Just like Morse code or a symphony, weakly electric fish in the Mormyridae family have their own unique language – pulses of electricity! These fascinating creatures use electric pulses to communicate and gather information about their surroundings. The timing of these pulse intervals, known as SPIs, varies depending on the behavior of the fish. Now, scientists have developed a computational model that accurately reproduces the different SPI patterns observed in these fish. By using a genetic algorithm, they tuned the connectivity parameters of the model to match the patterns recorded from real fish. The results were impressive, with the model consistently reproducing the set of SPI patterns and maintaining a dynamic balance within the network. This model can serve as a valuable tool for further research on the temporal structure of electrogeneration in these fish and even other biological networks that exhibit sequential patterns.

Mormyridae, a family of weakly electric fish, use electric pulses for communication and for extracting information from the environment (active electroreception). The electromotor system controls the timing of pulse generation. Ethological studies have described several sequences of pulse intervals (SPIs) related to distinct behaviors (e.g., mating or exploratory behaviors). Accelerations, scallops, rasps, and cessations are four different SPI patterns reported in these fish, each showing characteristic stereotyped temporal structures. This article presents a computational model of the electromotor command circuit that reproduces a whole set of SPI patterns while keeping the same internal network configuration. The topology of the model is based on a simplified representation of the network with four neuron clusters (nuclei). An initial configuration was built to reproduce nucleus characteristics and network topology as described by detailed morphological and electrophysiological studies. Then, a methodology based on a genetic algorithm (GA) was developed and applied to tune the model connectivity parameters to automatically reproduce a whole set of patterns recorded from freely-behaving Gnathonemus petersii specimens. Robustness analyses of input variability were performed to discard overfitting and assess validity. Results show that the set of SPI patterns is consistently reproduced reaching a dynamic balance between synaptic properties in the network. This model can be used as a tool to test novel hypotheses regarding temporal structure in electrogeneration. Beyond the electromotor model itself, the proposed methodology can be adapted to fit models of other biological networks that also exhibit sequential patterns.

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