Acknowledgements
23 Kroodsma, D. E. (1986) Anim. Behav. 34, 1573-1575 Research was 24 Marler, P., Peters, S,, Ball, G., Dufty, A. M. and Wingfield, J. C. (1988) Nature 336, 770-772 conducted in 25 Marler, P., Peters, S. and Wingfield, J. (1987) J. Neurobiol. collaboration with 18, 531-548 Susan Peters, and 26 Gurney, M. and Konishi, M. (1986) Science 208, 1380-1382 supported by Grant 27 Hutchison, J. B., Wingfield, J. C. and Hutchison, R. E. (1984) number MN14651. J. Endocrinol. 103,363-369 I am indebted to 28 DeVoogd, T. J. (1986) J. Neurobiol. 17, 177-201 Douglas Nelson and 29 Weichel, K., Schwager, G., Held, P., G0ttinger, H. R. and Pesch, A. (1986) Ethology 73,281-294 Stephen Nowicki for discussion and access 30 Adkins-Regan, E., Abdelnabi, M., Moberak, M. and Ottinger, M. A. (1990) Gen. Comp. Endocrinol. 78, 93-109 to unpublished work. 31 Konishi, M. (1965) Z. Tierpsychol. 22, 770-783 32 Marler, P. and Peters, S. (1982) Dev. Psychobiol. 15, 369-378 33 Marler, P. (1990)Proc. R. Soc. London Ser. B329, 109-114 34 West, M. J. and King, A. P. (1988) Nature 334, 244-246 35 Nelson, D. Anim. Behav. (in press) 36 Nice, M. M. (1943) Transactions of the Linnaean Society of New York 6, 1-238 37 Marler, P. and Peters, S. (1987) Ethology 76, 89--100 38 Slater, P. J. B., Eales, L. A. and Clayton, N. S. (1988) Adv. Study Behav. 18, 1-23 39 Simpson, H. B. and Vicario, D. S. (1990) J. Neurosci. 10, 1541-1556 40 Owren, M. J., Dieter, J. A., Seyfarth, R. M. and Cheney, D. L. Symp. Proc. XIII Congr. Int. PrimatoL Soc. (Vol. 1) (Nishida, T., McGrew, M., Marler, P., Pickford, M. and DeWaal, F., eds), (in press) 41 Pierce, J. D. (1985) Primates 26, 202-213 42 Green, S. (1975) Z. Tierpsychol. 38, 304-314 43 Masataka, N. Symp. Proc. XIII Congr. Int. Primatol. Soc. (Vol. 1) (Nishida, T., McGrew, M., Marler, P., Pickford, M. and DeWaal, F., eds), (in press) 44 Marler, P. and Sherman, V. (1983) J. Neurosci. 3,517-531 45 Marler, P. and Sherman, V. (1985) Anim. Behav. 33, 57-71 46 Nottebohm, F. (1968) Ibis 110, 549-568 47 Margoliash, D. (1983) J. Neurosd. 3, 1039-1057 48 Margoliash, D. (1986)J. Neurosci. 6, 1643-1661
49 Bottjer, S. W., Meisner, E. A. and Arnold, A. P. (1984) Science 224, 901-903 50 Sohrabji, F., Nordeen, E. J. and Nordeen, K. W. (1989) Behav. Neural Biol. 53, 51-63 51 Nottebohm, F. and Nottebohm, M. E. (1978) Z. Tierpsychol. 46, 298-305 52 Immelmann, K. (1969) in Bird Vocalizations (Hinde, R. A., ed.), pp. 61-74, Cambridge University Press 53 Eales, L. A. (1985) Anim. Behav. 33, 1293-1300 54 Clayton, N. (1987) Behaviour 102, 67-81 55 B6hner, J. (1990) Anim. Behav. 39, 369-374 56 Clayton, N. (1987) Anim. Behav. 35, 714-722 57 Kroodsma, D. E. and Pickert, R. (1980) Nature 288, 477-479 58 Eales, L. A. (1987) Anim. Behav. 35, 1356-1365 59 Nordeen, E. J. and Nordeen, K. W. (1990) Trends Neurosci. 13, 31-36 60 Marler, P. and Peters, S. (1988) Ethology 77, 76--84 61 Petrinovich, L. (1985) Behaviour 107, 208-240 62 Thielcke-Poltz, H. and Thielcke, G. (1960)Z. Tierpsychol. 17, 211-244 63 Hultsch, H. and Todt, D. (1989) J. Comp. Physiol. A 165, 197-203 64 Todt, D. H., Hultsch, H. and Heike, D. (1989) Z. Tierpsychol. 51, 23-35 65 Stoddard, P. K., Beecher, M. D. and Willis, M. S. (1988) Behav. Ecol. Sociobiol. 22, 125-130 66 Marler, P., Mundinger, P., Waser, M. S. and Lutjen, A. (1972) Anim. Behav. 20, 586-606 67 Konishi, M. (1989) Neuron 3,541-549 68 Nottebohm, F. (1989) Sci. Am. 260, 74-79 69 Bottjer, S. W. and Arnold, A. P. (1986) in Handbook of Behavioral Neurobiology (Blass, E. M., ed.), pp. 129-161, Plenum Press 70 Arnold, A. P. in Developmental Neuroethology (Stehouwer, D. J., ed.), John Wiley & Sons (in press) 71 Catchpole, C. C. (1987) Trends EcoL Evol. 2, 94-97 72 Krebs, J. R. and Kroodsma, D. E. (1980)Adv. Stud. Behav. 4, 143-177 73 Searcy, W. A. and Andersson, M. (1986) Annu. Rev. Ecol. Syst. 17, 507-533
Reassessingthe mechanismsand originsof vocallearningin birds Fernando Nottebohm Femando Nottebohm is at the Rockefeller University Field ResearchCenter, Millbrook, NY 12545, USA.
The most widely accepted hypothesis of vocal imitation in birds pre-dates many recent studies on the behavior, anatomy, physiology and cell biology of this phenomenon. It states that vocal learning involves two steps: (1) an auditory memory is laid down, and then (2) vocal ou~ut is modified until the auditory feedback it generates matches the model1. This black-box model of vocal imitation disregards circuitry. We now know that the brain pathways for vocal learning in birds include a series of well-defined nuclei and projections 2~. Some of these nuclei and projections develop late in ontogeny, at the time when auditory models are first acquired and imitated 6-9. We also know that the pathways involved in song production respond to sound, an observation that blurs the demarcation between what is an auditory and what is a motor circuit 1°-12. These and other recent discoveries call for a reassessment of the mechanisms and origins of vocal learning in birds and mammals. Many aspects of vocal learning in birds parallel speech acquisition in humans 13 and so it is, perhaps, inevitable that our thinking on vocal learning in birds should be influenced by our self-awareness of the phenom-
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enon. This could be a handicap or an opportunity for a broad biological perspective on vocal learning. The anatomical details of vocal learning will clearly differ between different groups of vertebrates, yet the general principles, drawing on common neurological heritage, might be shared. Of birds and humans The two-step hypothesis of vocal learning in birds emphasizes the separate contributions of auditory and motor processes and is congruent with two observations: (1) song development is aberrant in the absence of an external model; and (2) deafening after exposure to the model, but before imitation, cancels the effect of the earlier auditory experience 1. This two-step model of vocal learning in birds was accepted readily, perhaps because it fitted so well with our awareness of how we, as adults, imitate sounds - first we remember a sound; then we reproduce it, and it might take us several trials before we are satisfied with the results. However, vocal learning and its ontogeny are probably more complex than this. Basic to this complexity is the relationship between percep-
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tion and production of a sound. Two questions arise: (1) to what extent do perception and production pathways share components? (2) To what extent does production affect perception, and vice versa? I will comment first on this latter question. When we imitate a sound, the auditory signal activates a particular motor program, as suggested by Hinde for birds that countersing in kind 14. We do not know how this comes about. Perhaps we have a finite set of motor programs and each stands for a particular sound, so that we can only imitate a sound if we already have its motor program. Alternatively, we might know how our vocal tract works and can use this knowledge to produce a virtually endless set of sounds. These two mechanisms for vocal imitation might differ only in the size of the sound units for which our brain has a motor program. It is clear, though, that there are sounds that our vocal tract can make, and yet are difficult to imitate. So, for example, it is hard for adults to learn the sounds of a new language. We speak the foreign tongue with a 'foreign accent', i.e. with the sounds of our own language. It is not clear, however, to what extent foreign accents are a problem of motor control or speech perception, or both. Adult native speakers of Oriental languages that do not include the 'r' sound cannot tell the difference between an 'r' and an T. In this case there seems to be a link between the ability to produce and perceive a vocal sound, as suggested by the motor theory of speech perception 15. A general theory of vocal learning must take this into account. The early vocal practice of infants and birds - crying, cooing and babbling in the former; food begging and subsong in the latter - might influence how sounds are perceived and what sounds are imitated. A close relationship between brain pathways dealing with sound production and perception was first demonstrated by Ojemann and Mateer 16 in human patients. They described how sequential orofacial movements and phoneme identification were altered by electrical stimulation of the same brain sites. These authors inferred that there is a common system for language production and perception. Perception and production might also interact in this common pathway during ontogeny, though this has not been proved. Recent studies of the vocal control system of adult songbirds suggest that, in them also, sound production and perception share anatomical pathways 17. P a t h w a y s for vocal control and vocal learning in the songbird brain The brain pathways for auditory processing in birds have been described by anterograde tracers, starting with the cochlear nuclei. These ascending auditory pathways - the 'classical auditory system' - project to field L of the songbird neostriatum 18. Field L in turn projects to a layer of cells closely apposed to the ventral margin of the high vocal center (HVC) 18. The HVC is a large neostriatal3 vocal nucleus that plays an important role in the acquisition and production of learned vocalizations, including song. Figure 1 shows a partial sketch of these pathways in adult male canaries (Serinus canaria) and zebra finches (Taeniopygia guttata) "z-5, and they are probably very similar in other songbirds. The HVC projects to the robust nucleus of the archistriatum TINS, Vol. 14, No. 5, 1991
HVC FIELD L
ts nerve to trachea & Syrinx Fig. 1.5agittal section of adult songbird brain, showing the major pathways involved in song control Inputs to the HVC are shown m black. The descending efferent pathway is shown in white. The recursive loop is shown in grey, Field L is the auditory projection of the caudal neostriatum. Abbreviations: DLA4, medial portion of the dorsolateral thalamic nucleus; DM, pars dorsalis medialis of the nucleus intercollicularis; LMAN, lateral magnocellular nucleus of the anterior neostriatum; Nil, nucleus interface; RA, robust nucleus of the archistriatum; nXllts, pars tracheosyringealis of the hypoglossal nucleus; ts nerve, tracheosyringealis nerve; Uva, nucleus uvaeformis.
