ArticleScientific reports2018
High-resolution behavioral mapping of electric fishes in Amazonian habitats.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Integrating deep learning 3D tracking and biophysical EOD modeling for precise, noninvasive computational neuroethology in freely swimming weakly electric fish.Frontiers in computational neuroscience · 2026Article
- Tracking spatial patterns and daily modulation of behavior in a natural population of the pulse-type weakly electric fish,iScience · 2025Article
- Visualization of electric fields and associated behavior in fish and other aquatic animals.Behavior research methods · 2024Article
- Wide-angle, monocular head tracking using passive markers.Journal of neuroscience methods · 2022Article
- Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings.Frontiers in integrative neuroscience · 2022Article
- Electrocommunication signals indicate motivation to compete during dyadic interactions of an electric fish.The Journal of experimental biology · 2021Article
- The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish.Frontiers in behavioral neuroscience · 2021Article
- Spooky Interaction at a Distance in Cave and Surface Dwelling Electric Fishes.Frontiers in integrative neuroscience · 2020Article
- Dominance in Habitat Preference and Diurnal Explorative Behavior of the Weakly Electric FishFrontiers in integrative neuroscience · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of animal behavior has been revolutionized by sophisticated methodologies that identify and track individuals in video recordings. Video recording of behavior, however, is challenging for many species and habitats including fishes that live in turbid water. Here we present a methodology for identifying and localizing weakly electric fishes on the centimeter scale with subsecond temporal resolution based solely on the electric signals generated by each individual. These signals are recorded with a grid of electrodes and analyzed using a two-part algorithm that identifies the signals from each individual fish and then estimates the position and orientation of each fish using Bayesian inference. Interestingly, because this system involves eavesdropping on electrocommunication signals, it permits monitoring of complex social and physical interactions in the wild. This approach has potential for large-scale non-invasive monitoring of aquatic habitats in the Amazon basin and other tropical freshwater systems.
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Registered trials
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