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Günther K. H. Zupanc (2010), Scholarpedia, 5(10):5306. doi:10.4249/scholarpedia.5306 revision #148547 [link to/cite this article]
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Curator: Günther K. H. Zupanc

Neuroethology refers to the study of the neural basis of natural behavior in animals. It attempts to understand how sensory organs and central structures process behaviorally relevant stimuli, and how this information is integrated by the central nervous system to produce the behavioral output observed under natural conditions. Many of the concepts and techniques of neuroethology are derived from other biological disciplines, including ethology, neurophysiology, neuroanatomy, neuroendocrinology, and biological cybernetics. A characteristic overall goal of neuroethology is to understand, from mechanistic and evolutionary points of view, both specialization and diversity of neural control among different species.


History and key principles

Neuroethology is a multidisciplinary area of study that emerged as an independent scientific discipline in the 1970s and 1980s. This rather late development contrasts with the history of its two foundation disciplines, neurobiology and ethology. The beginnings of modern neurobiology can be dated back to the end of the nineteenth century after the histological studies of Santiago Ramón y Cajal (1852-1934) had provided experimental evidence in favor of the cell theory as an adequate description of the organization of the nervous system. Ethology was formally established between the 1930s and 1950s, particularly through the work of Konrad Lorenz (1903-1989) and Niko Tinbergen (1907-1988).

One reason for the late development of neuroethology lies in the lack of proper methodology and suitable model systems. Traditionally, neurobiologists have worked on anesthetized animals, or isolated parts of nervous tissue, or even single cells. The species is typically chosen based on technical considerations, such as the ease by which a favorable preparation can be obtained. For example, the classical investigations in the late 1940s and early 1950s of Alan Lloyd Hodgkin (1914-1998) and Andrew Fielding Huxley (born 1917) of the physicochemical factors that define the resting potential of neurons, their excitation, and the generation and propagation of the action potential, were possible only by using preparations of particularly large, and readily accessible, axons, such as the squid giant axon.

By contrast, ethologists employ a whole-animal approach. Often, they study the behavior of an animal in its natural habitat, avoiding disturbance by the experimenter as much as possible. If investigations in the laboratory are performed, the animal is kept under conditions mimicking those in the natural habitat as closely as possible. Many of the behaviors studied are rather complex, often occurring in the context of social interactions between conspecifics.

Obviously, combination of these two rather diametric approaches has been difficult, and continues to be challenging. For example, to explore the involvement of certain, anatomically defined brain areas in the control of specific behaviors it was reasonable to stimulate neurons of these areas electrically via electrodes implanted in the brain of awake, freely moving animals. This became possible after Walter Rudolf Hess (1881-1973) developed in the late 1920s the focal brain stimulation technique to examine how regions within the diencephalon control vegetative functions in cats. First successful attempts to employ such an approach in an ethological context were made by Franz Huber (born 1925) and Erich von Holst (1908-1962) in the time period between the mid 1950s and early 1960s. Huber had learned the focal brain stimulation technique from Hess, and he applied this approach to the brains of crickets. By stimulation of brain structures in the protocerebrum, he succeeded in eliciting and inhibiting complex behaviors, including calling, courtship, and aggressive songs, and associated motor patterns. Similarly, by stimulation of discrete areas in the hypothalamus of alert chicken Erich von Holst was able to evoke specific, and sometime even quite complex, behavioral patterns, and to study the interactive structure of behavioral motivations.

Besides ethology and neurophysiology, other scientific disciplines eased the birth of neuroethology. In the 1950s, major advances were made in the development of methods to trace neural connections using silver staining of degenerating axons. In the 1970s, these methods were replaced by more powerful techniques based on anterograde and retrograde transport of tracers, enabling neuroethologists to study pathways in the central nervous system involved in neural control of specific behavioral patterns. In the 1960s, the field of chemical neuroanatomy was established with the introduction of the Falck-Hillarp fluorescence method for identification of monoamine neurons. This step was followed in the 1970s and 1980s by novel immunohistochemical approaches based on indirect labeling techniques. These techniques offered, among others, the exciting opportunity to chemically characterize neurons involved in sensory processing of behaviorally relevant information or in the motor control of behavioral output. Other milestones in the historical development of neuroethology included in the 1960s the advent of techniques that allowed investigators to correlate morphological and physiological data by combining intracellular recording and tracer injection techniques.

