Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Insights into neural mechanisms and evolution of behaviour from electric fish

Nature Reviews Neuroscience volume 5, pages 943–951 (2004)Cite this article

Key Points

  • Behaviour and its neural control can be studied at proximate and ultimate levels. Much progress has been made in determining how neural circuits control behavior, but comparatively little is understood about why these particular solutions have arisen. This question can be addressed through comparative studies, aimed at understanding how neural circuits are modified during the evolution of new behaviours. Comparative studies in electrosensory systems provide insights into the neural mechanisms and evolution of behaviour.

  • The jamming avoidance response (JAR) is a behaviour in which fish change their frequency of electric organ discharge (EOD) to increase the difference in frequency between their own EOD and that of a neighbour. The JAR evolved convergently in electric fishes. The algorithm for the control of jamming avoidance behavior is complex, involving concurrent analyses of signal amplitude and timing differences across the receptor array, similar to those that underlie sound localization. Interestingly, this solution seems to have been utilized in at least three independent instances of evolution of this behaviour. The hypothesis that this computation is an ancestral trait is supported by its presence in a family of fishes that have some ancestral features of South American electric fishes, but lack a JAR.

  • These comparative data indicate that concurrent analyses of changes in signal amplitude and timing difference serve diverse functions in electrosensory species, and served as a preadaptation for the evolution of JARs. Analyses of the neural control of JARs strongly support the notion that this type of behaviour has evolved independently several times, and that subtle changes in neural circuitry were sufficient for its evolution.

  • Across three groups of fishes that have independently evolved electrosensory systems — skates, South American and African electric fishes — adaptive cancellation of expected sensory information is mediated by a common plasticity mechanism. First-order central electrosensory neurons gradually become less responsive to electrosensory input that is repeatedly associated in time with motor commands, or reliable correlates of those commands. This cancellation process results from the integration of this afferent input with a modifiable 'negative image' of the expected input. In all three cases, generation of this negative image involves plasticity at the parallel-fibre interface between primary sensory and cerebellar structures.

  • Cerebellar circuits are both phylogenetically very old and highly conserved. It seems that plasticity at parallel fibre synapses has had historic importance for adjusting the gain of neural responses. Because this role of cerebellar circuits predated the evolution of most electrosensory systems, it is likely that this plasticity mechanism served as a preadaptation for the convergent evolution of adaptive cancellation processes in these different electrosensory systems.

  • Together, these comparative findings support the idea that the structural and physiological organization of the nervous system cannot be understood with respect to current function alone; historical factors and the constraints they impose on systems must also be considered. Comparative studies provide an opportunity to study the neural control of behaviour at both the proximate and ultimate levels.

Abstract

Both behaviour and its neural control can be studied at two levels. At the proximate level, we aim to identify the neural circuits that control behaviour and to understand how information is represented and processed in these circuits. Ultimately, however, we are faced with questions of why particular neural solutions have arisen, and what factors govern the ways in which neural circuits are modified during the evolution of new behaviours. Only by integrating these levels of analysis can we fully understand the neural control of behaviour. Recent studies of electrosensory systems show how this synthesis can benefit from the use of tractable systems and comparative studies.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The jamming avoidance response.
Figure 2: Electrosensory circuits.
Figure 3: Adaptive filtering in electrosensory systems.

Similar content being viewed by others

References

  1. Dumont, J. P. C. & Robertson, R. M. Neuronal circuits: an evolutionary perspective. Science 33, 849–853 (1986).

    Google Scholar 

  2. Kavanau, J. L. Conservative behavioural evolution, the neural substrate. Anim. Behav. 39, 758–767 (1990).

    Google Scholar 

  3. Claudio, T., Ballivet, M., Patrick, J. & Heinemann, S. Nucleotide and deduced amino acid sequence of Torpedo californica acetylcholine receptor subunit. Proc. Natl Acad. Sci. USA 80, 1111–1115 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Zakon, H. et al. Plasticity of the electric organ discharge: implications for the regulation of ionic currents. J. Exp. Biol. 202, 1409–1416 (1999).

