Work

Probing Asymmetric Interactions with Time-Separated Mutual Information: A Case Study Using Golden Shiners

Year: 2024

Type: article

Abstract: Leader–follower modalities and other asymmetric interactions that drive the collective motion of organisms are often quantified using information theory metrics like transfer or causation entropy. These metrics are difficult to accurately evaluate without a much larger number of data than is typically available from a time series of animal trajectories collected in the field or from experiments. In this paper, we use a generalized leader–follower model to argue that the time-separated mutual information between two organism positions can serve as an alternative metric for capturing asymmetric correlations that is much less data intensive and more accurately estimated by popular k-nearest neighbor algorithms than transfer entropy. Our model predicts a local maximum of this mutual information at a time separation value corresponding to the fundamental reaction timescale of the follower organism. We confirm this prediction by analyzing time series trajectories recorded for a pair of golden shiner fish circling an annular tank.

Source: Entropy

DOI: 10.3390/e26090775

Authors: Katherine Daftari, Michael L. Mayo, Bertrand H. Lemasson, James M. Biedenbach, Kevin R. Pilkiewicz

Institutions: University of North Carolina at Chapel Hill, United States Army, U.S. Army Engineer Research and Development Center

Language: English

Topic: Complex Systems and Time Series Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,955

Funder: U.S. Army Corps of Engineers