment. The animal use in this study was authorized by the Centre for the Inspection and Control of the Environment, Ministry of Science, Technology, and Environment, Cuba.

Surgical procedures

Bats were prepared for surgery by anesthetizing them with sodium pentobarbital (0.05 mg/g body wt) via a subcutaneous injection in the neck. A longitudinal midline incision was made through the skin overlying the skull, and the underlying temporal musculature was reflected from the incision along the midline. Wound surfaces were treated with a lidocaine solution applied topically. A custom-made metal rod was then glued to the skull using dental cement. We let the animals rest for 24 h before electrophysiological recordings. After recovery, during the experiment, the awake bats were placed in a body mold made of plastic foam. The head was tightly held by the rod fixed in a metal holder. Using skull and brain-surface landmarks (the skull in this bat is semitransparent), a small hole (1 mm diam) was made over the IC with a scalpel blade. The hole was covered with saline solution during the experiments, and care was taken to prevent desiccation. A microelectrode (see following text) was then inserted through the hole in the skull. The experiments were conducted inside a soundproofed room (temperature: 27–32°C) for <6 h. After a recording session, the exposed skull was covered with sterile bone wax, and the animal was returned to its individual cage. Bats could be studied for several consecutive days. All experiments were in accordance with the Declaration of Helsinki (Experimental animal approval: Regierung von Oberbayern: AZ 211-2531-37/98)

Acoustic stimulation and recording

Acoustic stimuli were delivered from a MicroTech Gefell 1-in microphone capsule used as a loudspeaker and placed ~2 cm away from the bat's ear. The speaker response was flat (±5 dB) in the frequency range from 20 to 80 kHz, and intensity of the presented pure tone stimuli was on-line corrected in accordance with calibration frequency response curves of the speaker. Stimuli were controlled by custom software written in ASYST (Keithley Instruments). The stimuli used were pure tones for most neurons. Broadband noise bursts were used in five cases in which the neurons only responded to noise. For most measurements, stimuli were presented monaurally at the contralateral ear. Once an auditory neuron was isolated, an automatic routine calculated its threshold frequency tuning curve and measured the best frequency (BF) and BF threshold. The tone stimuli (rise/fall time: 0.5 ms, repetition period: 300 ms) were adjusted to the neuron's best frequency, and the intensity was changed in steps of 10 dB between threshold and 100 dB SPL (0 dB SPL = 20 µPa). At each intensity tested, the duration of the stimulus was changed, usually between 1 and 30 ms, at steps of 1 ms. Extracellular single-unit recordings were made from the animals with glass micropipettes (6–24 M{Omega}) filled with 3 M KCl. By injecting HRP at the recording sites, we verified that the neurons under study were located at the central nucleus of the IC. The spike activity was monitored audiovisually; band-pass filtered (200 Hz to 3 kHz), and discriminated by amplitude. Temporal resolution to discriminate single spikes was 0.001 ms, which correspond to a sampling rate of 1 GHz. From the spike times, peristimulus time histograms (PSTHs, 1-ms bin width) were constructed. The response latency was taken as the time needed to reach the 25% of maximal spike activity in the peristimulus time histogram.

Classification of filter characteristics

For classification of duration selectivity (i.e., short-, band-, and long-pass), we used the criteria proposed by Fuzessery and Hall (1999Go). The response of a neuron was classified as duration-selective if the spike count reached a maximum at a certain stimulus duration (best duration), and dropped to <50% of the maximum response at three consecutive longer and/or shorter durations. Band-pass selectivity was defined as a response in which the spike count dropped to <50% of peak value at three consecutives shorter and longer durations. Short-pass responses were defined as those that dropped to <50% of peak value at three consecutives longer duration. In addition, those responses maintain the number of spikes >50% of the maximum number when the stimulus duration was shortened (down to minimally 0.5 ms) below best duration. Because of the temporal resolution of 1-ms step for testing duration tuning, there is a limitation in the classification of short-pass responses because some of them could become a band-pass response if the stimuli were shortened beyond the 0.5-ms minimum limit. However, this limitation would apply only to two neurons in this study because the short-pass responses remain >50% of peak value at the shortest duration tested, and a move to the band-pass group would require three consecutive shorter duration which produce responses <50% of maximum activity.