    CAS  PubMed  Google Scholar 

  5. Heiligenberg, W. in Electroreception (eds Bullock, T. H. & Heiligenberg, W.) 613–649 (Wiley & Sons, New York, 1986).

    Google Scholar 

  6. Heiligenberg, W. Central processing of electrosensory information in gymnotiform fish. J. Exp. Biol. 146, 255–275 (1989).

    CAS  PubMed  Google Scholar 

  7. Heiligenberg, W. Neural Nets in Electric Fish (MIT Press, Cambridge, Massachusetts, 1991). Walter Heiligenberg's full account, to this date, of the progress made towards understanding the neural control of the JAR of Eigenmannia.

    Google Scholar 

  8. Bell, C. C., Bodznick, D., Montgomery, J. & Bastian, J. The generation and subtraction of sensory expectations within cerebellum-like structures. Brain Behav. Evol. 50, 17–31 (1997).

    PubMed  Google Scholar 

  9. Bastian, J. in Electroreception (eds Bullock, T. H. & Heiligenberg, W.) 577–612 (Wiley & Sons, New York, 1986).

    Google Scholar 

  10. Heiligenberg, W. Electrolocation of objects in the electric fish Eigenmannia (Rhamphichthyidae, Gymnotoidei). J. Comp. Physiol. A 77, 1–22 (1973).

    Google Scholar 

  11. Matsubara, J. & Heiligenberg, W. How well do electric fish electrolocate under jamming? J. Comp. Physiol. A 125, 285–290 (1978).

    Google Scholar 

  12. Watanabe, A. & Takeda, K. The change in discharge frequency by AC stimulus in a weakly electric fish. J. Exp. Biol. 40, 57–66 (1963).

    Google Scholar 

  13. Bullock, T., Behrend, K. & Heiligenberg, W. Comparison of the jamming avoidance responses of gymnotoid and gymnarchid electric fish: a case of convergent evolution of behavior and its sensory basis. J. Comp. Physiol. 103, 97–121 (1975).

    Google Scholar 

  14. Rose, G. J. & Fortune, E. S. Mechanisms for generating temporal filters in the electrosensory system. J. Exp. Biol. 202, 1281–1289 (1999).

    CAS  PubMed  Google Scholar 

  15. Fortune, E. S. & Rose, G. J. Short-term synaptic plasticity as a temporal filter. Trends Neurosci. 24, 381–385 (2001).

    CAS  PubMed  Google Scholar 

  16. Alves-Gomez, J. A., Orti, G., Haygood, M., Heiligenberg, W. & Meyer, A. Phylogenetic analysis of the South American electric fishes (order Gymnotiformes) and the evolution of their electrogenic system: a synthesis based on morphology, electrophysiology, and mitochondrial sequence data. Mol. Biol. Evol. 12, 298–318 (1995).

    Google Scholar 

  17. Mago-Leccia, F. Los peces de la familia Sternopygidae de Venezuela. Acta Cient. Venez. 29, 1–89 (1978).

    Google Scholar 

  18. Fink, S. V. & Fink, W. L. in Interrelationships of Fishes (eds Stiassny, M. L. J., Parenti, L. R. & Johnson, G. D.) 209–249 (Academic, San Diego, 1996).

    Google Scholar 

  19. Alves-Gomes, J. A. Systematic biology of gymnotiform and mormyiform electric fishes: phylogenetic relationships. Molecular clocks and rates of evolution in the mitochondrial rRNA genes. J. Exp. Biol. 202, 1167–1183 (1999).

    CAS  PubMed  Google Scholar 

  20. Kawasaki, M. Independently evolved jamming avoidance responses employ identical computational algorithms: a behavioral study of the African electric fish, Gymnarchus niloticus. J. Comp. Physiol. 173, 9–22 (1993). In a remarkable case of convergent evolution, this mormyriform wave-type electric fish was found to use the same algorithm to control its JAR as that used by South American (gymnotiform) fishes. Despite the ability of mormyrids to use corollary discharge information, Gymnarchus does not seem to evaluate foreign signals with respect to its own internal commands to discharge its electric organ.