(RA). The RA projects to the pars dorsalis medialis (DM) of the nucleus intercollicularis, and to the pars tracheosyringealis of the hypoglossal nucleus (nXIIts). The DM also projects to the nXIIts. These nuclei and the descending efferent circuits they form fall into two functional systems. The DM, nXIIts and associated brainstem pathways suffice for the production of unlearned calls19; the HVC and the RA are needed for the production of learned sounds 2' 19. None of the above nuclei, however, initiates song. For example, bilateral destruction of the HVC does not stop singing attempts - as judged by posture, bill movements and pulsation of throat - although only very faint and scratchy sounds are produced 2. Engagement of the vocal organ (the syrinx) in the production of learned sounds seems to require an intact HVC 2' 19. Electrical recordings from the brain of singing songbirds confirm that singing behavior does not start in the HVC. Song-related changes in neuronal activity occur first in the nucleus interface (NIf), which is an afferent to the HVC, and then they occur in the center itself2°; both these changes precede the onset of song. Song probably does not start in the NIf either. The nucleus uvaeformis (Uva) of the thalamus projects to the NIf, to the HVC and to the contralateral Uva3. Electrical stimulation of the Uva elicits responses in the song efferent pathway, including the HVC, the RA and the nXIIts, with a slightly shorter 207
latency in the ipsilateral than in the contralateral side (Williams, H., PhD thesis, Rockefeller University, 1984, and Ref. 21). Once the HVC is activated, it might provide the learned subroutines for each syllable type. The projections from the HVC to the RA, and from the RA to the DM and the nXIIts are all ipsilateral2; each nXIIts, in turn, only innervates the ipsilateral syringeal musculature z2. The projections from the Uva to the NIf and from both these nuclei to the HVC are also ipsilateral3. However, since each Uva also projects to the contralateral Uva 3'21, this might ensure the simultaneous activation of the right and left vocal control pathways during song production. In addition, each HVC receives auditory input from the ipsilateral field L 1°'18. Auditory feedback could help both sides integrate their output during vocal learning. Efferent integration might also occur in the brainstem, because each nucleus intercollicularis projects to the contralateral nucleus intercollicularis2. In species such as the chaffinch (Fringilla coelebs), white-crowned sparrow (Zonotrichia leucophrys) and canary, the right and left syringeal halves each produce their own set of sounds 23'24. Since a harmonious and stereotyped integration of these two sound sources persists after deafening23, it must arise at the level of the Uva. During song, the Uva might trigger activity in the Uva-NIf-HVC-RA-DM-nXIIts efferent pathway one sound at a time, rather than one song at a time. The side of the brain engaged in sound production at any one time, the type of sound produced and the order in which these sounds occur, might all be determined by the Uva. If so, this nucleus has a very important role in song learning. The fact that it also responds to sound (Williams, H., PhD thesis) might not be coincidental. This is a remarkable role for a nucleus that has only a few hundred neurons. It will be very interesting to know if there is a homologue of this nucleus in birds that do not learn their song. Might a sound-responsive Uva or its equivalent provide a link between auditory input and phonation in both vocal learners and non-learners? There is another circuit that is important for song learning: the recursive loop. The recursive loop links the ipsilateral HVC to area X of lobus parolfactorius, area X to the medial portion of the dorsolateral thalamic nucleus (DLM), the DLM 4'5 to the lateral magnocellular nucleus of the anterior neostriatum (LMAN), and the LMAN to the RA (Fig. 1). Thus, there are two pathways from the HVC to the RA: the short, direct one described earlier and a long, recursive one. The recursive loop21 is particularly interesting because it affects song learning but not production 6f learned song. Bilateral lesions of the LMAN25 or area X26'27 interfere with song learning, but if the same lesions are made after song has been mastered as a motor skill, song remains unaltered. The short path to the RA and the recursive loop interact in at least one cell type in the RA. This cell type (the commonest one) projects to the nXIIts and receives inputs from both the HVC and the LMAN; the number of these inputs increases under the influence of testosterone, as song becomes more stereotyped 28. Adult male canaries modify their song every year29'3°, a change that requires an intact HVC 2 and 208
an intact LMAN 17. We infer that both the direct HVCRA pathway and the recursive loop are necessary for vocal learning. Surprisingly, retention of the syllables that adult canaries have already mastered also requires an intact LMAN. Bilateral destruction of the LMAN leads to a gradual loss of these syllable types. A few weeks after the lesion, the size of the syllable repertoire has shrunk from between 20 and 30 to between two and five (Ref. 17). This result suggests that the entire song repertoire of canaries is relearned every year - a process that, as in young zebra finches ~5, depends on an intact LMAN and recursive loop. Each half of the songbird brain has its own pathway for song production and song learning. In some songbirds, such as the canary, the left half of the syrinx and its higher control centers contribute a majority of song syllables, as determined by unilateral denervation 24, unilateral destruction of the HVC ~, or unilateral bronchus plugging31. In the catbird (Dumetella carolinensis) and brown thrasher (Toxostoma rufum), each syringeal half also contributes a unique set of sounds, but the number of different sounds produced by each side is more equally balanced 32. The origin and significance of functional asymmetry in brain pathways for song control - particularly as it relates to learning - remains a mystery. However, there are indications that both sides of the songbird brain perceive sounds differently17. This material seems ripe for further experimentation.