These breakthroughs in neuroanatomy and neurophysiology were paralleled by the emergence of biological cybernetics. Starting in the 1950s, Bernhard Hassenstein (born 1922) and Werner Reichardt (1924-1992) pioneered the study of information processing and modeling by using the visual system of the beetle Chlorophanus, and later particularly the housefly Musca, as model systems. Based on experimental behavioral data, Hassenstein, Reichardt and others developed computational models that produced the observed behavioral output after sensory stimulation. Non-trivial predictions inferred from these models could be tested in experiments incorporating behavioral, neuroanatomical, neurophysiological, and computational approaches. A milestone of this work was the development of the Reichardt correlator, a autocorrelation scheme that made predictions about the algorithm employed by visual systems to detect motion. This and other models had a major influence on computational studies in neuroethology, with applications reaching as far as the design of integrated circuits modeled after neural networks.

An important step toward the establishment of neuroethology as an independent discipline was the focus on rather simple behaviors. However, especially in the early stages of neuroethology, these behaviors were often part of vegetative functions, instead of being displayed in a social context, so that they were largely ignored by ethologists. For example, neuroethologists have intensively studied rhythmic movements of internal organs such as the crustacean foregut and heart. Although few ethologists would attend to such motor activities, their study has provided valuable insights into a number of important neurobiological phenomena, such as central pattern generators and neuromodulation.

As a rough guide, the major questions of neuroethology focus on the neural basis of (i) identification of a behaviorally relevant stimulus; (ii) localization of such a stimulus in space; (iii) motivation underlying a specific behavior; (iv) generation of a behavioral pattern; and (v) modulation of a neural circuit mediating a stimulus-response. Such modulations are defined, among other factors, by the endocrine status of the animal and include the formation of memory. In this context, specific questions are addressed, including those regarding the mode of neural information processing (parallel distributed versus interactive versus convergent; cf. Bullock 1999) and the behavioral consequences of structural dynamics in neural networks, as they may result from the generation of new neurons in the adult central nervous system; cf. Zupanc, 2006).

Choice of suitable model systems

As in many other biological disciplines, neuroethological research crucially depends on the choice of suitable model systems. Ideally, the behavior under scrutiny should be simple, robust, readily accessible, and ethologically relevant. Thus, such behaviors are exhibited not only under natural conditions, but they can also be evoked without much difficulty, and even on repeated occasions, upon presentation of an adequate stimulus under standardized laboratory conditions. Furthermore, these behavioral patterns are clearly defined so that quantitative analysis is possible. The animal displaying such behaviors should be inexpensive and suitable for maintenance and breeding in the laboratory. Furthermore, the neural network underlying the behavior should be relatively simple in the sense that the nervous system consists of a rather small number of neurons, representing a minimal number of different classes of nerve cells.

Because of the difficulty of obtaining neurophysiological recordings from moving animals, often the only way to monitor the neural activity associated with the perception of sensory stimuli relevant for eliciting a given behavior, or with the generation of the corresponding motor activity, is to employ reduced preparations. Such preparations can be obtained by removing muscles or, most commonly, by immobilizing the animal through blocking synaptic transmission at the neuromuscular junction. Immobilized awake animals can still perceive and process sensory stimuli, and may still be able to generate the neural activity associated with the production of the motor action. These fictive behaviors approximate the real behavior and can be measured with relative ease. For example, tadpoles of the clawed-toad (Xenopus laevis) produce a well-characterized behavior called escape swimming upon sensory stimulation during the first day after hatching. The neural activity of the circuitry in the spinal cord that controls this behavior can be studied in animals that are immobilized by blocking synaptic transmission at the neuromuscular junction with alpha-bungarotoxin (a constituent protein of the venom of the Southeast Asian Krait, Bungarus multicinctus). The study of such fictive swimming in tadpoles has enabled investigators to identify universal mechanisms that control rhythmic motor patterns in vertebrates.

