Asymmetry as an indicator of stress: From population statistics to clinical life-saving applications

Abstract

Most symmetrical objects can be efficiently described in terms of their deviation from a specific symmetry group, whether it be a mirror, radial, or translatory symmetry, among other groups. Fundamentally, asymmetry is an individual trait, but the asymmetry distribution of a given population may provide valuable information about the well-being of that population. Quantification of these deviations from perfect symmetry evolved from counts and linear measures of distances to landmarks conducive to structures with consistent topology, and then to Continuous Symmetry Measures (CSM) conducive to structures with no consistent topology. We demonstrate the usefulness of this approach on quantification of leaf veins that mirror bifurcating structures. Deviations from a given symmetry group can be described in terms of (i) Fluctuating Asymmetries (FA) or (ii) broken asymmetries. Fluctuating Asymmetry (FA) is a controversial indicator of stress, and therefore tackling the problem needs a large number of species and populations in habitats with well-known stressors. We found such a site at “Evolution Canyon”, Israel, and we examine and discuss a study of twenty-four species that live in the canyon’s opposing slopes. We conclude with examples from asymmetry as a neurophysiological bioindicator by presenting several studies on Amyotrophic Lateral Sclerosis (ALS), Parkinson’s disease, and stroke. We show how machine-learning methods, applied on asymmetry indicators (in addition to the traditional signal processing features), can improve the sensitivity of the system and provide reliable diagnostic results.