Brain–body mass ratio

Résumé

Brain–body mass ratio, also known as the brain–body weight ratio, is the ratio of brain mass to body mass, which is hypothesized to be a rough estimate of the intelligence of an animal, although fairly inaccurate in many cases. A more complex measurement, encephalization quotient, takes into account allometric effects of widely divergent body sizes across several taxa. The raw brain-to-body mass ratio is however simpler to come by, and is still a useful tool for comparing encephalization within species or between fairly closely related species. TOC Brain–body size relationship Brain size usually increases with body size in animals (i.e. large animals usually have larger brains than smaller animals); the relationship is not, however, linear. Small mammals such as mice may have a brain/body ratio similar to humans, while elephants have a comparatively lower brain/body ratio. In animals, it is thought that the

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https://en.wikipedia.org/wiki/Brain%E2%80%93body_mass_ratio

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Robotic fish are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. In the context of our research on the social interactions of the zebrafish Danio Rerio, we developed a miniature robotic fish lure for direct underwater interaction with the living fish. This remotely controlled and waterproof device has a total length of 7.5 cm with the same size ratio as zebrafish and is able to beat its tail with different frequencies and amplitudes, while following the group of living animals using a mobile robot moving outside water that is coupled with the robotic lure using magnets. The robotic lure is also equipped with an easily rechargeable battery and can be used autonomously underwater for experiments of up to one hour. We performed experiments with the robot moving inside an aquarium with living fish in order to analyze its impact on the zebrafish behavior. We found that the beating rate of the tail increased the attractiveness of the lure among the zebrafish shoal. We also demonstrated that the lure could influence a collective decision of the zebrafish shoal, the swimming direction, when moving with a constant linear speed inside a circular corridor. This new robotic fish design and the experimental results are promising for the field of fish-robot interaction.

Springer2015

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Infiltrating the zebrafish swarm: design, implementation and experimental tests of a miniature robotic fish lure for fish–robot interaction studies

Frank Bonnet, Yuta Kato, Francesco Mondada

Robotic fish are nowadays developed for various types of research, such as bio-inspiredrobotics, biomimetics and animal behavior studies. In the context of our research on the social interactions of the zebrafish Danio Rerio, we developed a miniature robotic fish lure for direct underwater interaction with the living fish. This remotely controlled and waterproof device has a total length of 7.5 cm with the same size ratio as zebrafish and is able to beat its tail with different frequencies and amplitudes, while following the group of living animals using a mobile robot moving outside water that is coupled with the robotic lure using magnets. The robotic lure is also equipped with a rechargeable battery and can be used autonomously underwater for experiments of up to 1 h. We performed experiments with the robot moving inside an aquarium with living fish to analyze its impact on the zebrafish behavior. We found that the beating rate of the tail increased the attractiveness of the lure among the zebrafish shoal. We also demonstrated that the lure could influence a collective decision of the zebrafish shoal, the swimming direction, when moving with a constant linear speed inside a circular corridor. This new robotic fish design and the experimental results are promising for the field of fish–robot interaction.

Springer Verlag2016

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Predictability, efference copies, and non-retinotopic motion

Michael Herzog, Marc Michael Lauffs

Perception is usually non-retinotopic. For example, visual perception is stable even though the retinal image is constantly changing due to eye and body movements. Likewise, a reflector on the wheel of a bicycle is perceived to rotate on a circular orbit, while its “true” motion (in retinotopic or exogenous coordinates) is cycloidal. In the first example, the brain uses efference copies to predict and compensate for eye movements. But how does the brain compensate for motion without efference copies? To investigate non-retinotopic motion perception, we used the Ternus-Pikler display. Two disks are flashed on a computer screen. A dot moves linearly up-down in the left disk and left-right in the right disk (retinotopic percept). If a third disk is added alternatingly to the left and right, the three disks form a group moving back and forth horizontally. The dot in the central disk now appears to move on a circular orbit (non-retinotopic percept), because the brain subtracts the horizontal group motion from the combination of the up-down and left-right motion. Here, we asked whether predictability is necessary to compute non-retinotopic motion. In experiment 1, the three disks moved randomly in any direction, rather than horizontally back and forth. Still, a strong non-retinotopic dot rotation was perceived. In experiment 2, we additionally varied the shape and contrast polarity of the stimuli from frame to frame. Still, a strong non-retinotopic dot rotation was perceived. Hence, the visual system can flexibly solve the non-retinotopic motion correspondence problem, even when the retinotopic reference motion is unpredictable. It seems that, in the case of non-retinotopic motion, the brain computes the reference-frame in real-time and does not need efference copy-like signals based on the predictability of the stimulus.

2015

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