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Sleep impairment is a common comorbid and debilitating symptom for persons with opioid use disorder (OUD). Research into underlying mechanisms and efficacious treatment interventions for OUD-related sleep problems requires both precise and physiologic measurements of sleep-related outcomes and impairment. This pilot examined the feasibility of a wireless sleep electroencephalography (EEG) monitor (Sleep Profiler™) to measure sleep outcomes and architecture among participants undergoing supervised opioid withdrawal. Sleep outcomes were compared to a self-reported sleep diary and opioid withdrawal ratings. Participants (n = 8, 100% male) wore the wireless EEG 85.6% of scheduled nights. Wireless EEG detected measures of sleep architecture including changes in total, NREM and REM sleep time during study phases, whereas the diary detected changes in wakefulness only. Direct comparisons of five overlapping outcomes revealed lower sleep efficiency and sleep onset latency and higher awakenings and time spent awake from the wireless EEG versus sleep diary. Associations were evident between wireless EEG and increased withdrawal severity, lower sleep efficiency, less time in REM and non-REM stages 1 and 2, and more hydroxyzine treatment; sleep diary was associated with total sleep time and withdrawal only. Data provide initial evidence that a wireless EEG is a feasible and useful tool for objective monitoring of sleep in persons experiencing acute opioid withdrawal. Data are limited by the small and exclusively male sample, but provide a foundation for using wireless EEG sleep monitors for objective evaluation of sleep-related impairment in persons with OUD in support of mechanistic and treatment intervention research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Background: In response to the cancellation of clinical clerkships due to COVID-19, the Johns Hopkins (JH) Neurology Education Team developed a virtual elective to enhance medical students' clinical telemedicine skills and foster community between academic institutions., Methods: This two-week clinical elective, entitled "Virtual Patient Rounds in Neurology," was administered once in April 2020 and once in May 2020. The curriculum included attending/fellow-led Virtual Rounds, Student Presentations, and Asynchronous Educational Activities. We also developed a new lecture series entitled JHNeuroChats, which consisted of live synchronous lectures presented by JH faculty and Virtual Visiting Professors. Trainees and faculty from outside institutions were invited to participate in the JHNeuroChats. Students and faculty completed pre- and post-elective surveys to assess the educational impact of the elective. Student's t-tests were used to compare scores between pre- and post-elective surveys., Results: Seven JH medical students enrolled in each iteration of the elective, and an additional 337 trainees and faculty, representing 14 different countries, registered for the JHNeuroChats. We hosted 48 unique JHNeuroChats, 32 (66.7%) of which were led by invited Virtual Visiting Professors. At the end of the elective, students reported increased confidence in virtually obtaining a history (P < 0.0001) and performing a telehealth neurological physical exam (P < 0.0001), compared to the start of the course. In addition, faculty members reported increased confidence in teaching clinical medicine virtually, although these findings were not statistically significant (P = 0.15)., Conclusions: Despite the constraints imposed by COVID-19, this virtual Neurology elective increased medical students' confidence in certain telemedicine skills and successfully broadened our learning community to encompass learners from around the world. As virtual medical education becomes more prevalent, it is important that we are intentional in creating opportunities for shared learning across institutions. We believe that this elective can serve as a model for these future educational collaborations., (© 2021. The Author(s).)

