Keaveny, E. E. | Search bioRxiv

bioRxiv2022

Ciliary propulsion and metachronal coordination in reef coral larvae

Larval dispersal is critical to the survival of coral reefs. As the only motile stage of the reproductive cycle, coral larvae choose a suitable location to settle and mature into adult corals. Here, we present the first detailed study of ciliary propulsion in the common stony reef coral Acropora millepora. Using high-speed, high-resolution imaging, particle image velocimetry, and electron microscopy, we reveal the arrangement of the densely packed cilia over the larval body surface, and their organisation into diaplectic (transversely propagating) metachronal waves. We resolve the individual-ciliums beat dynamics and compare the resultant flows with a computational model of a ciliary array, and show that this form of ciliary metachronism leads to near-maximal pumping efficiency.

biophysics↗

bioRxiv2017

Recurrent Neural Networks with Interpretable Cells Predict and Classify Worm Behaviour

An important goal in behaviour analytics is to connect disease state or genome variation with observable differences in behaviour. Despite advances in sensor technology and imaging, informative behaviour quantification remains challenging. The nematode worm C. elegans provides a unique opportunity to test analysis approaches because of its small size, compact nervous system, and the availability of large databases of videos of freely behaving animals with known genetic differences. Despite its relative simplicity, there are still no reports of generative models that can capture essential differences between even well-described mutant strains. Here we show that a multilayer recurrent neural network (RNN) can produce diverse behaviours that are difficult to distinguish from real worms behaviour and that some of the artificial neurons in the RNN are interpretable and correlate with observable features such as body curvature, speed, and reversals. Although the RNN is not trained to perform classification, we find that artificial neuron responses provide features that perform well in worm strain classification.

animal behavior and cognition↗