The Fingerprint of Rapid Eye Movement: Its Algorithmic Detection in the Sleep Electroencephalogram Using a Single Derivation.

The strong associations of rapid eye movement (REM) sleep with dreaming and memory consolidation imply the existence of REM-specific brain electrical activity, notwithstanding the visual similarity of the electroencephalograms (EEGs) in REM and wake states. Our goal was to detect REM sleep by means of algorithmic analysis of the EEG. We postulated that novel depth and fragmentation variables, defined in relation to temporal changes in the signal (recurrences), could be statistically combined to allow disambiguation of REM epochs. The cohorts studied were consecutive patients with obstructive sleep apnea (OSA) recruited from a sleep medicine clinic, and clinically normal participants selected randomly from a national database (N = 20 in each cohort). Individual discriminant analyses were performed, for each subject based on 4 recurrence biomarkers, and used to classify every 30-second epoch in the subject's overnight polysomnogram as REM or NotREM (wake or any non-REM sleep stage), using standard clinical staging as ground truth. The primary outcome variable was the accuracy of algorithmic REM classification. Average accuracies of 90% and 87% (initial and cross-validation analyses) were achieved in the OSA cohort; corresponding results in the normal cohort were 87% and 85%. Analysis of brain recurrence allowed identification of REM sleep, disambiguated from wake and all other stages, using only a single EEG lead, in subjects with or without OSA.

A pilot study: portable out-of-center sleep testing as an early sleep apnea screening tool in acute ischemic stroke.

INTRODUCTION: Prompt diagnosis of obstructive sleep apnea (OSA) after acute ischemic stroke (AIS) is critical for optimal clinical outcomes, but in-laboratory conventional polysomnograms (PSG) are not routinely practical. Though portable out-of-center type III cardiopulmonary sleep studies (out-of-center cardiopulmonary sleep testing [OCST]) are widely available, these studies have not been validated in patients who have recently suffered from AIS. We hypothesized that OCST in patients with AIS would yield similar results when compared to conventional PSG. METHODS: Patients with AIS had simultaneous type III OCST and PSG studies performed within 72 hours from symptom onset. The accuracy of OCST was compared to PSG using: chi-square tests, receiver operatory characteristic curves, Bland-Altman plot, paired Student's t-test/Wilcoxon signed-rank test, and calculation of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: Twenty-one out of 23 subjects with AIS (age 61±9.4 years; 52% male; 58% African-American) successfully completed both studies (9% technical failure). Nearly all (95%) had Mallampati IV posterior oropharynx; the mean neck circumference was 16.8±1.6 in. and the mean body mass index (BMI) was 30±7 kg/m(2). The apnea hypopnea index (AHI) provided by OCST was similar to that provided by PSG (19.8±18.0 vs 22.0±22.7, respectively; P=0.49). On identifying subjects by OCST with an AHI ≥5 on PSG, OCST had the following parameters: sensitivity 100%, specificity 85.7%, PPV 93%, and NPV 100%. On identifying subjects with an AHI ≥15 on PSG, OCST parameters were as follows: sensitivity 100%, specificity 83.3%, PPV 81.8%, and NPV 100%. Bland-Altman plotting showed an overall diagnostic agreement between OCST and PSG modalities for an AHI cutoff >5, despite fine-grained differences in estimated AHIs. CONCLUSION: Compared with PSG, OCST provides similar diagnostic information when run simultaneously in AIS patients. OCST is a reliable screening tool for early diagnosis of OSA in AIS patients.

Continuous Positive Airway Pressure Device Time to Procurement in a Disadvantaged Population.

