Advertisement

Biological Cybernetics

, Volume 103, Issue 2, pp 105–118 | Cite as

Modeling the electric image produced by objects with complex impedance in weakly electric fish

  • Kazuhisa FujitaEmail author
  • Yoshiki Kashimori
Original Paper

Abstract

Weakly electric fish generate an electric field around their body by electric organ discharge (EOD). By measuring the modulation of the electric field produced by an object in the field these fish are able to accurately locate an object. Theoretical and experimental studies have focused on the amplitude modulations of EODs produced by resistive objects. However, little is known about the phase modulations produced by objects with complex impedance. The fish must be able to detect changes in object impedance to discriminate between food and nonfood objects. To investigate the features of electric images produced by objects with complex impedance, we developed a model that can be used to map the electric field around the fish body. The present model allows us to calculate the spatial distribution of the amplitude and phase shift in an electric image. This is the first study to investigate the changes in amplitude and phase shift of electric images induced by objects with complex impedance in wave-type fish. Using the model, we show that the amplitude of the electric image exhibits a sigmoidal change as the capacitance and resistance of an object are increased. Similarly, the phase shift exhibits a significant change within the object capacitance range of 0.1–100 nF. We also show that the spatial distribution of the amplitude and phase shifts of the electric image resembles a “Mexican hat” in shape for varying object distances and sizes. The spatial distribution of the phase shift and the amplitude was dependent on the object distance and size. Changes in the skin capacitance were associated with a tradeoff relationship between the magnitude of the amplitude and phase shift of the electric image. The specific range of skin capacitance (1–100 nF) allows the receptor afferents to extract object features that are relevant to electrolocation. These results provide a useful basis for the study of the neural mechanisms by which weakly electric fish recognize object features such as distance, size, and impedance.

