A continuous mapping of sleep states through association of EEG with a mesoscale cortical model.
Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.
Lopour
Beth A
BA
Department of Mechanical Engineering, University of California, Berkeley, CA 94720, USA. bethlopour@berkeley.edu
Tasoglu
Savas
S
Kirsch
Heidi E
HE
Sleigh
James W
JW
Szeri
Andrew J
AJ
D000465:Algorithms; D001931:Brain Mapping; D058256:Brain Waves / Q000502:physiology; D002540:Cerebral Cortex / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D008954:Models, Biological; D017711:Nonlinear Dynamics; D012894:Sleep Stages / Q000502:physiology*
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Nov;72(5 Pt 1):051910
16383648
Network. 2002 Feb;13(1):67-113
11878285
Anaesth Intensive Care. 2010 Jan;38(1):102-12
20191785
J Biol Rhythms. 2006 Dec;21(6):482-93
17107938
J Comput Neurosci. 2010 Jun;28(3):375-87
20135212
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:5489-92
18003254
J Neurophysiol. 2001 May;85(5):1969-85
11353014
Science. 2000 Dec 22;290(5500):2323-6
11125150
Nature. 2005 Oct 27;437(7063):1257-63
16251950
J Clin Neurophysiol. 2005 Oct;22(5):300-13
16357635
Circulation. 2000 Jun 13;101(23):E215-20
10851218
J Biol Phys. 2005 Dec;31(3-4):547-69
23345918
Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Aug;68(2 Pt 1):021902
14525001
Sleep Med. 2007 Jun;8(4):302-30
17468046
Sleep. 2000 Sep 15;23(6):738-44
11007440
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Apr;71(4 Pt 1):041902
15903696
J Neurosci. 2004 Dec 8;24(49):11137-47
15590930
Anesthesiology. 2009 Sep;111(3):547-55
19672164
Brain Res Rev. 2009 Oct;61(2):281-306
19695288
Sleep. 1995 Sep;18(7):557-64
8552926
Sleep. 2000 Nov 1;23(7):901-8
11083599
Biol Cybern. 1994;71(3):197-207
7918799
J Comput Neurosci. 2006 Dec;21(3):243-57
16927212
Sleep Res Online. 1998;1(1):1-10
11382851
Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1999 Dec;60(6 Pt B):7299-311
11970675
J R Soc Interface. 2005 Mar 22;2(2):113-27
16849171
J Comput Neurosci. 2007 Feb;22(1):63-80
16998642
Br J Anaesth. 2008 Dec;101(6):810-21
18852113
J Physiol. 2007 Nov 1;584(Pt 3):735-41
17884926
Trends Neurosci. 2005 Mar;28(3):152-7
15749169
Prog Biophys Mol Biol. 2004 Jun-Jul;85(2-3):369-85
15142753
Sleep. 1998 Nov 1;21(7):749-57
11286351