Project

Circadian Rhythm in Neural Networks and in Social Networks

Publisher

Supervisor

Location

Greater Copenhagen area

Project background. In the human or in mammals, the sleep/wake cycle (circadian rhythm) is mainly regulated by the supra-chiasmatic nucleus (SCN): a network consisting of N ~ 10^4 neurons.
Neurons in the SCN oscillate with a period typically around 24.5 h, and synchronize their phases so that they exhibit a common rhythm so that they act like one giant clock: the SCN serves as a primary master clock to control physiological processes in our body that adhere to a circadian rhythms. Such processes are vital and occur at the level of the body, organs, hormone production and individual cells, where they control body temperature, blood pressure, stress hormone release etc. Without external stimuli, cells in the SCN is slightly longer than 24.5 h, and a human will go through a sleep/wake cycle that is out of phase with the natural day/night cycle. However, under the sun's (or other) influence, the SCN's rhythm is locked to an exact 24 h cycle and matches the sun's cycle.
-- Why is this important? The absence of a regular daily activity or night work  occurs in particular for shift workers, but may also for people who are exposed to frequent jet lag. Entrainment to a regular circadian 24 h rhythm may be compromised by jet-lag or shift work. Failure to maintain a regular circadian rhythm increases risk for disease including clinical depression and cancer among other. While the solar activity is a primary effect entraining the circadian clock to an exact 24 h cycle, other important influences exist, in particular, social interactions. Thus, the social network and its interactions may greatly affect the ability to synchronize individual person's day/night rhythm.

Project aims and questions.
The project builds and extends on existing literature.
Model 1: What is the dynamic behavior of neurons with periodic forcing?  What is the transient dynamics during re-synchronization after a one-time perturbation (such as jet lag)?  Optimized methods to boost the re-synchronization process in terms of speed, e.g. via specially designed light devises?
Model 2: What has a stronger impact on resetting the circadian clock to T = 24 h, the sun's activity or stimuli from social interaction? How and when do people in a social network synchronize their day/night rhythms? How do model predictions match social network data?

Methods: bifurcation theory, dynamical systems theory, data analysis,  simulation, dimensional reduction, network theory.



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Contact

Company / Organization

DTU Compute

Name

Erik Andreas Martens

Position

Lektor

Mail

eama@dtu.dk

Supervisor info

BSc in Mathematics and Technology

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

MSc Eng in Quantitative Biology and Disease Modelling

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

MSc in Biomedical Engineering

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

MSc in Electrical Engineering

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

MSc in Mathematical Modelling and Computation

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

MSc in Physics and Nanotechnology

Supervisor

Erik Andreas Martens

Co-supervisors

Poul G. Hjorth, Sune Lehmann Jørgensen

ECTS credits

30

Type

MSc thesis

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