The evolution of temporal processing in the medial superior olive, an auditory brainstem structure

Progress in Neurobiology 61 (2000) 581±610

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The evolution of temporal processing in the medial superior olive, an auditory brainstem structure Benedikt Grothe* Max-Planck-Institute of Neurobiology, Am Klopferspitz 18a, 82152 Martinsried, Germany Received 11 October 1999

Abstract A basic concept in neuroscience is to correlate speci®c functions with speci®c neuronal structures. By discussing a speci®c example, an alternative concept is proposed: structures may be linked to rules of processing and these rules may serve di€erent functions in di€erent species or at di€erent stages of evolution. The medial superior olive (MSO), a mammalian auditory brainstem structure, has been thought to solely process interaural time di€erences (ITD), the main cue for localizing low frequency sounds. Recent ®ndings, however, indicate that this is not its only function since mammals that do not hear low frequencies and do not use ITDs for sound localization also posses a MSO. Recordings from the bat MSO indicate that it processes temporal cues in the milli- and submillisecond range, based on monaural or binaural inputs. In bats, and most likely in other small mammals, this temporal processing is related to pattern recognition and echo suppression rather than sound localization. However, the underlying mechanism, coincidence detection of several inputs, creates an epiphenomenal ITD sensitivity that is of no use for small mammals like bats or ancestral mammals. Such an epiphenomenal ITD sensitivity would have been a pre-adaptation which, when mammals grew larger during evolution and when localization of low frequency sounds became a question of survival, suddenly gained relevance. This way the MSO became involved in a new function without changing its basic rules of processing. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: Sound localization; Interaural time di€erences; Interaural level di€erences; Temporal processing; Medial superior olive; Superior olivary complex; Bats; Hearing; Evolution of sensory system

Contents 1.

Principles of sound localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 582 1.1. The need for coding interaural time di€erences . . . . . . . . . . . . . . . . . . . . . . . . . . . . 582 1.2. The principles of ITD coding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 584

2.

The classical picture of the MSO: the role of MSO in low frequency hearing mammals. . . . . 586

3.

The MSO in small, only high frequency hearing mammals . . . . . . . . . . . . . . . . . . . . . . . . . 590 3.1. The rat MSO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590 3.2. The MSO in bats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591

Abbreviations: AVCN, antero ventral cochlear nucleus; CN, cochlear nucleus; DMPO, dorsomedial periolivary nucleus; DNLL, dorsal nucleus of the lateral lemniscus; e/E, weakly excited from the ipsilateral side/excited from the contralateral side; E/E, excited from both sides; E/ I, excited from ipsilateral/inhibited from contralateral; IC, inferior colliculus (auditory midbrain); ILD, interaural level di€erence; IPD, interaural phase di€erence; ITD, interaural time di€erence; LNTB, lateral nucleus of the trapezoid body; LSO, lateral superior olive; MNTB, medial nucleus of the trapezoid body; MSO, medial superior olive; NL, nucleus laminaris; SAM, sinusoidally amplitude modulated; SOC, superior olivary complex; SPN, superior paraolivary nucleus; VCN, ventral cochlear nucleus. * Tel.: +49-89-8578-3728; fax: +49-89-8995-0048. E-mail address: [email protected] (B. Grothe). 0301-0082/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 3 0 1 - 0 0 8 2 ( 9 9 ) 0 0 0 6 8 - 4

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3.2.1. 3.2.2. 4.

The MSO in the mustached bat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593 The MSO in ``normal'' FM-bats. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607

1. Principles of sound localization 1.1. The need for coding interaural time di€erences A primary goal of the mammalian auditory system is to localize behaviorally relevant sounds in

space. Interaural level di€erences (ILD), caused by the head which acts as obstacle re¯ecting sound waves, enable even small mammals like insectivorous bats or mice to localize high frequency sounds with high spatial precision (Fig. 1A; Erulkar, 1972; Sim-

Fig. 1. Principles of interaural level and time di€erence coding in the mammalian auditory system. Left: High frequency sound waves are re¯ected by the head producing interaural level di€erences (ILD) if a sound source is not straight ahead. ILDs are initially processed by neurons in the LSO. These neurons receive excitatory from the ipsilateral ear via neurons from the ventral cochlear nucleus (VCN) and inhibitory inputs from the MNTB that, in turn, receive its inputs from the contralateral VCN. Because of the interaction of these two inputs LSO neurons respond maximally to ipsilateral sounds and minimally to contralateral sounds. The upper panel gives a typical ILD function of a LSO neuron (response rate as a function of ILD). Right: The head does not re¯ect long sound waves (low frequencies). Hence, interaural time di€erences (ITDs) are the only cue available to localize low frequencies in the azimuthal plane. ITDs are initially processed by neurons in the MSO that receives binaural excitatory and inhibitory inputs. The dominating principal in ITD coding by these neurons is thought to be coincidence detection of the excitatory inputs. For details see text. Black arrows: inhibitory projections; gray arrows: excitatory projections. N.VIII = auditory nerve; LNTB = lateral nucleus of the trapezoid body; LSO = lateral superior olive; MNTB = medial nucleus of the trapezoid body; MSO = medial superior olive; VCN = ventral cochlear nucleus.

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Fig. 2. Naturally occurring ILDs and ITDs in response to a 35 kHz tone in a small bat, Molossus ater, depending on the position of the sound source in the horizontal plane. Note the large ILDs of up to 40±50 dB in contrast to the very small ITDs of only up to 50 ms. After Harnischfeger et al. (1985).

mons, 1987; He€ner and He€ner, 1990). Even in a small bat with an inter ear distance of less than 2 cm, interaural level di€erences can reach 40 dB (Erulkar, 1972; Harnischfeger et al., 1985; Obrist et al., 1993; Fig. 2) which covers a signi®cant portion of the dynamic range of sound intensities the mammalian auditory system encodes (ca. 120 dB SPL; Viemeister and Bacon, 1988). Hence, ILD coding does not challenge the general abilities of the mammalian auditory system and is, consequently, used for sound localization whenever ILDs are available. However, at low frequencies, when the wavelength is equal or longer than the inter ear distance, the head does not re¯ect sound waves. Thus, ILDs are not available for localizing low frequency sounds. For instance, humans cannot localize sounds below 1.4 kHz by using ILDs (Rayleigh, 1907). For animals with smaller heads, this borderline is higher. In the freetailed bat, an insectivorous echolocating bat that will be discussed in some detail below, it is around 7±10 kHz. However, the audiogram of these animals hardly reach such ``low'' frequencies (Schmidt et al., 1990). In animals that do hear frequencies below this point, interaural time di€erences (ITDs) are the only cue 1 This should not be confused by the fact that in humans the low frequency range (<1400 Hz) Ð the range that dominates our acoustic communication Ð became so important that ITDs dominate IIDs in broad band sounds. From the evolutionary perspective, however, this is more an exception than the rule (He€ner and He€ner, 1990).

available to localize sounds of such low frequencies (Fig. 1B). However, the ITDs experienced by mammals are in the order of only a few hundreds or tens of microseconds. For instance, even sounds localized 908 from the vertical plane cause ITDs of < 800 ms in humans, < 400 ms in cats, < 100 ms in most rodents, and < 50 ms in most bats. ITDs that correspond to sound sources just slightly shifted from the vertical plane are in the range of only a few microseconds (humans) or even less than a microseconds in smaller mammals. Nevertheless, mammals with well-developed low frequency hearing, including humans, use these small ITDs for sound localization. The solution for ITDs in humans is in the range of only 20 ms. This accuracy is in remarkable contrast to the general time resolution with respect to other acoustic time cues. For instance, most mammals, including humans, cannot detect gaps in broadband noise if shorter than 1±2 ms (Rayleigh, 1907; Blauert, 1983; Moore, 1985; Wightman et al., 1989). Thus, the time resolution for gapdetection is two orders of magnitude above that for ITD coding. In order to process naturally occurring ITDs, special structures with signi®cantly improved time resolution had to be evolved. It, therefore, seems reasonable to use ILDs whenever available, simply because they are more prominent than ITDs. Accordingly, in humans, ILDs dominate over con¯icting ITDs (that can be arti®cially introduced in experiments using dichotic stimulation) in the high frequency range (Wightman and Kistler, 1992).1 However, there is a second reason why ILD coding

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is more widespread in mammals (He€ner and He€ner, 1990). The early type of the mammalian middle ear evolved in the Triassic period some 210 million years ago. Our ancestors before the Triassic, such as the earlier Pelycosaurs and later Therapsids, had no functional middle ear and could only hear substrate vibrations (for review, see Clack, 1997). In the early Triassic, the increasing success of archosaurs, especially of dinosaurs, was accompanied by a high rate of extinction of the rather large Mesozoic Therapsids (cf. Carroll, 1988), a dramatic bottleneck in mammalian evolution. Only the smallest survived and developed into what we call the earliest mammals (Hopson, 1973; Crompton and Jenkins, 1979). These animals had head widths of 2.5 cm or less (Rowe, 1988; Lillegraven and Krusat, 1991). For instance, Morganucodon, one of the most common early Mesozoic mammals, had an interaural distance of less than 3 cm (Kermack et al., 1981). These animals were, mostlikely, the ®rst in the lineage of our direct ancestors that were capable of hearing airborne sound by use of a functional middle ear (Allin, 1975; Crompton and Parker, 1978; for review, see Clack, 1997). Interestingly, in the Triassic period all recent tetrapode lineages independently evolved sound transducing middle ears (Allin, 1975; Maier, 1990; for review, see Clack, 1997). Whereas amphibians and reptiles (and descendants, birds) evolved one ossicle middle ears that are well, but only, suited for transmitting low frequencies, the mammalian middle ear started as a three ossicle structure. Reconstructions of the early mammalian middle ear suggest that it only transmitted frequencies above 4±5 kHz (Fleischer, 1978; Rosowski, 1992). In fact, these animals' middle ears were supposedly almost identical with those from recent opossums of the family Didelphidae (Gregory, 1929). Frost and Masterton (1994), testing opossums in a behavioral task, revealed their poor ability to hear low frequency sounds (below 4±6 kHz) which is in remarkable contrast to their well-developed high frequency hearing. Mesozoic mammals most likely relied on the use of ILDs as a primary binaural cue for exact sound localization for a time span of may be more than 100 million years (cf. Rowe, 1988). Therefore, it is not surprising that good high frequency hearing is still more common among mammals than good low frequency hearing (He€ner and He€ner, 1990). This corresponds to the fact that the ``intensity-di€erence pathway'' (Fig. 1A) in the mammalian ascending auditory system is well established and very similar across almost all mammalian orders. Low frequencies, however, travel longer distances and are important for animals with spatially large behavioral ranges like carnivores, ungulates, or primates, and for animals living in the desert (e.g. several rodents like gerbils; Rosowski et al., 1999). The audi-