Introduction. The management of obstructive sleep apnea (OSA) in patients who cannot afford a continuous positive airway pressure (CPAP) device is challenging. In this study we compare time to CPAP procurement in three groups of patients diagnosed with OSA: uninsured subsidized by a humanitarian grant (Group 1), uninsured unsubsidized (Group 2), and those with Medicare or Medicaid (Group 3). We evaluate follow-up and adherence in Group 1. We hypothesize that additional factors, rather than just the ability to obtain CPAP, may uniquely affect follow-up and adherence in uninsured patients. Methods. 30 patients were in Groups 1 and 2, respectively. 12 patients were in Group 3. Time of CPAP procurement from OSA diagnosis to CPAP initiation was assessed in all groups. CPAP adherence data was collected for Group 1 patients at 1, 3, 6, and 9 months. Results. There were no significant differences between groups in gender, age, body mass index, or apnea hypopnea index. The mean time to procurement in Group 1 was shorter compared to Group 2 but not significant. Compared to both Group 1 and Group 2, Group 3 patients had significantly shorter times to device procurement. Conclusion. Time to procurement of CPAP was significantly shorter in those with Medicaid/Medicare insurance compared to the uninsured.

Manual characterization of sleep spindle index in patients with narcolepsy and idiopathic hypersomnia.

This is a retrospective review of PSG data from 8 narcolepsy patients and 8 idiopathic hypersomnia (IH) patients, evaluating electrophysiologic differences between these two central hypersomnias. Spindles were identified according to the AASM Manual for the Scoring of Sleep and Associated Events; and counted per epoch in the first 50 epochs of N2 sleep and the last 50 epochs of N2 sleep in each patient's PSG. Spindle count data (mean ± standard deviation) per 30 second-epoch (spindle index) in the 8 narcolepsy patients was as follows: 0.37 ± 0.73 for the first 50 epochs of N2; 0.65 ± 1.09 for the last 50 epochs of N2; and 0.51 ± 0.93 for all 100 epochs of N2. Spindle index data in the 8 IH patients was as follows: 2.31 ± 2.23 for the first 50 epochs of N2; 2.84 ± 2.43 for the last 50 epochs of N2; and 2.57 ± 2.35 for all 100 epochs of N2. Intergroup differences in spindle count in the first 50 N2 epochs, the last 50 N2 epochs, and all 100 epochs of scored N2 were significant (P < 0.01) as were the intragroup differences between the first 50 N2 epochs and the last 50 N2 epochs.

Sleep-wake pattern following gunshot suprachiasmatic damage.

BACKGROUND: The suprachiasmatic nucleus (SCN) plays a critical role in maintaining melatonin and sleep-wake cycles. METHODS/PATIENT: We report a case of 38-year-old woman who, after gunshot wound to the right temple, developed a sleep complaint of multiple nocturnal awakenings and several naps throughout the day. RESULTS: Computerized tomography and magnetic resonance imaging revealed bilateral optic nerve and optic chiasm damage. Diagnostic polysomnography and actigraphy revealed an irregular sleep wake rhythm. CONCLUSIONS: We speculate concurrent damage of the SCN and optic nerves bilaterally resulted in the posttraumatic irregular sleep-wake rhythm.

Two-group classification of patients with obstructive sleep apnea based on analysis of brain recurrence.

OBJECTIVE: To demonstrate that the severity of obstructive sleep apnea (OSA) could be predicted algorithmically by means of recurrence analysis of the sleep-staged electroencephalogram (EEG). METHODS: A randomly selected cohort of 20 sleep-staged patients with OSA (apnea-hypopnea index (AHI) 5-30) was divided into mild and moderate sub-cohorts (AHI 5-15, 16-30, respectively), and the sleep EEG (C3) was analyzed using analysis of brain recurrence (ABR) (LSU cohort). Twenty distinct but related markers for sleep depth and fragmentation were computed from four ABR variables, and a marker function capable of classifying each patient into one of the two sub-cohorts was determined by linear discriminant analysis. Classification accuracy of individual patients was evaluated using area under the receiver operator characteristics curve (AUROC). As a control procedure, 20 additional sleep-staged patients with OSA whose polysomnographic data was obtained from an independent database were also evaluated (SHHS cohort). RESULTS: On average, markers for sleep depth were reduced and those for sleep fragmentation were increased in the patients with moderate OSA, as expected. All patients in both cohorts were correctly classified using as few as 5-6 markers. SIGNIFICANCE: The degree of severity of OSA was reflected in objective changes in the sleep EEG. Recurrence analysis of the EEG potentially has uses beyond identification of the degree of OSA.

