A computational neuroscience framework for quantifying warning signals
A computational neuroscience framework for quantifying warning signals
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用于量化警告信号的计算神经科学框架
DOI：
10.1111/2041-210x.14268
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发表时间：
2023
影响因子：
6.6
通讯作者：
Penacchio O
中科院分区：
文献类型：
--
作者：
Penacchio O
动物警告信号显示出显著的多样性，但主观上似乎共享某些视觉特征，使防御猎物脱颖而出，看起来不同于更神秘的美味物种。例如，许多（但远非所有）警告信号涉及高对比度元素，如条纹和斑点，并且通常涉及黄色和红色。警戒性物种与非警戒性物种在捕食者的眼睛（和大脑）上到底有什么不同？在这里，我们开发了一种新的计算建模方法，以量化猎物的警告信号，并建立它们共享的视觉特征。首先，我们开发了一个模型的视觉系统，由人工神经元与现实的感受野，提供一个定量的估计神经活动的第一阶段的视觉系统的捕食者在响应模式。该系统可以针对特定物种进行定制。其次，我们建立了一个新的模型，定义了一个“神经签名”，包括定量指标，衡量刺激的神经元群体的强度响应模式。该框架允许我们测试个体模式如何刺激模型捕食者视觉系统。对于捕食鳞翅目猎物的鸟类捕食者-猎物系统，我们比较了模型鸟类视觉系统对警戒和无防御蝴蝶和飞蛾的高光谱图像的刺激强度。警告信号在模型视觉系统中产生明显更强的活动，将它们与不设防物种的模式区分开来。这种活动也与对自然场景的反应大不相同。因此，对于捕食者而言，鳞翅目昆虫的警告模式与其非防御性的同类不同，并在一系列自然背景下脱颖而出。我们首次提出了一个客观和定量的警告信号定义，该定义基于模式如何在接收者大脑的神经模型中产生种群活动。这为理解和测试警告信号是如何演变的，以及更普遍的感觉系统如何约束信号设计开辟了新的视角。
Animal warning signals show remarkable diversity, yet subjectively appear to share certain visual features that make defended prey stand out and look different from more cryptic palatable species. For example, many (but far from all) warning signals involve high contrast elements, such as stripes and spots, and often involve the colours yellow and red. How exactly do aposematic species differ from non‐aposematic ones in the eyes (and brains) of their predators?Here, we develop a novel computational modelling approach, to quantify prey warning signals and establish what visual features they share. First, we develop a model visual system, made of artificial neurons with realistic receptive fields, to provide a quantitative estimate of the neural activity in the first stages of the visual system of a predator in response to a pattern. The system can be tailored to specific species. Second, we build a novel model that defines a ‘neural signature’, comprising quantitative metrics that measure the strength of stimulation of the population of neurons in response to patterns. This framework allows us to test how individual patterns stimulate the model predator visual system.For the predator–prey system of birds foraging on lepidopteran prey, we compared the strength of stimulation of a modelled avian visual system in response to a novel database of hyperspectral images of aposematic and undefended butterflies and moths. Warning signals generate significantly stronger activity in the model visual system, setting them apart from the patterns of undefended species. The activity was also very different from that seen in response to natural scenes. Therefore, to their predators, lepidopteran warning patterns are distinct from their non‐defended counterparts and stand out against a range of natural backgrounds.For the first time, we present an objective and quantitative definition of warning signals based on how the pattern generates population activity in a neural model of the brain of the receiver. This opens new perspectives for understanding and testing how warning signals have evolved, and, more generally, how sensory systems constrain signal design.
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影响因子：
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作者：
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影响因子：
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DOI：
--
发表时间：
2004
期刊：
Proceedings of the Royal Society of London. Series B: Biological Sciences
影响因子：
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DOI：
--
发表时间：
1996
期刊：
Journal of Comparative Physiology
影响因子：
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DOI：
--
发表时间：
1990
期刊：
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