tory system of these animals adapted to encode low frequency sounds that all ancient mammals could not and the majority of recent mammals still cannot hear. By improving low frequency hearing, these animals also evolved mechanisms to localize low frequencies by using ITDs. The basic structures that enables mammals to encode ITD is the medial superior olive (MSO). 1.2. The principles of ITD coding Fifty years ago Je€ress (1948) published a model of how the auditory system might encode ITDs. The keyfeature of his model is coincidence detection by neurons that only respond when binaural excitatory inputs arrive simultaneously. If the time to transmit sound evoked activity from both ears to a given neuron were identical, this neuron would only respond when a sound source were straight-ahead. If the travel time to a coincidence detector neuron would mismatch, coincidence would only occur if an interaural time di€erence compensates for this mismatch. Such a neuron would only respond if a sound source were in a particular position o€-midline. Je€ress proposed that systematically arranged mismatches of inputs to coincidence detector neurons due to di€erent travel times from both ears caused by di€erent axonal length (``delay lines''; Fig. 3) could create an ITD map that encodes the position of a sound in the horizontal plane. A necessary assumption of the Je€ress model is that the inputs carry timing information. For pure tone sinewaves this is done in the auditory nerve by ``phaselocking'': The discharge of the coincidence detector inputs is strongly related to a certain phase angle of

Fig. 3. The Je€ress model of ITD detection. An array of coincidence detector neurons that only respond if binaural excitatory inputs arrive exactly simultaneously. Variation of axonal length of the inputs causes di€erent traveling times of the neural activity to the coincidence detector neurons (so-called ``delay-lines''). Consequently, for di€erent azimuthal positions of a sound source (=di€erent ITDs) coincidence of inputs will occur at di€erent neurons. Thereby a systematic place code of azimuthal position could be created. After Je€ress (1948).

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Fig. 4. Some principles of coincidence detection shown for a neuron with equal traveling time of neuronal activity from the two ears. Actionpotentials of the inputs have to be phase-locked to either the sine wave of a pure tone (left) or the envelope of a high frequency sound (right, shown for a sinusoidally amplitude modulated sound). Left panels: the phase-locked inputs from the ipsilateral (``ipsi in'') and contralateral inputs (``contra in'') are coincident (left), the MSO output will be maximal. Right panel: the inputs are 1808 out of phase, the MSO output is minimal. The lower panel shows the spike rate for such a MSO neuron as a function of interaural phase di€erence (IPD).

the sinewave of a low frequency sound or to the envelope of complex sounds with a high frequency carrier2 (Fig. 4). Only then a coincidence detector is enabled to 2 by and large, neurons in the mammalian auditory system, only phase-lock to frequencies below 2 kHz. 3 Even though not only cable length but also varying conductance time seems to be responsible for the di€erences in traveling time of an action potential in the barn owl NL (Carr and Konishi, 1990).

process ITDs of an ongoing sound. Without such a temporal locking, only transients of sounds could be localized (Fig. 4). Studies from the barn owl (Carr and Konishi, 1990) and the chicken (Reyes et al., 1996) showed that the nucleus laminaris (NL), a lower auditory brainstem structure in birds, appears to be the site of the Je€ress coincidence detector3. However, there are unresolved di€erences in the organization of the NL of the chick

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Fig. 5. The anatomy of the cat superior olivary complex from the historic book of Ramon y Cajal (1907). A: the left SOC with the S-shaped LSO (``D'') and just medial to it the MSO (``C''). Note the orderly arrangement of the ®bers entering the MSO from both sides. B: Golgi-stained MSO cells of a right MSO. The MSO principal cells are bipolar with dendrites orthogonal to the dorso-ventral axis of the nucleus (``A''). From ``History of the nervous system, Vol. I'' by Ramon y Cajal, c 1995 by Oxford University Press, Inc. used by permission.

and the barn owl. In the chick, NL is a single monolayer of cells and the a€erents from the cochlear nucleus of either side project mediolaterally (Young and Rubel, 1983) in accordance with Je€ress' model. This establishes a map of ITDs along the mediolateral dimension. A similar organization is seen in the barn owl but here the NL is much thicker dorsoventrally and the map of ITDs is proposed to be along this dorsal±ventral dimension, despite the obvious delay line along the mediolateral dimension (Carr and Konishi, 1990). What happens along the more prominent delays along the mediolateral dimension of the barn owl has not been satisfactorily resolved. By far less clear, however, is the situation in the mammalian auditory system in which the MSO (Fig. 1) is thought to function as ITD detector following the principles described above.4 However, in contrast to the NL the evidences concerning the role of the MSO in auditory processing in general as well as the underlying mechanisms are

somewhat inconsistent. On the one hand, animals like bats that only hear high frequencies and should not possess ITD-detecting structures, do possess an MSO as other small mammals. Thus, the MSO in high frequency hearing animals either (1) has a di€erent function, or (2) the view of the MSO as a pure ITD detector is incomplete, or (3) ITD detection is indeed relevant for localizing high frequency sounds. On the other hand, the nature of the prominent inhibitory projections to the MSO (see below) is in some con¯ict to the idea of Je€ress' coincidence detector model purely based on excitation. These inhibitory inputs derive from the medial and lateral nuclei of the trapezoid body (Figs. 1 and 8) and provide exact timing information (see below). A comparative approach taking into account the general evolution of mammalian hearing might help to come to a more consistent picture of what the MSO does and how it is functioning.

4 The MSO and its equivalent in birds, the N. laminaris have been assumed to be homologues by several authors. However, to date this assumption is not proven since a similar structure does not exist in amphibians, the only terrestrial outgroup. A profound di€erence in the inhibitory input to these nuclei adds to the confusion (see below). Moreover, the fact that other superiorolivary nuclei do not have equivalent structures in birds prevent a nucleus by nucleus comparison between these brainstem regions. Last but not least, the fact that birds and mammal had no common ancestor capable of hearing airborne sound (Clack, 1997) requires the assumption of independent adaptations for ITDdetection in birds and mammals.

2. The classical picture of the MSO: the role of MSO in low frequency hearing mammals The MSO, originally described by Ramon y Cajal (1907) for the cat (Fig. 5), is part of the superior olivary complex (SOC), the ®rst station in the ascending mammalian auditory system that receives projections from both ears. The idea that MSO neurons act as coincidence detectors, matching the Je€ress model of ITD coding, is based on several

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Fig. 6. ITD sensitivity in the cat MSO. The left panel shows ITD functions of a cell in response to di€erent pure tones (500±1700 Hz). The response varies in a cyclic fashion depending on the cycle length of the pure tones. However, a peak of the ITD functions always occurs when the ipsilateral stimulus is delayed by about 33 ms. The other peaks and troughs are shifting as a function of the stimulus frequency. The right panel shows the result of a vector analysis of these functions. The mean interaural phase angels of all functions are calculated and plotted as a function of the stimulus frequency. The steepnes of the regression line of these data points give the characteristic delay …CP ˆ 33 ms) that corresponds to the best ITD, the intercept with the ordinate gives the characteristic phase …CP ˆ 0:63; cf. Fig. 7 and text). From Yin and Chan (1990).

lines of evidence derived mainly from studies of the cat and dog MSO. First, the MSO principal cells are bipolar with dendrites oriented in the mediolateral plane reaching in both directions (Ramon y Cajal, 1907; Stotler, 1953; Fig. 5) where they receive projections from spherical bushy cells in the ipsilateral and the contralateral cochlear nucleus (Warr, 1966; Osen, 1969). Second, single unit recordings in the MSO of cats (Galambos et al., 1959; Caird and Klinke, 1983; Yin and Chan, 1990), dogs (Goldberg and Brown, 1969), kangaroo rats (Moushegian et al., 1975; Crow et al., 1978), gerbils (Spitzer and Semple, 1995), rabbits (Batra et al., 1997a) and free-tailed bats (Grothe and Park, 1998) showed that the majority of MSO neurons can be driven monaurally by sound at either ear (socalled E/E units since they receive excitatory inputs from both sides). Third, the tonotopic organization in the dog and cat MSO is distorted in that low frequencies are over-represented compared to high frequencies (Goldberg and Brown, 1969; Guinan et al., 1972). Fourth, auditory nerve ®bers tuned to low frequencies respond to pure tones with a phase-locked discharge such that action potentials are synchronized with each cycle of a pure tone's sine wave (Galambos and Davis, 1943; Kiang et al., 1965; Rose et al., 1967). This phase-locking to low frequencies is enhanced in 5 For reasons of easy analysis, ITDs can also be expressed as phase di€erences (IPDs) when stimuli with a sinusoidal structure are used as test signals: low frequency pure tones (<2 kHz) or sinusoidally modulated high frequency signals. In the ®rst case, neurons phase lock to the pure tone, and in the latter case, neurons phase lock to the stimulus envelope.