The link between vitamin D metabolism and sleep medicine.

Vitamin D is a hormone that interacts with intranuclear receptors to effect transcriptional changes in many cell types including those in gut, bone, breast, prostate, brain, skeletal muscle, and the immune system. Inadequacy of vitamin D is widely prevalent, and leads to the classic diseases of bone demineralization as well as to more recently recognized problems such as nonspecific pain and noninflammatory skeletal myopathy, which may disrupt sleep and directly cause daytime impairment. Emerging lines of evidence suggest that low vitamin D levels increase the risk for autoimmune disease, chronic rhinitis, tonsillar hypertrophy, cardiovascular disease, and diabetes. These conditions are mediated by altered immunomodulation, increased propensity to infection, and increased levels of inflammatory substances, including those that regulate sleep, such as tumor necrosis factor alpha (TNF-α), interleukin (IL)-1, and prostaglandin D2 (PD2). Together, the recent reports suggest a role for inadequate vitamin D in the development of symptoms of wake impairment commonly associated with sleep disorders. Persistent inadequacy of vitamin D may also increase the risk for obstructive sleep apnea via promotion of adenotonsillar hypertrophy, airway muscle myopathy, and/or chronic rhinitis. Much remains to be learned concerning the complex relationship between chronically low levels of vitamin D, normal sleep, sleep disruption, and daytime neurocognitive impairment.

Nocturnal hypoxemia biomarker predicts sleepiness in patients with severe obstructive sleep apnea.

PURPOSE: This study aims to assess the association between excessive daytime sleepiness (EDS) and variables extracted from the pulse-oximetry signal obtained during overnight polysomnography. METHODS: A cross-sectional design was used to study the relation between four hypoxemia variables and EDS as determined by Epworth Sleepiness Scale scores (ESSS) in 200 consecutive patients, newly diagnosed with obstructive sleep apnea (OSA), as defined by an apnea-hypopnea index (AHI)≥ 15. Hypoxemia measurements were compared between sleepy (ESSS ≥ 10) and nonsleepy (ESSS<10) patients before and after dichotomizing the cohort for each hypoxemia variable (and for AHI) such that there were 35 (165) patients in each of the corresponding higher (lower) subcohorts. The hypoxemia variables were combined into a biomarker, and its accuracy for predicting sleepiness in individual patients was evaluated. We planned to interpret prediction accuracy above 80 % as evidence that hypoxemia predicted EDS. RESULTS: Hypoxemia was unassociated with sleepiness in OSA patients with AHI in the range of 15 to 50. In patients with AHI>50, the hypoxemia biomarker (but not individual hypoxemia variables) predicted sleepiness with 82 % accuracy. CONCLUSION: Nocturnal hypoxemia as determined by a polyvariable biomarker reliably predicted EDS in patients with severe OSA (AHI>50), indicating that oxygen fluctuation had a direct role in the development of EDS in patients with severe OSA.

Characterization of REM sleep without atonia in patients with narcolepsy and idiopathic hypersomnia using AASM scoring manual criteria.