Projection neurons and learning The HVC consists of at least two different types of neurons: those that project to area X (large), and those that project to the RA (small) 3~. Whereas most of the X-projecting cells are formed before hatching, most of the RA-projecting cells are generated later 9. It is of particular interest that large numbers of RAprojecting cells are produced during the very time when young canaries and zebra finches learn their song s'9. This raises the possibility that the generation, migration and differentiation of neurons projecting from the HVC to the RA might be influenced by the auditory and motor events that are part of vocal learning. Many new neurons continue to be added to the HVC of adult canaries 34. Intracellular recordings from such cells show that some of them respond to sound; this is clear evidence of their incorporation into existing circuits 35. Contrary to an earlier report 33, a majority of the HVC neurons formed in adult male canaries are projection neurons that link the center to the RA 36'37. Since the size of the HVC does not increase in adulthood38'39, and since the percentage of the cells that project from it to the RA changes little between the ages of one year and four years 36, the new RA-projecting neurons probably replace older ones of the same kind. This replacement seems to be particularly brisk during late summer, when adult canaries acquire new songs 36. The new RA-projecting neurons 'born' in late summer remain in place for at least eight months, until the following breeding season 37. This would be expected if the new cells became part of the motor circuits that mastered new songs. New neurons might also be added to area X of adult canaries, but this phenomenon has not yet been studied in detail (Nottebohm, F., unpublished observations). TINS, VoL 14, No. 5, 1991
Hormonal changes can induce dendritic growth, synaptogenesis and changes in synaptic anatomy in the RA of adult canaries 2s'4°'41. If anatomical changes of this magnitude provided sufficient plasticity to bring about successive behavioral modifications, why would neurons need to be replaced? There is no precedent for the replacement of neurons deep inside the brain of healthy individuals. Perhaps in some cases neurons, not synapses, are the units of learning. In these cells learning might be the final and irreversible stage in differentiation. If so, the more the HVC engages in learning, the less it will be able to learn thereafter. A way out of this limitation would be to replace old, 'learned' neurons with new ones. In such a hypothetical scenario older information would be dismissed for the sake of acquiring new information. A revolving door system of this kind would make sense if the amount of learning in the HVC were limited by the total number of cells. Although there is no direct evidence of such a causal relationship, two studies have reported that the size of the HVC and the complexity of learned song are correlated 3s'42. The above arguments sought to establish a link between adult neurogenesis and sustained vocal learning. However, adult zebra finches also add new neurons 43, including RA-projecting neurons s'36, to the HVC, though their song remains unchanged 44. Perhaps this center and the efferent pathway for song production play a role in song perception in adult male zebra finches. If new neurons have to be added to a motor pathway to code for new song perceptual memories, then the distinction between what is a motor memory and what is a perceptual memory has been blurred. Interestingly, if RA-projecting neurons are replaced without changes in song, then the motor memory for learned song might be in the RA; this might also be guessed from the fact that both the direct and recursive paths converge there.
Song perception and song production The response of HVC neurons to sound is biased in adulthood in favor of a bird's own song ] 1, which might provide a reference point against which all other songs are measured. However, it is not known when this bias first appears. Interestingly, the response is stronger to the bird's own song than to the external model by which the bird had been tutored 45'46. This suggests that, at the level of the HVC at least, inputs are more likely to be measured against production standards than against external models. Other experiments also suggest that the HVC plays a role in song perception. (1) Adult female canaries in reproductive condition respond to canary song by adopting a copulation posture. However, if the HVC is lesioned bilaterally, they also respond in this manner to the song of other species 47. (2) Adult male zebra finches with bilateral lesions of the HVC take longer to master a discrimination between conspecific songs than do intact birds (Cynx, J. and Nottebohm, F., unpublished observations). (3) Female zebra finches, which have a very small HVC and which lack the connection between it and the RA, take more trials to discriminate between conspecific songs than males 17. Responses in the HVC to sound do not stop there, but are transmitted to the RA and the nXIIts, from where sound-induced activity is conveyed to the muscles of the syrinx 12. We do not know whether the TIN& Vol. 14, No. 5, 1991
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lateral MAN 20ms Fig. 2. Auditory responses in the zebra finch song system. Each trace represents the response to a tone burst as recorded extrace//u/ar/y within a song system nucleus, characterized by name. The recordings are arranged in the order of increasing latency from the stimulus onset. These recordings were obtained from several birds under anesthesia and are representative of the relative latencies seen in all recordings. Abbreviations: DLM, media/portion of the dorso/atera/ tha/amic nucleus; HVC, high vocal center; LMAN, lateral magnoce//u/ar nucleus of the anterior neostriatum; N/f, nucleus interface; RA, robust nucleus of the archistriatum; nXI/ts, pars tracheosyringea/is of the hypog/ossa/ nucleus; NX//ts, tracheosyringea/ branch of the hypoglossus nerve (same as ts nerve in Fig. 1). (Taken, with permission, from Ref. 21.)
209
recursive loop affects this progression. The latency of sound responses increases in the following order: field L < Nil < HVC < RA < nXIIts < area X < DLM < LMAN (Fig. 2), suggesting that the sound responses recorded from the nXIIts descend directly from the HVC to the RA and from the RA to the nXIIts. Playback of different song components selectively activates different clusters of motor cells in nXIIts 12. This apparent conversion of auditory input to gestural information could affect the perception of conspecific sounds, as suggested by the motor theory of speech perception 15. Perhaps birds, like humans, perceive conspecific sounds in a self-centered manner, colored by each individual's vocal skills. If so, then communication among members of a local population must integrate these perceptual idiosyncrasies. The vocal dialects of birds and humans might have evolved to share both a system of signals and meanings, and also a system of perceptions. A need for shared perceptions might also be the reason why some birds learn to produce many more songs than they end up using4s. The original, larger repertoire might help them to discriminate among other conspecifics. If these speculations are proved to be correct, then we might have to reevaluate the origins of vocal learning. Rigid vocal ontogenies might have been relaxed, not just to generate new sounds, but also to generate new perceptual subtleties. If auditory and motor activity share pathways, not only in adulthood but also during development, then auditory experience might influence the ontogeny of brain pathways for producing learned vocalizations. It was mentioned earlier that HVC neurons that project to the RA are 'born' during development, when young zebra finches and canaries first learn their song&9. The addition of these cells and the formation of connections throughout the motor pathways for song control might be regulated directly by auditory experience. Deafening after exposure to a model, but before conversion to a learned vocal score, might negate the effects of the auditory experience by (1) preventing the use of auditory feedback to match the model ~, (2) affecting the survival of cells and connections already in place, or (3) affecting the recruitment of new cells and connections. All three effects could occur and interact.
Stapedius muscle and origins of vocal learning Vocal learning has been studied mostly in birds that imitate sounds, but a recent discovery suggests that the first step towards vocal learning might have had little to do with vocal imitation, Roosters, (Gallus gallus) develop normal crowing without access to auditory feedback49, yet elimination of the middle ear stapedius muscle early in ontogeny shifts the emphasis of crowing from a lower to a higher harmonic 5°. The stapedius muscle dampens the response of the avian middle ear to loud, low frequencies of selfproduced vocalizations51. In the absence of the stapedius muscle, a young rooster shifts the energy of crowing from the first to the second harmonic, thus making up for the lack of middle ear dampening. Other species, such as the zebra finch, can regulate and imitate patterns of harmonic emphasis s2 as part of a broad, vocal-learning ability. The ability to modify vocal sounds by reference to 210
auditory feedback might have arisen as a mechanism to protect an animal's cochlear cells. A system that is sensitive to faint sounds will be damaged by very loud sounds. Signals such as birdsong and the song of some cetaceans, which have evolved to have an effect over long distances, are loud at source and include low frequencies. In extreme cases of signal loudness, vocal production and middle ear dampening might have to interact to keep sound production within a safe range of frequency amplitude. A first step towards the evolution of vocal learning might have taken place in animals that used vocal sounds to communicate over long distances, and that also depended on their hearing to detect danger or find food. In some of these animals, the dampening at source of some harmonics to preserve cochlear sensitivity might have introduced a new, auditorily guided vocal flexibility that then became available for influencing more effectively the behavior of conspecifics - perhaps by producing the sounds of dominance53, or nearness 54, or many55, or merely sounds more pleasing to the ear56t The same auditory-vocal connection might also have been used to better perceive the signals of other conspecifics, which would now elicit, not just an auditory response, but also an internalized vocal gesture. Presumably these dual pressures to better perceive and better manipulate57 other members of a species remain with us and have shaped all instances of vocal learning, including vocal imitation. Thus, the roots of vocal learning, the most momentous breakthrough in animal communication, might be found in a modest brainstem reflex. It will be fascinating to uncover how this reflex evolved into a function of the forebrain as we now know it.
