Chaotic heteroclinic network dynamics can explain random dwelling and switching behavior in biology

What is it about?

Biological activity can often be described as randomly transitioning between different semi-stable states. We propose a chaotic heteroclinic network as a model for these types of dynamics. We show how dwell time and transition statistics for different semi-stable states can be determined by controlling how the stable and unstable manifolds intersect. The neural activity of the nematode C. elegans, and its corresponding behavior, transitions between semi-stable states; we fit our model to C. elegans activity.

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Photo by Alina Grubnyak on Unsplash

Photo by Alina Grubnyak on Unsplash

Why is it important?

In many biological systems, such as C. elegans, it is unclear what the fundamental mechanisms are that determine and drive behavior. Having models that can describe the mechanisms underlying behavior can help neuroscientists gain insights into how the brain works and potentially lead to novel therapies for diseases that affect behavior.