Display options
Share it on

Front Neuroinform. 2013 Dec 05;7:33. doi: 10.3389/fninf.2013.00033. eCollection 2013.

Electroencephalogram approximate entropy influenced by both age and sleep.

Frontiers in neuroinformatics

Gerick M H Lee, Sara Fattinger, Anne-Laure Mouthon, Quentin Noirhomme, Reto Huber

Affiliations

  1. Institute of Neuroinformatics, University of Zurich and ETH Zurich Zurich, Switzerland ; Child Development Center, University Children's Hospital Zurich Zurich, Switzerland.
  2. Child Development Center, University Children's Hospital Zurich Zurich, Switzerland.
  3. Coma Science Group, Neurology Department, Cyclotron Research Centre, University Hospital of Liège, University of Liège Liège, Belgium.

PMID: 24367328 PMCID: PMC3852001 DOI: 10.3389/fninf.2013.00033

Abstract

The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done to investigate the applicability of such measures to children. For our work, we used the approximate entropy (ApEn), a measure previously shown to correlate with changes in conscious state when applied to the electroencephalogram (EEG), and sought to confirm whether previously reported trends in adult ApEn values across wake and sleep were present in children. Besides validating the prior findings that ApEn decreases from wake to sleep (including wake, rapid eye movement (REM) sleep, and non-REM sleep) in adults, we found that previously reported ApEn decreases across vigilance states in adults were also present in children (ApEn trends for both age groups: wake > REM sleep > non-REM sleep). When comparing ApEn values between age groups, adults had significantly larger ApEn values than children during wakefulness. After the application of an 8 Hz high-pass filter to the EEG signal, ApEn values were recalculated. The number of electrodes with significant vigilance state effects dropped from all 109 electrodes with the original 1 Hz filter to 1 electrode with the 8 Hz filter. The number of electrodes with significant age effects dropped from 10 to 4. Our results support the notion that ApEn can reliably distinguish between vigilance states, with low-frequency sleep-related oscillations implicated as the driver of changes between vigilance states. We suggest that the observed differences between adult and child ApEn values during wake may reflect differences in connectivity between age groups, a factor which may be important in the use of EEG to measure consciousness.

Keywords: approximate entropy; consciousness; development; electroencephalogram; sleep

References

  1. Ann N Y Acad Sci. 2008;1129:330-4 - PubMed
  2. Proc Natl Acad Sci U S A. 2007 May 15;104(20):8496-501 - PubMed
  3. Brain Res Bull. 2003 Dec 15;62(2):143-50 - PubMed
  4. Clin Neurophysiol. 2007 Jan;118(1):31-52 - PubMed
  5. Clin Neurophysiol. 2007 Feb;118(2):449-56 - PubMed
  6. J Psychiatr Res. 1982-1983;17(4):319-34 - PubMed
  7. Sleep. 2002 Sep 15;25(6):606-14 - PubMed
  8. Clin EEG Neurosci. 2005 Jan;36(1):21-4 - PubMed
  9. J Neurophysiol. 2001 May;85(5):1969-85 - PubMed
  10. Med Biol Eng Comput. 2008 Oct;46(10):1019-28 - PubMed
  11. Science. 2005 Sep 30;309(5744):2228-32 - PubMed
  12. Clin Neurophysiol. 2007 Sep;118(9):1906-22 - PubMed
  13. Clin Neurophysiol. 2008 Sep;119(9):2026-36 - PubMed
  14. Anesthesiology. 2000 Oct;93(4):981-5 - PubMed
  15. Anesthesiology. 2008 Sep;109(3):448-56 - PubMed
  16. J Comp Neurol. 1997 Oct 20;387(2):167-78 - PubMed
  17. Math Biosci. 1994 Aug;122(2):161-81 - PubMed
  18. Hum Brain Mapp. 2007 Mar;28(3):228-37 - PubMed
  19. Electroencephalogr Clin Neurophysiol. 1988 Feb;69(2):91-9 - PubMed
  20. Cogn Neurosci. 2010 Sep;1(3):176-183 - PubMed
  21. BMC Neurosci. 2003 Dec 02;4:31 - PubMed
  22. Psychophysiology. 2000 Mar;37(2):163-78 - PubMed
  23. Brain Cogn. 2010 Feb;72(1):56-65 - PubMed
  24. Biol Bull. 2008 Dec;215(3):216-42 - PubMed
  25. PLoS Comput Biol. 2008 Jun 13;4(6):e1000091 - PubMed
  26. Brain Res. 1979 Mar 16;163(2):195-205 - PubMed
  27. IEEE Trans Biomed Eng. 2001 Dec;48(12):1424-33 - PubMed
  28. Cereb Cortex. 2011 Mar;21(3):607-15 - PubMed
  29. Am J Physiol. 1994 Apr;266(4 Pt 2):H1643-56 - PubMed
  30. BMC Neurosci. 2004 Nov 02;5:42 - PubMed
  31. Biomed Tech (Berl). 2006 Jul;51(2):89-94 - PubMed
  32. Sci Transl Med. 2013 Aug 14;5(198):198ra105 - PubMed
  33. Br J Anaesth. 2012 Dec;109(6):928-34 - PubMed
  34. Anesthesiology. 2003 Mar;98(3):621-7 - PubMed
  35. J Neurosci. 2010 Aug 25;30(34):11379-87 - PubMed
  36. Proc Natl Acad Sci U S A. 1991 Mar 15;88(6):2297-301 - PubMed
  37. Cereb Cortex. 2014 Jun;24(6):1529-39 - PubMed
  38. Neurosci Lett. 2012 May 31;517(2):87-91 - PubMed
  39. Neurosci Lett. 1982 Dec 13;33(3):247-52 - PubMed
  40. Neuroimage. 2012 Nov 1;63(2):959-65 - PubMed
  41. J Neurosci. 2010 Oct 6;30(40):13211-9 - PubMed
  42. IEEE Trans Biomed Eng. 1998 Sep;45(9):1186-91 - PubMed
  43. Sleep. 1980;2(4):453-60 - PubMed
  44. Arch Ital Biol. 2012 Dec;150(4):293-329 - PubMed
  45. Sleep. 2001 Mar 15;24(2):171-9 - PubMed
  46. Proc Natl Acad Sci U S A. 2010 Feb 9;107(6):2681-6 - PubMed
  47. Anesthesiology. 2000 Mar;92(3):715-26 - PubMed

Publication Types