    CAS  Google Scholar 

  21. Rose, G. J. & Canfield, J. G. Discrimination of the sign of frequency differences by Sternopygus, an electric fish without a jamming avoidance response. J. Comp. Physiol. A 168, 461–467 (1991). Although it lacks a JAR, the gymnotiform wave-type fish Sternopygus can determine whether foreign signals are higher or lower than its own EOD frequency. Experiments involved conditioning electromotor responses. Forward or backward tracking responses, elicited by movement of the surround (unconditioned stimulus), were preceded by the presentation of external signals. After training, forward or backward movements could be elicited by delivery of the appropriate stimulus.

    Google Scholar 

  22. Hopkins, C. D. Neuroethology of electric communication. Annu. Rev. Neurosci. 11, 497–535 (1988).

    CAS  PubMed  Google Scholar 

  23. Hopkins, C. D. Electric communication in the reproductive behavior of Sternopygus macrurus (Gymnotoidei). Z. Tierpsychol. 35, 518–535 (1974).

    CAS  PubMed  Google Scholar 

  24. Rose, G., Keller, C. & Heiligenberg, W. 'Ancestral' neural mechanisms of electrolocation suggest a substrate for the evolution of the jamming avoidance response. J. Comp. Physiol. A 160, 491–500 (1987).

    CAS  PubMed  Google Scholar 

  25. Rose, G. & Heiligenberg, W. Neural coding of difference frequencies in the midbrain of the electric fish Eigenmannia: reading the sense of rotation in an amplitude-phase plane. J. Comp. Physiol. A 158, 613–624 (1986).

    CAS  PubMed  Google Scholar 

  26. Bastian, J. & Yuthas, J. The jamming avoidance response of Eigenmannia: properties of a diencephalic link between sensory processing and motor output. J. Comp. Physiol. A 154, 895–908 (1984). The first study to show that strongly sign-selective neurons could be recorded in the electrosensorius region.

    Google Scholar 

  27. Keller, C. H. Stimulus discrimination in the diencephalon of Eigenmannia: the emergence and sharpening of a sensory filter. J. Comp. Physiol. A 162, 747–757 (1988).

    CAS  PubMed  Google Scholar 

  28. Keller, C. H. & Heiligenberg, W. From distributed sensory processing to discrete motor representations in the diencephalon of the electric fish, Eigenmannia. J. Comp. Physiol. A 164, 565–576 (1989). Glutamate iontophoresis was used to show a simple motor map in the diencephalic electrosensorius complex, in which increases or decreases in the pacemaker frequency could be elicited by stimulating particular regions. This study paved the way for elucidating the premotor pathways involved in the control of the JAR of Eigenmannia.

    CAS  PubMed  Google Scholar 

  29. Keller, C. H., Maler, L. & Heiligenberg, W. Structural and functional organization of a diencephalic sensory-motor interface in the gymnotiform fish, Eigenmannia. J. Comp. Neurol. 293, 347–376 (1990).

    CAS  PubMed  Google Scholar 

  30. Metzner, W. The jamming avoidance response in Eigenmannia is controlled by two separate motor pathways. J. Neurosci. 13, 1862–1878 (1993). Previously, it was thought that JAR-related increases and decreases in the pacemaker frequency were controlled by a single region, the prepacemaker nucleus. This study showed that a second region, the sublemniscal prepacemaker nucleus, is important for controlling frequency decreases.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Metzner, W. Neural circuitry for communication and jamming avoidance in gymnotiform fish. J. Exp. Biol. 202 1365–1375 (1999).