Selected references 1 Konishi, M. (1965) Z. Tierpsychol. 22, 770-783 2 Nottebohm, F., Stokes, T. M. and Leonard, C. M. (1976) J. Comp. Neurol. 165, 457-486 3 Nottebohm, F., Kelley, D. B. and Paton, J. A. (1982) J. Comp. Neurol. 207, 344-357 4 0 k u h a t a , S. and Saito, N (1987) Brain Res. Bull. 18, 35-44 5 13ottjer, S. W., Ha}sema, K. A., Brown, S. A. and Miesner, E. A. (1989) J. Comp. Neurol. 279, 312-326 6 Nottebohm, F. (1980) in Progress in Psychobiology and Physiological Psychology (Vol. 9) (Sprage, J. M. S. and Epstein, A. N. E., eds), pp. 85-124, Academic Press 7 Konishi, M. and Akutagawa, E. (1985) Nature315, 145-147 8 Nordeen, K. W. and Nordeen, E. J. (1988) Nature 334, 149-151 9 Alvarez-13uylla, A., Theelen, M. and Nottebohm, F. (1988) Proc. Natl Acad. Sci. USA 85, 8722-8726 10 Katz, L. C. and Gurney, M. E. (1981) Brain Res. 221,192-197 11 Margoliash, D. (1983)J. Neurosci. 3, 1039-1057 12 Williams, H. and Nottebohm, F. (1985) Science 229, 279-282 13 Marler, P. (1970) Am. Sci. 58, 669-673 14 Hinde, R. A. (1958)Anim. Behav. 6, 211-218 15 Liberman, A. M., Cooper, F. S., Shankweiler, D. and Stucldert-Kennedy, M. (1967) Psychol. Rev. 74, 431-461 16 Ojemann, G. and Mateer, C (1979) Science205, 1401-1403 17 Nottebohm, F. et aL (1990) Philos. Trans. R. Soc. London Ser. B 329, 115-124 18 Kelley, D. 13.and Nottebohm, F. (1979) J. Comp. NeuroL 183, 455-470 19 Simpson, H. 13. and Vicario, D. (1990) J. Neurosci. 10, 1541-1556 20 McCasland, J. S. (1987) J. Neurosci. 7, 23-39 21 Williams, H. (1989) Ann. NYAcad. Sci. 563, 148-164 22 Vicario, D. S. and Nottebohm, F. (1988) J. Comp. NeuroL 271,346-354 23 Nottebohm, F. (1971) J. Exp. Zoo/. 177, 229-261 24 Nottebohm, F. and Nottebohm, M. E. (1976) J. Comp.
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Physiol. A 108, 171-192 25 Bottjer, S. W., Miesner, E. A. and Arnold, A. P. (1984) Science 224, 901-903 26 Scharff, C. and Nottebohm, F. (1989) Soc. Neurosci. Abstr. 15, 618 27 Sohrabji, F., Nordeen, E. J. and Nordeen, K. W. (1990) Behav, Neural Biol. 53, 51-63 28 Canady, R. A., Burd, G. D., DeVoogd, T. J. and Nottebohm, F. (1988)J. Neurosci. 8, 3770-3784 29 Nottebohm, F. and Nottebohm, M. E. (1978) Z. Tierpsychol. 46, 298-305 30 Nottebohm, F., Nottebohm, M. E., Crane, L. A. and Wingfield, J. C. (1987) Behav. Neural Biol. 47, 197-411 31 Hartley, R. S. and Suthers, R. A. (1990) J. Neurobiol. 22, 1236-1248 32 Suthers, R. A. (1990) Nature 347, 473-477 33 Paton, J. A., O'Loughlin, B. and Nottebohm, F. (1985) J. Neurosci. 5, 3088-3093 34 Goldman, S. A. and Nottebohm, F. (1983) Proc. NatlAcad. Sci. USA 80, 2390-2394 35 Paton, J. A. and Nottebohm, F. (1984) Science 225, 1046-1048 36 Alvarez-Buylla, A., Kirn, J. R. and Nottebohm, F. (1990) Science 249, 1444-1446 37 Kirn, J. R., Alvarez-Buylla, A. and Nottebohm, F. J. Neurosd. (in press) 38 Nottebohm, F., Kasparian, S. and Pandazis C. (1981) Brain Res. 213, 99-109
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Deducing Function from Structure (Vol. 2). Information Processing in the Retina by Fritiof S. Sjostrand, Academic Press, 1990. $69.95 (xi + 233 pages) ISBN 0 126 47656 X
This is a tale of one man's obsession with a big idea: the notion that a minutely detailed examination of the ultrastructure of retinal synapses would provide great insight into how the outer retina processes visual information. A tendency to attribute functional meaning to every detail of the observed microanatomy led Sj6strand to reject currently held views of the different functional roles of rods and cones in the retina, of the mechanism of lateral inhibition, and of the way in which information passes from photoreceptors to ON bipolar cells. Such refreshing iconoclasm would be warmly welcomed if it were based on convincing evidence: unfortunately it was not and, as Sj6strand records, granting agencies stopped supporting his work. In broad terms, information processing by the outer retina is well understood. Light is converted into a change of membrane potential by rods and cones, rods being more sensitive but providing poorer temporal TIN& Vol. 14, No. 5, 1991
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39 Gahr, M. (1990) J. Comp. NeuroL 294, 30-36 40 DeVoogd, T. and Nottebohm, F. (1981) Science 214, 202-204 41 DeVoogd, T., Nixdorf, B. and Nottebohm, F. (1985) Brain Res. 329, 304-308 42 Canady, R. A., Kroodsma, D. E. and Nottebohm, F. (1984) Proc. Natl Acad. Sci. USA 81, 6232-6234 43 Nottebohm, F. (1984) Condor 86, 227-236 44 Immelmann, K, (1969) in Bird Vocalizations (Hinde, R. A., ed.), pp. 61-74, Cambridge University Press 45 Margoliash, D. and Konishi, M. (1985) Proc. NatlAcad. Sci. USA 82, 5997-6000 46 Margoliash, D. (1986)J. Neurosci. 6, 1643-1661 47 Brenowitz, E. (1991) Science 251,303-305 48 Marler, P. and Peters, S. (1981) Science 213,780-782 49 Konishi, M. (1963) Z. Tierpsychol. 20, 349-367 50 Grassi,S., Ottaviani, F. and Bambagioni, D. (1990) Brain Res. 529, 158-164 51 Borg, E. and Counter, S. A. (1989) Sci. Am. 261, 74-80 52 Williams, H., Cynx, J. and Nottebohm, F. (1989) J. Comp. PsychoL 103,366-380 53 King, A. P. and West, M. J. (1977) Nature 305, 704-706 54 Morton, E. G. (1986) Behaviour 99, 65-86 55 Krebs, J. R. (1976) Behav, EcoL Sociobiol. 1,215-227 56 Ryan, M. J., Fox, J. H., Wilczynski, W. and Rand, S. (1990) Nature 343, 66-67 57 Krebs,J. R. and Dawkins, R. (1984) in BehavioralEcology, an Evolutionary Approach, pp. 380-402, SinauerAssociates
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resolution than cones. Visual information is then passed from the photoreceptors to two types of bipolar cell (ON and OFF cells, which are depolarized and hyperpolarized, respectively, by light falling in the centre of their receptive fields), which in turn send information on to the inner retina and hence to the brain. In addition, information flows laterally across the outer retina through a pathway from photoreceptors to bipolar cells via horizontal cells. This pathway generates an antagonistic surround to the bipolar cell receptive field, and thus mediates lateral inhibition in the outer retina. This description of outer retinal function is based on a combination of electrophysiological recording of the cells' light responses and anatomical investigation of the synaptic connections of the cells. Sj~strand's approach was to carry out a three-dimensional reconstruction (from electron microscope pictures) of all the cell processes in an area of retina, to build models of these processes, and then to try to deduce the function of the tissue from the details of the microanatomy. The details of the reconstruction process, and the precise relative positions of the cell processes in the retinal areas reconstructed, are described in overwhelming detail in this book. Put charitably,
III III III Sj6strand does not believe in briefly summarizing the evidence essential for making his points. He prefers to give the reader every available piece of data. This extensive description of his work may be valuable for showing the kind of complexity in the arrangement of the cells that exists at a microanatomical level. Furthermore, many of his models of cell processes (shown as photographs in the book) are aesthetically pleasing in themselves, having more than a passing resemblance to the sculptures of Henry Moore. However, Sj6strand never raises the obvious question of whether microanatomical complexity (for example, the fact that the bipolar cell processes receiving synapses from rods and cones are of different sizes) must reflect the way in which information is processed, or whether it is simply a consequence of the developmental programme needed to specify how the neurones must grow in order to make the necessary connections between them. Some of Sj6strand's disagreements with current views of retinal function are based on a disregard of existing electrophysiological evidence. Thus, when rejecting the notion that cones have a higher threshold and a faster temporal response than rods (Chapter 7), he ignores the fact that these properties
Acknowledgements / thank the N/H, USPHS,and the Mary FlaggterCary Charitable Trust for researchsupport, and my wife, Marta E. Nottebohm, for editorial help and encouragement.
books David Attwell Department of Physiolo~7, University College London, London WC1E6BT, UK.
