MyoRec
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Automated analysis of feeding dynamics from electromyographic recordings in a blood-sucking insect
Feeding behavior in blood-sucking insects relies on gustatory evaluation to decide on sustained ingestion, yet quantifying this process from electromyogram (EMG) recordings is labor-intensive. Here we developed MyoRec, an automated computational framework employing machine learning to analyse EMG signals from the triatomine bug Rhodnius prolixus. Using recordings under appetitive and aversive conditions, a convolutional neural network detected ingestion events with 97.7% accuracy.