the spherical bushy cells of the cochlear nucleus that project to the MSO (Joris et al., 1994a, 1994b). Low frequency MSO neurons also exhibit a phase-locked discharge to low frequency tones (Galambos et al., 1959; Goldberg and Brown, 1969; Crow et al., 1978; Yin and Chan, 1990; Spitzer and Semple, 1995; Batra et al., 1997a). Fifth, when ongoing pure tones are presented at the two ears simultaneously but with varying interaural phase di€erences (IPD),5 MSO neurons respond best to certain IPDs (Fig. 6). In most cases, the response to favorable IPDs is highly facilitated with spike rates signi®cantly exceeding the sum of separate ipsilateral and contralateral stimulation. Additionally, the responses to these IPDs exhibit a far higher degree of phaselocking than to unfavorable IPDs (Goldberg and Brown, 1969; Crow et al., 1978; Caird and Klinke, 1983; Yin and Chan, 1990; Spitzer and Semple, 1995; Batra et al., 1997a). Sixth, the best interaural phase delay (best ITD for a given test frequency) can be predicted by the phase delay of the two monaural responses (Goldberg and Brown, 1969; Yin and Chan, 1990; Spitzer and Semple, 1995; Grothe and Park, 1998). The two last criteria, in particular, are indicative, even though no proof, of a Je€ress-type coincidence detector mechanism. Seventh, the ITD of maximal discharge of an individual neuron remains stable when tested at di€erent frequencies, whereas the trough shifts as a function of frequency, as shown in Fig. 6 and schematically in Fig. 7 (Yin and Chan, 1990; Spitzer and Semple, 1995; Batra et al., 1997a; Grothe and Park, 1998). This ITD is de®ned as the characteristic delay (CD) that derives from the slope of a function of interaural phase delays (interaural phase delays as a function of the test fre-

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Fig. 7. A: ITD functions as they would result from a neuron that acts as a coincidence detector for binaural excitatory inputs (E/E). The ITD functions for di€erent stimulus frequencies are perfectly lining up at a certain best ITD (``peak-type''; left panel). The regression line of the calculated mean ITD angles expressed as interaural phase delays (right panel) intercepts the ordinate of the interaural phase function at 0 indicating a characteristic phase (CP) of 0. A characteristic phase around 0 or 1 is indicative of a coincidence detector mechanism. Note that the functions closely resemble those of the cat MSO neuron shown in Fig. 6. B: In contrast to A, an E/I interaction would cause a stable trough in the ITD functions (``trouph-type'') instead of a stable peak when tested at di€erent stimulus frequencies. The calculated mean angles give a CP of 0.5, indicating that the maximum spike rate occurs when the stimuli are maximally out of phase (1808).

quency). This stability of the peak in the ITD function (``peak-type'') is predicted by the concept of excitatory±excitatory coincidence detection.6 Eighth, albino cats exhibit a pronounced atrophy of MSO neurons (Conlee et al., 1984, 1986) that corresponds to behavioral de®cits in azimuthal sound localization (He€ner and He€ner, 1987) and a diminished ITD sensitivity at the level of the auditory midbrain (Yin et al., 1990). Still an uncertainty represents the question of whether MSO inputs take the course of delay lines as proposed by Je€ress (1948). In contrast to the inputs to the NL in birds, the length of single axons entering the MSO is dicult to estimate. Moreover, some ®bers 6 In contrast, in neurons with one excitatory and one inhibitory input (E/I), the trough of the ITD function remains stable whereas the peak shifts as a function of frequency (Yin and Kuwada, 1983), as depicted in Fig. 6c.

coming from the contralateral cochlear nucleus match the concept of delay lines whereas others do not. This problem is even more severe concerning the ipsilateral inputs (Smith et al., 1993; Beckius et al., 1999). A similar problem concerns the question whether there is a systematic representation of best ITDs in the MSO according to the place code proposed by Je€ress (1948). In contrast to the bird NL, there is only very weak evidence for such a map of best ITDs along the rostro-caudal axis of the MSO (Yin and Chan, 1990). If there is such a map of ITDs, it is an enigma what happens to it at the next higher level, the central nucleus of the inferior colliculus where no systematic representation of ITDs has been found. Taken together, there is little doubt that MSO neurons in mammals with good low frequency hearing like carnivores and desert rodents show a good ITD sensitivity. However, beside the problem of what MSO-cells might do in only high frequency hearing mammals there are two major problems concerning the MSO in

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low frequency hearing mammals when exclusively viewed as a Je€ress-type coincidence detector for coding ITDs. The ®rst problem is that ITD coding has been considered as the only function of the MSO even though about 36% of dog MSO neurons do not exhibit binaural excitation, 12% being strictly monaural (Goldberg and Brown, 1968; cf. Fig. 1). Eighteen percent of cat MSO neurons have been described as monaural as well (Yin and Chan, 1990). Since these neurons cannot work as coincidence detectors as proposed by the Je€ress model, other tasks like temporal processing in the context of pattern recognition have to be considered as additional or alternative function of MSO neurons. The second problem concerns the fact that the Jeffress model does not include any inhibitory input. Theoretically, there is no need for inhibitory inputs to coincidence detector neurons (Colburn et al., 1990; Han and Colburn, 1993). However, there is sucient evidence from anatomical studies that MSO neurons receive inputs form both, the medial and the lateral nucleus of the trapezoid body (MNTB, LNTB; Fig. 8A) (cat: Clark, 1969; Perkins, 1973; Cant, 1991; gerbil: Cant and Hyson, 1992; Kuwabara and Zook, 1992). This conforms to indirect physiological results indicative of inhibitory inputs (Goldberg and Brown, 1969; Barrett, 1976; Grothe et al., 1997; Batra et al., 1997a; Grothe and Park, 1998) or results from pharmacological approaches directly proving the existence of glycinergic inhibition (Grothe et al., 1992; Grothe and Sanes, 1993, 1994; Smith, 1995; Grothe, 1997). The MNTB is considered to be the nucleus with the highest concentration of the inhibitory transmitter glycine in the entire mammalian brain (Wenthold et al., 1987). Additionally, MNTB neurons receive their input mainly via one single synapse per soma: the giant calyx of Held (Ramon y Cajal, 1907; Morest, 1968) that is thought to be the fastest and most secure synapse in our brain (Forsythe and Barnes-Davies, 1993; Brew and Forsythe, 1995). Indeed, the output of the majority of MNTB neurons seems to resemble the response patterns of their input from cochlear nucleus globular bushy cells (Smith et al., 1998). Thus, this inhibitory input via the MNTB is not just a ``normal'' inhibitory input. It rather is the most precise inhibitory input known. This is in some contrast to models of E/E-coincidence detection including inhibition but

Fig. 8. Schematic drawing of the overall connection pattern of the MSO and its appearance in several mammals. A: It has been known for several decades that the MSO receives excitatory inputs from the anteroventral cochlear nuclei at both sides. Studies of the last 10 years revealed additional glycinergic, inhibitory inputs from the LNTB (ipsilaterally driven) and the MNTB (contralaterally driven). B: The outline of the MSO in several mammals as apparent from transversal sections. LNTB = lateral nucleus of the trapezoid body; LSO = lateral superior olive; MNTB = medial nucleus of the trapezoid body; MSO = medial superior olive; SPN = superior paraolivary nucleus (rodents); DMPO = dorsomedial periolivary nucleus (non-rodents); AVCN = anteroventral cochlear nucleus.

7 The bird nucleus laminaris receives a di€use, not phase locked GABAergic inhibition from the SOC (not to be homologized with the mammalian SOC) that creates a shunting outward current that shortens EPSPs and thereby decreases the period in which coincidence can occur. On the other hand, this GABAergic, di€use inhibition might help to adjust the coincidence detector to the actual sound level (BruÈckner and Hyson, 1999).

assuming a di€use modulatory inhibition (Reed and Durbeck, 1995) that prevents the MSO from responding to intense monaural inputs and thereby making the coincidence detector independent of absolute sound intensity.7 Most likely similar adjectives as for the MNTB can be attributed to the sub-population of

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LNTB cells that project to the MSO. A signi®cant population of LNTB neurons is glycinergic (Spirou and Berrebi, 1997) and, as MNTB neurons, these neurons receive their input from ventral cochlear nucleus globular bushy cells. Moreover, there inputs resembles the fast and secure synapses at the globular bushy cells itself, the baskets of Held (Spirou and Berrebi, 1996). These anatomical circumstances are coherent with the physiological properties of LNTB cells (Grothe and Park, 1998). Moreover, in the gerbil slice preparation (Grothe and Sanes, 1993, 1994) and in the free-tailed bat MSO (Grothe et al., 1997), no fundamental di€erence between contralateral (MNTB) and the ipsilateral (LNTB) inhibitory inputs could be found. In summary, there is consistent evidence that the majority of MSO neurons in low frequency hearing mammals is sensitive to ITDs. The observed ITD sensitivity is indicative of an underlying mechanism based on coincidence of binaural excitatory inputs. However, the role of inhibitory inputs is unknown and might request a signi®cant variation of the Je€ress model. Moreover, even in cats, dogs and gerbils there is a signi®cant portion of cells performing a di€erent function in auditory processing. The most puzzling fact, as will be pointed out below, still is the existence of a welldeveloped MSO in several, only high frequency hearing mammals like echolocating bats.