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23 Kroodsma, D. E. (1986) Anim. Behav. 34, 1573-1575 Research was 24 Marler, P., Peters, S,, Ball, G., Dufty, A. M. and Wingfield, J. C. (1988) Nature 336, 770-772 conducted in 25 Marler, P., Peters, S. and Wingfield, J. (1987) J. Neurobiol. collaboration with 18, 531-548 Susan Peters, and 26 Gurney, M. and Konishi, M. (1986) Science 208, 1380-1382 supported by Grant 27 Hutchison, J. B., Wingfield, J. C. and Hutchison, R. E. (1984) number MN14651. J. Endocrinol. 103,363-369 I am indebted to 28 DeVoogd, T. J. (1986) J. Neurobiol. 17, 177-201 Douglas Nelson and 29 Weichel, K., Schwager, G., Held, P., G0ttinger, H. R. and Pesch, A. (1986) Ethology 73,281-294 Stephen Nowicki for discussion and access 30 Adkins-Regan, E., Abdelnabi, M., Moberak, M. and Ottinger, M. A. (1990) Gen. Comp. Endocrinol. 78, 93-109 to unpublished work. 31 Konishi, M. (1965) Z. Tierpsychol. 22, 770-783 32 Marler, P. and Peters, S. (1982) Dev. Psychobiol. 15, 369-378 33 Marler, P. (1990)Proc. R. Soc. London Ser. B329, 109-114 34 West, M. J. and King, A. P. (1988) Nature 334, 244-246 35 Nelson, D. Anim. Behav. (in press) 36 Nice, M. M. (1943) Transactions of the Linnaean Society of New York 6, 1-238 37 Marler, P. and Peters, S. (1987) Ethology 76, 89--100 38 Slater, P. J. B., Eales, L. A. and Clayton, N. S. (1988) Adv. Study Behav. 18, 1-23 39 Simpson, H. B. and Vicario, D. S. (1990) J. Neurosci. 10, 1541-1556 40 Owren, M. J., Dieter, J. A., Seyfarth, R. M. and Cheney, D. L. Symp. Proc. XIII Congr. Int. PrimatoL Soc. (Vol. 1) (Nishida, T., McGrew, M., Marler, P., Pickford, M. and DeWaal, F., eds), (in press) 41 Pierce, J. D. (1985) Primates 26, 202-213 42 Green, S. (1975) Z. Tierpsychol. 38, 304-314 43 Masataka, N. Symp. Proc. XIII Congr. Int. Primatol. Soc. (Vol. 1) (Nishida, T., McGrew, M., Marler, P., Pickford, M. and DeWaal, F., eds), (in press) 44 Marler, P. and Sherman, V. (1983) J. Neurosci. 3,517-531 45 Marler, P. and Sherman, V. (1985) Anim. Behav. 33, 57-71 46 Nottebohm, F. (1968) Ibis 110, 549-568 47 Margoliash, D. (1983) J. Neurosd. 3, 1039-1057 48 Margoliash, D. (1986)J. Neurosci. 6, 1643-1661
49 Bottjer, S. W., Meisner, E. A. and Arnold, A. P. (1984) Science 224, 901-903 50 Sohrabji, F., Nordeen, E. J. and Nordeen, K. W. (1989) Behav. Neural Biol. 53, 51-63 51 Nottebohm, F. and Nottebohm, M. E. (1978) Z. Tierpsychol. 46, 298-305 52 Immelmann, K. (1969) in Bird Vocalizations (Hinde, R. A., ed.), pp. 61-74, Cambridge University Press 53 Eales, L. A. (1985) Anim. Behav. 33, 1293-1300 54 Clayton, N. (1987) Behaviour 102, 67-81 55 B6hner, J. (1990) Anim. Behav. 39, 369-374 56 Clayton, N. (1987) Anim. Behav. 35, 714-722 57 Kroodsma, D. E. and Pickert, R. (1980) Nature 288, 477-479 58 Eales, L. A. (1987) Anim. Behav. 35, 1356-1365 59 Nordeen, E. J. and Nordeen, K. W. (1990) Trends Neurosci. 13, 31-36 60 Marler, P. and Peters, S. (1988) Ethology 77, 76--84 61 Petrinovich, L. (1985) Behaviour 107, 208-240 62 Thielcke-Poltz, H. and Thielcke, G. (1960)Z. Tierpsychol. 17, 211-244 63 Hultsch, H. and Todt, D. (1989) J. Comp. Physiol. A 165, 197-203 64 Todt, D. H., Hultsch, H. and Heike, D. (1989) Z. Tierpsychol. 51, 23-35 65 Stoddard, P. K., Beecher, M. D. and Willis, M. S. (1988) Behav. Ecol. Sociobiol. 22, 125-130 66 Marler, P., Mundinger, P., Waser, M. S. and Lutjen, A. (1972) Anim. Behav. 20, 586-606 67 Konishi, M. (1989) Neuron 3,541-549 68 Nottebohm, F. (1989) Sci. Am. 260, 74-79 69 Bottjer, S. W. and Arnold, A. P. (1986) in Handbook of Behavioral Neurobiology (Blass, E. M., ed.), pp. 129-161, Plenum Press 70 Arnold, A. P. in Developmental Neuroethology (Stehouwer, D. J., ed.), John Wiley & Sons (in press) 71 Catchpole, C. C. (1987) Trends EcoL Evol. 2, 94-97 72 Krebs, J. R. and Kroodsma, D. E. (1980)Adv. Stud. Behav. 4, 143-177 73 Searcy, W. A. and Andersson, M. (1986) Annu. Rev. Ecol. Syst. 17, 507-533
Reassessingthe mechanismsand originsof vocallearningin birds Fernando Nottebohm Femando Nottebohm is at the Rockefeller University Field ResearchCenter, Millbrook, NY 12545, USA.
The most widely accepted hypothesis of vocal imitation in birds pre-dates many recent studies on the behavior, anatomy, physiology and cell biology of this phenomenon. It states that vocal learning involves two steps: (1) an auditory memory is laid down, and then (2) vocal ou~ut is modified until the auditory feedback it generates matches the model1. This black-box model of vocal imitation disregards circuitry. We now know that the brain pathways for vocal learning in birds include a series of well-defined nuclei and projections 2~. Some of these nuclei and projections develop late in ontogeny, at the time when auditory models are first acquired and imitated 6-9. We also know that the pathways involved in song production respond to sound, an observation that blurs the demarcation between what is an auditory and what is a motor circuit 1°-12. These and other recent discoveries call for a reassessment of the mechanisms and origins of vocal learning in birds and mammals. Many aspects of vocal learning in birds parallel speech acquisition in humans 13 and so it is, perhaps, inevitable that our thinking on vocal learning in birds should be influenced by our self-awareness of the phenom-
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enon. This could be a handicap or an opportunity for a broad biological perspective on vocal learning. The anatomical details of vocal learning will clearly differ between different groups of vertebrates, yet the general principles, drawing on common neurological heritage, might be shared. Of birds and humans The two-step hypothesis of vocal learning in birds emphasizes the separate contributions of auditory and motor processes and is congruent with two observations: (1) song development is aberrant in the absence of an external model; and (2) deafening after exposure to the model, but before imitation, cancels the effect of the earlier auditory experience 1. This two-step model of vocal learning in birds was accepted readily, perhaps because it fitted so well with our awareness of how we, as adults, imitate sounds - first we remember a sound; then we reproduce it, and it might take us several trials before we are satisfied with the results. However, vocal learning and its ontogeny are probably more complex than this. Basic to this complexity is the relationship between percep-
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tion and production of a sound. Two questions arise: (1) to what extent do perception and production pathways share components? (2) To what extent does production affect perception, and vice versa? I will comment first on this latter question. When we imitate a sound, the auditory signal activates a particular motor program, as suggested by Hinde for birds that countersing in kind 14. We do not know how this comes about. Perhaps we have a finite set of motor programs and each stands for a particular sound, so that we can only imitate a sound if we already have its motor program. Alternatively, we might know how our vocal tract works and can use this knowledge to produce a virtually endless set of sounds. These two mechanisms for vocal imitation might differ only in the size of the sound units for which our brain has a motor program. It is clear, though, that there are sounds that our vocal tract can make, and yet are difficult to imitate. So, for example, it is hard for adults to learn the sounds of a new language. We speak the foreign tongue with a 'foreign accent', i.e. with the sounds of our own language. It is not clear, however, to what extent foreign accents are a problem of motor control or speech perception, or both. Adult native speakers of Oriental languages that do not include the 'r' sound cannot tell the difference between an 'r' and an T. In this case there seems to be a link between the ability to produce and perceive a vocal sound, as suggested by the motor theory of speech perception 15. A general theory of vocal learning must take this into account. The early vocal practice of infants and birds - crying, cooing and babbling in the former; food begging and subsong in the latter - might influence how sounds are perceived and what sounds are imitated. A close relationship between brain pathways dealing with sound production and perception was first demonstrated by Ojemann and Mateer 16 in human patients. They described how sequential orofacial movements and phoneme identification were altered by electrical stimulation of the same brain sites. These authors inferred that there is a common system for language production and perception. Perception and production might also interact in this common pathway during ontogeny, though this has not been proved. Recent studies of the vocal control system of adult songbirds suggest that, in them also, sound production and perception share anatomical pathways 17. P a t h w a y s for vocal control and vocal learning in the songbird brain The brain pathways for auditory processing in birds have been described by anterograde tracers, starting with the cochlear nuclei. These ascending auditory pathways - the 'classical auditory system' - project to field L of the songbird neostriatum 18. Field L in turn projects to a layer of cells closely apposed to the ventral margin of the high vocal center (HVC) 18. The HVC is a large neostriatal3 vocal nucleus that plays an important role in the acquisition and production of learned vocalizations, including song. Figure 1 shows a partial sketch of these pathways in adult male canaries (Serinus canaria) and zebra finches (Taeniopygia guttata) "z-5, and they are probably very similar in other songbirds. The HVC projects to the robust nucleus of the archistriatum TINS, Vol. 14, No. 5, 1991
HVC FIELD L
ts nerve to trachea & Syrinx Fig. 1.5agittal section of adult songbird brain, showing the major pathways involved in song control Inputs to the HVC are shown m black. The descending efferent pathway is shown in white. The recursive loop is shown in grey, Field L is the auditory projection of the caudal neostriatum. Abbreviations: DLA4, medial portion of the dorsolateral thalamic nucleus; DM, pars dorsalis medialis of the nucleus intercollicularis; LMAN, lateral magnocellular nucleus of the anterior neostriatum; Nil, nucleus interface; RA, robust nucleus of the archistriatum; nXllts, pars tracheosyringealis of the hypoglossal nucleus; ts nerve, tracheosyringealis nerve; Uva, nucleus uvaeformis.