    CAS  PubMed  Google Scholar 

  32. Green, R. L. & Rose, G. J. Structure and function of neurons in the complex of the nucleus electrosensorius of Sternopygus and Eigenmannia: diencephalic substrates for the evolution of the jamming avoidance response. Brain Behav. Evol. 64, 85–103 (2004).

    PubMed  Google Scholar 

  33. Keller, C. H., Kawasaki, M. & Heiligenberg, W. The control of pacemaker modulations for social communication in the weakly electric fish Sternopygus. J. Comp. Physiol. A 169, 441–450 (1991).

    CAS  PubMed  Google Scholar 

  34. Heiligenberg, W., Metzner, W., Wong, C. & Keller, C. Motor control of the jamming avoidance response of Apteronotus leptorhynchus: evolutionary changes of a behavior and its neuronal substrates. J. Comp. Physiol. A 179, 653–674 (1996).

    CAS  PubMed  Google Scholar 

  35. Heiligenberg, W. & Rose, G. Phase and amplitude computations in the midbrain of an electric fish: intracellular studies of neurons participating in the jamming avoidance response of Eigenmannia. J. Neurosci. 5, 515–531 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Kawasaki, M. & Guo, Y. -X. Neuronal circuitry for comparison of timing in the electrosensory lateral line lobe of the African wave-type electric fish Gymnarchus niloticus. J. Neurosci. 16, 380–391 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Matsushita, A. & Kawasaki, M. Unitary giant synapses embracing a single neuron at the convergent site of time-coding pathways of an electric fish, Gymnarchus niloticus. J. Comp. Neurol. 472, 140–155 (2004). This investigation showed that sign-selective neurons are present in the midbrain of this African electric fish. This finding, predicted by behavioural studies, makes the case that concurrent analysis of amplitude and phase difference information served as a preadaptation for the evolution of JARs.

    PubMed  Google Scholar 

  38. von Holst, E. & Mittelstaedt, H. Das reafferenzprinzip. Naturwissenschaften 37, 464–476 (1950).

    Google Scholar 

  39. Bullock, T. H. in Sensory Biology of Aquatic Animals (eds Atema, J., Fay, R. R., Popper, A. N. & Tavolga, W. N.) 269–284 (Springer, New York, 1988).

    Google Scholar 

  40. Zipser, B. & Bennett, M. V. L. Interaction of electrosensory and electromotor signals in lateral line lobe of a mormyrid fish. J. Neurophysiol. 39, 713–721 (1976). The first evidence that mormyrid electric fish use corollary discharge information to evaluate electrosensory information, showing that sensory input was blocked if it was timed to the fish's command to produce an EOD.

    CAS  PubMed  Google Scholar 

  41. Bell, C. C. An efference copy which is modified by reafferent input. Science 214, 450–453 (1981). This study showed that mormyrids can construct a 'negative image' of the expected reafferent (self induced) ampullary-type electrosensory information, and that this 'efference copy' is plastic; it can be modified, based on experience, to precisely cancel the sensory effects of its own electric organ discharges.

    CAS  PubMed  Google Scholar 

  42. Bell, C. C. Properties of a modifiable efference copy in electric fish. J. Neurophysiol. 47, 1043–1056 (1982).

    CAS  PubMed  Google Scholar 

  43. Bell, C. C. Duration of plastic change in a modifiable efference copy. Brain Res. 369, 29–36 (1986).

    CAS  PubMed  Google Scholar 

  44. Bastian, J. Plasticity of feedback inputs in the apteronotid electrosensory system. J. Exp. Biol. 202, 1327–1337 (1999).

    CAS  PubMed  Google Scholar 

  45. New, J. G. & Bodznick, D. Medullary electrosensory processing in the little skate. II. Supression of self-generated electrosensory interference during respiration. J. Comp. Physiol. 167, 295–307 (1990).

    CAS  Google Scholar 

  46. Bodznick, D., Montgomery, J. C. & Bradley, D. J. Suppression of common mode signals within the electrosensory system of the little skate Raja erinacea. J. Exp. Biol. 171, 127–138 (1992).