In long-pass responses, the spike count either increased with duration to a maximum plateau value at longer durations or continued to increase over the range of durations tested. Long-pass responses were defined as those that required >=5 ms of stimulus duration to reach 25% of maximum activity and the spike count of which did not decrease with longer durations. The 5-ms minimum duration criterion was used to emphasize the point that the magnitudes of long- and short-pass duration responses will be changing dramatically in opposite directions over a narrow range of durations. At a duration of <=3 ms, the majority of short-pass duration responses will be near 100% maximum value, while long-pass duration responses will be at only 0–25% maximum value.

Because the duration-filter characteristic of a neuron could change with the intensity of the stimuli, something that indeed happened frequently along this study, a filter type will characterize the response of a neuron at a particular intensity. Thus one neuron could contribute to more than one filter group if it showed different filter characteristics at different intensities.

Three different procedures were used as experimental controls to ensure that the variations observed in duration-filter characteristics were caused by variations in intensity. 1) Whenever we detected changes in spike rate or firing pattern, we repeated the stimulation protocol to make sure that the neuron's duration selectivity characteristics were stable over time. 2) Instead of varying the stimulus duration for a fixed sound level we varied the SPLs for a fixed duration to confirm the observed intensity-dependent changes in duration selectivity. 3) During all experiments, higher and lower intensity values were alternated, to rule out adaptation effects. The duration selectivity of only two neurons changed during the course of the experiment. The data of these two neurons were not included in this study.


 RESULTS
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Duration selectivity and basic response properties

Duration selectivity was studied in 61 IC neurons that responded to pure tones and in 5 neurons that responded exclusively to broadband noise. Of the 61 neurons studied, 43 (70%) showed at least one form of duration selectivity at one or more stimulus intensities. The remaining 18 (30%) were not affected by sound duration, including one of the five neurons that responded to broadband noise (Fig. 1).



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FIG. 1. A and B: total number of spikes ({bullet}) and the latency of the 1st stimulus-induced spike ({circ}) as a function of stimulus duration for 2 nonselective neurons. The frequency and sound pressure level of the stimuli are given in the top right. C and D: spike histograms from 30 responses to 3 stimulus durations. The time bin was 1 ms. , position and duration of the stimuli, and the value (in ms) is given. The left neuron [with a minimum threshold (MT) of 33 dB SPL] has a phasic response, whereas the right one (MT = 3 dB SPL) shows a phasic-tonic response. Both are onset responses. The presented data correspond A with C and B with D.

 
Sixty percent of IC neurons, whether or not they were duration selective, had no spontaneous activity. In those that did have spontaneous activity, it was low, <5 spikes/s.

All of the neurons that were not selective for stimulus duration at any intensity had onset and sustained responses (Fig. 1). We defined as sustained responses those that contained more than three spikes for stimuli >10 ms, distributed along the entire length of the stimulus or >70% of its length. In the onset responses, the first spikes of the response had a constant temporal relation to the beginning of the sound stimulus and therefore were triggered by the beginning of the stimulus.

Duration-selective neurons had either transient onset or offset responses or both. We defined as transient responses those containing <3 spikes regardless of the duration of the stimuli, limited to <50% of the length of the stimuli >10 ms. In offset responses, the first spikes of the response varied as a function of stimulus duration and therefore were triggered by the end of the stimulus. In the cases in which offset responses were found for selective neurons, they were always transient, so we will refer to them simply as offset responses. Onset responses in duration-selective neurons were mainly transient except for long-pass neurons in which sustained responses were described.

Filter characteristics

Among the duration-selective neurons, we found three different types of filter characteristics, long-, band-, and short-pass.

Long-pass responses were found in neurons that made up 33% (14/43) of the neurons in our sample, including one that was sensitive to broadband noise (Fig. 2). In some neurons with long-pass responses, shorter durations elicited no response at all (Fig. 2, B and D). The discharge patterns of long-pass responses were sustained (Fig. 2, A and C) or offset (Fig. 2, B and D). Several long-pass neurons with offset responses, including the one shown in Fig. 2, B–D, had spike-count functions that continuously increased for durations between 9 and 39 ms. These findings support the idea that duration-selective neurons do not act as energy detectors, even in long-pass neurons that intuitively show the simplest case of duration filtering: the longer the duration, the higher the energy content, and consequently the larger the response (Ehrlich et al. 1997Go).