(RA). The RA projects to the pars dorsalis medialis (DM) of the nucleus intercollicularis, and to the pars tracheosyringealis of the hypoglossal nucleus (nXIIts). The DM also projects to the nXIIts. These nuclei and the descending efferent circuits they form fall into two functional systems. The DM, nXIIts and associated brainstem pathways suffice for the production of unlearned calls19; the HVC and the RA are needed for the production of learned sounds 2' 19. None of the above nuclei, however, initiates song. For example, bilateral destruction of the HVC does not stop singing attempts - as judged by posture, bill movements and pulsation of throat - although only very faint and scratchy sounds are produced 2. Engagement of the vocal organ (the syrinx) in the production of learned sounds seems to require an intact HVC 2' 19. Electrical recordings from the brain of singing songbirds confirm that singing behavior does not start in the HVC. Song-related changes in neuronal activity occur first in the nucleus interface (NIf), which is an afferent to the HVC, and then they occur in the center itself2°; both these changes precede the onset of song. Song probably does not start in the NIf either. The nucleus uvaeformis (Uva) of the thalamus projects to the NIf, to the HVC and to the contralateral Uva3. Electrical stimulation of the Uva elicits responses in the song efferent pathway, including the HVC, the RA and the nXIIts, with a slightly shorter 207
latency in the ipsilateral than in the contralateral side (Williams, H., PhD thesis, Rockefeller University, 1984, and Ref. 21). Once the HVC is activated, it might provide the learned subroutines for each syllable type. The projections from the HVC to the RA, and from the RA to the DM and the nXIIts are all ipsilateral2; each nXIIts, in turn, only innervates the ipsilateral syringeal musculature z2. The projections from the Uva to the NIf and from both these nuclei to the HVC are also ipsilateral3. However, since each Uva also projects to the contralateral Uva 3'21, this might ensure the simultaneous activation of the right and left vocal control pathways during song production. In addition, each HVC receives auditory input from the ipsilateral field L 1°'18. Auditory feedback could help both sides integrate their output during vocal learning. Efferent integration might also occur in the brainstem, because each nucleus intercollicularis projects to the contralateral nucleus intercollicularis2. In species such as the chaffinch (Fringilla coelebs), white-crowned sparrow (Zonotrichia leucophrys) and canary, the right and left syringeal halves each produce their own set of sounds 23'24. Since a harmonious and stereotyped integration of these two sound sources persists after deafening23, it must arise at the level of the Uva. During song, the Uva might trigger activity in the Uva-NIf-HVC-RA-DM-nXIIts efferent pathway one sound at a time, rather than one song at a time. The side of the brain engaged in sound production at any one time, the type of sound produced and the order in which these sounds occur, might all be determined by the Uva. If so, this nucleus has a very important role in song learning. The fact that it also responds to sound (Williams, H., PhD thesis) might not be coincidental. This is a remarkable role for a nucleus that has only a few hundred neurons. It will be very interesting to know if there is a homologue of this nucleus in birds that do not learn their song. Might a sound-responsive Uva or its equivalent provide a link between auditory input and phonation in both vocal learners and non-learners? There is another circuit that is important for song learning: the recursive loop. The recursive loop links the ipsilateral HVC to area X of lobus parolfactorius, area X to the medial portion of the dorsolateral thalamic nucleus (DLM), the DLM 4'5 to the lateral magnocellular nucleus of the anterior neostriatum (LMAN), and the LMAN to the RA (Fig. 1). Thus, there are two pathways from the HVC to the RA: the short, direct one described earlier and a long, recursive one. The recursive loop21 is particularly interesting because it affects song learning but not production 6f learned song. Bilateral lesions of the LMAN25 or area X26'27 interfere with song learning, but if the same lesions are made after song has been mastered as a motor skill, song remains unaltered. The short path to the RA and the recursive loop interact in at least one cell type in the RA. This cell type (the commonest one) projects to the nXIIts and receives inputs from both the HVC and the LMAN; the number of these inputs increases under the influence of testosterone, as song becomes more stereotyped 28. Adult male canaries modify their song every year29'3°, a change that requires an intact HVC 2 and 208
an intact LMAN 17. We infer that both the direct HVCRA pathway and the recursive loop are necessary for vocal learning. Surprisingly, retention of the syllables that adult canaries have already mastered also requires an intact LMAN. Bilateral destruction of the LMAN leads to a gradual loss of these syllable types. A few weeks after the lesion, the size of the syllable repertoire has shrunk from between 20 and 30 to between two and five (Ref. 17). This result suggests that the entire song repertoire of canaries is relearned every year - a process that, as in young zebra finches ~5, depends on an intact LMAN and recursive loop. Each half of the songbird brain has its own pathway for song production and song learning. In some songbirds, such as the canary, the left half of the syrinx and its higher control centers contribute a majority of song syllables, as determined by unilateral denervation 24, unilateral destruction of the HVC ~, or unilateral bronchus plugging31. In the catbird (Dumetella carolinensis) and brown thrasher (Toxostoma rufum), each syringeal half also contributes a unique set of sounds, but the number of different sounds produced by each side is more equally balanced 32. The origin and significance of functional asymmetry in brain pathways for song control - particularly as it relates to learning - remains a mystery. However, there are indications that both sides of the songbird brain perceive sounds differently17. This material seems ripe for further experimentation.
