"Uncovering Common Waveform Features in Sharp-Wave Ripples Across Species Using Machine Learning"
A study on brain rhythms, specifically hippocampal sharp-wave ripples (SWRs), reveals common waveform features across species. Researchers organized a hackathon to develop machine learning models for SWR detection, resulting in the selection of five promising models. The models were trained and tested using LFP recordings from mice and macaques, demonstrating their generalizability. The study also evaluated the influence of input characteristics and processing parameters on model performance, providing insights for the development of new tools for SWR detection.