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
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Cited by
Sorted by citations
Items 101–142 of 142
Active Electrolocation and Spatial Learning
Jung, S. N., & Engelmann, J. (2019) · Springer handbook of auditory research · doi:10.1007/978-3-030-29105-1_12 · Cited by 2
Why the brown ghost chirps at night
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2025) · eLife · doi:10.7554/elife.88287.5 · Cited by 2
Self-citationA Finite Element Method of Electric Image in Weakly Electric Fish
Ahn, S., & Kim, D. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33093-3_13 · Cited by 2
Multi-scale Classification for Electrosensing
Baldassari, L., & Scapin, A. (2021) · SIAM Journal on Imaging Sciences · doi:10.1137/20m1344317 · Cited by 2
Henninger, J., Krahe, R., Sinz, F. H., & Benda, J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/550814 · Cited by 2
Self-citationBehavioral and Neural Aspects of the Spatial Processing of Conspecifics in the Electrosensory SystemPreprint
Milam, O. E., Ramachandra, K. L., & Marsat, G. (2019) · Preprints.org · doi:10.20944/preprints201811.0132.v2 · Cited by 2
Why the brown ghost chirps at nightPreprint
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2023) · eLife · doi:10.7554/elife.88287 · Cited by 2
Self-citationAn 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
“While [34] refers to the electric sources as “charges”, they based their model on the previous work of [31], where the sources are referred to as “currents”.”
InfluentialHou, M., Peng, J., Yang, M., Jiang, T., & Chen, Y. (2025) · Defence Technology · doi:10.1016/j.dt.2025.10.021 · Cited by 1
Krahe, R. (2008) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2008.10.014 · Cited by 1
Self-citationSignal cancellation in neural systems: encoding sensory input in the weakly electric fish
Bol, K., Marsat, G., Mejías, J. F., Harvey‐Girard, E., Maler, L., & Longtin, A. (2012) · International Conference on Information Science, Signal Processing and their Applications (ISSPA) · doi:10.1109/isspa.2012.6310656 · Cited by 1
“Small objects such as prey create spatially localized amplitude modulations (AMs) of the EOD, whereas tailbending or communication signals (for instance, low frequency sinusoidal AMs arise from the beating between the EODs of two electric fishes if both frequencies are relatively close) induce spatially global AMs [3,…”
BackgroundInfluentialMotion parallax for object localization in electric fields
Hunke, K., Engelmann, J., Meyer, H. G., & Schneider, A. (2021) · Bioinspiration & Biomimetics · doi:10.1088/1748-3190/ac3215 · Cited by 1
“Nonetheless, the calculation of the local electric potential has frequently been used to provide fast simulations of electric images in order to reach an abstract understanding of active electric imaging [12, 15, 16].”
MethodSawtell, N. B., & Bell, C. C. (2021) · Springer eBooks · doi:10.1007/978-3-030-23810-0_55 · Cited by 1
Hunke, K., Engelmann, J., & Schneider, A. (2022) · IEEE Instrumentation & Measurement Magazine · doi:10.1109/mim.2022.9955466 · Cited by 1
“In addition, Chen et al. proposed the full-width at half-maximum (FWHM) as a characteristic feature [15].”
BackgroundInfluentialDistance Discrimination of Weakly Electric Fish with a Sweep of Tail Bending Movements
Sim, M., & Kim, D. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21283-3_8 · Cited by 1
Sim, M., & Kim, D. (2010) · Cited by 1
Wallach, A., Harvey‐Girard, E., Jun, J. J., Longtin, A., & Maler, L. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/285494 · Cited by 1
“Thus, the number of PGl cells is sufficient to attain the observed behavioral precision, even when additional encoding errors (e.g. in heading and velocity estimation) are taken into account.”
BackgroundMilam, O. E. (2023) · doi:10.33915/etd.12120 · Cited by 1
Estimating Relative Positions of Multiple Objects in the Weakly Electric Fish
Sim, M., & Kim, D. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15193-4_20
“Chen et al. [ 6 ] showed an experiment with a moving object near the body surface of weakly electric fish.”
