Modeling signal and background components of electrosensory scenes

Ling Chen, Jonathan L. House, Rüdiger Krahe, Mark E. Nelson

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)331-345
Number of pages15
JournalJournal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology
Issue number4
StatePublished - Apr 2005


  • Electric organ
  • Electrolocation
  • Electroreception
  • Natural scenes
  • Prey capture

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Physiology
  • Physiology (medical)
  • Behavioral Neuroscience
  • General Neuroscience


Dive into the research topics of 'Modeling signal and background components of electrosensory scenes'. Together they form a unique fingerprint.

Cite this