Classical model systems in neuroethology

In contrast to biomedically oriented disciplines, which typically focus on a few model organisms, neuroethology is distinguished by the diversity of taxa studied. The wealth of data obtained through investigations that ask similar questions but are conducted in different species offers the opportunity to examine evolutionary aspects by employing a comparative approach. For example, in gastropod molluscs, similarities and differences in feeding behavior among different species have been linked to anatomical, physiological, and pharmacological properties of the underlying neural network (Elliott and Susswein, 2002). Neuroethological investigations in African mormyrid fishes have examined the role of sexual signal evolution in relation to morphological and ecological divergence during species radiation (Arnegard et al., 2010). Comparative studies in weakly electric fishes have provided the basis for a phylogenetic comparison of neural systems specialized for time coding (Kawasaki, 2009).

The following brief description of four classical model systems aims at exemplifying neuroethological research.

  • Recognition of prey and predators in toads. This was one of the first major neuroethological research endeavors, led by Jörg-Peter Ewert in the 1960s. It was aimed at the question whether there are neurons that respond selectively to specific features of prey- or predator-like stimuli (so-called feature detectors). By combination of behavioral and physiological experiments, neurons were found in the thalamic-pretectum and the optic tectum, each of which receives visual input from retinal ganglion cells. A specific subpopulation of neurons in the thalamic-pretectum responds best to predator-like features, and electrical stimulation of this area activates escape behavior. On the other hand, a specific subpopulation of neurons in the optic tectum responds best to prey-like features, and stimulation of the brain region evokes prey-catching behavior in toads. Applying a sophisticated method, records of action potentials from freely moving toads showed that the efficiency in prey detection and predator detection are ensured by pretecto-tectal inhibitory interactions. After lesioning pretectal connections to the optic tectum, both prey-selective neurons (recorded by a microelectrode) and prey-catching behavior were disinhibited. After such treatment, these neurons can be activated by any moving object, including predator-like stimuli. For reviews, see Ewert (1980, 1997).
  • The neural basis of acoustic communication in crickets. In crickets, communication is largely carried by acoustic signals that are produced by males and transmitted to females or other males. Calling songs, for example, are generated to attract sexually receptive females. A female cricket that is in the state of copulatory readiness responds to these songs by flying or walking toward the source of sound, until she reaches the male (positive phonotaxis). Behavioral experiments have shown that the phonotactic response of female crickets is best elicited by a sound of the carrier frequency and the syllable rate matching those of natural songs produced by the male. This behavioral preference to certain sound parameters is reflected by the tuning to the carrier frequency of the tympanal membrane of the cricket's ear, and an optimal response of certain auditory interneurons to syllable repetition rates in the range that best elicits phonotaxis in females in behavioral tests. These neurons evidently function as recognition neurons. For reviews, see Huber (1990); Gerhardt and Huber (2002).
  • The jamming avoidance response of the weakly electric fish of the genus Eigenmannia. A central theme of neuroethology is based on the question of how sensory information is integrated with motor programs to produce a specific, ethologically relevant behavior in response to an adequate stimulus. The first behavior for which a comprehensive answer to this question could be provided was the jamming avoidance response of the weakly electric fish Eigenmannia sp. This behavior consists of shifting the frequency of the fish’s electric-organ discharge away from the neighbor’s frequency to avoid ‘jamming’, which would impair the fish’s ability to electrolocate objects in its vicinity. Using this model system, it has been possible to identify the entire neural chain underlying this behavior — from the sensory receptors to the effector organ and including the major behavioral and neural rules that govern the sensory processing and the generation of the behavioral output. An important discovery made in the course of the investigations was that different physical parameters of the external electric stimulus triggering the jamming avoidance response are, at lower levels of central processing, analyzed separately (parallel processing), but converge at higher brain levels. For reviews, see Heiligenberg (1991); Metzner (1999).
  • Neuromodulation of the stomatogastric ganglion of decapod crustaceans. Neural networks are rarely static. Instead, they often exhibit the potential for neural plasticity. This phenomenon forms the basis for behavioral plasticity. Endogenous control of plastic changes in behavior is evident in cases in which stimuli arising from the environment are held constant. The mechanisms that mediate such changes have been studied in great detail in the stomatogastric ganglion of decapod crustaceans. Using this model system, it has been shown that the mode of function of the ganglion is determined by the actual modulatory environment — the anatomical network provides only a physical backbone upon which neuromodulators, particularly neuropeptides and monoamines, can operate. This makes it possible that a single neural network can produce multiple variations in behavioral output under different conditions. For the latter concept, Peter Getting and Michael Dekin coined the term polymorphic network. For reviews, see Getting (1989); Harris-Warrick and Marder (1991); Marder and Calabrese (1996).