BackgroundInfluentialObject localization with electrosensory mechanism in weakly electric fish
Sim, M., & Kim, D. (2011) · BMC Neuroscience · doi:10.1186/1471-2202-12-s1-p302
“In fact, weakly electric fish have many positive poles distributed along the midline [2-4], and the normal component is more dominant in the middle of the body surface.”
BackgroundSynaptic regulation of intrinsic dynamics in ell pyramidal cells
Mehaffey, W. H. (2008) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/2082
Electroreceptor Afferents Limits of Linear Rate Coding of Dynamic Stimuli by
Benda, J., Maler, L., Jun, J. J., Longtin, A., Metzen, M. G., Chacron, M. J., Jamali, M., Carriot, J., Ávila, O., & Kathleen, E. (2015)
Marcoux, C. M. (2016) · uO Research (University of Ottawa) · doi:10.20381/ruor-5531
“Detection can occur with prey further than 3 cm from the fish’s body (Nelson and Maciver, 1999), which translates to a <1 µV increase over a baseline EOD amplitude of ~1.3 mV (Nelson and Maciver, 1999; Chen et al., 2005).”
BackgroundInfluentialA neural filter for electrolocation in weakly electric fish
Sim, M., & Kim, D. (2011)
Design Challenges and Considerations for Nanomedical Device Signal Acquisition and Propagation
Boehm, F. (2013) · CRC Press eBooks · doi:10.1201/b15626-8
Motion Sensing Behaviour in Weakly Electric Fish
Young, C. (2014) · uO Research (University of Ottawa) · doi:10.20381/ruor-3473
“A close object will produce an electric image with a large amplitude and a narrow peak; whereas an object which is further away will produce a smaller amplitude coupled with a wider peak (Hoshimiya et al., 1980; Rasnow, 1996; Rother et al., 2003; Chen et al., 2005; Babineau et al., 2006).”
BackgroundModeling electrosensory system of weakly electric fish
Sim, M., & Kim, D. E. (2011)
Active Control of Sensing Through Movements in Active Electrolocation
Engelmann, J., & Lucks, V. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.24212-0
An Internal Model of Sensorimotor Context in Freely Swimming Electric FishPreprint
Wallach, A., & Sawtell, N. B. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.08.495343
“Electrostatic Multipole Model To model the fish’s electric field and its modulations due to tail motion and external objects, we used the multipole electrostatic model developed by Chen et al (19).”
BackgroundMethodNeural mechanisms of corollary discharge in weakly electric mormyrid fish
Fukutomi, M. (2023) · Hikaku seiri seikagaku(Comparative Physiology and Biochemistry) · doi:10.3330/hikakuseiriseika.40.97
Why the brown ghost chirps at nightPreprint
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2023) · doi:10.7554/elife.88287.1
Self-citationWhy the brown ghost chirps at nightPreprint
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2024) · eLife · doi:10.7554/elife.88287.2
Self-citationWhy the brown ghost chirps at nightPreprint
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2024) · eLife · doi:10.7554/elife.88287.3
Self-citationeLife Assessment: Why the brown ghost chirps at night
Carr, C. E. (2024) · eLife · doi:10.7554/elife.88287.3.sa4
Author response: Why the brown ghost chirps at night
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2024) · eLife · doi:10.7554/elife.88287.3.sa0
Self-citationWhy the brown ghost chirps at nightPreprint
Oboti, L., Pedraja, F., Ritter, M., Lohse, M., Klette, L., & Krahe, R. (2024) · eLife · doi:10.7554/elife.88287.4
Self-citationElectrolocation without an electric image
Lewis, G. M., Callanan, A. J., & Lewis, J. E. (2025) · Physical Biology · doi:10.1088/1478-3975/ae1d06
“This configuration creates an electric field that resembles an elongated dipole which mimics the electric field that is produced by the electric organ of certain species of electric fish [13].”
fish2eod: finite element modelling of active electric sensing
Shifman, A. R., Upshall, M., & Lewis, J. E. (2025) · Journal of Experimental Biology · doi:10.1242/jeb.251003
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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