3. The MSO in small, only high frequency hearing mammals Most of the studies of the MSO mentioned so far have been performed in mammals with well-developed low frequency hearing. As pointed out above, in mammals, the ability of hearing low frequency air-borne sounds represents a secondary adaptation that evolved in large headed species (the minority among mammals) and those living in deserts. In these animals, coherent with the common problems caused by the new achievement, the MSO is rather identical in its anatomical structure, physiology, and function (dog: Goldberg and Brown, 1969; cat: Yin and Chan, 1990; Gerbil: Spitzer and Semple, 1995). There are two possible interpretations of this similarity. One would be that the MSO evolved several times independently de novo. This would be a rather unlikely event per se. But it becomes even more unlikely when we consider that there is an MSO-like structure at least in rats (Rogowski and Feng, 1981), opossums (Willard and Martin, 1983, 1984), bats (Covey and Casseday, 1995), 8 or at least a speci®c cell type that has been intermingled with other cell types. Later these cells could have formed a distinct nucleus, the MSO.

and mice (Franklin and Paxinos, 1997), although the anatomical outline of the MSO in these animals is by far not as specicalized as described for low frequency hearing mammals (Fig. 8B). The existence of an MSOlike structure in small high frequency hearing mammals and the similarity of the MSO in di€erent low frequency hearing lineages rather indicates a second interpretation assuming a common ancestral structure as starting point for this phylogenetic development. Most likely there had been a common ancient8 structure that performed a di€erent function than ITD coding, a structure that was concerned with temporal processing using binaural inputs. Such a structure might have been pre-adapted for ITD coding and only later evolved into what we now know as the ``typical'' MSO. Thus, if we want to learn about the original function of MSO cells and how they had to be modi®ed for processing ITDs in the range of only tens of microseconds, we have to take into account the MSO in small mammals with poor low frequency hearing. Therefore, we now turn to the rat MSO and then to the MSO and its adaptations in di€erent bat species. 3.1. The rat MSO The ®rst recordings from a MSO in a mammal not adapted for low frequency hearing were performed in the rat. Anatomically, the rat MSO is not such a peculiar structure as shown for low frequency hearing mammals. Nevertheless, this nucleus is anatomically distinct and the dorsal portion even shows a column like arrangement of bipolar fusiform cells (Feng and Rogowski, 1980; Rogowski and Feng, 1981; Fig. 9). Inbody and Feng (1981) recorded from rat MSO neurons using either pure tones or broad band noise. They only found MSO neurons that responded to frequencies above 2.2 kHz, which is consistent with the rat audiogram (Kelly and Masterton, 1977). Since mammalian auditory neurons normally do not phase-lock to frequencies above 2 kHz, it is not surprising that Inbody and Feng did not observe any IPD selectivity in response to pure tones. Moreover, only half of the cells exhibited binaural excitatory inputs. Thus, at least the other half of the neurons in the rat MSO performs a function other than ITD coding. Of the cells that showed binaural input, however, some exhibited a weak ITD sensitivity to the stimulus onset. In these cells, the ITD functions showed a 50% drop or more in discharge rate when tested over a range of 21 ms ITD (Fig. 10). However, within the biologically relevant range of ITDs for the rat (max2150 ms; shaded area in Fig. 10), the drop was less then 25% in the best case and about 10% in the other two examples presented in their study. At the same time, the rat MSO neurons showed a much more profound ILD sensitivity that was well within the biologically relevant

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3.2. The MSO in bats

mammals with good high frequency hearing, whereas the MSO is supposedly well developed in low frequency hearing mammals (Masterton and Diamond, 1967). Hence, animals like bats that only use high frequencies to localize sounds in space would not need a MSO. However, more than 50 years after Poljak's studies Schweizer (1981) working on horseshoe bats (Rhinolophus ferrumequinum ), and Zook and Casseday (1982a, 1982b) using mustached bats (Pteronotus parnellii ), reintroduced anatomical evidence for the existence of a MSO-like structure in bats (Figs. 8B and 11). Horseshoe bats and mustached bats belong to the most intensively investigated bat species because of their very specialized echolocating calls (see studies by G. Neuweiler, G. Pollak, H.-U. Schnitzler, N. Suga, and others). However, it turned out that the MSO and its adjacent mediolateral neighbor, the dorsomedial periolivary nucleus (DMPO; in rodents called superior paraolivary nucleus, SPN; Scho®eld and Cant, 1991) are somehow modi®ed in these bats. This will be discussed for the mustached bat further below. In the case of the horseshoe bats, the questions of homology are rather unclear (Casseday et al., 1988; Vater and Feng, 1990). Therefore, we exclude the latter one from further discussions. Other bats that are more representative for the majority of bats, the velvety free-tailed bat, Molossus ater (Harnischfeger et al., 1985), the Mexican free-tailed bat, Tadarida brasiliensis mexicana (Grothe et al., 1994), and the big brown bat, Eptesicus fuscus (Covey and Casseday, 1995), possess both, a distinct MSO and DMPO that are easy to homologize with those of other mammals. Even though the MSO in these animals does not show the prominent alignment of principal cells in one cell column, all other basic anatomical

More information is available about the MSO in bats. Poljak (1926) ®rst described an MSO-like structure in di€erent bats (Rhinolophus ferrumequinum, Nyctalus noctula ). However, his anatomical work had been ignored for several decades. Moreover, in the 60s, Harrison and Irving in a comparative anatomical study claimed that bats as well as dolphins do not posses an MSO at all (Harrison and Irving, 1966; Irving and Harrison, 1967). They speculated that the MSO is involved in inducing eye saccades toward acoustic sources in space. Accordingly, animals not using vision for orientation, like bats, or animals that use audition under water but vision above water, like dolphins, should not possess an MSO. Although most likely not correct, Harrison and Irving's statements have later been used by Masterton and Diamond to tightly link the two prominent SOC structures, LSO and MSO, to the Duplex theory of hearing (Fig. 1). They argued that the LSO as an ILD-detector is well developed in

Fig. 10. ITD functions of three neurons in the rat MSO in response to pure tones. All three neurons had best frequencies above 2 kHz and did not phase lock to pure tones. The gray area indicates the behaviorally relevant range of ITDs for the rat (2180 ms). From Inbody and Feng (1981).

Fig. 9. The rat MSO contains typical MSO neurons even though the nucleus is smaller than in cats. Its cells are less orderly arranged as in the cat. From Rogowski and Feng (1981).

range. Thus, ITD sensitivity seems not to be, if at all, the main function of the rat MSO. This is somehow consistent with the poor localization abilities at lower frequencies of rats (Kelly and Phillips, 1991). Since no stimuli were used in this study which would elicit an ongoing phase-locked response of the MSO inputs, it remains unknown whether any ITD sensitivity is due to the same principles of neural processing as shown for MSO cells in low frequency hearing mammals.

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features strongly suggested a homology with the MSO of other mammals. The main criteria used for de®ning this homology are 1. MSO and DMPO can be found at the same relative positions within the SOC as in other mammals (Figs. 8B and 11A±D; Poljak, 1926; Zook and Casseday, 1982a; Harnischfeger et al., 1985; Zook and

DiCaprio, 1988; Grothe et al., 1994; Covey and Casseday, 1995). Fig. 11 shows the MSO and its neighboring nuclei in the free-tailed bat in Nissl (B), ®ber (C) and acetylcholinesterase stained transversal sections (showing the high concentration of AcH positive cells in the peri- and paraolivary nuclei, but not in the MSO). 2. MSO neurons are mostly fusiform cells, often with

Fig. 11. Anatomy of the SOC in the free-tailed bat, a small echolocating mammal. A±D: Outline of the identi®able nuclei. DMPO, MSO and LSO (from left to right) can be distinguished in the ®ber stained sections (C) and several additional nuclei in the Nissl staining (B). Acetylcholinesterase staining (D) is prominent in the DMPO but not in the MSO (section is Nissl counter stained). Calibration bar = 20 mm. E: Retrogradely HRP-®lled neuron in the free-tailed bat MSO showing the typical bipolar shape. Calibration bar = 100 mm. From Grothe et al. (1994).

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3.

4.

5.

6.

7.

two principal dendrites pointing in the medial or lateral direction (Fig. 11E; Zook and Casseday, 1982a; Grothe et al., 1994). The sources of excitatory inputs are anteroventral cochlear nucleus (AVCN) bushy cells, of inhibitory inputs MNTB and LNTB (Fig. 8; Zook and DiCaprio, 1988; Covey et al., 1991; Grothe et al., 1992; Kuwabara and Zook, 1992; Grothe et al., 1994, 1997). The main ascending projection originating from MSO cells reaches the ipsilateral inferior colliculus (Zook and Casseday, 1982b; Ross and Pollak, 1989; Grothe et al., 1994; Covey and Casseday, 1995). In contrast to the LSO that contains many glycinergic neurons and the DMPO (SPN) with almost all cells being GABAergic, MSO neurons do not immunostain for GABA or glycine9 (Winer et al., 1995; Vater, 1995; Fubara et al., 1996). As in other mammals, there is a tonotopic arrangement with neurons tuned to low frequencies in the dorsal part, to high frequencies in the ventral portion of the MSO (Harnischfeger et al., 1985; Covey et al., 1991; Grothe et al., 1994, 1997). Many binaurally excitable neurons show an ITD sensitivity that is comparable to that described in other mammals (Grothe and Park, 1998).

As pointed out in detail below, the MSO in some bats does not ful®l all of these criteria. However, the recordings from di€erent bats that are using very di€erent echolocation strategies for hunting ¯ying insects reveal new aspects of the MSO and its possible functions. Moreover, the studies on the bat MSO uncovered the role of the inhibitory inputs to MSO neurons in temporal processing. We will now turn to the most extreme case of an MSO, that of the mustached bat, and then will discuss the data from more ``normal'' MSOs, mainly of the free-tailed bat. 3.2.1. The MSO in the mustached bat The most extreme case of an MSO has been found in the mustached bat, Pteronotus p. parnellii. First, the MSO of this small (<13 g body weight) echolocating bat that does not hear frequencies below 10 kHz (Grinnell, 1970; Kossl and Vater, 1985) is extremely large and spans nearly the entire rostro-caudal and dorso-ventral extension of the SOC (Covey et al., 9 In contrast to the MSO in other bats the mustached bat MSO contains some GABAergic neurons that are restricted along the medio-dorsal border of the nucleus. It can be speculated that this cell group is homologue to the principal cells of the superior paraolivary nucleus (SPN) in other rodents and the dorsomedial periolivary nucleus (DMPO) in cats since this nucleus cannot be de®ned in the mustached bat (Vater, personal communications).