    Google Scholar 

  47. Bodznick, D. The specificity of an adaptive filter that suppresses unwanted reafference in electrosensory neurons of the skate medulla. Biol. Bull. 185, 312–314 (1993).

    CAS  PubMed  Google Scholar 

  48. Bodznick, D., Montgomery, J. C. & Carey, M. Adaptive mechanisms in the elasmobranch hindbrain. J. Exp. Biol. 202, 1357–1364 (1999).

    CAS  PubMed  Google Scholar 

  49. Bastian, J. Pyramidal cell plasticity in weakly electric fish: a mechanism for attenuating responses to reafferent electrosensory inputs. J. Comp. Physiol. 176, 63–78 (1995).

    CAS  Google Scholar 

  50. Bastian, J. Plasticity in an electrosensory system. I. General features of a dynamic sensory filter. J. Neurophysiol. 76, 2483–2496 (1996).

    CAS  PubMed  Google Scholar 

  51. Conley, R. A. & Bodznick, D. The cerebellar dorsal granular ridge in an elasmobranch has proprioceptive and electroreceptive representations and projects homotopically to the medullary electrosensory nucleus. J. Comp. Physiol. 174, 707–721 (1994).

    CAS  Google Scholar 

  52. Bell, C. C., Han, V. Z., Sugawara, Y. & Grant, K. Synaptic plasticity in the mormyrid electrosensory lobe. J. Exp. Biol. 202, 1339–1347 (1999).

    CAS  PubMed  Google Scholar 

  53. Bastian, J. Plasticity in an electrosensory system. II. Postsynaptic events associated with a dynamic sensory filter. J. Neurophysiol. 76, 2497–2507 (1996).

    CAS  PubMed  Google Scholar 

  54. Carlson, B. A. & Kawasaki, M. Nonlinear response properties of combination-sensitive electrosensory neurons in the midbrain of Gymnarchus niloticus. J. Neurosci. 24, 8039–8048 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Rose, G. J., Kawasaki, M. & Heiligenberg, W. 'Recognition units' at the top of a neuronal hierarchy? J. Comp. Physiol. 162, 759–772 (1988). Extracellular recordings showing that neurons in the prepacemaker nucleus of Eigenmannia code the sign of frequency differences unambiguously; they represent 'negative Df' detectors. These neurons showed selectivity comparable to that of the behaviour. Here, neurons perform the final 'tallying' of the votes cast by the neuronal democracy upstream.

    CAS  Google Scholar 

  56. Chadderton, P., Margrie, T. W. & Hausser, M. Integration of quanta in cerebellar granule cells during sensory processing. Nature 428, 856–857 (2004). The first in vivo intracellular recordings from cerebellar granule cells. Granule cells show little spontaneous activity, can be excited by somatosensory stimulation and generally respond only after temporal summation of at least two EPSPs.

    CAS  PubMed  Google Scholar 

  57. Bass, A. H. in Electroreception (eds Bullock, T. H. & Heiligenberg, W.) 13–70 (Wiley & Sons, New York, 1986).

    Google Scholar 

  58. Assad, C., Rasnow, B. & Stoddard, P. K. Electric organ discharges and electric images during electrolocation. J. Exp. Biol. 202, 1185–1193 (1999).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The author thanks D. Bodznick and M. Kawasaki for helpful comments on an earlier draft of this paper, C. Bell for providing figure materials and E. Fortune and R. Green for their help in constructing this review.

Author information

Authors and Affiliations

  1. Department of Biology, University of Utah, Salt Lake City, 84112-0840, Utah, USA

    Gary J. Rose

Authors
  1. Gary J. Rose
    View author publications

    You can also search for this author in PubMed Google Scholar

Ethics declarations

Competing interests

The author declares no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Rose's laboratory

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rose, G. Insights into neural mechanisms and evolution of behaviour from electric fish. Nat Rev Neurosci 5, 943–951 (2004). https://doi.org/10.1038/nrn1558

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrn1558

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing