Cats understand the principle of cause and effect as well as some elements of physics. Combining these abilities with their keen sense of hearing, they can predict where possible prey¹ hides. These are the findings of researchers from Kyoto University in Japan, led by Saho Takagi and published in Springer's journal Animal Cognition. Previous work conducted by the Japanese team established that cats predict the presence of invisible objects based on what they hear. In the present study, the researchers wanted to find out if cats use a causal rule to infer if a container holds an object, based on whether it is shaken along with a sound or not. The team also wanted to establish if cats expect an object to fall out or not, once the container is turned over.

 

Thirty domestic cats were videotaped while an experimenter shook a container. In some cases this action went along with a rattling² sound. In others it did not, to simulate that the vessel³ was empty. After the shaking phase, the container was turned over, either with an object dropping down or not.

 

Two experimental conditions were congruent with physical laws, where shaking was accompanied by a (no) sound and an (no) object to fall out of the container. The other two conditions were incongruent to the laws of physics. Either a rattling sound was followed by no object dropping out of the container or no sound while shaking led to a falling object.

 

The cats looked longer at the containers which were shaken together with a noise. This suggests that cats used a physical law to infer the existence (or absence) of objects based on whether they heard a rattle⁴ (or not). This helped them predict whether an object would appear (or not) once the container was overturned.

 

The animals also stared longer at containers in incongruent conditions, meaning an object dropped despite its having been shaken noiselessly or the other way around. It is as if the cats realized that such conditions did not fit into their grasp of causal logic⁵.

 

"Cats use a causal-logical understanding of noise or sounds to predict the appearance of invisible objects," says Takagi.

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