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FIG. 2. A and B: total number of spikes ({bullet}) and latency of the 1st stimulus-induced spike ({circ}) as a function of stimulus duration for 2 long-pass neurons. - - -, the stimulus offset. C and D: spike histograms of 30 responses to 4 stimulus durations. The left neuron (MT = 12 dB SPL) shows a tonic response, whereas the right one (MT = 43 dB SPL) has a phasic offset response. The latency values of the onset neuron cross the line that represents the stimulus offset (A), whereas in the offset neuron the latency curve runs parallel to this line. The same conventions as in Fig. 1 are used. A corresponds with C and B with D.

 
Short-pass responses were found in only 16% (7/43) of the neurons in our sample, including one that responded only to broadband noise (Fig. 3). Neurons with short-pass responses fired transiently to stimulus offset, (3/7 neurons; Fig. 3, A and D), onset (3/7 neurons; Fig. 3, B and E), or both (1 neuron; Fig. 3, C and F). In the neuron with both onset and offset responses, both components showed short-pass duration selectivity.



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FIG. 3. AC: total number of spikes ({bullet}) and latency of the 1st stimulus-induced spike ({circ}) as a function of stimulus duration for 3 short-pass neurons. - - -, the stimulus offset. Neuron A (MT = 26 dB SPL) responds only to broadband noise and shows an offset response with its latency fixed to the stimulus offset. Neuron B (MT = 13 dB SPL) shows an onset response with its latency curve crossing the line of stimulus offset. Neuron C (MT = 23 dB SPL) shows a response with 2 components of different latencies: an onset component of shorter latency, and an offset component of longer latency. DF: spike histograms of 30 responses to 5 stimulus durations. The same conventions are used as in Fig. 1. Correspondence: A with D, B with E, and C with F.

 
Band-pass duration selectivity was present in 81% (35/43) of the neurons in our sample (Fig. 4). Band-pass neurons responded transiently at either the offset of the stimulus (12/34; Fig. 4, A and D) or the onset (22/34; Fig. 4, B and E). In the case of one neuron in Fig. 4C, the onset response (Fig. 4C, —) was nonselective to stimulus duration while the offset response (Fig. 4C, - - -) was band-pass. Thus this neuron coded the duration of the stimulus in the offset component only.



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FIG. 4. AC: total number of spikes ({bullet}) and latency of the 1st stimulus-induced spike ({circ}) as a function of stimulus duration for 3 band-pass neurons. - - -, the stimulus offset. A (MT = 33 dB SPL) represents an offset response and B (MT = 12 dB SPL) an onset response. C (MT = 17 dB SPL) shows the onset response (—) and the offset response (· · ·) for the same neuron. The onset component is not selective for the stimulus duration, whereas the offset component shows a band-pass response. DF: spike histograms of 30 responses to 5 stimulus durations. The same conventions are used as in Fig. 1. Correspondence: A with D, B with E, and C with F.

 
In the response of neurons that behaved as band- or short-pass filters for stimulus duration, often a second peak in their spike count functions was visible (Fig. 5). The second peak, however, was always confined to the range of stimulus durations between 10 and 16 ms. Thirty percent of the duration-selective neurons showed two distinct best durations at least at one of the intensities tested. In those two-peaked responses, the number of spikes elicited at each of the peaked durations is >200% of the number of spikes elicited at durations consecutively shorter and longer than that of the peak. Both onset (Fig. 5, A and C) and offset (Fig. 5, B and D) responses could have two peak durations.



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FIG. 5. A and B: total number of spikes count ({bullet}) and latency of the 1st stimulus-induced spike ({circ}) as a function of stimulus duration for 2 neurons with 2 preferred durations. - - -, the stimulus offset. The frequency and sound pressure level (SPL) of the stimuli are given in the top right. A (MT = 6 dB SPL) shows an onset response and B (MT = 24 dB SPL) an offset response, manifested in the behavior of their latency curves. C and D: spike histograms from 30 responses to the 1st 20 stimulus durations studied. The time bin was 1 ms. , position and duration of the stimuli. The vertical line emphasizes shifts in the response latency. A corresponds with C and B with D.

