Summary
Cephalopod camouflage (or crypsis) is one of the most fascinating behaviors in the animal kingdom. It is also very relevant for neuroscience, for many reasons. First, the ability of cephalopods to escape detection by vertebrate predators or invertebrate prey indicates that the perception of textures must follow similar principles in most species; if they did not, crypsis would not be successful. Because cephalopods and vertebrates diverged over 550 M years ago from a primitive common ancestor, these principles must reflect functional convergence. Second, cryptic patterning gives observers a read-out of an animal’s perception of visual scenes, eliminating the need for complex behavioral paradigms to question the animal. Third, cephalopod camouflage is controlled neurally by the brain, through the action of motoneurons onto a large array of specialized pigment cells (chromatophores) and based on visual information received by single-lens eyes. The behavior thus consists in transforming a retinal image into a matching skin pattern, via a large central brain and ultimately in the form of a fine motor output. Fourth, crypsis works as a statistical approximation rather than faithful copy of a scene. Such statistical matching is non-trivial: convolutional neural networks, for example, need hundreds of thousands of training trials to reach good performance. Fifth, because skin chromatophores are controlled by motoneurons, a chromatophore-resolution read-out of the state of the skin is an indirect read-out of the brain’s output, enabling large-scale neural imaging by proxy. This observation led us to develop methods to describe the skin output of cuttlefish at sub-chromatophore resolution and 25-60 frames/s, over hours to months. Our results in turn led to functional and mechanistic predictions about camouflage control. This 5-year project will test some of these predictions using molecular, ultrastructural, computational, physiological and behavioral approaches.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101141501 |
| Start date: | 01-08-2024 |
| End date: | 31-07-2029 |
| Total budget - Public funding: | 2 499 758,00 Euro - 2 499 758,00 Euro |
Cordis data
Original description
Cephalopod camouflage (or crypsis) is one of the most fascinating behaviors in the animal kingdom. It is also very relevant for neuroscience, for many reasons. First, the ability of cephalopods to escape detection by vertebrate predators or invertebrate prey indicates that the perception of textures must follow similar principles in most species; if they did not, crypsis would not be successful. Because cephalopods and vertebrates diverged over 550 M years ago from a primitive common ancestor, these principles must reflect functional convergence. Second, cryptic patterning gives observers a read-out of an animal’s perception of visual scenes, eliminating the need for complex behavioral paradigms to question the animal. Third, cephalopod camouflage is controlled neurally by the brain, through the action of motoneurons onto a large array of specialized pigment cells (chromatophores) and based on visual information received by single-lens eyes. The behavior thus consists in transforming a retinal image into a matching skin pattern, via a large central brain and ultimately in the form of a fine motor output. Fourth, crypsis works as a statistical approximation rather than faithful copy of a scene. Such statistical matching is non-trivial: convolutional neural networks, for example, need hundreds of thousands of training trials to reach good performance. Fifth, because skin chromatophores are controlled by motoneurons, a chromatophore-resolution read-out of the state of the skin is an indirect read-out of the brain’s output, enabling large-scale neural imaging by proxy. This observation led us to develop methods to describe the skin output of cuttlefish at sub-chromatophore resolution and 25-60 frames/s, over hours to months. Our results in turn led to functional and mechanistic predictions about camouflage control. This 5-year project will test some of these predictions using molecular, ultrastructural, computational, physiological and behavioral approaches.Status
SIGNEDCall topic
ERC-2023-ADGUpdate Date
17-11-2024
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