A continuous mapping of sleep states through association of EEG with a mesoscale cortical model.
Summary of "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.
Affiliation
Department of Mechanical Engineering, University of California, Berkeley, CA, 94720, USA, bethlopour@berkeley.edu.
Journal Details
This article was published in the following journal.
Name: Journal of computational neuroscience
ISSN: 1573-6873
Pages:
Links
- PubMed Source: http://www.ncbi.nlm.nih.gov/pubmed/20809258
- DOI: http://dx.doi.org/10.1007/s10827-010-0272-1
Medical and Biotech [MESH] Definitions
Polysomnography
Simultaneous and continuous monitoring of several parameters during sleep to study normal and abnormal sleep. The study includes monitoring of brain waves, to assess sleep stages, and other physiological variables such as breathing, eye movements, and blood oxygen levels which exhibit a disrupted pattern with sleep disturbances.
Sleep Stages
Periods of sleep manifested by changes in EEG activity and certain behavioral correlates; includes Stage 1: sleep onset, drowsy sleep; Stage 2: light sleep; Stages 3 and 4: delta sleep, light sleep, deep sleep, telencephalic sleep.
Sleep Disorders, Intrinsic
Dyssomnias (i.e., insomnias or hypersomnias) associated with dysfunction of internal sleep mechanisms or secondary to a sleep-related medical disorder (e.g., sleep apnea, post-traumatic sleep disorders, etc.). (From Thorpy, Sleep Disorders Medicine, 1994, p187)
Parasomnias
Movements or behaviors associated with sleep, sleep stages, or partial arousals from sleep that may impair sleep maintenance. Parasomnias are generally divided into four groups: arousal disorders, sleep-wake transition disorders, parasomnias of REM sleep, and nonspecific parasomnias. (From Thorpy, Sleep Disorders Medicine, 1994, p191)
Delta Rhythm
One of the four types of brain waves seen on EEG characterized by a high amplitude and a frequency of 4 Hz and below. They are considered the "deep sleep waves" observed during sleep in dreamless states, infancy, and in some brain disorders.
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