Behavior dynamics at high temporal resolutions: the relevance of a right scale for sampling

Abstract

Abstract Many species used in behavioral studies are small vertebrates with high metabolic rates and potentially enhanced temporal resolution of perception. Nevertheless, the temporal organization of behaviors at fast time scales (≤ 1s) has received little attention. Herein, we studied the temporal organization of behaviors at short time scales to gain insight into behavioral dynamics and to rethink how behavioral events are defined. We statistically explored high-resolution quail (Coturnix japonica) datasets encompassing 17 coarse- and fine-grained defined behaviors. We show that for the majority of these behaviors, events last predominately < 300ms and can be shorter than 70ms. Insufficient sampling resolution, even in the order of 1s, of behaviors that involve spatial displacement (e.g. walking) yields distorted probability distributions of event durations and overestimation of event durations. Contrarily, behaviors without spatial displacement (e.g. vigilance) maintain non-Gaussian, power-law-type distributions indicative of long-term memory, independently of the sampling resolution evaluated. Since data probability distributions reflect underlying biological processes, our results highlight the importance of quantification of behavioral dynamics based on the temporal scale pertinent to the species, and data distribution. We propose a hierarchical model that links diverse types of behavioral definitions and distributions, and paves the way towards a statistical framework for defining behaviors.