Projection neurons and learning The HVC consists of at least two different types of neurons: those that project to area X (large), and those that project to the RA (small) 3~. Whereas most of the X-projecting cells are formed before hatching, most of the RA-projecting cells are generated later 9. It is of particular interest that large numbers of RAprojecting cells are produced during the very time when young canaries and zebra finches learn their song s'9. This raises the possibility that the generation, migration and differentiation of neurons projecting from the HVC to the RA might be influenced by the auditory and motor events that are part of vocal learning. Many new neurons continue to be added to the HVC of adult canaries 34. Intracellular recordings from such cells show that some of them respond to sound; this is clear evidence of their incorporation into existing circuits 35. Contrary to an earlier report 33, a majority of the HVC neurons formed in adult male canaries are projection neurons that link the center to the RA 36'37. Since the size of the HVC does not increase in adulthood38'39, and since the percentage of the cells that project from it to the RA changes little between the ages of one year and four years 36, the new RA-projecting neurons probably replace older ones of the same kind. This replacement seems to be particularly brisk during late summer, when adult canaries acquire new songs 36. The new RA-projecting neurons 'born' in late summer remain in place for at least eight months, until the following breeding season 37. This would be expected if the new cells became part of the motor circuits that mastered new songs. New neurons might also be added to area X of adult canaries, but this phenomenon has not yet been studied in detail (Nottebohm, F., unpublished observations). TINS, VoL 14, No. 5, 1991
Hormonal changes can induce dendritic growth, synaptogenesis and changes in synaptic anatomy in the RA of adult canaries 2s'4°'41. If anatomical changes of this magnitude provided sufficient plasticity to bring about successive behavioral modifications, why would neurons need to be replaced? There is no precedent for the replacement of neurons deep inside the brain of healthy individuals. Perhaps in some cases neurons, not synapses, are the units of learning. In these cells learning might be the final and irreversible stage in differentiation. If so, the more the HVC engages in learning, the less it will be able to learn thereafter. A way out of this limitation would be to replace old, 'learned' neurons with new ones. In such a hypothetical scenario older information would be dismissed for the sake of acquiring new information. A revolving door system of this kind would make sense if the amount of learning in the HVC were limited by the total number of cells. Although there is no direct evidence of such a causal relationship, two studies have reported that the size of the HVC and the complexity of learned song are correlated 3s'42. The above arguments sought to establish a link between adult neurogenesis and sustained vocal learning. However, adult zebra finches also add new neurons 43, including RA-projecting neurons s'36, to the HVC, though their song remains unchanged 44. Perhaps this center and the efferent pathway for song production play a role in song perception in adult male zebra finches. If new neurons have to be added to a motor pathway to code for new song perceptual memories, then the distinction between what is a motor memory and what is a perceptual memory has been blurred. Interestingly, if RA-projecting neurons are replaced without changes in song, then the motor memory for learned song might be in the RA; this might also be guessed from the fact that both the direct and recursive paths converge there.
Song perception and song production The response of HVC neurons to sound is biased in adulthood in favor of a bird's own song ] 1, which might provide a reference point against which all other songs are measured. However, it is not known when this bias first appears. Interestingly, the response is stronger to the bird's own song than to the external model by which the bird had been tutored 45'46. This suggests that, at the level of the HVC at least, inputs are more likely to be measured against production standards than against external models. Other experiments also suggest that the HVC plays a role in song perception. (1) Adult female canaries in reproductive condition respond to canary song by adopting a copulation posture. However, if the HVC is lesioned bilaterally, they also respond in this manner to the song of other species 47. (2) Adult male zebra finches with bilateral lesions of the HVC take longer to master a discrimination between conspecific songs than do intact birds (Cynx, J. and Nottebohm, F., unpublished observations). (3) Female zebra finches, which have a very small HVC and which lack the connection between it and the RA, take more trials to discriminate between conspecific songs than males 17. Responses in the HVC to sound do not stop there, but are transmitted to the RA and the nXIIts, from where sound-induced activity is conveyed to the muscles of the syrinx 12. We do not know whether the TIN& Vol. 14, No. 5, 1991
,LOnset of tone burst I
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lateral MAN 20ms Fig. 2. Auditory responses in the zebra finch song system. Each trace represents the response to a tone burst as recorded extrace//u/ar/y within a song system nucleus, characterized by name. The recordings are arranged in the order of increasing latency from the stimulus onset. These recordings were obtained from several birds under anesthesia and are representative of the relative latencies seen in all recordings. Abbreviations: DLM, media/portion of the dorso/atera/ tha/amic nucleus; HVC, high vocal center; LMAN, lateral magnoce//u/ar nucleus of the anterior neostriatum; N/f, nucleus interface; RA, robust nucleus of the archistriatum; nXI/ts, pars tracheosyringea/is of the hypog/ossa/ nucleus; NX//ts, tracheosyringea/ branch of the hypoglossus nerve (same as ts nerve in Fig. 1). (Taken, with permission, from Ref. 21.)
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recursive loop affects this progression. The latency of sound responses increases in the following order: field L < Nil < HVC < RA < nXIIts < area X < DLM < LMAN (Fig. 2), suggesting that the sound responses recorded from the nXIIts descend directly from the HVC to the RA and from the RA to the nXIIts. Playback of different song components selectively activates different clusters of motor cells in nXIIts 12. This apparent conversion of auditory input to gestural information could affect the perception of conspecific sounds, as suggested by the motor theory of speech perception 15. Perhaps birds, like humans, perceive conspecific sounds in a self-centered manner, colored by each individual's vocal skills. If so, then communication among members of a local population must integrate these perceptual idiosyncrasies. The vocal dialects of birds and humans might have evolved to share both a system of signals and meanings, and also a system of perceptions. A need for shared perceptions might also be the reason why some birds learn to produce many more songs than they end up using4s. The original, larger repertoire might help them to discriminate among other conspecifics. If these speculations are proved to be correct, then we might have to reevaluate the origins of vocal learning. Rigid vocal ontogenies might have been relaxed, not just to generate new sounds, but also to generate new perceptual subtleties. If auditory and motor activity share pathways, not only in adulthood but also during development, then auditory experience might influence the ontogeny of brain pathways for producing learned vocalizations. It was mentioned earlier that HVC neurons that project to the RA are 'born' during development, when young zebra finches and canaries first learn their song&9. The addition of these cells and the formation of connections throughout the motor pathways for song control might be regulated directly by auditory experience. Deafening after exposure to a model, but before conversion to a learned vocal score, might negate the effects of the auditory experience by (1) preventing the use of auditory feedback to match the model ~, (2) affecting the survival of cells and connections already in place, or (3) affecting the recruitment of new cells and connections. All three effects could occur and interact.
Stapedius muscle and origins of vocal learning Vocal learning has been studied mostly in birds that imitate sounds, but a recent discovery suggests that the first step towards vocal learning might have had little to do with vocal imitation, Roosters, (Gallus gallus) develop normal crowing without access to auditory feedback49, yet elimination of the middle ear stapedius muscle early in ontogeny shifts the emphasis of crowing from a lower to a higher harmonic 5°. The stapedius muscle dampens the response of the avian middle ear to loud, low frequencies of selfproduced vocalizations51. In the absence of the stapedius muscle, a young rooster shifts the energy of crowing from the first to the second harmonic, thus making up for the lack of middle ear dampening. Other species, such as the zebra finch, can regulate and imitate patterns of harmonic emphasis s2 as part of a broad, vocal-learning ability. The ability to modify vocal sounds by reference to 210
auditory feedback might have arisen as a mechanism to protect an animal's cochlear cells. A system that is sensitive to faint sounds will be damaged by very loud sounds. Signals such as birdsong and the song of some cetaceans, which have evolved to have an effect over long distances, are loud at source and include low frequencies. In extreme cases of signal loudness, vocal production and middle ear dampening might have to interact to keep sound production within a safe range of frequency amplitude. A first step towards the evolution of vocal learning might have taken place in animals that used vocal sounds to communicate over long distances, and that also depended on their hearing to detect danger or find food. In some of these animals, the dampening at source of some harmonics to preserve cochlear sensitivity might have introduced a new, auditorily guided vocal flexibility that then became available for influencing more effectively the behavior of conspecifics - perhaps by producing the sounds of dominance53, or nearness 54, or many55, or merely sounds more pleasing to the ear56t The same auditory-vocal connection might also have been used to better perceive the signals of other conspecifics, which would now elicit, not just an auditory response, but also an internalized vocal gesture. Presumably these dual pressures to better perceive and better manipulate57 other members of a species remain with us and have shaped all instances of vocal learning, including vocal imitation. Thus, the roots of vocal learning, the most momentous breakthrough in animal communication, might be found in a modest brainstem reflex. It will be fascinating to uncover how this reflex evolved into a function of the forebrain as we now know it.