INTRODUCTION: The AASM Manual for the Scoring of Sleep and Associated Events (Manual) has provided standardized definitions for tonic and phasic REM sleep without atonia (RSWA). This study used Manual criteria to characterize REM sleep in patients with narcolepsy and idiopathic hypersomnia (IH). METHODS: A retrospective review of PSG data from ICSD-2 defined patients with narcolepsy or IH, performed by two board certified sleep medicine physicians. Data compiled included REM sleep epochs and the presence in REM sleep of epochs scored as sustained muscle activity (tonic), and excessive transient muscle activity (phasic) as defined by Manual criteria. RESULTS: PSG data from 8 narcolepsy patients (mean age: 27.5 years; age range: 11-55) showed mean ± standard deviation values for: total REM sleep epochs 205 ± 46.1; RSWA/ phasic epochs 56.1 ± 25.4; and RSWA/tonic epochs 15.0 ± 10.7. PSG data from 8 IH patients (mean age: 33.1 years; age range: 20-57) showed mean ± standard deviation values of total REM sleep epochs 163.8 ± 67.9; RSWA/phasic epochs 6.2 ± 3.5; and RSWA/tonic epochs 0.2 ± 0.4. Comparison revealed intergroup differences in phasic REM sleep (p < 0.01) and tonic REM sleep (p < 0.01) were significantly increased in narcoleptics compared to IH. CONCLUSION: Our retrospective analysis showed that RSWA phasic activity and RSWA tonic activity are significantly increased in patients meeting ICSD-2 criteria for narcolepsy compared to patients meeting ICSD-2 criteria for IH. This robust difference, with further validation, could be useful as electrophysiological criteria differentiating the two disorders and understanding the physiological differences.

EEG recurrence markers and sleep quality.

OBJECTIVES: To show that EEG markers formed using the variable percent recurrence reliably quantified two related aspects of sleep quality, sleep depth and sleep fragmentation. As hypotheses, the depth marker would increase and the fragmentation marker decrease in patients where improved sleep quality occurred when assessed by polysomnography. METHODS: The patients (N=20) had been diagnosed with obstructive sleep apnea during diagnostic polysomnography (dPSG), and had exhibited increased REM sleep (clinical indication of improved sleep quality) during subsequent polysomnography to titrate the pressure of a treatment device (cPSG). Percent recurrence was computed second-by-second from the EEG; sleep-depth and sleep-stability markers were obtained algorithmically. By assumption, the markers contained temporal information regarding the extent of deterministic (non-random) brain activity. Marker means were compared between the dPSG and the cPSG for NREM and REM sleep. RESULTS: Sleep depth was greater and sleep fragmentation was less during cPSG, as hypothesized (P<0.05). The effects occurred during NREM and REM sleep, but were greater during NREM sleep (P<0.05). At least one of the predicted changes occurred in 95% of the patients. CONCLUSIONS: The factors generally regarded as responsible for subjective sleep quality were objectively quantified on the basis of dynamical changes in the EEG.

Manual quantitative assessment of amplitude and sleep stage distribution of excessive fragmentary myoclonus.

INTRODUCTION: Excessive fragmentary myoclonus (EFM) consists of brief, asynchronous, twitch-like movements appearing asymmetrically in sleep. The new AASM Manual for the Scoring of Sleep and Associated Events identifies some EFM scoring criteria but does not provide amplitude criteria for scoring EFM. Older observational series have used 50 µVs. We report data from various amplitude criteria using blinded comparisons. METHODS: EFMs were analyzed on the polysomnograms of 8 patients (7 men and 1 woman, mean age 57 years, range: 47-79) using a standardized protocol for sensitivity, tonus threshold, impedance, amplitude measurements, and sleep stage. The first 20 minutes each of wake, Stage 1-2, SWS, and REM were analyzed. EFMs ≥ 25, ≥ 40, and ≥ 50 microvolts (µVs) in negative deflection above the baseline were counted in tibialis anterior muscle electromyography (EMG) channels bilaterally. RESULTS: The mean EFM index per minute for wake, regardless of impedance, was: 7.19 ± 5.90 for ≥ 25 µV amplitude; 2.43 ± 2.02 for ≥ 40 µVs; and 2.08 ± 2.23 for ≥ 50 µVs. For sleep stages, the EFM index by stage and amplitude criteria used for measurements were: Stage 1-2: 7.38 ± 5.79 for ≥ 25 µVs; 3.13 ± 3.33 for ≥ 40 µVs; and 2.36 ± 2.66 for ≥ 50 µVs; SWS: 10.05 ± 8.04 for ≥ 25 µVs; 2.71 ± 3.13 for ≥ 40 µVs; and 1.38 ± 1.92 for ≥ 50 µVs; Total REM: 15.96 ± 11.32 for ≥ 25 µVs; 6.32 ± 4.25 for ≥ 40 µVs; and 3.94 ± 3.73 for ≥ 50 µVs; Phasic REM: 19.69 ± 15.45 for ≥ 25 µVs; 8.63 ± 7.06 for ≥ 40 µVs; and 5.52 ± 6.44 for ≥ 50 µVs; Non-phasic REM: 13.93 ± 11.31 for ≥ 25 µVs; 5.16 ± 3.57 for ≥ 40 µVs; and 3.20 ± 2.92 for ≥ 50 µVs. CONCLUSION: EFM rates increase with SWS and total REM with the highest EFM rates occurring during phasic REM. EFM rates were increased across all sleep stages when impedance was > 30 KΩ.