 
Duration selectivity and stimulus intensity

The influence of stimulus intensity on duration selectivity was examined in 44 neurons. Of the 44 neurons in which two or more intensities were tested, 36 (82%) showed duration selectivity at some of the intensities presented. In Table 1, the neurons are arranged according to the number of used stimulus levels to show that the probability of finding duration selectivity is correlated with the range of intensities tested.


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TABLE 1. Effect of stimulus intensity on duration selectivity in neurons from the IC of M. molossus

 
In 9 of the 36 neurons showing duration selectivity, varying the stimulus intensity did not affect the type of selectivity (Table 1, Fig. 6A). For example, in three of the eight neurons tested with seven intensities, covering a range of 80 dB, the type of filter characteristic remained unchanged across sound level. In some neurons, however, although the filter characteristic type was not affected by sound level, the best duration changed dramatically (Fig. 6B). In the neuron shown in Fig. 6B, an increment of just 10 dB caused the spike count at 11 ms to change from peak count to minimum count.



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FIG. 6. Examples of the variations in the duration-selectivity properties due to intensity changes (in steps of 10 dB) in 4 neurons of the inferior colliculus of M. molossus. The responses are in percent in respect to the maximal number of spikes elicited at each intensity, to facilitate the identification of the criteria used in the classification of the types of duration selectivity. - - -, 50% of maximal spike activity. Above each graph is the SPLs given in dB SPL and the stimulus frequency is indicated. A: the response retains a band-pass filter characteristic for stimulus duration independently of the intensity used; MT = 12 dB SPL. B: even while keeping a band-pass filter characteristic, the best duration changes dramatically for different intensity values. The maximal response found at 11 ms at 10 dB SPL becomes a minimal response at 20 dB SPL, an intensity that provokes 2 peaks in the response at 4 and 15 ms. With an intensity of 30 dB SPL, the peak moved to 2-ms duration; MT = 6 dB SPL. C: for 2 intensities separated by 20 dB from each other, the neuron is not duration selective (50, 70 dB SPL). In contrast, at the intermediate level of 60 dB SPL, the same neuron acts as a short-pass filter; MT = 22 dB SPL. D: a high-pass response changes to a nonselective and to a band-pass response with successive increases in SPL in steps of 10 dB; MT = 4 dB SPL.

 
In the majority of neurons, changes in SPL produced dramatic changes in the type of filter characteristic. For example, in the neuron shown in Fig. 6C, the nonselective response at 50 dB SPL changed to a short-pass response at 60 dB SPL and again to a nonselective response at 70 dB SPL. The neuron in Fig. 6D acted as a high-pass filter at 8 dB SPL, changed to a nonselective response at 18 dB SPL, and finally to a band-pass filter at 28 dB SPL. In the example displayed in Fig. 7, an additional response component at short durations appeared at sound pressure levels >=85 dB SPL. This change in discharge pattern changed the neuron's filter characteristic from long-pass (1st component) to band-pass (2nd component, best duration: 3.5 ms) and later to short-pass (2nd component, best duration: 2.5 ms).



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FIG. 7. A: total number of spikes as a function of the stimulus duration, at 4 different intensities, in a neuron from the inferior colliculus (IC) of M. molossus. At 38 and 68 dB SPL, the response of the neuron behaves as a high-pass filter for the stimulus duration. At 85 dB SPL, an additional component appears in the response to short stimulus durations that makes the response act as a band-pass filter even when the high-pass selectivity observed at low intensities is still present. This new component with a preference for shorter durations is dominant at 91 dB SPL and determines a short-pass selectivity type. The frequency and SPL of the stimuli are given in the top right corner. The MT in this neuron was 17 dB SPL. B: raster displays of the spikes elicited in the 30 responses obtained with each of the durations tested. The same temporal scale is used for all panels.

