Modeling homeostatic and circadian modulation of human pain sensitivity

被引:2
作者
Crodelle, Jennifer [1 ]
Vanty, Carolyn [1 ]
Booth, Victoria [2 ]
机构
[1] Middlebury Coll, Dept Math, Middlebury, VT 05753 USA
[2] Univ Michigan, Dept Math & Anesthesiol, Ann Arbor, MI 48109 USA
关键词
thermal pain; sleep-wake flip-flop; circadian clock; sleep deprivation; jet lag; sleep homeostasis; pain sensitivity; SLEEP-DEPRIVATION; INTERINDIVIDUAL DIFFERENCES; MATHEMATICAL-MODEL; DIURNAL-VARIATION; DYNAMICS; PHYSIOLOGY; DECREASES; CLOCK; CYCLE;
D O I
10.3389/fnins.2023.1166203
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
IntroductionMathematical modeling has played a significant role in understanding how homeostatic sleep pressure and the circadian rhythm interact to influence sleep-wake behavior. Pain sensitivity is also affected by these processes, and recent experimental results have measured the circadian and homeostatic components of the 24 h rhythm of thermal pain sensitivity in humans. To analyze how rhythms in pain sensitivity are affected by disruptions in sleep behavior and shifts in circadian rhythms, we introduce a dynamic mathematical model for circadian and homeostatic regulation of sleep-wake states and pain intensity. MethodsThe model consists of a biophysically based, sleep-wake regulation network model coupled to data-driven functions for the circadian and homeostatic modulation of pain sensitivity. This coupled sleep-wake-pain sensitivity model is validated by comparison to thermal pain intensities in adult humans measured across a 34 h sleep deprivation protocol. ResultsWe use the model to predict dysregulation of pain sensitivity rhythms across different scenarios of sleep deprivation and circadian rhythm shifts, including entrainment to new environmental light and activity timing as occurs with jet lag and chronic sleep restriction. Model results show that increases in pain sensitivity occur under conditions of increased homeostatic sleep drive with nonlinear modulation by the circadian rhythm, leading to unexpected decreased pain sensitivity in some scenarios. DiscussionThis model provides a useful tool for pain management by predicting alterations in pain sensitivity due to varying or disrupted sleep schedules.
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页数:13
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