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1991). Second, and even more interesting, the ipsilateral inputs are highly reduced (Covey et al., 1991; Grothe et al., 1992) turning the MSO into a predominantly monaural nucleus. Thus, the main function in this MSO has to be a di€erent one than ITD coding. But what might its function be? Covey et al. (1991) ®rst showed that the vast majority of the mustached bat's MSO cells respond with a transient ``on'' or ``o€'' discharge without any sustained components. This clearly distinguishes their response from the primary-like, excitatory input from cochlear nucleus bushy cells (Rhode et al., 1983; Oertel, 1999). Covey and colleagues in their study also con®rmed the projection from MNTB to MSO, which had not been recognized as a typical feature of the MSO at that time. Therefore, they speculated that the transient responses might result from an interaction of the excitatory, primary-like bushy cell input and a primary-like inhibitory MNTB input. A pharmacological approach con®rmed this speculation. Application of the glycine antagonist strychnine in vivo antagonizes the inhibitory post-synaptic e€ect of the MNTB input. As a result, the phasic ``on'' or ``o€'' discharge patterns are turned into a primary-like response re¯ecting the excitatory input (Grothe et al., 1992; Grothe, 1994; Fig. 12). Such phasic responses do not occur in the auditory nerve. They ®rst appear in the cochlear nucleus in so-called ``octopus cells'' due to their membrane properties (Oertel, 1999). However, since a response of these cells requires a high amount of converging input this mechanism of converting a primary-like into a phasic response is rather slow. Therefore, the MSO pathway might provide faster time markers for the beginning and, another advantage, also for the end of a pure tone. This might be of particular behavioral relevance for these echolocating bats as will be discussed below. However, the consequences of this interaction of excitation and a delayed but otherwise identical inhibition (Fig. 13A) reach further than simply causing phasic response patterns. The temporal interaction of excitation and inhibition revealed by the pharmacological experiments also creates a speci®c ®lter characteristic for the temporal structure of sounds. This can be exempli®ed using sinusoidally amplitude modulated (SAM) sounds. As shown in Fig. 13B, a MSO cell should follow each modulation cycle of a SAM stimulus with a phasic response. However, when the modulation frequency reaches a certain limit, the delayed inhibition should overlap with the excitation in response to the next modulation cycle. This overlap occurs when the SAM frequency reaches the point where the duration of the SAM cycle is equal to or shorter than the relative delay of the inhibition (Fig. 13C). Depending on the particular delay and duration of inhibition the low-pass ®l-

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Fig. 12. The impact of glycinergic inhibition on responses to pure tones in three monaural MSO cells (each column gives the PSTHs of one cell) in the mustached bat. Normally, the neurons respond with phasic ``on'' or ``o€'' discharge patterns. Iontophoretic application of glycine completely abolishes any response (middle PSTHs in the left and middle column). Only seconds after the application the cell's response recovers (lower left PSTH). Application of strychnine blocks the glycinergic inhibition and causes primary-like response patterns (lower PSTH in the middle column and middle PSTH in the right column). The e€ects of strychnine last for several minutes after application before the cell completely recovers (lower right PSTH). From Grothe (1994).

ter cut-o€ varies among cells from 80±300 Hz (shorter delays and shorter durations of inhibition cause higher cuto€s and vice versa; Grothe, 1994). Fig. 14 gives an example of how a mustached bat MSO neuron responds to SAM stimuli. In this case the cuto€ is already around 90 Hz modulation frequency. Since each neuron has its individual cut-o€ frequency, over the population of MSO neurons there should be a population code for the modulation frequency of an acoustic stimulus. Blocking glycinergic inhibition with iontophoretic application of strychnine eliminates the low-pass ®lter allowing all MSO cells to follow much higher SAM modulation frequencies (Fig. 15), in most cases up to 800±1000 Hz (Grothe, 1994). Unpublished data from the MSO in another bat, the big brown bat, Eptesicus fuscus, shows that basically the same ®lter characteristics as shown for amplitude modulations also occur when the neurons are tested with frequency modulations or with trains of pulses (Grothe, Covey and Casseday, unpublished data). The MSO, therefore, seems to be an initial station within the ascending auditory pathway that actively creates low-pass ®lter characteristics for the temporal structure of sounds (SAM is only one example). The

existence of such low-pass ®lters has been proposed for years, since most auditory midbrain neurons are highly selective for the modulation rate. Thus, ®lters acting between the cochlear nucleus (CN, the ®rst station of the ascending auditory system) and the IC (central nucleus of inferior colliculus, the main auditory midbrain structure) or within the IC itself have to be present (Langner, 1992; Fig. 16). However, the underlying mechanisms have been speculative. The one described for the MSO is, most likely, not the only low-pass ®lter mechanism for temporal cues in the ascending auditory system. However, a similar interaction of excitation and inhibition has also been shown for the dorsal nucleus of the lateral lemniscus (DNLL; Yang and Pollak, 1997). There, the interaction of excitation and GABAergic inhibition causes low-pass ®lter characteristics for SAM sounds similar to those described for the MSO. In the IC of freetailed bats and big brown bats itself, however, this interaction has not been found to signi®cantly shape ®lter functions for SAM (Burger and Pollak, 1998) or sinusoidally frequency modulated sounds (Koch and Grothe, 1998). Unclear is whether similar SAM ®ltering might also be a feature of the MSO cells in low-frequency hearing

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1994). In the cat MSO, the few cells tested for SAM also showed a low-pass ®lter characteristic (Joris, 1996) as do high frequency gerbil MSO neurons (Behrend et al., 2000). The ®ltering of amplitude and frequency modulations as well as the precise coding of the beginning and the end of a stimulus is of particular biological relevance for the mustached bat. Whereas the echolocation pulses of most bats take the form of a short (1± 3 ms) downward frequency sweep, the mustached bat emits pulses with a long (30±40 ms) constant frequency (CF) portion (Fig. 17). The CF part is used as a carrier for frequency and amplitude modulations in the echo. Such modulations are imposed onto the echo by the wing beats of ¯ying insects (Henson et al., 1987; Kober and Schnitzler, 1990). This elegant strategy enables these bats to hunt ¯ying insects even in a cluttered environment, for example, in the foliage of trees and bushes and represents a special adaptation in these bats (Neuweiler, 1990). Accordingly, mustached bats are highly attracted by echoes from ¯uttering targets (Goldman and Henson, 1977). Thus, they rely to

Fig. 13. Schematic drawing of the monaural interaction of excitation from the AVCN (gray) and inhibition from the MNTB (black) as ®rst described for the MSO in the mustached bat. A: Pure tone stimulation leads to primary like activity in the excitatory AVCN and the inhibitory MNTB input. In most neurons the inhibition is delayed by a ®xed amount (ÿ3 to +5 ms), leaving a small window where the MSO cell can respond to the excitatory input before it is completely inhibited by the MNTB. The result is a phasic on-response except in a minority of cells where the inhibition arrives simultaneously or even earlier. These neurons are inhibited throughout the stimulus duration but respond with a rebound ``o€''. B: The same temporal interaction of excitation and delayed inhibition will cause a phase-locked response to the envelope of sinusoidally amplitude modulated tones (SAM), as long as the modulation frequency is low. C: Because of the ®xed delay, the inhibition will start to overlap with the excitation in response to the following subsequent cycle when the modulation frequency reaches a certain limit (the limit depends on the actual delay of the inhibition). The response to all cycles except the ®rst would start to decrease at this modulation frequency and completely stop at even higher rates. A slightly slower time course of the inhibition (little longer duration) and some temporal summation would prevent the cell from recovering at much higher rates. After Grothe (1994).

mammals. Results from in-vitro experiments blocking glycinergic inhibition while presenting repetitive pulses in the gerbil brain slice preparation indicate a similar role of the glycinergic inputs (Grothe and Sanes,

Fig. 14. PSTHs of the response of a mustached bat MSO neuron to sinusoidally amplitude modulated tones (SAM). The neuron responds with a phase-locked discharge to each modulation cycle up to modulation frequencies of 80 Hz. Above this limit the cell only responds to the ®rst modulation cycle. From Grothe (1994).

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Fig. 15. Normalized response rates of a MSO neuron to SAM stimuli with di€erent modulation frequencies (modulation transfer function). The abscissa gives the modulation frequency, the ordinate the normalized response. Under control conditions the neuron only responds to modulation frequencies below 200 Hz. In the presence of strychnine, however, the neuron responds to much higher modulation frequencies. Using the 50% level as a criterion, the cuto€ frequency shifts from about 180 (control) to above 700 Hz when glycinergic inhibition is blocked.

a large extent on analyzing the temporal structure of echoes re¯ected from ¯uttering targets. These bats might have experienced evolutionary constraints to improve their ability to analyze amplitude modulations and periodicity information. A monaural MSO, with reduced ipsilateral inputs and, therefore, reduced binaural, position-dependent e€ects (see below) might help to achieve the required accuracy in temporal coding. Thus, the MSO in the mustached bat may be adapted particularly to perform a temporal analysis of the temporal structure of a stimulus which is important for detecting and identifying insect prey. 3.2.2. The MSO in ``normal'' FM-bats The MSO in three ``normal'' bats using FM-echolocation calls has been investigated so far: in Molossus ater (Harnischfeger et al., 1985), the free-tailed bat, Tadarida brasiliensis mexicana (Grothe et al., 1994, 1997; Grothe and Park, 1998), and the big brown bat, Eptesicus fuscus (Grothe, Casseday and Covey, unpublished data). In all of them, only high frequency neurons that did not phase-lock to pure tones have been found. In this respect they are similar to the MSO of the mustached bat. However, in these bats, the proportion of binaural MSO neurons is considerably higher, as depicted in Fig. 18. Particularly the MSO in Molossus ater and the free-tailed bat contains almost as many binaurally excited neurons as the dog MSO.