Selected references 1 Konishi, M. (1965) Z. Tierpsychol. 22, 770-783 2 Nottebohm, F., Stokes, T. M. and Leonard, C. M. (1976) J. Comp. Neurol. 165, 457-486 3 Nottebohm, F., Kelley, D. B. and Paton, J. A. (1982) J. Comp. Neurol. 207, 344-357 4 0 k u h a t a , S. and Saito, N (1987) Brain Res. Bull. 18, 35-44 5 13ottjer, S. W., Ha}sema, K. A., Brown, S. A. and Miesner, E. A. (1989) J. Comp. Neurol. 279, 312-326 6 Nottebohm, F. (1980) in Progress in Psychobiology and Physiological Psychology (Vol. 9) (Sprage, J. M. S. and Epstein, A. N. E., eds), pp. 85-124, Academic Press 7 Konishi, M. and Akutagawa, E. (1985) Nature315, 145-147 8 Nordeen, K. W. and Nordeen, E. J. (1988) Nature 334, 149-151 9 Alvarez-13uylla, A., Theelen, M. and Nottebohm, F. (1988) Proc. Natl Acad. Sci. USA 85, 8722-8726 10 Katz, L. C. and Gurney, M. E. (1981) Brain Res. 221,192-197 11 Margoliash, D. (1983)J. Neurosci. 3, 1039-1057 12 Williams, H. and Nottebohm, F. (1985) Science 229, 279-282 13 Marler, P. (1970) Am. Sci. 58, 669-673 14 Hinde, R. A. (1958)Anim. Behav. 6, 211-218 15 Liberman, A. M., Cooper, F. S., Shankweiler, D. and Stucldert-Kennedy, M. (1967) Psychol. Rev. 74, 431-461 16 Ojemann, G. and Mateer, C (1979) Science205, 1401-1403 17 Nottebohm, F. et aL (1990) Philos. Trans. R. Soc. London Ser. B 329, 115-124 18 Kelley, D. 13.and Nottebohm, F. (1979) J. Comp. NeuroL 183, 455-470 19 Simpson, H. 13. and Vicario, D. (1990) J. Neurosci. 10, 1541-1556 20 McCasland, J. S. (1987) J. Neurosci. 7, 23-39 21 Williams, H. (1989) Ann. NYAcad. Sci. 563, 148-164 22 Vicario, D. S. and Nottebohm, F. (1988) J. Comp. NeuroL 271,346-354 23 Nottebohm, F. (1971) J. Exp. Zoo/. 177, 229-261 24 Nottebohm, F. and Nottebohm, M. E. (1976) J. Comp.
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Physiol. A 108, 171-192 25 Bottjer, S. W., Miesner, E. A. and Arnold, A. P. (1984) Science 224, 901-903 26 Scharff, C. and Nottebohm, F. (1989) Soc. Neurosci. Abstr. 15, 618 27 Sohrabji, F., Nordeen, E. J. and Nordeen, K. W. (1990) Behav, Neural Biol. 53, 51-63 28 Canady, R. A., Burd, G. D., DeVoogd, T. J. and Nottebohm, F. (1988)J. Neurosci. 8, 3770-3784 29 Nottebohm, F. and Nottebohm, M. E. (1978) Z. Tierpsychol. 46, 298-305 30 Nottebohm, F., Nottebohm, M. E., Crane, L. A. and Wingfield, J. C. (1987) Behav. Neural Biol. 47, 197-411 31 Hartley, R. S. and Suthers, R. A. (1990) J. Neurobiol. 22, 1236-1248 32 Suthers, R. A. (1990) Nature 347, 473-477 33 Paton, J. A., O'Loughlin, B. and Nottebohm, F. (1985) J. Neurosci. 5, 3088-3093 34 Goldman, S. A. and Nottebohm, F. (1983) Proc. NatlAcad. Sci. USA 80, 2390-2394 35 Paton, J. A. and Nottebohm, F. (1984) Science 225, 1046-1048 36 Alvarez-Buylla, A., Kirn, J. R. and Nottebohm, F. (1990) Science 249, 1444-1446 37 Kirn, J. R., Alvarez-Buylla, A. and Nottebohm, F. J. Neurosd. (in press) 38 Nottebohm, F., Kasparian, S. and Pandazis C. (1981) Brain Res. 213, 99-109
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Deducing Function from Structure (Vol. 2). Information Processing in the Retina by Fritiof S. Sjostrand, Academic Press, 1990. $69.95 (xi + 233 pages) ISBN 0 126 47656 X
This is a tale of one man's obsession with a big idea: the notion that a minutely detailed examination of the ultrastructure of retinal synapses would provide great insight into how the outer retina processes visual information. A tendency to attribute functional meaning to every detail of the observed microanatomy led Sj6strand to reject currently held views of the different functional roles of rods and cones in the retina, of the mechanism of lateral inhibition, and of the way in which information passes from photoreceptors to ON bipolar cells. Such refreshing iconoclasm would be warmly welcomed if it were based on convincing evidence: unfortunately it was not and, as Sj6strand records, granting agencies stopped supporting his work. In broad terms, information processing by the outer retina is well understood. Light is converted into a change of membrane potential by rods and cones, rods being more sensitive but providing poorer temporal TIN& Vol. 14, No. 5, 1991
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39 Gahr, M. (1990) J. Comp. NeuroL 294, 30-36 40 DeVoogd, T. and Nottebohm, F. (1981) Science 214, 202-204 41 DeVoogd, T., Nixdorf, B. and Nottebohm, F. (1985) Brain Res. 329, 304-308 42 Canady, R. A., Kroodsma, D. E. and Nottebohm, F. (1984) Proc. Natl Acad. Sci. USA 81, 6232-6234 43 Nottebohm, F. (1984) Condor 86, 227-236 44 Immelmann, K, (1969) in Bird Vocalizations (Hinde, R. A., ed.), pp. 61-74, Cambridge University Press 45 Margoliash, D. and Konishi, M. (1985) Proc. NatlAcad. Sci. USA 82, 5997-6000 46 Margoliash, D. (1986)J. Neurosci. 6, 1643-1661 47 Brenowitz, E. (1991) Science 251,303-305 48 Marler, P. and Peters, S. (1981) Science 213,780-782 49 Konishi, M. (1963) Z. Tierpsychol. 20, 349-367 50 Grassi,S., Ottaviani, F. and Bambagioni, D. (1990) Brain Res. 529, 158-164 51 Borg, E. and Counter, S. A. (1989) Sci. Am. 261, 74-80 52 Williams, H., Cynx, J. and Nottebohm, F. (1989) J. Comp. PsychoL 103,366-380 53 King, A. P. and West, M. J. (1977) Nature 305, 704-706 54 Morton, E. G. (1986) Behaviour 99, 65-86 55 Krebs, J. R. (1976) Behav, EcoL Sociobiol. 1,215-227 56 Ryan, M. J., Fox, J. H., Wilczynski, W. and Rand, S. (1990) Nature 343, 66-67 57 Krebs,J. R. and Dawkins, R. (1984) in BehavioralEcology, an Evolutionary Approach, pp. 380-402, SinauerAssociates
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resolution than cones. Visual information is then passed from the photoreceptors to two types of bipolar cell (ON and OFF cells, which are depolarized and hyperpolarized, respectively, by light falling in the centre of their receptive fields), which in turn send information on to the inner retina and hence to the brain. In addition, information flows laterally across the outer retina through a pathway from photoreceptors to bipolar cells via horizontal cells. This pathway generates an antagonistic surround to the bipolar cell receptive field, and thus mediates lateral inhibition in the outer retina. This description of outer retinal function is based on a combination of electrophysiological recording of the cells' light responses and anatomical investigation of the synaptic connections of the cells. Sj~strand's approach was to carry out a three-dimensional reconstruction (from electron microscope pictures) of all the cell processes in an area of retina, to build models of these processes, and then to try to deduce the function of the tissue from the details of the microanatomy. The details of the reconstruction process, and the precise relative positions of the cell processes in the retinal areas reconstructed, are described in overwhelming detail in this book. Put charitably,
III III III Sj6strand does not believe in briefly summarizing the evidence essential for making his points. He prefers to give the reader every available piece of data. This extensive description of his work may be valuable for showing the kind of complexity in the arrangement of the cells that exists at a microanatomical level. Furthermore, many of his models of cell processes (shown as photographs in the book) are aesthetically pleasing in themselves, having more than a passing resemblance to the sculptures of Henry Moore. However, Sj6strand never raises the obvious question of whether microanatomical complexity (for example, the fact that the bipolar cell processes receiving synapses from rods and cones are of different sizes) must reflect the way in which information is processed, or whether it is simply a consequence of the developmental programme needed to specify how the neurones must grow in order to make the necessary connections between them. Some of Sj6strand's disagreements with current views of retinal function are based on a disregard of existing electrophysiological evidence. Thus, when rejecting the notion that cones have a higher threshold and a faster temporal response than rods (Chapter 7), he ignores the fact that these properties
Acknowledgements / thank the N/H, USPHS,and the Mary FlaggterCary Charitable Trust for researchsupport, and my wife, Marta E. Nottebohm, for editorial help and encouragement.
books David Attwell Department of Physiolo~7, University College London, London WC1E6BT, UK.
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