Computational geometric tools for quantitative comparison of locomotory behavior

Matthew T Stamps,Soo Go,Ajay S Mathuru

doi:10.1038/s41598-019-52300-8

Matthew T Stamps, Soo Go + Show 1 more

Open Access

https://doi.org/10.1038/s41598-019-52300-8

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Abstract

A fundamental challenge for behavioral neuroscientists is to accurately quantify (dis)similarities in animal behavior without excluding inherent variability present between individuals. We explored two new applications of curve and shape alignment techniques to address this issue. As a proof-of-concept we applied these methods to compare normal or alarmed behavior in pairs of medaka (Oryzias latipes). The curve alignment method we call Behavioral Distortion Distance (BDD) revealed that alarmed fish display less predictable swimming over time, even if individuals incorporate the same action patterns like immobility, sudden changes in swimming trajectory, or changing their position in the water column. The Conformal Spatiotemporal Distance (CSD) technique on the other hand revealed that, in spite of the unpredictability, alarmed individuals exhibit lower variability in overall swim patterns, possibly accounting for the widely held notion of “stereotypy” in alarm responses. More generally, we propose that these new applications of established computational geometric techniques are useful in combination to represent, compare, and quantify complex behaviors consisting of common action patterns that differ in duration, sequence, or frequency.

Highlights

A fundamental challenge for behavioral neuroscientists is to accurately quantifysimilarities in animal behavior without excluding inherent variability present between individuals
Motivated by a classic result in differential geometry called the Frenet-Serret Formula[27], we introduce the notion of a behavior curve associated to an animal’s trajectory and derive a measure that we call the Behavioral Distortion Distance (BDD)
Complex behaviors with common action patterns or modules, albeit in exaggerated or in compressed forms, can be precluded from identification as different. To address this issue we investigated two new applications of known techniques in computational geometry for curve alignment, which we call the Behavioral Distortion Distance or BDD, and for surface alignment that we call the Conformal Spatiotemporal Distance or CSD

Summary

Introduction

A fundamental challenge for behavioral neuroscientists is to accurately quantify (dis)similarities in animal behavior without excluding inherent variability present between individuals. In examining the entire behavioral repertoire www.nature.com/scientificreports of the hydra[9], for automated annotation of behavior in fruit flies[10], for discovering generative rules governing Drosophila locomotion[11], for identifying the temporal features that explain spontaneous swimming behavior in worms[12], for identifying the dynamics of shoaling in fish[13], and for detecting sub-second modules in mice behavior[14] Such studies are providing new insights like the continuity between behavioral states[15], between the generative rules of locomotion of vertebrates and invertebrates[11], and objective means for comparison of new data-sets to perform spatiotemporal mapping of posture of non-stereotyped actions[7]. Motivated by a classic result in differential geometry called the Frenet-Serret Formula[27], we introduce the notion of a behavior curve associated to an animal’s trajectory and derive a measure that we call the Behavioral Distortion Distance (BDD) This can be efficiently calculated via dynamic time warping to provide meaningful quantitative comparisons for entire episodes of locomotion

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