Skip to main content Accessibility help
×
Home
  • Print publication year: 2012
  • Online publication date: September 2012

Chapter 18 - Fatigue management: the art of the state

from Section 4 - Summary and Conclusions

Summary

Histamine (HA) is a biogenic amine, providing a number of functional roles throughout the body. HA release triggers inflammatory responses as a protective reaction against foreign pathogens. Released from basophils and mast cells in the periphery, HA causes increased vascular permeability and dilation of blood vessels to allow increased fluid infiltration into tissues which in turn induces swelling. Research designed to test the role of HA in mediating central nervous system (CNS) activity demonstrated that HA immunoreactive brain neurons actively fire action potentials and release HA during the wake phase but are essentially silent during sleep, supporting the hypothesis that increased HA tone is related to levels of wakefulness. Results of experiments investigating the effects of HA in the CNS, either through direct injection of HA or through pharmacological inhibition of its synthesis, show that increases in HA are positively correlated with amounts of wakefulness.

References

[7] CzeislerCA, DuffyJF, ShanahanTL, et al. Stability, precision, and near-24-hour period of the human circadian pacemaker. Science 1999; 284: 2177–81.
[8] Van DongenH. Comparison of mathematical model predictions to experimental data of fatigue and performance. Aviat Space Environ Med 2004; 75(3 Suppl): A15–36.
[9] MallisMM, MejdalS, NguyenTT, DingesDF. Summary of the key features of seven biomathematical models of human fatigue and performance. Aviat Space Environ Med 2004; 75(3 Suppl): A4–14.
[10] Dean DA 2nd, FletcherA, HurshSR, KlermanEB. Developing mathematical models of neurobehavioral performance for the “real world”. J Biol Rhythms 2007; 22(3): 246–58.
[11] DingesDF. Critical research issues in development of biomathematical models of fatigue and performance. Aviat Space Environ Med 2004;75(3Suppl): A181–91.
[12] FriedlKE, MallisMM, AhlersST, PopkinSM, LarkinW. Research requirements for operational decision-making using models of fatigue and performance. Aviat Space Environ Med. 2004; 75(3 Suppl): A192–9.
[13] BorbelyAA, AchermannP. Concepts and models of sleep regulation: an overview. J Sleep Res 1992; 1(2): 63–79.
[14] AkerstedtT, FolkardS. The three-process model of alertness and its extension to performance, sleep latency, and sleep length. Chronobiol Int 1997; 14(2): 115–23.
[15] HurshSR, RedmondDP, JohnsonML, et al. Fatigue models for applied research in warfighting. Aviat Space Environ Med 2004; 75(3 Suppl): A44–53.
[16] BelenkyG, WesenstenNJ, ThorneDR, et al. Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J Sleep Res 2003; 12(1): 1–12.
[17] Van DongenHP, MaislinG, MullingtonJM, DingesDF. The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 2003; 26(2): 117–26.
[18] JohnsonML, BelenkyG, RedmondDP, et al. Modulating the homeostatic process to predict performance during chronic sleep restriction. Aviat Space Environ Med 2004; 75(3 Suppl): A141–6.
[19] McCauleyP, KalachevLV, SmithAD, et al. A new mathematical model for the homeostatic effects of sleep loss on neurobehavioral performance. J Theor Biol 2009; 256(2): 227–39.
[20] RuppTL, WesenstenNJ, BliesePD, BalkinTJ. Banking sleep: realization of benefits during subsequent sleep restriction and recovery. Sleep 2009; 32(3): 311–21.
[25] National Transportation Safety Board. Uncontrolled Collision with Terrain American International Airways Flight 808, Douglas DC-8-61, N814CK. NTSB Report #AAR-94-04, NTIS #PB94-910406.
[27] Van DongenHP, MottCG, HuangJK, et al. Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes. Sleep 2007; 30(9): 1129–43.
[28] RajaramanS, GribokAV, WesenstenNJ, BalkinTJ, ReifmanJ. Individualized performance prediction of sleep-deprived individuals with the two-process model. J Appl Physiol 2008; 104(2): 459–68.
[29] RajaramanS, GribokAV, WesenstenNJ, BalkinTJ, ReifmanJ. An improved methodology for individualized performance prediction of sleep-deprived individuals with the two-process model. Sleep 2009; 32(10): 1377–92.
[30] BalkinTJ, KamimoriGH, RedmondDP, et al. On the importance of countermeasures in sleep and performance models. Aviat Space Environ Med 2004; 75(3 Suppl): A155–7.
[31] Benitez BenitezPL, KamimoriGH, BalkinTJ, GreeneA, JohnsonML. Modeling fatigue over sleep deprivation, circadian rhythm, and caffeine with a minimal performance inhibitor model. Methods Enzymol 2009; 454: 405–21.
[32] PuckeridgeM, FulcherBD, PhillipsAJ, RobinsonPA. Incorporation of caffeine into a quantitative model of fatigue and sleep. J Theor Biol 2011; 273(1): 44–54.
[33] BalkinTJ, BadiaP. Relationship between sleep inertia and sleepiness: cumulative effects of four nights of sleep disruption/restriction on performance following abrupt nocturnal awakenings. Biol Psychol 1988; 27(3): 245–58.
[34] TassiP, MuzetA. Sleep inertia. Sleep Medicine Reviews 2000; 4(4): 341–53.