Neuroethology has its roots in a variety of disciplines, including ethology, neurophysiology, neuroanatomy, and biological cybernetics. Its future growth will crucially depend on its ability to further integrate ideas and techniques from other areas of research. It is quite safe to predict that among the disciplines that are likely to have a major influence on neuroethology over the coming years molecular biology and genetics will play a particularly prominent role. The power of these two disciplines has already been demonstrated, for example through the success in the identification and cloning of clock genes in the fruit fly, Drosophila melanogaster (Konopka and Benzer, 1971). Mutations in these genes result in severe disturbances in rhythmic behaviors.

Recent advances in molecular biology have included the sequencing of the complete genome of one of the major neuroethological model systems, the zebra finch, Taeniopygia guttata (Warren et al., 2010). It is likely that information on the genome of other neuroethological model systems will also become available over the next few years. This information, together with the collection of specific tools derived from such genomes, will provide neuroethologists with unprecedented opportunities to study relationships between genes, brains, and behavior, and analyze the data from an evolutionary point of view.


The first textbook of neuroethology was Neuro-Ethologie: Einführung in die neurophysiologischen Grundlagen des Verhaltens by Jörg-Peter Ewert, published in German by Springer-Verlag (Berlin/Heidelberg/New York) in 1976. An English edition entitled Neuroethology: An Introduction to the Neurophysiological Fundamentals of Behavior appeared in 1980. The second textbook was Neuroethology: Nerve Cells and the Natural Behavior of Animals by Jeffrey M. Camhi, published by Sinauer (Sunderland/Massachusetts) in 1984. Both texts were important steps toward the formal establishment of neuroethology as an independent discipline.

Currently, two major textbooks are available for teaching neuroethology courses at the undergraduate and/or graduate level:

  • Thomas J. Carew: Behavioral Neurobiology: The Cellular Organization of Natural Behavior. ISBN 0-87893-092-2. Sinauer, Sunderland, Massachusetts (2000)
  • Günther K.H. Zupanc: Behavioral Neurobiology: An Integrative Approach. Second Edition. Foreword by Theodore H. Bullock. ISBN 978-0-19-920830-2. Oxford University Press, Oxford/New York (2010)
Figure 1: Neuroethology textbooks. From left, Ewert, Neuro-Ethologie: Einführung in die neurophysiologischen Grundlagen des Verhaltens; Camhi, Neuroethology: Nerve Cells and the Natural Behavior of Animals; Carew, Behavioral Neurobiology: The Cellular Organization of Natural Behavior; Zupanc, Behavioral Neurobiology: An Integrative Approach (Second Edition)