In this respect, the MSO of the big brown bat represents an intermediate state between the free-tailed bat and the mustached bat. The evolutionary implications of this distribution will be discussed below. In agreement with the high percentage of binaural input patterns, many free-tailed bat MSO neurons show the bipolar shape with thick principal dendrites orthogonal to the main axis of the nucleus (Grothe et al., 1994; Fig. 11B). Moreover, in this bat the morphology of the SOC allows a clear distinction between the MSO and the DMPO (or SPN; Fig. 11A). The distribution of presumable input patterns, as shown in Fig. 18, implies that instead of binaural excitation, the basic input patterns existing in almost all MSO cells (including the gerbil MSO; Cant, 1991; Cant and Hyson, 1992; Grothe and Sanes, 1993) is the combination of excitation and inhibition from the contralateral side rather than binaural excitation. However, in addition, most cells receive either ipsilateral inhibition or ipsilateral inhibition and excitation. Thus, the di€erences in binaural response types among species may simply be a consequence of the balance of the excitatory and inhibitory projections to MSO (Cant, 1991; Grothe et al., 1992). Therefore, it is not surprising that the response of MSO neurons in the free-tailed bat and the big brown bat to contralateral stimuli is more or less identical with that observed in the mustached bat MSO. The similarities include the appearance of neurons responding only with an o€-response, and, more important, similar low-pass ®lter characteristics for SAM stimuli that can be blocked by

Fig. 16. Modulation transfer functions of three neurons at di€erent levels of the mammalian auditory system: the cochlear nucleus (CN), the MSO, and the auditory midbrain (IC). The CN neuron responds to modulation frequencies up to about 1000 Hz (all-pass), the MSO neuron responds only to modulation frequencies below 200 Hz (lowpass). The IC neuron exhibits the highest degree of selectivity in that it only responds to a small band of modulation frequencies around 100 Hz (band-pass).

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Fig. 17. Two di€erent echolocating strategies in insectivorous bats hunting for ¯ying insects. Most bats emit short (few milliseconds) downward frequency modulated sweeps (FM; left panels). Spectral changes in the echo compared to the pulse itself contain information about the object, the echo delay about the objet distance. Using this echolocation call it is dicult to distinguish objets from background in dense foliage. Some bats specialized for hunting in dense foliage use a combination of a FM sweep for distance measurement and a constant frequency component (CF) for prey recognition. CF components can last up to 80 ms. When re¯ected from a ¯uttering target the CF component in the echo is modulated in frequency and amplitude according to the insect's wing beat frequency. Doppler shifts in the CF component contain additional information about the relative velocity of the target. The upper panels give the oscillogram (time versus amplitude) of pulse (black) and echo (gray). The lower panels display the frequency changes in the echo (time vs. frequency).

pharmacological blockade of glycine (Grothe, 1997; Grothe et al., 1997). Fig. 19A shows the response of a neuron in the MNTB (Grothe and Park, 1998) that provides inhibitory input to the MSO. Fig. 19B shows the response of a MSO neuron to the same set of stimuli (Grothe et al., 1997). Whereas the MNTB neuron phase-locks up to high modulation rates (>1000 Hz), the MSO neuron only responds with an ongoing phase-locked discharge to rates below 300 Hz. Again, the low-pass ®lter in MSO neurons can be eliminated by blocking glycinergic transmission (Grothe, 1997). Thus, as in the mustached bat MSO, the relative timing of an excitatory and a delayed inhibitory input creates ®lter properties for the temporal structure of

sounds. The fundamental di€erence, however, to the mustached bat MSO is that most neurons are binaurally innervated. About 60% of the neurons receive a second, ipsilaterally driven input that basically behaves as the contralateral input does. Consequently, E/E neurons in the free-tailed bat show similar ®lter properties for SAM when tested either for ipsilateral or contralateral stimulation only (Grothe et al., 1997; Fig. 20). Thus, these cells possess two ``subsets'' of low-pass ®lters. In the ``real world'', under normal stimulus conditions, these ``subsets'' are not separated. However, using dichotic stimulation one can de®ne the ®lter characteristics of these inputs separately. Such a test revealed that the 50% cut-o€ points in the modu-

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have been described for auditory midbrain neurons in frogs (Melssen and Epping, 1990, 1992; Melssen et al., 1990; Gooler et al., 1996) and bats (Grothe et al., 1996; Koch and Grothe, 1997, 2000). The impact of spatial cues on temporal ®ltering of MSO neurons has been shown by introducing ILDs, but not ITDs (Grothe et al., 1997). ``Natural sounds'', however, contain both ILDs and ITDs. But how would this circuitry with binaural excitation and inhibition with well described timing properties behave if we introduce ITDs? Lets simply adopt the scenario of the temporal interaction of excitation and inhibition shown above (Fig. 13) to symmetrical binaural inputs. The only thing that has to be added is some factor for facilitation due to the binaural excitation. As shown

Fig. 18. The distribution of projection patterns to MSO neurons in di€erent mammals. The schematic drawings on the left show the main input patterns as suggested by anatomical and physiological studies in several mammals. The right panels show the percentage of the corresponding binaural type as derived from physiological studies. Note that an ``E/E'' classi®cation in normal extracellular recordings does not necessarily tell whether there is an additional inhibitory input from the same side. Thus, the corresponding pattern in the schematic on the left is the most likely corresponding input pattern, but not inevitably true for all neurons. Note that in all animals including dogs at least one third of the cells apparently lack ipsilateral excitation. The mustached bat (Pp) is, even among bats, the most extreme case with almost only monaural cells. Ef = Eptesicus fuscus (the big brown bat); Ma = Molossus ater (velvety freetailed bat); Pp = Pteronotus parnellii (mustached bat); Tb = Tadarida brasiliensis (free-tailed bat).

lation transfer functions (the modulation frequency at which the spike rate per SAM cycle dropped below 50% of the maximal rate) are not identical for ipsilateral and contralateral stimulation (Fig. 20B and A). Hence, there is a mismatch of the ®lter properties for ipsilateral and contralateral stimulus presentation. Consequently, the actual ®lter cut-o€ for binaural SAM stimuli depends on the weight of the two inputs which, in turn, depends on the actual ILD and, hence, on the spatial position of a sounds source. Fig. 21 shows the modulation transfer functions for a representative free-tailed bat MSO cell depending on the ILD. Thus, binaural MSO neurons in the free-tailed bat MSO (as in the big brown bat MSO, unpublished results, Grothe, Casseday and Covey) integrate spatial and temporal information. Similar inter-dependencies

Fig. 19. PSTHs of responses to SAM stimuli of two neurons in the free-tailed bat. A: The response of a typical MNTB neuron shows a precise phase-locking up to 1000 Hz modulation frequency (the PSTH with 1 ms bin-width does not resolve the phase-locking at 1000 Hz, completed after Grothe and Park, 1998). B: In contrast, the MSO neuron only phase-locks to modulation frequencies below 200 Hz (from Grothe et al., 1997).

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of a Je€ress-type coincidence detector mechanism. However, here we deal with a more complex coincidence-detector that includes (and depends on) well timed inhibitory inputs. But do MSO neurons in the bat show such ITD sensitivity? Indeed, it turned out that binaurally innervated MSO neurons in the free-tailed bat show ITD sensitivity when tested with SAM stimuli (Fig. 23). A stimulus that allows ongoing phase-locking of the inputs is necessary to investigate the mechanism that underlies the observed ITD sensitivity. It should be noted that Yin and Chan (1990) also recorded from a cat MSO neuron tuned to high frequencies which did not cause phase-locking in itself. However, by using SAM stimuli they could show a similar ITD sensitivity, in this case to the stimulus envelope of the SAM tones. This ITD sensitivity to the sound envelope seems to follow the same principles as the ITD sensitivity of low frequency neurons in response to pure tones. A comparable ITD sensitivity to SAM of high frequency neurons has also been shown for the rabbit IC (Batra et al., 1993) and it has been argued that this ITD sensitivity also arises in the MSO. The majority of binaurally innervated MSO cells in the free-tailed bat behave the same way as ITD-sensitive cells in other mammals: (1) Most E/E neurons show a cyclic ITD sensitivity in that they respond best when the ipsi- and contralateral SAM stimuli are more or less in phase. Out of phase stimulation suppresses the response (Figs. 23 and 24A). (2) The best ITD of these neurons can be predicted by the phase angle of the phase-locked response to monaural stimulation. The Fig. 20. Distribution of 50% ®lter cuto€s of SAM modulation transfer functions in the MSO of the free-tailed bat. A: Most neurons show a decrease in the response rate of more than 50% already at SAM modulation frequencies below 200 Hz. This holds for monaural (ipsilateral or contralateral) as well as binaural stimulation. B: Even though the distribution in A does not indicate signi®cant di€erences for di€erent binaural stimulation conditions, the cuto€s in individual neurons do not match for ipsilateral and contralateral stimulation. Only one out of 17 neurons had matching cuto€s (less than 25% di€erence; this range is indicated by the space between the two dotted lines). From Grothe et al. (1997).

below, a factor of 1/3 for the facilitatory e€ect roughly ®ts the data from dogs and cats (Goldberg and Brown, 1969; Yin and Chan, 1990) and from the free-tailed bat (Grothe and Park, 1998; see below). Fig. 22 shows this simple scenario for a 100 Hz SAM stimulus (modi®ed after Grothe and Park, 1998). The lower panel shows the ITD functions calculated for 100, 150 and 200 Hz SAM stimuli. First, an ITD sensitivity can be predicted from this interaction. Second, the ITD functions are ``peak-type'' with aligning best ITDs. The latter has widely been accepted as proof indicative

Fig. 21. SAM modulation transfer functions of a free-tailed bat MSO neuron. The transfer functions di€er substantially for the di€erent binaural conditions used. Positive ILDs indicate louder stimulation at the contralateral ear. From Grothe et al. (1997).

