Cited by 99Fish biology, ecology, and behaviorPlant and Biological Electrophysiology StudiesTactile and Sensory Interactions

The DOI matches its Crossref record.

Distance, shape and more: recognition of object features during active electrolocation in a weakly electric fish

von der Emde, Gerhard, Fetz, Steffen·2007·Journal of Experimental Biology

Abstract

SUMMARY: In the absence of light, the weakly electric fish Gnathonemus petersii detects and distinguishes objects in the environment through active electrolocation. In order to test which features of an object the fish use under these conditions to discriminate between differently shaped objects,we trained eight individuals in a food-rewarded, two-alternative,forced-choice procedure. All fish learned to discriminate between two objects of different shapes and volumes. When new object combinations were offered in non-rewarded test trials, fish preferred those objects that resembled the one they had been trained to (S+) and avoided objects resembling the one that had not been rewarded (S–). For a decision, fish paid attention to the relative differences between the two objects they had to discriminate. For discrimination, fish used several object features, the most important ones being volume, material and shape. The importance of shape was demonstrated by reducing the objects to their 3-dimensional contours, which sufficed for the fish to distinguish differently shaped objects. Our results also showed that fish attended strongly to the feature `volume', because all individuals tended to avoid the larger one of two objects. When confronted with metal versus plastic objects, all fish avoided metal and preferred plastic objects, irrespective of training. In addition to volume, material and shape,fish attended to additional parameters, such as corners or rounded edges. When confronted with two unknown objects, fish weighed up the positive and negative properties of these novel objects and based their decision on the outcome of this comparison. Our results suggest that fish are able to link and assemble local features of an electrolocation pattern to construct a representation of an object, suggesting that some form of a feature extraction mechanism enables them to solve a complex object recognition task.

Overview

Integrity signals

Registry

Crossref · 10.1242/jeb.005694

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Behavioral studies suggest that microvolt changes in EOD amplitude and sub-microsecond temporal distortions of the EOD waveform can be detected by the fish.

    “Behavioral studies suggest that microvolt changes in EOD amplitude and sub-microsecond temporal distortions of the EOD waveform can be detected by the fish [2, 3, 4, 5].”

    From An end-to-end model of active electrosensation (2024) · cites this paper as [4]

  • Weakly electric fish can spatially localize objects and characterize their properties (including size, shape, and electrical resistance and capacitance) in the dark, based solely on information extracted from their EODs.

    “The outcome of EOD signal processing is the remarkable ability of weakly electric fish to spatially localize objects and characterize their properties (including size, shape, and electrical resistance and capacitance) in the dark, based solely on information extracted from their EODs [2, 3, 4].”

    From An end-to-end model of active electrosensation (2024) · cites this paper as [4]

