An Algorithmic Approach to Natural Behavior.

Current Biology : CB
Andrew M HeinGraham K Taylor

Abstract

Uncovering the mechanisms and implications of natural behavior is a goal that unites many fields of biology. Yet, the diversity, flexibility, and multi-scale nature of these behaviors often make understanding elusive. Here, we review studies of animal pursuit and evasion - two special classes of behavior where theory-driven experiments and new modeling techniques are beginning to uncover the general control principles underlying natural behavior. A key finding of these studies is that intricate sequences of pursuit and evasion behavior can often be constructed through simple, repeatable rules that link sensory input to motor output: we refer to these rules as behavioral algorithms. Identifying and mathematically characterizing these algorithms has led to important insights, including the discovery of guidance rules that attacking predators use to intercept mobile prey, and coordinated neural and biomechanical mechanisms that animals use to avoid impending collisions. Here, we argue that algorithms provide a good starting point for studies of natural behavior more generally. Rather than beginning at the neural or ecological levels of organization, we advocate starting in the middle, where the algorithms that link sensory input t...Continue Reading

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Citations

Sep 30, 2020·Proceedings of the National Academy of Sciences of the United States of America·Michael A GilAndrew M Hein
Nov 17, 2020·Frontiers in Systems Neuroscience·Jay Love, Moriel Zelikowsky
May 25, 2021·Frontiers in Behavioral Neuroscience·Brian KeyDeborah J Brown
Jun 10, 2021·Behavioral Ecology : Official Journal of the International Society for Behavioral Ecology·Caroline H BrightonGraham K Taylor
Jun 2, 2021·Integrative and Comparative Biology·Ashley N PetersonMatthew J McHenry
Jul 14, 2021·Journal of the Royal Society, Interface·Zachary P KilpatrickAhmed El Hady
Jul 21, 2021·Integrative and Comparative Biology·Chelsea N CookLisa A Mangiamele

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