Medical students need to understand core neuroscience principles as a foundation for their required clinical experiences in neurology. In fact, they need a solid neuroscience foundation for their clinical experiences in all other medical disciplines also because the nervous system plays such a critical role in the function of every organ system. Because of the rapid pace of neuroscience discoveries, it is unrealistic to expect students to master the entire field. It is also unnecessary, as students can expect to have ready access to electronic reference sources no matter where they practice. In the preclerkship phase of medical school, the focus should be on providing students with the foundational knowledge to use those resources effectively and interpret them correctly. This article describes an organizational framework for teaching the essential neuroscience background needed by all physicians. This is particularly germane at a time when many medical schools are reassessing traditional practices and instituting curricular changes such as competency-based approaches, earlier clinical immersion, and increased emphasis on active learning. This article reviews factors that should be considered when developing the preclerkship neuroscience curriculum, including goals and objectives for the curriculum, the general topics to include, teaching and assessment methodology, who should direct the course, and the areas of expertise of faculty who might be enlisted as teachers or content experts. These guidelines were developed by a work group of experienced educators appointed by the Undergraduate Education Subcommittee (UES) of the American Academy of Neurology (AAN). They were then successively reviewed, edited, and approved by the entire UES, the AAN Education Committee, and the AAN Board of Directors., (© 2021 American Academy of Neurology.)

In this study, we aim to automate the sleep stage scoring process of overnight polysomnography (PSG) data while adhering to expert-based rules. We developed a sleep stage scoring algorithm utilizing the generalized linear modelling (GLM) framework and extracted features from electroencephalogram (EEG), electromyography (EMG) and electrooculogram (EOG) signals based on predefined rules of the American Academy of Sleep Medicine (AASM) Manual for Scoring Sleep. Specifically, features were computed in 30-s epochs in the time and frequency domains of the signals and were then used to model the probability of an epoch being in each of five sleep stages: N3, N2, N1, REM or Wake. Finally, each epoch was assigned to a sleep stage based on model predictions. The algorithm was trained and tested on PSG data from 38 healthy individuals with no reported sleep disturbances. The overall scoring accuracy reached on the test set was 81.50 ± 1.14% (Cohen's kappa, κ = 0.73 ± 0.02 ). The test set results were highly comparable to the training set, indicating robustness of the algorithm. Furthermore, our algorithm was compared to three well-known commercialized sleep-staging tools and achieved higher accuracies than all of them. Our results suggest that automatic classification is highly consistent with visual scoring. We conclude that our algorithm can reproduce the judgement of a scoring expert and is also highly interpretable. This tool can assist visual scorers to speed up their process (from hours to minutes) and provides a method for a more robust, quantitative, reproducible and cost-effective PSG evaluation, supporting assessment of sleep and sleep disorders., (© 2020 European Sleep Research Society.)

Patients are increasingly looking to optimize sleep as a health and wellness strategy. Sleep health is often individualized based on three elements that correspond to overall physical and mental well-being: (1) sleep quality, which refers to the continuity and depth of sleep as well as a feeling of restoration upon awakening; (2) sleep quantity, which refers to the duration of sleep that is appropriate for a given age group; and (3) timing of the sleep window, which refers to the positioning of sleep that is aligned with an individual's circadian rhythm for sleep or an ideal circadian zone. In the past, prescribing hypnotic medications was considered the primary approach for improving sleep. However, there has been a recent paradigm shift to favor behavioral approaches, particularly in the case of insomnia where cognitive-behavioral therapy has been shown to have a more favorable benefit-to-harm profile than medications. The clinical vignette is presented here as a springboard for discussion regarding the latest evidence and efficacy for sleep behavior techniques and consumer monitoring devices developed to improve sleep health and awareness for clinicians to consider when educating their patients on maximizing sleep health behaviors.

Background: The characterization of sleep in those with neurodegenerative disease (NDD) is essential in understanding the potential neurobiological mechanisms that underlie the connection between sleep disruption and NDD manifestations and progression., Objective: Explore the inter-relationships between NDD and age, sex, diagnosis of obstructive sleep apnea, snoring, and duration of sleep time with the head in the supine and non-supine positions., Methods: A case-control design was used to evaluate differences in sleep position obtained from multi-night, in-home Sleep Profiler recordings in 45 patients with diagnosed NDD (24 with mild cognitive impairment, 15 with Alzheimer's disease, and 6 with Lewy Body, Parkinson's, or other dementias) and 120 age-sex matched controls with normal cognition (NC)., Results: The frequency of supine sleep >2 h/night was significantly greater in the NDD than in the NC group (p < 0.001, odds ratio = 3.7), and remained significant after controlling for age, sex, snoring, and obstructive sleep apnea diagnosis (p = 0.01). There were no group differences in nocturnal mobility i.e., number of head position changes/h., Conclusion: This study demonstrates the utility of in-home measurements of sleep in defining the association of supine sleep position with neurodegenerative disorders. Our findings warrant further investigation, particularly in light of the recent evidence suggesting that sleep may an active role in the brain's ability to clear CNS neurotoxins and metabolites.

