Abstract
Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervised learning approaches offer a promising tool to automate or semiautomate the workflow, and thereby allowing the analysis of much longer episodes of behavior in a reasonable amount of time. We provide a detailed workflow mainly based on open resource software. We demonstrate the usefulness by applying the approach to the analysis of dyadic interactions of Gnathonemus petersii. Coupling of the proposed methods with a boundary element modeling approach, we are thereby able to model the information gained and provided during agonistic encounters. The data indicate that the passive electrosensory input, in particular, provides sufficient information to localize a contender during the pre-contest phase, fish did not use or rely on the theoretically also available sensory information of the contest outcome-determining size difference between contenders before engaging in agonistic behavior.
Highlights
Electric fish are active at night and are frequently found in dark and turbid environments (Moller et al, 1979)
We will first detail the steps we took in optimizing the electric organ discharge (EOD) recording setup using supervised learning methods to demonstrate how two different models performed in automatically localizing an EOD-emitting fish in the setup
To further demonstrate the robustness of the approach we found to be best suited, we will report data where the random forest regressor (RFR) model approach is being used on dyadic interactions of fish to investigate if and how the resource holding potential (RHP) may be perceived and used in conflict resolution between dyads of G. petersii
Summary
Electric fish are active at night and are frequently found in dark and turbid environments (Moller et al, 1979). The specialized electric sense enables weakly electric fish well adapted to cope with the specific challenges imposed by this lifestyle (Carlson and Sisneros, 2019). They produce electric signals for both, electrolocalization and electrocommunication with conspecifics (Möhres, 1957; Lissmann, 1958; Lissmann and Machin, 1958; Moller, 1970). EODs are low in amplitude (often in the order of 1 mV) and, in addition, these signals attenuate steeply with distance from the emitting fish (Rasnow, 1996; Sicardi et al, 2000; Chen et al, 2005; Nelson and MacIver, 2006)
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