Unsupervised electric signal separation for linking behavior and electrocommunication in Gnathonemus petersii.

ABSTRACT: The transfer of information between individuals is fundamental to living systems and requires comprehensive research in various species. Weakly electric fish, Gnathonemus petersii, provides a unique model organism for such investigations due to its advanced electrocommunication via electric organ discharges (EODs). As separating EODs from multiple individuals remains challenging, we developed an unsupervised approach for EOD separation in two free-swimming individuals. Using continuous wavelet transform, t-distributed Stochastic Neighbor Embedding, and hierarchical clustering, we achieved accurate discrimination of EODs without the necessity of any training data. This approach overcomes the supervised algorithms based on previously published methods in accuracy and computational efficiency

SUBMITTER: Chrtkova I 

PROVIDER: S-EPMC12479879 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature