Animals generate complex patterns of behavior across life that distinguish them from one another, a property called individuality. Studying the processes by which behavioral individuality is generated and maintained is crucial for our understanding of the large individual-to-individual diversity in behavioral patterns observed within animal populations, including in humans.
Shay Stern’s lab has recently developed a novel multi-camera imaging setup, using the nematode C. elegans as a model, that allowed for the first time to study behavioral individuality across the full generation time of multiple animals, at high spatiotemporal resolution and under tightly controlled environmental conditions (Stern et al. Cell). The behavioral data acquired by this unique system presents ‘big data’ challenges which require the development and application of efficient and smart image analysis and behavioral quantification methods.
The Stern lab is highly multi-disciplinary, integrating cutting edge computational methods from image analysis to machine-learning with state-of-the-art genetic, neuronal, and behavioral analyses.
For more information please visit: www.ssternlab.com