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Modeling the Influence of Synaptic Plasticity on After-effects.
Journal of Biological Rhythms ( IF 2.9 ) Pub Date : 2019-08-22 , DOI: 10.1177/0748730419871189
Semra Foster 1, 2 , Tom Christiansen 1, 2 , Michael C Antle 1, 2, 3
Affiliation  

While circadian rhythms in physiology and behavior demonstrate remarkable day-to-day precision, they are also able to exhibit plasticity in a variety of parameters and under a variety of conditions. After-effects are one type of plasticity in which exposure to non-24-h light-dark cycles (T-cycles) will alter the animal's free-running rhythm in subsequent constant conditions. We use a mathematical model to explore whether the concept of synaptic plasticity can explain the observation of after-effects. In this model, the SCN is composed of a set of individual oscillators randomly selected from a normally distributed population. Each cell receives input from a defined set of oscillators, and the overall period of a cell is a weighted average of its own period and that of its inputs. The influence that an input has on its target's period is determined by the proximity of the input cell's period to the imposed T-cycle period, such that cells with periods near T will have greater influence. Such an arrangement is able to duplicate the phenomenon of after-effects, with relatively few inputs per cell (~4-5) being required. When the variability of periods between oscillators is low, the system is quite robust and results in minimal after-effects, while systems with greater between-cell variability exhibit greater magnitude after-effects. T-cycles that produce maximal after-effects have periods within ~2.5 to 3 h of the population period. Overall, this model demonstrates that synaptic plasticity in the SCN network could contribute to plasticity of the circadian period.

中文翻译:

建模突触可塑性对后效应的影响。

尽管生理和行为的昼夜节律表现出卓越的日常精度,但它们也能够在各种参数和各种条件下表现出可塑性。后效应是一种可塑性,其中暴露于非24小时的明暗循环(T循环)会在随后的恒定条件下改变动物的自由运动节奏。我们使用数学模型来探索突触可塑性的概念是否可以解释对后效应的观察。在此模型中,SCN由一组从正态分布总体中随机选择的单个振荡器组成。每个单元都从一组定义的振荡器接收输入,并且一个单元的总周期是其自身周期和其输入周期的加权平均值。输入对其目标的影响' s的周期由输入单元的周期与施加的T周期的接近程度决定,因此周期接近T的单元将具有更大的影响。这样的安排能够复制后效应现象,每个单元需要相对较少的输入(〜4-5)。当振荡器之间的周期的可变性较低时,系统将非常健壮,并产生最小的后效应,而具有较大单元间可变性的系统则表现出较大的后效应。产生最大后效应的T周期在种群周期的约2.5至3小时内。总体而言,该模型表明SCN网络中的突触可塑性可能有助于昼夜节律时期的可塑性。这样周期接近T的单元将具有更大的影响。这样的安排能够复制后效应现象,每个单元需要相对较少的输入(〜4-5)。当振荡器之间的周期的可变性较低时,系统将非常健壮,并产生最小的后效应,而具有较大单元间可变性的系统则表现出较大的后效应。产生最大后效应的T周期在种群周期的约2.5至3小时内。总体而言,该模型表明SCN网络中的突触可塑性可能有助于昼夜节律时期的可塑性。这样周期接近T的单元将具有更大的影响。这样的安排能够复制后效应现象,每个单元需要相对较少的输入(〜4-5)。当振荡器之间的周期的可变性较低时,系统将非常健壮,并产生最小的后效应,而具有较大单元间可变性的系统则表现出较大的后效应。产生最大后效应的T周期在种群周期的约2.5至3小时内。总体而言,该模型表明SCN网络中的突触可塑性可能有助于昼夜节律时期的可塑性。当振荡器之间的周期的可变性较低时,该系统将非常健壮,并产生最小的后效应,而具有较大单元间可变性的系统则表现出较大的后效应。产生最大后效应的T周期在种群周期的约2.5至3小时内。总体而言,该模型表明SCN网络中的突触可塑性可能有助于昼夜节律时期的可塑性。当振荡器之间的周期的可变性较低时,系统将非常健壮,并产生最小的后效应,而具有较大单元间可变性的系统则表现出较大的后效应。产生最大后效应的T周期的周期约为种群周期的2.5至3小时。总体而言,该模型表明SCN网络中的突触可塑性可能有助于昼夜节律时期的可塑性。
更新日期:2019-11-01
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