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欧洲乌贼的多层次自适应伪装控制。

Multi-level control of adaptive camouflage by European cuttlefish.

机构信息

School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.

UMR 6552 EthoS Equipe NECC, UNICAEN, University of Rennes, CNRS, 14032 Caen, France.

出版信息

Curr Biol. 2022 Jun 6;32(11):2556-2562.e2. doi: 10.1016/j.cub.2022.04.030. Epub 2022 May 3.

Abstract

To camouflage themselves on the seafloor, European cuttlefish Sepia officinalis control the expression of about 30 pattern components to produce a range of body patterns. If each component were under independent control, cuttlefish could produce at least 2 patterns. To examine how cuttlefish deploy this vast potential, we recorded cuttlefish on seven experimental backgrounds, each designed to resemble a pattern component, and then compared their responses to predictions of two models of sensory control of component expression. The body pattern model proposes that cuttlefish integrate low-level sensory cues to categorize the background and co-ordinate component expression to produce a small number of overall body patterns. The feature matching model proposes that each component is expressed in response to one (or more) local visual features, and the overall pattern depends upon the combination of features in the background. Consistent with the feature matching model, six of the backgrounds elicited a specific set of one to four components, whereas the seventh elicited eleven components typical of a disruptive body pattern. This evidence suggests that both modes of control are important, and we suggest how they can be implemented by a recent hierarchical model of the cuttlefish motor system..

摘要

为了在海底伪装自己,欧洲乌贼 Sepia officinalis 控制着大约 30 种图案成分的表达,以产生一系列的身体图案。如果每个成分都受到独立的控制,乌贼可以产生至少 2 种图案。为了研究乌贼如何利用这种巨大的潜力,我们在七个实验背景下记录了乌贼的反应,每个背景都设计成类似于一种图案成分,然后将它们的反应与两种感官控制成分表达模型的预测进行比较。身体图案模型提出,乌贼整合低水平的感官线索来对背景进行分类,并协调成分的表达,以产生少量的整体身体图案。特征匹配模型提出,每个成分都是针对一个(或多个)局部视觉特征表达的,而整体图案则取决于背景中的特征组合。与特征匹配模型一致,六个背景引发了一组特定的一到四个成分,而第七个背景则引发了十一个典型的扰乱身体图案的成分。这一证据表明,这两种控制模式都很重要,我们提出了它们如何通过最近的乌贼运动系统层次模型来实现。

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