Abstract
Barcode-based tracking of individuals revolutionizes the study of animal behaviour, but further progress hinges on whether specific behaviours can be monitored. We achieve this goal by combining information obtained from the barcodes with image analysis through convolutional neural networks. Applying this novel approach to a challenging test case, the honeybee hive, we reveal that food exchange among bees generates two distinct social networks with qualitatively different transmission capabilities.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵† Present affiliations: Department of Ecology and Evolutionary Biology, Princeton University, 106A Guyot Lane, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, South Drive, Princeton, NJ 08544, USA