 
Because we found that duration selectivity varied with stimulus intensity, we used three different intensity ranges to quantify best durations in the population of neurons studied. Low intensities were defined as 10–30 dB SPL, medium intensities as 40–60 dB SPL, and high intensities as 70–90 dB SPL. The distribution and range of best durations was approximately the same for all groups (Fig. 8A). In each group, all best durations are <20 ms except one different neuron in each of the three categories. The maximum number of neurons was at a best duration of 2 ms for all intensities tested. Figure 8B plots best duration as a function of BF. We included the best duration values obtained at each intensity tested in a single neuron. Therefore for the same BF, one neuron can be represented in this figure with more than one best duration. It should be noted that the widest range of best durations (from 1 to 25 ms) is found in the frequency range between 30 and 40 kHz.



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FIG. 8. A: distribution of best durations in neurons from the IC of M. molossus for 3 different intensity ranges. The histograms have been calculated with a temporal resolution of 1 ms in each of the 3 groups. B: BF of each duration-selective neuron. The graphic includes the values obtained with each of the intensities tested, and therefore 1 neuron could be represented more than once. The widest distribution of best durations is found for neurons that process frequencies between 30 and 40 kHz.

 

 DISCUSSION
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Mechanisms underlying duration selectivity

It is well known that a large proportion of auditory neurons above the lower brain stem respond transiently regardless of the duration of the acoustic stimuli (e.g., Galazyuk and Feng 1997Go; Jen and Schlegel 1982Go), so there are few sustained responses to provide information about stimulus duration. On the other hand, neurons selective to narrow ranges of durations are common in the auditory midbrain and the primary auditory cortex (Brand et al. 2000Go; Casseday et al. 1994Go; Chen 1998Go; Erlich et al. 1997; Faure et al. 2003Go; Fuzessery and Hall 1999Go; Hall and Feng 1986Go; He et al. 1997Go; Ma and Suga 2001Go; Narins and Capranica 1980Go; Penna et al. 2001Go; Pinheiro et al. 1991Go). Two different physiological mechanisms have been proposed to explain how duration selectivity arises in the IC of bats: coincidence and anti-coincidence (Casseday et al. 1994Go; Erlich et al. 1997; Fuzessery and Hall 1999Go). It has been shown that these same mechanisms can explain duration selectivity in other animal groups such as cats and mice (Brand et al. 2000Go; He et al. 1997Go).

The coincidence model requires offset excitation or rebound from inhibition in duration-selective neurons. Support for this model comes from the fact that >50% of duration-selective neurons in the IC of E. fuscus (Erlich et al. 1997) and 42% of neurons that responding best to short durations in the IC of A. pallidus (Fuzessery and Hall 1999Go) are clearly offset responders. In the population of duration-tuned cells studied in the IC of M. molossus, a similar proportion of offset neurons was found. Thirty-nine percent of the short- and band-pass neurons in Molossus were clearly offset responders and thus consistent with the coincidence model (Figs. 3, A and C, and 4, A and C). The coincidence model predicts that the broader the range of latencies in a population of neurons, the broader should be the range of best durations. Latencies measured in neurons of the IC of E. fuscus were between 2 and 30 ms (Haplea et al. 1994Go), whereas the best durations of duration-selective neurons were between 1 and 20 ms (Ehrlich et al. 1997Go). In M. molossus, the latencies of the collicular neurons ranged between 5 and 38 ms, and the best durations between 1 and 25 ms, which is comparable to the situation in E. fuscus.

In addition to an offset excitatory component, the coincidence model requires also an onset-evoked subthreshold excitatory input. In other words, the presence of OFF responses does not automatically implicate a coincidence mechanism; particularly if OFF responses occur over a wide range of durations. Thus the coincidence of the two components predicts that maximum OFF responses will occur over a limited duration range. In view of the complexity of neural connectivity in the IC, there is a high probability that single neurons receive several excitatory input synapses, which are temporally segregated and strong enough to produce postsynaptic potentials that would bring the cell to threshold if they coincide with a postinhibitory rebound (Fig. 9). Thus the coincidence model would predict that the temporal shift of the rebound produced by increasing the stimulus duration could lead to a spike response at more than one stimulus duration. Two-peaked duration spike-count functions have been described only in some neurons of the IC of E. fuscus (Pinheiro et al. 1991Go), and 28% of the duration-selective neurons in the IC of M. molossus have two-peaked spike-count functions. Therefore we propose that the synaptic interactions underlying duration selectivity are in some cases more complex than those modeled so far in the literature. In >50% of the neurons showing two duration peaks in our study, the presence of the two peaks (Fig. 5B) could be explained by two temporally segregated excitatory inputs interacting with the postinhibitory rebound over two different duration ranges (visualized in Fig. 9). In some neurons, there appeared to be convergence between excitatory inputs involved in duration tuning and other excitatory components that were independent of stimulus duration. In the neuron shown in Fig. 4C, the onset excitatory input was strong enough to generate spike responses at every duration tested.



