Quantitative Analysis of the Coordinated Movement of Cells in a Freely Moving Cell Population

Author:

Umetsu Daiki1ORCID,Yamaji Satoshi23,Wakita Daiki2ORCID,Kano Takeshi2ORCID

Affiliation:

1. Graduate School of Science, Osaka University, 1-1 Machikaneyama, Toyonaka, Osaka 560-0043, Japan

2. Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi 980-8577, Japan

3. Graduate School of Engineering, Tohoku University, 6-6-01 Aramaki Aza-Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan

Abstract

Coordinated movement of self-propelled agents has been well studied in collectives or swarms that display directional movement. Self-propelled agents also develop stable spatial patterns in which the agents do not necessarily exhibit directional collective movement. However, quantitative measures that are required to analyze the local and temporal coordinated movements during pattern formation processes have not been well established. Here, we study the coordinated movement of individual pairs of two different types of cells in a freely moving cell population. We introduced three criteria to evaluate coordinated movement in live imaging data obtained from the abdomen of the fruit fly, Drosophila melanogaster, at the pupal stage. All three criteria were able to reasonably identify coordinated movement. Our analysis indicates that the combined usage of these criteria can improve the evaluation of whether a pair of cells exhibits coordinated movement or not by excluding false positives. Quantitative approaches to identifying coordinated movement in a population of freely moving agents constitute a key foundational methodology to study pattern formations by self-propelled agents.

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Review of Interdisciplinary Approach to Swarm Intelligence;Journal of Robotics and Mechatronics;2023-08-20

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