The role of network structure in circadian system adaptation
ORAL
Abstract
Circadian rhythms, physiological and behavioral changes following a 24-hour cycle, are a ubiquitous feature of life on Earth. While they persist in constant conditions, they can be entrained to environmental cues such as light. Nearly every cell in animals has an autonomous molecular oscillator, which are synchronized by a network of cellular interactions.
This complex system has previously been modeled as a globally connected network of limit cycle oscillators. However, this simple model does not account for any internal structure that might influence its robustness and adaptation to external influences. Our goal is to understand the relationship between the structural properties of this network and its response to changes in the environment.
We focus on the phenomenon of jet lag as an example: adjusting to a new time-zone after flying westward is generally easier than flying eastward. Starting from an all-to-all connected network of Kuramoto oscillators, we make systematic changes to the structure and quantify the east/west adjustment asymmetry in each case. We find that hierarchical networks have the most gradual and asymmetrical re-entrainment and regular networks the least. These insights may also be applied to other adaptable networked systems.
This complex system has previously been modeled as a globally connected network of limit cycle oscillators. However, this simple model does not account for any internal structure that might influence its robustness and adaptation to external influences. Our goal is to understand the relationship between the structural properties of this network and its response to changes in the environment.
We focus on the phenomenon of jet lag as an example: adjusting to a new time-zone after flying westward is generally easier than flying eastward. Starting from an all-to-all connected network of Kuramoto oscillators, we make systematic changes to the structure and quantify the east/west adjustment asymmetry in each case. We find that hierarchical networks have the most gradual and asymmetrical re-entrainment and regular networks the least. These insights may also be applied to other adaptable networked systems.
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Presenters
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Sneha Kachhara
Northwestern University
Authors
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Sneha Kachhara
Northwestern University
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Rosemary Braun
Northwestern University