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FIG. 9. Schematic drawing of the elements that are required for the coincidence mechanism proposed by Ehrlich et al. (1997Go) for explaining duration tuning. {blacksquare}, position and duration of the stimuli. i, the short-latency inhibitory input persists for the duration of the stimulus; r, excitatory rebound from inhibition; e1 and e2, delayed excitations triggered by the stimulus onset. A: none of the excitatory components can reach the spike threshold. B and C: at certain stimulus durations, the rebound from inhibition will converge with excitatory postsynaptic potentials and the spike threshold is reached. The duration-dependent spike-count function of this neuron will have 2 maxima as the 1 shown in Fig. 5B.

 
Because some duration-tuned neurons in E. fuscus (Ehrlich et al. 1997Go) and most duration-tuned neurons in A. pallidus (Fuzessery and Hall 1999Go) respond to sound onset, a second model, anti-coincidence, was proposed to explain duration selectivity (Fuzessery and Hall 1999Go). In the anti-coincidence model, excitatory input will generate spikes until duration is such that a shorter-latency sustained inhibitory input lasts long enough to coincide with the transiently excitatory response and cancel it. So, responses are triggered only if excitation and inhibition are noncoincident. This type of mechanism may produce short-pass selectivity. In M. molossus, we have found neurons showing responses consistent with the noncoincidence model (Figs. 3B and 4B). However, this model alone cannot account for the two-peaked spike-count functions that we found in M. molossus (Fig. 5A). One possible explanation for onset double-peaked duration tuning could be a noncoincidence mechanism that creates one of the peaks and that the other peak reflects a strong input from another duration-selective neuron. Thus some duration-selective neurons in the IC would project on other duration-selective IC neurons that will end up showing each selectivity. There is evidence that some IC neurons preserve the selectivity properties of their input because blocking local inhibitory synapses did not affect duration tuning in those neurons (Casseday et al. 1994Go; Fuzessery and Hall 1999Go).

Duration selectivity and stimulus intensity

When only one stimulus intensity was considered, ~41% (7/17) of the neurons in Molossus are duration selective. This percentage is roughly comparable to that described in other species [E. fuscus: 36% (Ehrlich et al. 1997Go); A. pallidus: 53% (Fuzessery and Hall 1999Go)]. However, if we include several stimulus intensities in the analysis, the percentage of duration-selective neurons increases to 70% (43/61). Such a high percentage of duration-selective neurons has been described only in the auditory cortex of Myotis lucifugus (69%) (Galazyuk and Feng 1997Go). Considering that 10/18 of the neurons classified as nonselective for stimulus duration were stimulated with only one intensity, it is likely that the percentage of duration-selective neurons would increase if each neuron were studied with several intensities (see Table 1).

The results obtained in M. molossus show that in this species the stimulus intensities used for testing can dramatically affect our estimate of the occurrence and types of duration selectivity in the IC. In other bat species investigated so far, the effect of changes in stimulus level either has not been tested systematically (Ehrlich et al. 1997Go; Fuzessery and Hall 1999Go) or the observed changes in duration tuning were small (Casseday et al. 1994Go). Recently it has been demonstrated that one third of the IC neurons of E. fuscus slightly change their duration-selectivity characteristics when stimulus intensity is increased by >20 dB (Faure et al. 2003Go; Zhou and Jen 2001Go). However, with intensity variations of <20 dB, there was almost no effect on duration selectivity. The pronounced intensity-dependent changes in duration selectivity observed in M. molossus could represent a possible interfamily difference because the rest of the species studied so far belong to the family Vespertilionidae and M. molossus to Molossidae.