At present, there is no journal on the market that is exclusively devoted to the publication of neuroethological research. Instead, articles appear in a large number of scientific journals in the wider fields of animal behavior and neurosciences. The two journals that have, arguably, played the most important role in the publication of research papers in the field of neuroethology are:

  • Brain, Behavior and Evolution, edited by Georg F. Striedter, and published by S. Karger, Basel (Switzerland)
  • Journal of Comparative Physiology-A, edited by Friedrich G. Barth, Kentaro Arikawa, John G. Hildebrand, Peter N. Narins, Hans-Joachim Pflüger, and Günther K.H. Zupanc, and published by Springer-Verlag, Berlin/Heidelberg (Germany)

Professional Society and International Meetings

The professional society devoted to the promotion of neuroethology is the International Society for Neuroethology (ISN). It was founded during a NATO-sponsored Advanced Study Institutes meeting (organized by Jörg-Peter Ewert, Robert R. Capranica, and David J. Ingle) on Advances in Vertebrate Neuroethology in Kassel (Germany) in 1981. First president of the ISN was Theodore H. Bullock. Its first congress, organized by Kiyoshi Aoki, was held in Tokyo (Japan) in 1986. Since then, meetings took place in Berlin, Germany (1989), Montréal, Canada (1992), Cambridge, United Kingdom (1995), San Diego, United States (1998), Bonn, Germany (2001), Nyborg, Denmark (2004), Vancouver, Canada (2007), Salamanca, Spain (2010), College Park, Maryland, USA (2012). The next congress will be held in 2014 in Sapporo, Japan.

In addition to a number of topic-specific or regional meetings and workshops, a second important forum for exchange of ideas among neuroethologists has been provided by the Neuroethology: Behavior, Evolution & Neurobiology Gordon Research Conferences. The next conference will be held in 2013 in Mount Snow, VT [1].


