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Updated: Jul 12, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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Noise autocorrelation and jamming avoidance performance in pulse type electric fish.

Alberto Capurro1, C P Malta

  • 1Instituto de Física, Universidade de São Paulo (USP), Rua do Matão, Travessa R187, Cidade Universitária, Butantã, 05508-900 São Paulo, Brazil. alberto@fma.if.usp.br

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Summary

Fish electric organ discharge patterns show that increased noise autocorrelation improves jamming avoidance. This adaptation enhances signal detection and prevents disruption from amplitude variations.

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Area of Science:

  • Neuroethology
  • Bioacoustics
  • Animal Communication

Background:

  • Electric fish like Gymnotus carapo use electric organ discharges (EODs) for navigation and communication.
  • Social interactions can alter the characteristics of EODs, including noise affecting discharge intervals.
  • The jamming avoidance response (JAR) is crucial for distinguishing self-generated signals from others.

Purpose of the Study:

  • To investigate the functional role of noise amplitude and autocorrelation in the JAR of Gymnotus carapo.
  • To determine if noise characteristics influence the efficiency of the JAR in paired fish.

Main Methods:

  • Estimated noise amplitude and autocorrelation in isolated and interacting Gymnotus carapo.
  • Simulated EOD interval variability using autoregressive models based on experimental data.
  • Incorporated JAR as transient interval shortenings in simulated EOD trains.
  • Quantified JAR efficiency by measuring the number of simultaneous discharges (coincidences).

Main Results:

  • Noise autocorrelation and amplitude increased in slower-discharging fish during social interaction.
  • Simulations revealed that JAR efficiency decreased with increasing autocorrelation when JAR was absent.
  • When JAR was included, decreasing coincidences correlated with increasing autocorrelation.
  • Increased noise amplitude negatively impacted JAR efficiency, with this effect being inversely proportional to autocorrelation.

Conclusions:

  • Persistent correlations in EOD variability are an adaptation enhancing JAR efficiency.
  • Autocorrelation acts as a protective mechanism, improving JAR performance against amplitude variations.
  • This study highlights the adaptive significance of neural noise in signal processing for social communication.