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Fig. 22. A simple prediction of how EI/EI MSO neurons in the free-tailed bat would respond to SAM stimuli presented at di€erent ITDs based on the interaction of binaural excitatory and inhibitory inputs (cf. Fig. 13). The upper panels show the temporal interaction of the binaural MSO inputs for 100 Hz SAM at ®ve di€erent ITDs (ÿ5 to +5 ms). The lower graph shows the calculated ITD functions for three di€erent modulation frequencies (100, 150, 200 Hz SAM). The calculation is based on 100 ms stimulus duration. Black bars indicate inhibition, gray bars excitation, hatched bars the MSO-response. Inhibition is weighted with ÿ1, excitation with +1. The response derives from the total of two hundred 0.5 ms segments. Facilitation is assumed to be 50% (1/3 of the resulting response). Modi®ed after Grothe and Park (1998).

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Fig. 23. ITD sensitivity of a free-tailed bat MSO neuron with binaural excitation and inhibition (EI/EI) in response to 200 Hz SAM stimuli. Upper panels: PSTHs to selected ITDs. Lower panel: Full ITD function. Arrows give response rates to monaural stimulation. From Park and Grothe, 1996.

best IPD corresponds to the phase di€erence of the monaural response to ipsi- and contralateral stimulation (see Fig. 24C). (3) The response rate for the best ITD is about one-third above the sum for monaural responses, hence, there is a signi®cant amount of facilitation (Figs. 23 and 24). (4) The best ITD of these

neurons is independent of the modulation frequency used (as shown in Fig. 24A), thus, these neurons exhibit ``peak-type'' ITD functions. In other words, the best interaural phase varies systematically and linearly with increasing modulation frequency. The interaural phase vs. frequency function for the neuron in

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Fig. 24. ITD sensitivity of a neuron that receives binaural excitation and inhibition (EI/EI) in response to SAM stimuli. A: Normalized discharge rates to SAM stimuli with 100, 200 and 300 Hz modulation rates. Note that the peaks are rather stable whereas the troughs shift as a function of the modulation frequency. B: The corresponding values of phase-locking to the stimulus envelope (vector strength). C: Histograms showing the monaural responses to 100 Hz SAM as a function of modulation phase. Form these histograms an interaural delay around 0 could be predicted. D: Best interaural phase diagram (right panel). The regression line intercepts with the ordinate around 1 indicating an E/E coincidence mechanism. From Grothe and Park (1998).

Fig. 24D intercepts with the y-axis around 0, which has been taken indicative of a Je€ress-like coincidence detector-mechanism (cf. Fig. 7). Hence, all crucial criteria that ``prove'' a Je€ress type coincidence detector based on excitatory inputs only are satis®ed. However, they also ful®l all criteria of the binaural interaction model including coincidence of excitation and inhibition described above (Grothe and Park, 1998). Intracellular recordings from the ger-

bil brain slice also indicate that the timing of the inhibitory input might play a crucial role in ITD coding (Grothe and Sanes, 1994). An important factor in the above model is a constant duty cycle of the cyclic inputs when the modulation frequency is raised. In other words, at higher modulation frequencies the duration that the stimulus level is above threshold for eliciting inhibition is shortening (Fig. 13). Without this characteristic the ITD functions would not be ``peak type''. In contrast, changes in duty cycle of the inhibitory inputs due to changes in the test tone frequency would not be predicted when low frequency pure tones are used. However, a possible extension would be a prominent asymmetry in the frequency tuning of the inhibitory inputs to a given MSO neuron. Such an asymmetry could signi®cantly a€ect the timing of the di€erent inputs (Bonham and Lewis, 1999) and could, therefore, cause similar e€ects for low frequency pure tones as described for SAM stimuli. It is important to stress that in both models the underlying principal of the observed ITD sensitivity is a kind of coincidence detection. Traditionally, coincidence detection has been associated with excitatory inputs only. However, Batra and colleagues pointed out that trough-type ITD functions based on E/I inputs actually act as anticoincidence detectors and that ``coincidence and anticoinicdence are two facets of the same phenomenon'' (Batra et al., 1997b). This, at least, holds on the level of the circuit, not necessarily on the level of the cell compartments that might include speci®c membrane specializations necessary for precise E/E coincidence detection. In any case, coincidence, anticoincidence, or a mixture of both has to be based on phase-locked inputs. Thus, coincidence detection based ITD sensitivity only works out for frequencies all inputs can signi®cantly phase-lock to (Batra et al., 1997b). The model proposed for the bat MSO (Grothe and Park, 1998) does not contradict the idea of coincidence detection but extend it. However, the input with the lowest cut-o€ for phase-locking will set the limit for the frequency range ITDs can be encoded from. On the other hand, the combination of the four inputs would give the system more freedom for adjusting the best ITD of a MSO neuron and, thus, would be an alternative solution of the concept of delay lines. The existence of a binaural coincidence detector mechanism by no means prove that the resulting ITD sensitivity is of actual relevance for an animal. ITDfunctions from the free-tailed bat MSO are comparable to those from recordings in the dog, cat, or gerbil MSO. Fig. 25 compares ITD functions in response to a periodic stimulation with 300 Hz for a cat and a free-tailed bat MSO neuron. The cat MSO neuron was stimulated with a 300 Hz pure tone the MSO neuron phase-locked to (from Yin and Chan, 1990). The bat MSO neuron was stimulated with a high frequency

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neurons would not follow high SAM rates, the ITD functions are not very sharp. Only few of the MSOcells in the free-tailed bat showed ITD-functions that would indicate a time-resolution of less than a few hundred microseconds. Moreover, less than half of the 51 neurons tested for ITD sensitivity in this bat exhibited ITD sensitivity for the onset of SAM or pure tones. If they did so, the ITD sensitivity was, again, in the range of several hundreds of microseconds or even milliseconds (Grothe and Park, 1998). But what about ITDs in response to short (2 ms) FM sweeps (25 kHz) that mimic the echolocation calls of these animals in the ®nal approach phase before they catch an insect prey? As shown in Fig. 26, the observed ITD sensitivity was in the range of hundreds of microseconds or even several milliseconds. Thus, good ITD coding in the range of 100 ms or better was only found in a very small fraction of the free-tailed bat MSO cells. Moreover, changes of several other stimulus parameters including ILDs or SAM rate impact on the neurons' responses by an order of magnitude larger than ITDs. Hence, there is no indi-

Fig. 25. ITD sensitivity of a cat MSO neuron (A; from Yin and Chan, 1990; their Fig. 3) in comparison to that of a free-tailed bat MSO neuron (B; from Grothe and Park, 1998, their Fig. 7). In the example shown for the cat, the neuron was tested with a 300 Hz pure tone. The stimulus presented to the bat was a high frequency tone that was amplitude modulated at a rate of 300 cycles/s. The shaded areas on each graph display the range of ITDs that naturally occur for these species.

tone (70 kHz, the neuron's best frequency) that was sinusoidally amplitude modulated with a modulation frequency of 300 Hz the neuron phase-locked to (from Grothe and Park, 1998). Obviously, the ITD functions are very similar. The only, but important di€erence is that for the cat a signi®cant drop in the ITD function occurs within the biologically relevant range of ITDs (2300 ms; shaded area in Fig. 25). However, the drop in the ITD functions was far outside the relevant range for the free-tailed bat (230 ms). In other words, biologically relevant ITDs will cause signi®cant changes in the cat MSO ®ring rate but not in that of the bat MSO. When measuring ITD sensitivity of single neurons using sinusoidal stimuli the slope of the functions depends to a signi®cant degree on the frequency the inputs are phase-locked to (whether it is to low frequency pure tone or the envelope of SAM stimuli). This, of course, partly de®nes the maximal ITD sensitivity measured for the neurons. Since the bat MSO

Fig. 26. Response of an EI/EI neuron to short (2 ms) FM sweeps (downward 2 5 kHz around the best frequency of the neuron) as a function of ITD. The neuron responded with only one to two spikes per sweep to contralateral or ipsilateral stimulation. A: Relative spike rate evoked by ipsilateral stimulation for a variety of electronically introduced ITDs. B: Relative spike rate evoked by contralateral stimulation for the same cell. The gray area indicates the range of ITD that caused a 50% reduction (or more) in the normalized spike rate. From Grothe et al. (1997).

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cation at all that the ITD sensitivity in this bat's MSO can be used for sound localization. This ®nding might be in some contrast to ®ndings from two other studies in bats, one concerned with the MSO, the other with auditory midbrain neurons. In Molossus ater (from the same family Molossidae as the free-tailed bat), 45% of the MSO neurons exhibited excitatory inputs from both ears, 36% had I/E response characteristics, and about 19% showed no signs of ipsilateral inputs (Harnischfeger et al., 1985; Fig. 18). However, for the free-tailed bat MSO tests using pure tones often failed to reveal inhibitory inputs that were obvious when other stimuli were applied (Grothe et al., 1997). In contrast to all other bats, the majority of MSO neurons in Molossus ater responded with a tonic discharge to pure tones. Nevertheless, nonmonotonic rate-level-functions in about 70% of the cells indicate the existence of inhibitory inputs to MSO cells in this bat as well. Harnischfeger (1981) tested 21 binaural MSO cells using ITDs of 2500 ms of which four showed at least 20% change in spike rate. Only one of them was characterized as e/E (weak excitation from ipsilateral, strong excitation from contralateral), all others as I/E. Two of the four neurons (the e/E neuron ``U14'' and one I/E neuron ``U15'') showed a 20% spike rate change within the biologically relevant range of ITDs (250 ms). The ITD functions of these two neurons are shown in Fig. 27A. The I/E neuron showed a 60% drop in response rate from ipsilateral leading by 10 ms to contralateral leading by 20 ms. The ITD function of the e/E neuron decreased about 20% going from ÿ20 to +30 ms ITD. Harnischfeger et al. (1985) interpreted this result as evidence for the ability of the bat MSO to encode behaviorally relevant ITDs. However, both neurons had best frequencies well above 20 kHz and showed signi®cant ILD sensitivity (Fig. 27B). For example, the ILD function of the e/E neuron drops 53% going from an ILD of ÿ20 dB (contralateral stimulus more intense) to +10 dB (ipsilateral stimulus more intense). Converting these values to the common azimuthal angle according to Fig. 2, the ITD sensitivity would be about 0.16% change in spike rate per azimuthal degree, whereas the ILD sensitivity would be about 1.5% change in spike rate per degree. Thus, the observed ILD sensitivity is one order of magnitude higher than the ITD sensitivity. Even in the I/E neuron which showed the best ITD sensitivity of all neurons in the study by Harnischfeger et al., the ILD sensitivity is at least 14 times better. Similar to the study by Inbody and Feng (1981) in the rat MSO, only pure tones have been used to measure the ITD sensitivity in the Molossus MSO. Since the neurons showed no phase-locking to these stimuli the nature of the ITD sensitivity remains

