Margolis Andrew, Gordus Andrew
Department of Biology, Johns Hopkins University, Baltimore, MD.
David Geffen School of Medicine, University of California, Los Angeles, CA.
ArXiv. 2024 Oct 30:arXiv:2309.15174v2.
Abrupt changes in behavior can often be associated with changes in underlying behavioral states. When placed off food, the foraging behavior of can be described as a change between an initial local-search behavior characterized by a high rate of reorientations, followed by a global-search behavior characterized by sparse reorientations. This is commonly observed in individual worms, but when numerous worms are characterized, only about half appear to exhibit this behavior. We propose an alternative model that predicts both abrupt and continuous changes to reorientation that does not rely on behavioral states. This model is inspired by molecular dynamics modeling that defines the foraging reorientation rate as a decaying parameter. By stochastically sampling from the probability distribution defined by this rate, both abrupt and gradual changes to reorientation rates can occur, matching experimentally observed results. Crucially, this model does not depend on behavioral states or information accumulation. Even though abrupt behavioral changes do occur, they are not necessarily indicative of abrupt changes in behavioral states, especially when abrupt changes are not universally observed in the population.
行为的突然变化通常可能与潜在行为状态的变化相关。当不给食物时，[某种生物]的觅食行为可描述为从以高重定向率为特征的初始局部搜索行为，转变为以稀疏重定向为特征的全局搜索行为。这在单个蠕虫中很常见，但当对大量蠕虫进行特征描述时，似乎只有大约一半表现出这种行为。我们提出了一种替代模型，该模型预测重定向的突然和连续变化，且不依赖于行为状态。该模型的灵感来自分子动力学建模，将觅食重定向率定义为一个衰减参数。通过从由该速率定义的数据分布中进行随机采样，重定向率可以发生突然和逐渐的变化，与实验观察结果相匹配。至关重要的是，该模型不依赖于行为状态或信息积累。即使确实发生了突然的行为变化，它们也不一定表明行为状态的突然变化，特别是当群体中并非普遍观察到突然变化时。