Positional central apnea and vascular medullary compression.

A 66-year-old man with hypertension presented with complaints of excessive daytime sleepiness (Epworth Sleepiness Score 14/24), dyspnea upon exertion, and episodes of noninjurious dream-enacting behavior. He reported tongue biting when sleeping in the right lateral decubitus position. Medications included atenolol 12.5 mg, lovastatin 20 mg, doxazosin 2 mg, amlodipine 5 mg, isosorbide mononitrate 60 mg, and aspirin 81 mg. He denied headaches, visual changes, dysarthria, dysphagia, or localized weakness. He denied use of alcohol, tobacco, or drugs.

Continuous EEG-based dynamic markers for sleep depth and phasic events.

Sleep architecture is characterized by classifying polysomnographic epochs into mutually exclusive stages. Notwithstanding the clinical importance of staging, it has the drawback of representing sleep as a discrete process. Metrics based on the electroencephalogram (EEG) are needed to supplement conventional sleep staging by allowing a description of sleep in terms of unitary, continuous markers. Traditional linear and nonlinear techniques for achieving this goal have not proved sufficient. Employing recurrence analysis, we developed a method for capturing and quantifying the dynamical states of the brain during sleep. The method yields markers for continuously determining sleep depth, for detecting sleep-specific phasic events, and for objectively defining potentially useful sleep markers and indices. Recurrence markers captured the coarse- and fine-grained temporal activity of the sleep EEG, thereby permitting continuous quantitation of brain electrical activity on any desired time scale. The markers were validated with respect to the tonic behavior (time scale of seconds) of the sleep EEG by establishing that they disambiguated the stages of sleep that are defined solely on the basis of EEG activity. Validation of the markers over time scales of milliseconds was achieved by showing that common types of sleep-EEG phasic events could be detected by recurrence analysis. The method was also used to define a generalized EEG arousal index that quantified previously unrecognized sleep-stage-dependent deterministic properties of brain electrical activity. Using nonlinear analysis that quantified the recurrence properties of the EEG, we described a novel method for producing dynamic markers of brain states during sleep.

Increased determinism in brain electrical activity occurs in association with multiple sclerosis.

OBJECTIVE: Increased determinism (decreased complexity) of brain electrical activity has been associated with some brain diseases. Our objective was to determine whether a similar association occurred for multiple sclerosis (MS). METHODS: Ten subjects with a relapsing-remitting course of MS who were in remission were studied; the controls were age- and gender-matched clinically normal subjects. Recurrence plots were calculated using representative electroencephalogram (EEG) epochs (1-7 seconds) from six derivations; the plots were quantified using the nonlinear variables percent recurrence (%R) and percent determinism (%D). The results were averaged over all derivations for each participant, and the means were compared between the groups. As a linear control procedure the groups were also compared using spectral analysis. RESULTS: The mean±SD of %R for the MS subjects was 6·6±1·3%, compared with 5·1±1·3% in the normal group (P = 0·017), indicating that brain activity in the subjects with MS was less complex, as hypothesized. The groups were not distinguishable using %D or spectral analysis. DISCUSSION: Taken together with our earlier report that %R could be used to discriminate between MS and normal subjects based on the ability to exhibit evoked potentials, the evidence suggests that complexity analysis of the EEG has potential for development as a diagnostic test for MS.

