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Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

机译:基于果蝇幼虫趋光强度与方向性的导航决策统计模型

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摘要

Organisms use environmental cues for directed navigation. Understanding the basic logic behind navigational decisions critically depends on the complexity of the nervous system. Due to the comparably simple organization of the nervous system of the fruit fly larva, it stands as a powerful model to study decision-making processes that underlie directed navigation. We have quantitatively measured phototaxis in response to well-defined sensory inputs. Subsequently, we have formulated a statistical stochastic model based on biased Markov chains to characterize the behavioural basis of negative phototaxis. Our experiments show that larvae make navigational decisions depending on two independent physical variables: light intensity and its spatial gradient. Furthermore, our statistical model quantifies how larvae balance two potentially-contradictory factors: minimizing exposure to light intensity and at the same time maximizing their distance to the light source. We find that the response to the light field is manifestly non-linear, and saturates above an intensity threshold. The model has been validated against our experimental biological data yielding insight into the strategy that larvae use to achieve their goal with respect to the navigational cue of light, an important piece of information for future work to study the role of the different neuronal components in larval phototaxis.
机译:有机体利用环境提示进行定向导航。对导航决策背后的基本逻辑的理解至关重要,这取决于神经系统的复杂性。由于果蝇幼虫神经系统的组织比较简单,它是研究定向导航基础的决策过程的有力模型。我们已经对定义良好的感觉输入做出了定量测量的趋光性。随后,我们建立了基于有偏马尔可夫链的统计随机模型,以表征负趋光性的行为基础。我们的实验表明,幼虫根据两个独立的物理变量做出导航决策:光强度及其空间梯度。此外,我们的统计模型量化了幼虫如何平衡两个潜在矛盾的因素:最大程度地减少暴露于光强度,同时最大化它们到光源的距离。我们发现,对光场的响应显然是非线性的,并且在强度阈值以上饱和。该模型已针对我们的实验生物学数据进行了验证,从而深入了解了幼虫用于实现其关于光导航线索的目标的策略,这是今后研究幼虫不同神经元成分的作用的重要信息趋光性。

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