Limits of Entrainment of Circadian Neuronal Networks
- URL: http://arxiv.org/abs/2208.11119v1
- Date: Tue, 23 Aug 2022 17:57:21 GMT
- Title: Limits of Entrainment of Circadian Neuronal Networks
- Authors: Yorgos M. Psarellis, Michail Kavousanakis, Michael A. Henson, Ioannis
G. Kevrekidis
- Abstract summary: Circadian rhythmicity lies at the center of various important physiological and behavioral processes in mammals.
We study a modern computational neuroscience model to determine the limits of circadian synchronization to external light signals of different frequency and duty cycle.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Circadian rhythmicity lies at the center of various important physiological
and behavioral processes in mammals, such as sleep, metabolism, homeostasis,
mood changes and more. It has been shown that this rhythm arises from
self-sustained biomolecular oscillations of a neuronal network located in the
Suprachiasmatic Nucleus (SCN). Under normal circumstances, this network remains
synchronized to the day-night cycle due to signaling from the retina.
Misalignment of these neuronal oscillations with the external light signal can
disrupt numerous physiological functions and take a long-lasting toll on health
and well-being. In this work, we study a modern computational neuroscience
model to determine the limits of circadian synchronization to external light
signals of different frequency and duty cycle. We employ a matrix-free approach
to locate periodic steady states of the high-dimensional model for various
driving conditions. Our algorithmic pipeline enables numerical continuation and
construction of bifurcation diagrams w.r.t. forcing parameters. We
computationally explore the effect of heterogeneity in the circadian neuronal
network, as well as the effect of corrective therapeutic interventions, such as
that of the drug molecule Longdaysin. Lastly, we employ unsupervised learning
to construct a data-driven embedding space for representing neuronal
heterogeneity.
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