Electromagnetic hypersensitivity: evidence for a novel neurological syndrome.

OBJECTIVE: We sought direct evidence that acute exposure to environmental-strength electromagnetic fields (EMFs) could induce somatic reactions (EMF hypersensitivity). METHODS: The subject, a female physician self-diagnosed with EMF hypersensitivity, was exposed to an average (over the head) 60-Hz electric field of 300 V/m (comparable with typical environmental-strength EMFs) during controlled provocation and behavioral studies. RESULTS: In a double-blinded EMF provocation procedure specifically designed to minimize unintentional sensory cues, the subject developed temporal pain, headache, muscle twitching, and skipped heartbeats within 100 s after initiation of EMF exposure (p < .05). The symptoms were caused primarily by field transitions (off-on, on-off) rather than the presence of the field, as assessed by comparing the frequency and severity of the effects of pulsed and continuous fields in relation to sham exposure. The subject had no conscious perception of the field as judged by her inability to report its presence more often than in the sham control. DISCUSSION: The subject demonstrated statistically reliable somatic reactions in response to exposure to subliminal EMFs under conditions that reasonably excluded a causative role for psychological processes. CONCLUSION: EMF hypersensitivity can occur as a bona fide environmentally inducible neurological syndrome.

Numerical analysis of recurrence plots to detect effect of environmental-strength magnetic fields on human brain electrical activity.

Environmental magnetic fields may activate the neuroendocrine stressor system leading to some human diseases. The stressor theory predicts that the fields can trigger changes in brain electrical activity, like known stressors. We exposed subjects to 1 and 5 µT, 60 Hz while recording electroencephalograms (EEGs) from six derivations, and used a novel method based on numerical analysis of recurrence plots computed from the signals to detect brain electrical potentials evoked by onset and/or offset of the field. The EEGs were also analyzed using linear methods (time averaging). Evoked potentials occurred in all 22 subjects (family-wise error rate less than 0.05 for each subject); the average latency was 250 ms, as expected based on earlier studies using stronger magnetic fields. Field-induced changes in brain electrical activity were not found using time averaging. Control procedures and measurements obtained from electrical phantoms reasonably excluded recording artifacts or chance as explanations for the effects. Onset and offset of magnetic fields produced immediate changes in brain electrical activity, suggesting that the fields were detected by sensory transduction, like ordinary somatic stressors.

Simulated MR magnetic field induces steady-state changes in brain dynamics: Implications for interpretation of functional MR studies.

We examined whether a magnetic field comparable to one of the fields produced during MRI induced steady-state changes in brain electrical activity while the field was applied (called a presence effect to distinguish it from evoked potentials). The electroencephalogram was measured from standard scalp locations in the presence and absence of 100-200 microT, 60 Hz, and the effect of the field was evaluated by nonlinear (recurrence analysis) and linear techniques; individual subjects served as their own controls. Using recurrence analysis, changes in brain activity lasting 1 sec (the longest interval considered) were found in 21 of 22 subjects (P < 0.05 for each subject). The presence effect was not detected using linear analysis and was reversible, as indicated by a return of brain activity to baseline levels in all subjects within 2 sec of field offset. The possible role of artifacts or systematic errors was ruled out by studies using electrical phantoms and by analyses of electroencephalograms recorded during sham exposure. It is reasonable to expect that actual scanner magnetic fields also produce nonlinear steady-state perturbations of brain dynamical activity. The effect may influence the picture of brain connectivity inferred in some functional MR studies.