High mirror symmetry in mouse exploratory behavior

TL;DR

This study reveals that mouse exploratory behavior shows high mirror symmetry, suggesting underlying constraints that shape their movement patterns.

Contribution

The paper introduces a novel phenomenon of high mirror symmetry in mouse locomotion and links it to a neural mechanism.

Findings

Mouse exploratory behavior exhibits high mirror symmetry in locomotion.

Adding constraints to locomotion retains the characteristic 'mousiness' in behavior.

The findings are linked to a known neural mechanism that may explain the symmetry.

Abstract

The physicality of the world in which the animal acts—its anatomical structure, physiology, perception, emotional states, and cognitive capabilities—determines the boundaries of the behavioral space within which the animal can operate. Behavior, therefore, can be considered as the subspace that remains after secluding all actions that are not available to the animal due to constraints. The very signature of being a certain creature is reflected in these limitations that shape its behavior. A major goal of ethology is to expose those constraints that carve the intricate structure of animal behavior and reveal both uniqueness and commonalities between animals within and across taxa. Exploratory behavior in an empty arena seems to be stochastic; nevertheless, it does not mean that the moving animal is a random walker. In this study, we present how, by adding constraints to the animal’s locomotion, one can gradually retain the ‘mousiness’ that characterizes the behaving mouse. We then introduce a novel phenomenon of high mirror symmetry along the locomotion of mice, which highlights another constraint that further compresses the complex nature of exploratory behavior in these animals. We link these findings to a known neural mechanism that could explain this phenomenon. Finally, we suggest our novel finding and derived methods to be used in the search for commonalities in the motion trajectories of various organisms across taxa.

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