The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Modeling signal and background components of electrosensory scenes
Abstract
Weakly electric fish are able to detect and localize prey based on microvolt-level perturbations in the fish's self-generated electric field. In natural environments, weak prey-related signals are embedded in much stronger electrosensory background noise. To better characterize the signal and background components associated with natural electrolocation tasks, we recorded transdermal voltage modulations in restrained Apteronotus albifrons in response to moving spheres, tail bends, and large nonconducting boundaries. Spherical objects give rise to ipsilateral images with center-surround structure and contralateral images that are weak and diffuse. Tail bends and laterally placed nonconducting boundaries induce relatively strong ipsilateral and contralateral modulations of opposite polarity. We present a computational model of electric field generation and electrosensory image formation that is able to reproduce the key features of these empirically measured signal and background components in a unified framework. The model comprises an array of point sources and sinks distributed along the midline of the fish, which can conform to arbitrary body bends. The model is computationally fast and can be used to estimate the spatiotemporal pattern of activation across the entire electroreceptor array of the fish during natural behaviors.
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“Our framework captures the spatial geometry of the fish and objects (Fig 3 A), using the field model fitted to data in [34].”
From An end-to-end model of active electrosensation (2024) · cites this paper as [34]
Citations
Cites
(2020) · Princeton University Press eBooks · doi:10.2307/j.ctv131bv37.5 · Cited by 22,595
The Handbook of brain theory and neural networks
(1996) · Choice Reviews Online · doi:10.5860/choice.33-4484 · Cited by 3,913
Relations between the statistics of natural images and the response properties of cortical cells
Field, D. J. (1987) · Journal of the Optical Society of America A · doi:10.1364/josaa.4.002379 · Cited by 3,241
Some informational aspects of visual perception.
Attneave, F. (1954) · Psychological Review · doi:10.1037/h0054663 · Cited by 2,938
Haykin, S. (1978) · Cited by 1,827
The Handbook of brain theory and neural networks
(2003) · Choice Reviews Online · doi:10.5860/choice.41-0300 · Cited by 1,540
Statistics of natural images: Scaling in the woods
Ruderman, D., & Bialek, W. (1994) · Physical Review Letters · doi:10.1103/physrevlett.73.814 · Cited by 936
On the Function and Evolution of Electric Organs in Fish
Lissmann, H. W. (1958) · Journal of Experimental Biology · doi:10.1242/jeb.35.1.156 · Cited by 553
The electrical properties of metal microelectrodes
Robinson, D. A. (1968) · Proceedings of the IEEE · doi:10.1109/proc.1968.6458 · Cited by 459
Niel, F. (2021) · Springer theses · doi:10.1007/978-3-030-73547-0_2 · Cited by 446
Research works printed but not linked: 2
- 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?70
- Zakon HH (1986) The electroreceptive periphery. In: Bullock TH, Heiligenberg W (eds) Electroreception. Wiley, New York, pp 103?156
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Sorted by citations
Sensory acquisition in active sensing systems
Nelson, M. E., & MacIver, M. A. (2006) · Journal of Comparative Physiology A · doi:10.1007/s00359-006-0099-4 · Cited by 247
“Empirical measurements indicate that the return signal for the active electric sense falls off approximately as the fourth power of distance for small targets over the behaviorally relevant range of target distances (Chen et al. 2005), similar to geometric spreading effects in other systems.”
BackgroundSelf-citationThe hydrodynamics of ribbon-fin propulsion during impulsive motion
Shirgaonkar, A. A., Curet, O., Patankar, N. A., & MacIver, M. A. (2008) · Journal of Experimental Biology · doi:10.1242/jeb.019224 · Cited by 119
“This may facilitate sensory performance as the body houses the electric field generator, and movement of the tail causes modulations of the field that are more than a factor of 10 larger than prey-related modulations (Chen et al., 2005; Nelson and MacIver, 1999).”
BackgroundOmnidirectional sensory and motor volumes in electric fish
Snyder, J. B., Nelson, M. E., Burdick, J. W., & MacIver, M. A. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050301 · Cited by 112
“(A) Magnitude of the self-generated electric field in water of 35-lS/cm conductivity from an empirically validated computational model [41].”
MethodTemporal Processing Across Multiple Topographic Maps in the Electrosensory System
Krahe, R., Bastian, J., & Chacron, M. J. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90300.2008 · Cited by 110
Self-citationMaler, L. (2009) · The Journal of Comparative Neurology · doi:10.1002/cne.22124 · Cited by 105
Metadata
- Authors
- Chen, L., House, J. L., Krahe, R., & Nelson, M. E.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Nelson, Mark E.
- ORCID
- Nelson, Mark E.
- Venue
- Journal of Comparative Physiology A
- Published
- 2004-12-17
- Volume
- 191
- Issue
- 4
- Pages
- 331-345
- ISSN
- 0340-7594 (ISSN-L)
- 1432-1351
- OpenAlex
- W1969494732
- Cited by
- 142
- References
- 49
- Citations by year
- 2025: 5 · 2024: 11 · 2023: 5 · 2022: 4 · 2021: 4 · 2020: 5 · 2019: 6 · 2018: 4 · 2017: 3 · 2016: 5 · 2015: 9 · 2014: 10 · 2013: 18 · 2012: 13
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Comparative Physiology A (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- National Institute of Mental Health (R01-MH49242, R01MH049242)
- 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 › Biochemistry, Genetics and Molecular Biology › Biophysics › Electromagnetic Fields and Biological Effects
- Keywords
- weakly electric fish, electrolocation, Apteronotus albifrons, prey detection, electric field generation, computational model
- MeSH terms
- Animals, Electric Organ, Electrophysiology, Field Dependence-Independence, Membrane Potentials, Models, Biological, Perception, Sensory Receptor Cells, Computational Biology, Gymnotiformes
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