Decentralized Competition Produces Nonlinear Dynamics Akin to Klinotaxis

Pedro Manrique, Mason Klein, Yao Sheng Li, Chen Xu, Pak Ming Hui and Neil Johnson

Complexity, 2018, vol. 2018, 1-8

Abstract:

One of the biggest challenges in unravelling the complexity of living systems, is to fully understand the neural logic that translates sensory input into the highly nonlinear motor outputs that are observed when simple organisms crawl. Recent work has shown that organisms such as larvae that exhibit klinotaxis (i.e., orientation through lateral movements of portions of the body) can perform normal exploratory practices even in the absence of a brain. Abdominal and thoracic networks control the alternation between crawls and turns. This motivates the search for decentralized models of movement that can produce nonlinear outputs that resemble the experiments. Here, we present such a complex system model, in the form of a population of decentralized decision-making components (agents) whose aggregate activity resembles that observed in klinotaxis organisms. Despite the simplicity of each component, the complexity created by their collective feedback of information and actions akin to proportional navigation, drives the model organism towards a specific target. Our model organism’s nonlinear behaviors are consistent with empirically observed reorientation rate measures for Drosophila larvae as well as nematode C. elegans .

Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2018/9803239.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2018/9803239.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:9803239

DOI: 10.1155/2018/9803239

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().