Narcolepsy is a chronic sleep disorder characterized by excessive daytime sleepiness (EDS) causing uncontrollable and sometimes inappropriate napping. Though the naps are often refreshing their frequent occurrences can severely impair daily social functioning. Apart from EDS the cardinal symptoms are; hypnagogic hallucinations, sleep paralysis, sleep onset rapid eye movement periods (SOREMP) and approximately 50% of all patients also suffer from cataplexy; sudden episodes of emotionally triggered muscle weakness (Saper et al., 2001, Schenck et al., 2007). In healthy individuals sleep normally progresses from light drowsiness to deep sleep and after approximately 90 minutes it will transition ...view middle of the document...
, 2008, Thomas, 2005). We turned to resting state fMRI, which provides and excellent neuroimaging tool to assess functional connectivity of the brain and is performed with the subject resting with eyes either closed or opened(Fox and Raichle, 2007). Low-frequency fluctuations (LFF), less than <0.1Hz, of blood oxygen level dependent (BOLD) signals in resting state fMRI data are thought to reflect spontaneous neural activity in humans and are referred to as resting state networks (RSN). A benefit of using resting state fMRI is the possibility to avoid some of the problems that can arise when using task based tools; such as failure to correctly interpret instructions or poor performance by the participants(Hampson et al., 2012). RSN have been successfully employed to assess pathological brain activity in several neurological and psychological disorders(Husain and Schmidt, 2013, Yang et al., 2013). Previous studies on sleep with resting state fMRI have also shown that these networks are preserved through all stages of sleep(Boly et al., 2008).
Spontaneous neural activity has also been proposed to underlie periods of quasi stability observed in the scalp topography of electroencephalography (EEG)(Lehmann et al., 1998). EEG measures the direct electrical activity of the brain and in contrast to the fMRI has a higher temporal resolution, but a fairly low spatial resolution. Spatio-temporal analysis of the EEG can be used to characterize the EEG as a sequence of quasi-stable scalp potential field maps(Wackermann et al., 1993). During resting state EEG four maps can generally be observed, these maps, arbitrarily named A, B, C and D, are referred to as EEG microstates and appear to be persistent in both healthy and diseased individuals and throughout the life span. They have been shown to preceed cognition and are sometimes referred to as the “building blocks of cognition” or “the atoms of thought” and may represent different types of mental processes much like the RSN of fMRI (Lehmann and Michel, 2011, Koenig et al., 2002, Kondakor et al., 1997, Kondakor et al., 1995). Recently they were found to correlate with four known RSN when convolved with the hemodynamic BOLD-response suggesting that the dynamics of these may be a lot faster than previously assumed (Britz et al., 2010, Van de Ville et al., 2010). EEG has been used to study sleep as well as brain function in narcolepsy however new technology enabling the use of EEG in the MRI environment has opened up for studying the disease using both modalities simultaneously.
Our aim is to study brain function during sleep attacks in narcolepsy. We intend to accomplish this by comparing brain activation during sleep and wake stages between patients and healthy controls using a combination of EEG and fMRI.
This report will focus on describing the methods used to process and analyze the EEG data. Some preliminary results from the microstate analysis will also be presented.
Materials and methods