  • Arnegard, M.E., McIntyre, P.B., Harmon, L.J., Zelditch, M.L., Crampton, W.G., Davis, J.K., Sullivan, J.P., Lavoué, S., and Hopkins, C.D. (2010) Sexual signal evolution outpaces ecological divergence during electric fish species radiation. American Naturalist, 176, 335-356.
  • Arshavsky, Y.I., Orlovsky, G.N., Panchin, Y.V., Roberts, A., and Soffe, S.R. (1993) Neuronal control of swimming locomotion: analysis of the pteropod mollusc Clione and embryos of the amphibian Xenopus. Trends in Neurosciences, 16, 227-233.
  • Bullock, T.H. (1999) Neuroethology has pregnant agendas. Journal of Comparative Physiology A, 185, 291-295.
  • Egelhaaf, M., Hausen, K., Reichardt, W., and Wehrhahn, C. (1988) Visual course control in flies relies on neuronal computation of object and background motion. Trends in Neurosciences, 11, 351-358.
  • Elliott, C.J., and Susswein, A.J. (2002) Comparative neuroethology of feeding control in molluscs. Journal of Experimental Biology, 205, 877-896.
  • Ewert, J.-P. (1980) Neuroethology: An Introduction to the Neurophysiological Fundamentals of Behavior. Springer-Verlag, Berlin/Heidelberg/New York.
  • Ewert, J.-P. (1997) Neural correlates of key stimulus and releasing mechanisms: a case study and two concepts. Trends in Neurosciences, 20, 332-339.
  • Gerhardt, H.C., and Huber, F. (2002) Acoustic Communication in Insects and Anurans: Common Problems and Diverse Solutions. University of Chicago Press, Chicago.
  • Getting, P.A. (1989) Emerging principles governing the operation of neural networks. Annual Reviews in Neuroscience, 12, 185-204.
  • Harris-Warrick, R.M., and Marder, E. (1991) Modulation of neural networks for behavior. Annual Review of Neurosciences, 14, 39-57.
  • Heiligenberg, W. (1991) Neural Nets in Electric Fish. MIT Press, Cambridge, Massachusetts.
  • Huber, F. (1962) Central nervous control of sound production in crickets and some speculations on its evolution. Evolution, 16, 429-442.
  • Huber, F. (1990) Cricket neuroethology: neuronal basis of intraspecific acoustic communication. Advances in the Study of Behavior, 19, 299-356.
  • Kawasaki M. (2009) Evolution of time-coding systems in weakly electric fishes. Zoological Science, 26, 587-599.
  • Konopka, R.J., and Benzer, S. (1971) Clock mutants of Drosophila melanogaster. Proceedings of the National Academy of Sciences U.S.A., 68, 2112-2116.
  • Marder, E., and Calabrese, R.L. (1996) Principles of rhythmic motor pattern generation. Physiological Reviews, 76, 687-717.
  • Metzner, W. (1999) Neural circuitry for communication and jamming avoidance in gymnotiform fish. Journal of Experimental Biology, 202, 1365-1375.
  • Pflüger, H.-J., and Menzel, R. (1999) Neuroethology, its roots and future. Journal of Comparative Physiology A, 185, 389-392.
  • Warren, W.C., Clayton, D.F., Ellegren, H., Arnold, A.P., Hillier, L.W., Künstner, A., Searle, S., White, S., Vilella, A.J., Fairley, S., Heger, A., Kong, L., Ponting, C.P., Jarvis, E.D., Mello, C.V., Minx, P., Lovell, P., Velho, T.A., Ferris, M., Balakrishnan, C.N., Sinha, S., Blatti, C., London, S.E., Li, Y., Lin, Y.C., George, J., Sweedler, J., Southey, B., Gunaratne, P., Watson, M., Nam, K., Backström, N., Smeds, L., Nabholz, B., Itoh, Y., Whitney, O., Pfenning, A.R., Howard, J., Völker, M., Skinner, B.M., Griffin, D.K., Ye., L., McLaren, W.M., Flicek, P., Quesada, V., Velasco, G., López-Otín, C., Puente, X.S., Olender, T., Lancet, D., Smit, A.F., Hubley, R., Konkel, M.K., Walker, J.A., Batzer, M.A., Gu, W., Pollock, D.D., Chen, L., Cheng, Z., Eichler, E.E., Stapley, J., Slate, J., Ekblom, R., Birkhead, T., Burke, T., Burt, D., Scharff, C., Adam, I., Richard, H., Sultan, M., Soldatov, A., Lehrach, H., Edwards, S.V., Yang, S.P., Li, X., Graves, T., Fulton, L., Nelson, J., Chinwalla, A., Hou, S., Mardis, E.R., Wilson, R.K. (2010) The genome of a songbird. Nature, 464, 757-762.
  • Zupanc, G.K.H. (2006) Neurogenesis and neuronal regeneration in the adult fish brain. Journal of Comparative Physiology A, 192, 649-670.

Internal references

  • Valentino Braitenberg (2007) Brain. Scholarpedia, 2(11):2918.
  • Clifford Saper (2009) Hypothalamus. Scholarpedia, 4(1):2791.
  • Tamas Freund and Szabolcs Kali (2008) Interneurons. Scholarpedia, 3(9):4720.
  • Howard Eichenbaum (2008) Memory. Scholarpedia, 3(3):1747.
  • Almut Schüz (2008) Neuroanatomy. Scholarpedia, 3(3):3158.
  • Rodolfo Llinas (2008) Neuron. Scholarpedia, 3(8):1490.
  • John Dowling (2007) Retina. Scholarpedia, 2(12):3487.
  • Robert E. Burke (2008) Spinal cord. Scholarpedia, 3(4):1925.

Further reading

  • Zupanc, G.K.H. (2010) Behavioral Neurobiology: An Integrative Approach. Second Edition. Chapters 1 ('Introduction') and 4 ('The study of animal behavior: a brief history'). Oxford University Press, Oxford/New York.

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