In a study on the vespertilionid bat M. lucifugus, Galazyuk and Feng (1997Go) showed that varying intensity affected duration selectivity of cortical neurons but not IC neurons. This result, together with the finding that every cortical duration-selective neuron had an onset response, made the authors suggest that duration selectivity undergoes considerable transformations between the IC and the cortex. Because our data suggest that the types of transformations that occur between the IC and cortex in Myotis have already occurred at the IC in M. molossus, more studies of the vespertilionid IC would be needed before conclude about this physiological difference as an interfamily distinctive character.

Neuroethological considerations

Neuronal selectivity for stimulus duration is a mechanism that presumably operates during the processing of biologically important signals such as echolocation calls in bats. In the pallid bat, all duration tuned IC neurons had best durations below 7 ms, which coincides with the range of duration values in its echolocation calls (Fuzessery and Hall 1999Go). Similarly, in E. fuscus and M. lucifugus, this range was broader with best-duration values <=20 ms corresponding to the longer call durations used by these species (Ehrlich et al. 1997Go; Galazyuk and Feng 1997Go). In M. molossus, the best-duration histograms showed peaks around the duration values that characterize the echolocation calls used by this species while searching for its prey or while entering or exiting its diurnal roost (Kössl et al. 1999Go). In addition, these are calls with a frequency content usually limited to the range from 30 to 40 kHz, where most duration tuned neurons were found. Neurons' best durations coincide with duration values of M. molossus ' echolocation calls, even in the cases in which neurons showed two peaks in their spikes count functions. Approximately one-third of the duration-selective neurons in the IC of this species process stimulus durations between 8 and 14 ms, a range that corresponds to the calls emitted when searching for prey. Another 40% of IC neurons in M. molossus process durations between 2 and 5 ms, a range of durations that includes the three types of calls that are emitted when the animals leave or return to their roost and those calls emitted during the final buzz of their hunting behavior (Kössl et al. 1999Go). These percentages remain constant along the three groups of intensities analyzed.

Duration coding appears to be a general mechanism spread throughout the animal kingdom. In species that strongly depend on acoustic information (i.e., bats and frogs), it seems to contribute to selective processing of behaviorally relevant sounds, such as those used to find food or mates (Ehrlich et al. 1997Go; Fuzessery and Hall 1999Go; Galazyuk and Feng 1997Go; Hall and Feng 1986Go; Penna et al. 2001Go). However, the significance of duration-selective neurons in species that rely more on visual information is not as clear (Brand et al. 2000Go; He et al. 1997Go).

The observed intensity-dependent changes in duration tuning point to the possibility that different subpopulations of duration-selective neurons in the IC of M. molossus are responsible for different tasks concerning sound identification based on sound duration. Thus the subpopulation of neurons in which the duration-filter characteristics remain unchanged across sound level (25% in this study) could be in charge of tracking the bat's own sounds both while dealing with emitted calls or returning echoes. Another subpopulation of neurons show pronounced changes in their duration-filter characteristics with slight changes in sound intensity. These neurons may respond preferentially to specific combinations of duration and intensity of a sound signal such as the duration of the echolocation calls and the echo intensity that corresponds to a limited bat-target distance. If this is the case, this subpopulation of neurons will help in addressing the estimation of the distance to the target in parallel to delay-sensitive neurons (Covey and Casseday 1999Go; Saitoh and Suga 1995Go).


 ACKNOWLEDGMENTS
 
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Our gratitude to Dr. Ellen Covey for valuable comments on the manuscript. We also thank Dr. Elisabeth Foeller and others at the Zoological Institute of the University of Munich for caring for the animals and advice during the experiments.

GRANTS

The authors thank the Volkswagen Foundation (project: I/77306) and the Deutsche Forschungsgemeinschaft for support.


 FOOTNOTES
 
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.

Address for reprint requests and other correspondence: E. C. Mora, Dept. of Animal and Human Biology, Faculty of Biology, Havana University, Calle 25 No. 455 entre J e I, Vedado, CP. 10 400, Ciudad de La Habana, Cuba (E-mail: emanuel_mora{at}yahoo.com).


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