Fig. 27. Response to binaural cues of two neurons in the MSO of the velvety free-tailed bat, Molossus ater. Unit ``U14'' had been characterized as ``e/E'' (binaural excitation, although it showed nonmonotonic rate-level functions), unit ``U15'' as I/E (ipsilateral inhibition and contralateral excitation). Abscissae in both panels give the full range of occurring interaural di€erences. A: ITD sensitivity. B: ILD sensitivity. Even though there was substantial ITD sensitivity in these neurons, ILDs had a much more profound e€ect on the discharge rate. From Harnischfeger (1981) (``U14'') and Harnischfeger et al. (1985) (``U15'').

obscure. Moreover, the robustness of the observed ITD sensitivity, for instance, in face of ILD changes (again, all MSO neurons were tuned to high frequencies that are subject to changes induced by signi®cant ILDs), has not been tested. Thus, the relevance of the ITD sensitivity observed in one out of two neurons is unclear. A possible role of the bat MSO in localization via time-intensity-trading has also been discussed (Harnischfeger et al., 1985; Grothe et al., 1994). It is a wellknown phenomenon that an increase in stimulus level causes a shortening in the latency of most auditory neurons. Consequently, ILDs can cause systematic internal latency di€erences. A consequence of this phenomenon is that ILDs can be compensated for by introducing paradoxical ITDs. This so-called ``timeintensity-trading'' has been found on the perceptual level (Young and Levine, 1977) as well as in single

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neurons in the cortex (Irvine et al., 1996), the midbrain (Yin et al., 1985; Irvine et al., 1995) and the LSO (Grothe and Park, 1995; Park et al., 1996). But why should there be a second structure beside the welldeveloped LSO processing the very same parameter, ILDs? Beside this problem, the data from the freetailed bat MSO excludes ILD coding via internal arrival time di€erence processing anyway. First, in I/E neurons, ITD sensitivity vanished if the intensity at the ipsilateral ear was decreased and was only slightly a€ected when it was increased. Second, in E/E cells, changes in the ITD sensitivity due to ILDs were unpredictable and could not be explained by timeintensity-trading e€ects, e.g. amplitude dependent latency shifts. Additionally, in half of the neurons, ITD sensitivity vanished for ILD shifts in both directions (Grothe and Park, 1998). A second study indicating a relevant ITD sensitivity in bats comes from the pallid bat, a very specialized hunter that uses high frequency echolocation calls in a frequency range from 30 to 60 kHz (Bell, 1982) for general orientation. However, for the detection and localization of terrestrial prey, they use passive listening. In this context frequencies well below 15 kHz are relevant for these animals. Because of the small head size (see above) ILDs are rather small at these ``low'' frequencies raising the question of whether these animals use ITDs for passive localization. Indeed, in the auditory midbrain of these animals, Fuzessery (1997) found ITD sensitive neurons with an ITD resolution in the range of 270 ms in response to trains of short pulses (square-wave amplitude modulations), clicks, or FM-pulses (Fig. 28). The source of this ITD sensitivity is unknown. The MSO, of course, cannot be excluded. However, only six out of 26 neurons showed somewhat cyclic ITD functions. However, these functions do not necessarily seem to re¯ect the periodicity of the stimulus and do not show the typical ``peak-type'' or ``trough-type'' characteristics. For example, the response of the neuron shown in Fig. 28 shows rather similar functions in response to a 250 and 500 Hz SAM sound. Therefore, it does not appear that the underlying mechanism is identical with that observed in ITD sensitive cells in the MSO. The di€erent absolute ITD sensitivity observed in di€erent animals (like that in the MSO of the freetailed bat and the IC of the pallid bat) raises the question of whether the observed ITD sensitivity rather re¯ects the stimulus used to measure it than the maximum sensitivity (Fuzessery, 1997). However, the ITD sensitivity in the MSO of the free-tailed bat to short FM-sweeps (2 ms, 25 kHz) revealed the same range of ITD sensitivity as for SAM stimuli (Grothe et al., 1997; Fig. 26). This contradicts the idea that the ITD sensitivity found in bats simply re¯ects the stimulus used. It rather re¯ects real species speci®c di€erences,

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Fig. 28. ITD sensitivity of a neuron in the ventro-lateral low-frequency region of the inferior colliculus in the pallid bat, Antrozous pallidus, in response to square-wave amplitude modulations. The pulse duration was 0.4 ms, the pulse rate 250 and 500 Hz, respectively. The resulting ITD sensitivity is cyclic but does not show shifts of the troughs as typical for MSO neurons. From Fuzessery (1997).

wherever their anatomical and physiological basis would be. Pallid bats, as other gleaning bats using similar hunting strategies, might represent an unusual case with an extraordinary high pressure on precise localization in an intermediate frequency range that, because of the small head size, does not provide sucient ILDs. ITD coding at higher auditory stations in ``normal'' high frequencies mammals like rats (Kelly and Phillips, 1991) or free-tailed bats (Pollak, 1988) do not show such precise ITD coding. This is coherent with the rather poor localization acuity in the rat (Kelly and Phillips, 1991) and the big brown bat that seems not to use ITDs for sound localization (Koay et al., 1998).

4. Conclusions Taken together, many bat MSO cells show evidence for an ITD sensitivity that is basically similar to that in other mammals. However, the observed ITD resolution of these cells seems to be too small for being of any use for sound localization. That there is no compelling evidence for the bat MSO being involved in ITD coding is coherent with the Duplex theory of sound localization. Given the fact that there is no evidence for bats being better in sound localization than other small mammals (Koay et al., 1998), it would be hard to explain why there should be such a prominent structure as the bat MSO beside the very large bat LSO that would only function in the context of sound localization of high frequency sounds. It, therefore, seems likely that the observed ITD coding is an epiphenomenon of the binaural temporal processing of cues other than ITDs. Such an epipheno-

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menal ITD sensitivity has also been described for the LSO in the cat (Joris and Yin, 1995) and the freetailed bat (Park et al., 1996). There, amplitude dependent latency shifts help in adjusting the ILD sensitivity of the cells. This mechanism, however, creates an arti®cial ITD sensitivity when tested with unphysiological ITDs under dichotic stimulation conditions. The function of the bat MSO (and that of other only high frequency hearing mammals) remains unclear. It might, however, be a good guess to suspect it in the context of echo suppression, in creating comodulation-masking-release, or in a general construction of temporal contours depending on the position of sounds. Hence, the MSO could establish spatial± temporal receptive ®elds (Grothe and Neuweiler, 2000). Whatever the function of a binaural MSO in small mammal might be, an epiphenomenal ITD sensitivity in ancient small high frequency hearing mammals could have been a pre-adaptation in case the animals are growing larger during phylogeny. By

growing larger naturally occurring ITDs started to signi®cantly a€ect the output of these cells. At this point new constraints might have forced improvement of the ITD resolution by changing membrane properties for better coincidence detection (Smith, 1995) or by shortening the duration of the glycinergic inhibition (Clark, 1969; Kapfer et al., 1999), or changing the overall impact of inhibition. An alternative path in evolution of the MSO could be to use it to perform more precise time pattern detection by eliminating binaural interactions, as in the mustached bat. Fig. 29 gives a simple scenario for the possible evolution of MSO. It is evident that MSO neurons process information by an interaction of four inputs, one excitatory and one inhibitory input from each ear (EI/EI). This interaction of excitation and inhibition creates a sensitivity to interaural time di€erences (ITDs) important for localizing low frequency sounds. However, at the same time this interaction creates ®lter characteristics for the temporal structure of a sound that is important for

Fig. 29. A scenario for the evolution of the MSO. The ancestral precursor is assumed as similar to the free-tailed bat MSO in that it neither showed specializations for pure AM processing, nor for ITD processing. This kind of MSO would have shown pattern ®ltering (for example, amplitude modulation ®ltering). The ®lter characteristics were, however, in¯uenced by binaural cues and, hence, by the position of a sound source. This kind of MSO might be rather unchanged in most mammals that do not show any adaptations for low frequency hearing. Some bats (like the mustached bat and partly the big brown bat) reduced the ipsilateral inputs to the MSO and, thereby, turned it into a pure pattern ®lter. A di€erent direction took the evolution of the MSO in low frequency hearing mammals. Because of the pre-adaptation for ITD coding it has been used as the primary site for localizing low frequency sounds in the horizontal plane. Several specializations occurred in order to improve the ITD sensitivity. One might have been a change in the inhibitory inputs by re®ning it to the cell somata.

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sound recognition. Therefore, MSO neurons apply a speci®c rule of processing temporal cues of the incoming signal. ITD sensitivity is only one aspect of this rule, SAM ®ltering another one. We might have to modify our view of parallel processing, that is, separating the computation of speci®c physical cues. It might be more persuasive to assume that not speci®c physical parameters are separated in the di€erent parallel pathways of the lower ascending auditory system, but the rules applied in processing complex stimuli. From this point of view, the apparent contradictions concerning the MSO in small mammals simply disappear.

Acknowledgements I thank Drs. Magdalena GoÈtz and Tom Yin for critical comments on the manuscript, Drs. John H. Casseday, Ellen Covey, Gerhard Neuweiler, and Thomas J. Park for many interesting and helpful discussions. The work was supported by the Deutsche Forschungsgemeinschaft (FG HoÈrobjekte, TP3/ Grothe).

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