@article {Laan018176, author = {Andres Laan}, title = {Intensity matching in cuttlefish}, elocation-id = {018176}, year = {2015}, doi = {10.1101/018176}, publisher = {Cold Spring Harbor Laboratory}, abstract = {For efficient background matching it is essential that animals closely match a set of salient visual statistics of their visual surroundings. The mean intensity of a background is a key statistic, because it can be estimated across a large range of viewing distances by a simple computation. We investigated how the dynamic neuromuscular camouflage system of the cuttlefish Sepia offcinalis responds to changes in the mean background intensity of uniform backgrounds. We find that cuttlefish adapt their body intensity in response to variations in the mean background intensity, yet show biases in their body intensity beyond what can be predicted from the limited dynamic range of their camouflage system. On sandy backgrounds of various reflectance values their uniform body patterns maintain a constant yellow hue. This color constancy may represent an example of a color prior in a colorblind animal because a yellow body color would be the optimal hue for camouflage on sands typically encountered in their natural environment. Cuttlefish adapt their appearance to the background via a dynamic process composed of a complex mixture of intensity transients spanning timescales from the subsecond to the minute range. In very young animals camouflaging on dark sands the masquerade strategy is preferred over background matching. Masquerade is implemented by combining partial background matching with frequent expression of disruptive components. We furthermore provide an objective definition of disruptive components using hierarchical clustering and automated image analysis thus highlighting the role of chromatophore activity correlations in structuring the motor output of S.officinalis.}, URL = {https://www.biorxiv.org/content/early/2015/04/16/018176}, eprint = {https://www.biorxiv.org/content/early/2015/04/16/018176.full.pdf}, journal = {bioRxiv} }