Keywords

Electric image Phase shift Complex impedance Electrolocation Finite-element model 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albeck Y (2003) Sound localization and binoral processing. In: Arbib MA (eds) Handbook of brain theory and neural networks, 2nd edn. MIT Press, Cambridge, pp 1061–1064Google Scholar
  2. Assad C (1997) Electric field maps and boundary element simulations of electrolocation in weakly electric fish. PhD thesis, California Institute of Technology, Pasadena, CAGoogle Scholar
  3. Assad C, Rasnow B, Stoddard PK, Bower JM (1998) The electric organ discharges of the gymnotiform fishes: II. Eigenmannia. J Comp Physiol A 183(4): 419–432CrossRefPubMedGoogle Scholar
  4. Assad C, Rasnow B, Stoddard PK (1999) Electric organ discharges and electric images during electrolocation. J Exp Biol 202(Pt 10): 1185–1193PubMedGoogle Scholar
  5. Babineau D, Longtin A, Lewis JE (2006) Modeling the electric field of weakly electric fish. J Exp Biol 209(Pt 18): 3636–3651CrossRefPubMedGoogle Scholar
  6. Babineau D, Lewis JE, Longtin A (2007) Spatial acuity and prey detection in weakly electric fish. PLoS Comput Biol 3(3): e38CrossRefPubMedGoogle Scholar
  7. Bacher M (1983) A new method for the simulation of electric fields, generated by electric fish, and their distorsions by objects. Biol Cybern 47(1): 51–58PubMedGoogle Scholar
  8. Bass AH (1986) Electric organs revisited: evolution of a vertebrate communication and orientation organ. In: Bullock TH, Heiligenberg W (eds) Electroreception. Wiley, New York, pp 13–70Google Scholar
  9. Bastian J (1986) Electroloaction: behavior, anatomy, and physiology. In: Bullock TH, Heiligenberg W (eds) Electroreception. Wiley, New York, pp 577–612Google Scholar
  10. Bennett MVL (1971) Electric organ. In: Hoar WS, Randall DJ (eds) Fish physiology. Academic, New York, vol .5, pp 347–491Google Scholar
  11. Budelli R, Caputi AA (2000) The electric image in weakly electric fish: perception of objects of complex impedance. J Exp Biol 203(Pt 3): 481–492PubMedGoogle Scholar
  12. Budelli R, Caputi AA, Gomez L, Rother D, Grant K (2002) The electric image in Gnathonemus petersii. J Physiol Paris 96(5–6): 421–429CrossRefPubMedGoogle Scholar
  13. Caputi AA, Budelli R (1995) The electric image in weakly electric fish: I. A data-based model of waveform generation in Gymnotus carapo. J Comput Neurosci 2(2): 131–147CrossRefPubMedGoogle Scholar
  14. Caputi AA, Budelli R, Grant K, Bell CC (1998) The electric image in weakly electric fish: physical images of resistive objects in Gnathonemus petersii. J Exp Biol 201(Pt 14): 2115–2128PubMedGoogle Scholar
  15. Carr CE, Maler L (1986) Electroloaction: central anatomy and physiology. In: Bullock TH, Heiligenberg W (eds) Electroreception. Wiley, New York, pp 319–373Google Scholar
  16. Chen L, House JL, Krahe R, Nelson ME (2005) Modeling signal and background components of electrosensory scenes. J Comp Physiol A 191(4): 331–345CrossRefGoogle Scholar
  17. Dusenbery DB (1992) Sensory ecology: how organisms acquire and respond to information. Freeman, New YorkGoogle Scholar
  18. Fujita K, Kashimori Y (2006) Population coding of electrosensory stimulus in receptor network. Neurocomputing 69(10–12): 1206–1210CrossRefGoogle Scholar
  19. Fujita K, Kashimori Y, Zheng M, Kambara T (2006) A role of synchronicity of neural activity based on dynamic plasticity of synapses in encoding spatiotemporal features of electrosensory stimuli. Math Biosci 201(1–2): 113–124CrossRefPubMedGoogle Scholar
  20. Fujita K, Kashimori Y, Kambara T (2007) Spatiotemporal burst coding for extracting features of spatiotemporally varying stimuli. Biol Cybern 97(4): 293–305CrossRefPubMedGoogle Scholar
  21. Heiligenberg W (1973) Electrolocation of objects in the electric fish Eigenmannia (Rhamphichthytidae gynmotoidei). J Comp Physiol 87: 137–164CrossRefGoogle Scholar
  22. Heiligenberg W (1975) Theoretical and experimental approaches to spatial aspects of electrolocation. J Comp Physiol 103: 247–272CrossRefGoogle Scholar
  23. Heiligenberg W (1991) Neural nets in electric fish. MIT Press, CambridgeGoogle Scholar
  24. Hoshimiya N, Shogen K, Matsuo T, Chichibu S (1980) The Apteronotus EOD field: waveform and EOD field simulation. J Comp Physiol A 135(4): 283–290CrossRefGoogle Scholar
  25. Knudsen EI (1975) Spatial aspects of the electric fields generated by weakly electric fish. J Comp Physiol 99: 103–118CrossRefGoogle Scholar
  26. Konishi M (1993) Listening with two ears. Sci Am 268(4): 66–73CrossRefPubMedGoogle Scholar
  27. Lewis JE, Maler L (2001) Neuronal population codes and the perception of object distance in weakly electric fish. J Neurosci 21(8): 2842–2850PubMedGoogle Scholar
  28. Lissman HW, Machin KE (1958) The mechanism of object location in Gymnarchus niloticus. J Exp Biol 35: 451–486Google Scholar
  29. Marr D (1982) Vision. Freeman, San FranciscoGoogle Scholar
  30. Migliaro A, Caputi AA, Budelli R (2005) Theoretical analysis of pre-receptor image conditioning in weakly electric fish. PLoS Comput Biol 1(2): 123–131CrossRefPubMedGoogle Scholar
  31. Nelson ME, Maclver MA (1999) Prey capture in the weakly electric fish Apteronotus albifrons: sensory acquisition strategies and electrosensory consequences. J Exp Biol 202(Pt 10): 1195–1203PubMedGoogle Scholar
  32. Nelson ME, MacIver MA, Coombs S (2002) Modeling electrosensory and mechanosensory images during the predatory behavior of weakly electric fish. Brain Behav Evol 59(4): 199–210CrossRefPubMedGoogle Scholar
  33. Rasnow B (1996) The effects of simple objects on the electric field of Apteronotus. J Comp Physiol A 178: 397–411Google Scholar
  34. Rasnow B, Bower B (1996) The electric organ discharges of the gymnotiform fishes: I. Apteronous leptorhynchus. J Comp Physiol A 178: 383–396Google Scholar
  35. Schwan HP (1963) Determination of biological impedances. In: Nastuk WL (eds) Physical techniques in biological research. Academic, New York, pp 323–407Google Scholar
  36. von der Emde G (1990) Discrimination of objects through electrolocation in the weakly electric fish, Gnathonemus petersii. J Comp Physiol A 167: 412–421Google Scholar
  37. von der Emde G (1998) Capacitance detection in the wave-type electric fish Eigenmannia during active electrolocation. J Comp Physiol A 182: 217–224CrossRefGoogle Scholar
  38. von der Emde G (2004) Distance and shape: perception of the 3-dimensional world by weakly electric fish. J Physiol Paris 98(1–3): 67–80PubMedGoogle Scholar
  39. von der Emde G, Bleckmann H (1992) Differential responses of two types of electroreceptive afferents to signal distortions may permit capacitance measurement in a weakly electric fish, Gnathonemus petersii. J Comp Physiol A 171: 683–694CrossRefGoogle Scholar
  40. von der Emde G, Ronacher B (1994) Perception of electric properties of objects in electrolocating weakly electric fish: two-dimensional similarity scaling reveals City-Block metric. J Comp Physiol A 175: 801–812Google Scholar
  41. Wojtenek W, Hofmann MH, Wilkens LA (2001a) Primary afferent electrosensory neurons represent paddlefish natural prey. Neurocomp 38–40: 451–458CrossRefGoogle Scholar
  42. Wojtenek W, Pei X, Wilkens LA (2001b) Paddlefish strike at artificial dipoles simulating the weak electric fields of planktonic prey. J Exp Biol 204: 1391–1399PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Computer and Information EngineeringTsuyama National Collage of TechnologyTsuyama, OkayamaJapan
  2. 2.Department of Applied Physics and ChemistryUniversity of Electro-CommunicationsChofu, TokyoJapan
  3. 3.Department of Human Media Systems, Graduate School of Information SciencesUniversity of Electro-CommunicationsChofu, TokyoJapan

Personalised recommendations