Networks of Causal Linkage Between Eigenmodes Characterize Behavioral Dynamics of Caenorhabditis elegans - Saberski, Erik; Bock, Antonia K.; Goodridge, Rachel; Agarwal, Vitul; Lorimer, Tom; Rifkin, Scott A.; Sugihara, George (PLOS Computational Biology, 2021)
Author summary A primary reason for studying C. elegans is the possibility of achieving an end-to-end understanding of animal behaviour—one that mechanistically links genes to behaviour through neurobiology. With the genome and connectome fully mapped, techniques for measuring the behavior of C. elegans have traditionally relied on easily identified changes in posture and motion. Such approaches, however, can miss complex and more subtle behaviors that cannot be readily distinguished by eye. To explore this issue, we develop an attractor-based network approach to show that the four basic shapes classically used to describe worm position can be related to each other in a network that represents how the shapes interact with each other over time. That is, we study not just worm poses, but how the poses interact. Importantly, we find that these interaction networks can distinguish subtle high dimensional behaviors among mutant strains previously classified as phenotypically similar, thereby making genetic distinctions not previously possible. Thus, the value of this attractor-based network approach is its ability to detect subtle differences that can discriminate macroscopic behavior at the gene-mutation level. We anticipate these methods will be of interest to behaviorists, neuroscientists, and geneticists studying the connection between behavior and genes.