Modeling the Influence of Synaptic Plasticity on After-effects

Area of Science:

• Chronobiology
• Neuroscience
• Mathematical Biology

Background:

• Circadian rhythms exhibit daily precision but also plasticity.
• After-effects, where altered light-dark cycles change rhythms, are a form of this plasticity.

Purpose of the Study:

• To investigate if synaptic plasticity within the suprachiasmatic nucleus (SCN) network can account for observed circadian after-effects.
• To model the influence of synaptic plasticity on circadian period adaptability.

Main Methods:

• Developed a mathematical model of the SCN network, comprising individual oscillators with a normally distributed period range.
• Modeled cell period as a weighted average of intrinsic period and inputs, with input influence dependent on period proximity to the imposed T-cycle.
• Simulated exposure to non-24-h light-dark cycles (T-cycles) and analyzed subsequent free-running rhythms.

Main Results:

• The model successfully replicated the phenomenon of circadian after-effects.
• Relatively few inputs per cell (approximately 4-5) were sufficient to generate after-effects.
• Higher between-cell period variability in the SCN network led to greater after-effect magnitudes.
• T-cycles with periods 2.5-3 h different from the population period induced maximal after-effects.

Conclusions:

• Synaptic plasticity within the SCN network is a plausible mechanism contributing to the plasticity of the circadian period.
• The degree of circadian after-effects is influenced by the variability of intrinsic periods among SCN oscillators.