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 38

  1. Bastian, J. (1994). Electrosensory organisms. Phys. Today47,30-37. · DOI
  2. Bleckmann, H., Mogdans, J. and Dehnhardt, G.(2003). Processing of dipole and more complex hydrodynamic stimuli under still- and running-water conditions. In Sensory Processing in Aquatic Environments (ed. S. P. Collin and J. Marshall), pp. 108-121. New York:Springer. · DOI
  3. Burt de Perera, T. and Braithwaite, V. A.(2005). Laterality in a non-visual sensory modality – the lateral line of fish. Curr. Biol.15,R241-R242. · DOI
  4. Caputi, A. and Budelli, R. (2006). Peripheral electrosensory imaging by weakly electric fish. J. Comp. Physiol. A192,587-600. · DOI
  5. Caputi, A. A., Budelli, R., Grant, K. and Bell, C. C.(1998). The electric image in weakly electric fish: physical images of resistive objects in Gnathonemus petersii.J. Exp. Biol.201,2115-2128. · DOI
  6. Carlson, B. A. (2002). Electric signalling behavior and the mechanisms of electric organ discharge production in mormyrid fish. J. Physiol. Paris96,405-419. · DOI
  7. Davis, D. and von der Emde, G. (2003). Recognition of object shape during active electrolocation in electric fish. In Proceedings of the 29th Göttingen Neurobiology Conference (ed. H. Zimmermann and N. Elsner), p.1018. Göttingen: Georg Thieme Verlag.
  8. Davison, M. L. (1983). Multidimensional Scaling. New York, Singapore: John Wiley.
  9. Douglas, R. H., Eva, J. and Guttridge, N.(1988). Size constancy in goldfish (Carassius auratus). Behav. Brain Res.30,37-42. · DOI
  10. Dyer, A. G., Neumeyer, C. and Chittka, L.(2005). Honeybee (Apis mellifera) vision can discriminate between and recognise images of human faces. J. Exp. Biol.208,4709-4714. · DOI
  11. Gellermann, L. W. (1933). Chance orders of alternating stimuli in visual discrimination experiments. J. Genet. Psychol.42,206-208. · DOI
  12. Graff, C., Kaminski, G., Gresty, M. and Ohlmann, T.(2004). Fish perform spatial pattern recognition and abstraction by exclusive use of active electrolocation. Curr. Biol.14,818-823. · DOI
  13. Heiligenberg, W. (1973). Electrolocation of objects in the electric fish Eigenmannia (Rhamphichthyidae,Gymnotoidei). J. Comp. Physiol.87,137-164. · DOI
  14. Heiligenberg, W. (1975). Theoretical and experimental approaches to spatial aspects of electrolocation. J. Comp. Physiol.103,247-272. · DOI
  15. Hopkins, C. D. (2005). Passive electrolocation and the sensory guidance of oriented behavior. In Electroreception (ed. T. H. Bullock, C. D. Hopkins, A. N. Popper and R. R. Fay), pp. 264-289. New York:Springer. · DOI
  16. Lehrer, M. and Campan, R. (2005). Generalization of convex shapes by bees: what are shapes made of?J. Exp. Biol.208,3233-3247. · DOI
  17. Leibowitz, H. W. (1971). Sensory, learned, and cognitive mechanisms of size perception. Ann. N. Y. Acad. Sci.188,47-60. · DOI
  18. Lissmann, H. W. and Machin, K. E. (1958). The mechanism of object location in Gymnarchus niloticus and similar fish. J. Exp. Biol.35,451-486. · DOI
  19. Migliaro, A., Caputi, A. A. and Budelli, R.(2005). Theoretical analysis of pre-receptor image conditioning in weakly electric fish. PLoS Comp. Biol.1, 123-131. · DOI
  20. Nieder, A. (2002). Seeing more than meets the eye: processing of illusory contours in animals. J. Comp. Physiol. A188,249-260. · DOI
  21. Palmeri, T. J. and Gauthier, I. (2004). Visual object understanding. Nat. Rev. Neurosci.5, 291-304. · DOI
  22. Pusch, R. (2006). Sinnesreize während der aktiven Elektroortung: Elektrische Bilder von Objekten bei Gnathonemus petersii. Staatsexamensarbeit, Institut für Zoologie, pp. 90. Bonn: Universität Bonn.
  23. Rasnow, B. and Bower, J. M. (1997). Imaging with electricity: how weakly electric fish might perceive objects. In Computational Neuroscience: Trends in Research, 1997(ed. J. M. Bower), pp. 795-800. New York, London:Plenum Press. · DOI
  24. Schuster, S. and Amtsfeld, S. (2002). Template-matching describes visual pattern-recognition tasks in the weakly electric fish Gnathonemus petersii.J. Exp. Biol.205,549-557. · DOI
  25. Schwarz, S. (2000). Gnathonemus petersii: three-dimensional object shape detection and the geometry of the self-produced electric field. PhD Thesis, Zoological Institute,University of Bonn, Germany.
  26. Schwarz, S. and von der Emde, G. (2001). Distance discrimination during active electrolocation in the weakly electric fish Gnathonemus petersii.J. Comp. Physiol. A186,1185-1197. · DOI · Paper page
  27. Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science237,1317-1323. · DOI · Paper page
  28. Srinivasan, M. V. (1994). Pattern recognition in the honeybee: recent progress. J. Insect Physiol.40,183-194. · DOI
  29. Toerring, M. J. and Belbenoit, P. (1979). Motor programmes and electroreception in mormyrid fish. Behav. Ecol. Sociobiol.4,369-379. · DOI
  30. Toerring, M. J. and Moller, P. (1984). Locomotor and electric displays associated with electrolocation during exploratory behavior in Mormyrid fish. Behav. Brain Res.12,291-306. · DOI · Paper page
  31. von der Emde, G. (1990). Discrimination of objects through electrolocation in the weakly electric fish, Gnathonemus petersii.J. Comp. Physiol. A167,413-421. · DOI · Paper page
  32. von der Emde, G. (1992). Electrolocation of capacitive objects in four species of pulse-type weakly electric fish. II. Electric signalling behavior. Ethology92,177-192. · DOI
  33. von der Emde, G. (2004). Distance and shape:perception of the 3-dimensional world by weakly electric fish. J. Physiol. Paris98,67-80. · DOI
  34. von der Emde, G. (2006). Non-visual environmental imaging and object detection through active electrolocation in weakly electric fish. J. Comp. Physiol. A192,601-612. · DOI
  35. von der Emde, G. and Bleckmann, H. (1998). Finding food: senses involved in foraging for insect larvae in the electric fish, Gnathonemus petersii.J. Exp. Biol.201,969-980. · DOI
  36. von der Emde, G. and Ronacher, B. (1994). Perception of electric properties of objects in electrolocating weakly electric fish: two-dimensional similarity scaling reveals a City-Block metric. J. Comp. Physiol. A175,801-812. · DOI
  37. von der Emde, G., Schwarz, S., Gomez, L., Budelli, R. and Grant,K. (1998). Electric fish measure distance in the dark. Nature395,890-894. · DOI
  38. Wehner, R. (1967). Pattern recognition in bees. Nature215,1244-1248. · DOI

Cited by

Sorted by citations

  • An end-to-end model of active electrosensation

    Turcu, D., Zadina, A., Abbott, L. F., & Sawtell, N. B. (2024) · bioRxiv (preprint) · doi:10.1101/2024.10.22.619741 · Cited by 4

    “The outcome of EOD signal processing is the remarkable ability of weakly electric fish to spatially localize objects and characterize their properties (including size, shape, and electrical resistance and capacitance) in the dark, based solely on information extracted from their EODs [2, 3, 4].”

Metadata

Authors
von der Emde, G., & Fetz, S.
Affiliations
University of Bonn (DE)
Venue
Journal of Experimental Biology
Published
2007-09-01
Volume
210
Issue
17
Pages
3082-3095
ISSN
  • 0022-0949 (ISSN-L)
  • 1477-9145
OpenAlex
W1989790153
Cited by
99
References
0
Citations by year
2025: 4 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 4 · 2017: 9 · 2016: 8 · 2015: 5 · 2014: 6 · 2013: 11 · 2012: 9
FWCI
3.81
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Experimental Biology (publishedVersion)
  • PubMed (publishedVersion)
  • HighWire Press Open Archive (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish biology, ecology, and behavior
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant and Biological Electrophysiology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
Keywords
active electrolocation, weakly electric fish, Gnathonemus petersii, object recognition, object shape discrimination, feature extraction, electroreception, novel object recognition
MeSH terms
Animals, Discrimination Learning, Distance Perception, Electric Conductivity, Electric Fish, Form Perception

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review