Abstract: Obstructive sleep apnea (OSA) is a globally recognized medical condition, associated with development of long-term adverse health consequences, including cardiovascular disease, cerebrovascular disease, neurocognitive deficiencies, and vehicular and occupational accidents. OSA can be screened effectively, because it can be identified well before the manifestation of the aforementioned poor health and public safety consequences. Additionally, appropriate management of OSA includes an assessment of outcomes before and after therapeutic intervention initiation. OSA clinical screening and outcome assessment tools exist; however, a key existing knowledge gap is identifying which tools are most clinically relevant and efficient to use in clinical practice models. The American Academy of Sleep Medicine (AASM) commissioned a task force (TF) of sleep medicine experts to identify and evaluate current OSA screening and assessment tools for adult patients and determine if they are reliable, effective, and feasible for use in clinical settings. No single tool met all the TF's objective criteria and subjective evaluation for clinical validity and feasibility to be recommended by the AASM. The TF provides several suggestions for the development of new tools or modifications to existing tools that would enhance their functionality in adults., (© 2018 American Academy of Sleep Medicine.)

Objective: To characterize features of medical student exposure to difficult conversations during a neurology core clerkship., Methods: This was a cross-sectional concurrent nested mixed methods study, and all students rotating through a required neurology clerkship between 2014 and 2015 were enrolled. Data collection included an electronic communication tracker, baseline and end-of-clerkship surveys, and 4 facilitated focus groups. Students were asked to log exposure to patient-clinician conversations about (1) new disability, (2) poor prognosis, (3) prognostic uncertainty (4), terminal diagnosis, and (5) end-of-life care., Results: A total of 159 students were enrolled and 276 conversations were tracked. Most (70%) students observed at least 1 difficult conversation, and conversations about poor prognosis, new disability, and prognostic uncertainty were most commonly logged. At clerkship end, most students (87%) desired additional bedside training in communication skills. Exposure to one of the predefined conversation types did not improve student perceived preparedness to lead difficult conversations in the future. In focus groups, students noted that the educational value of observation of a difficult conversation could be optimized with preconversation planning and postconversation debriefing., Conclusions: Difficult conversations are common in neurology, and represent a valuable opportunity to provide communication skills training on the wards. Future curricula should consider ways to leverage these existing opportunities to enhance communication skills training., (Copyright © 2018 American Academy of Neurology.)

This Viewpoint is based on a recent panel featured at the 2017 Winter Conference on Brain Research in which the psychiatric comorbidities of HIV infection were discussed. Psychiatric comorbid conditions occur at high rates in HIV infected patients, complicating treatment and contributing to poor outcomes. A complex relationship between HIV infection and psychiatric comorbidity is an active area of investigation, but increased awareness of the impact of psychiatric complications of NeuroAIDS is needed in both the laboratory and the clinic to better understand and treat these interrelated conditions.

Study Objectives: To assess the validity of sleep architecture and sleep continuity biomarkers obtained from a portable, multichannel forehead electroencephalography (EEG) recorder., Methods: Forty-seven subjects simultaneously underwent polysomnography (PSG) while wearing a multichannel frontopolar EEG recording device (Sleep Profiler). The PSG recordings independently staged by 5 registered polysomnographic technologists were compared for agreement with the autoscored sleep EEG before and after expert review. To assess the night-to-night variability and first night bias, 2 nights of self-applied, in-home EEG recordings obtained from a clinical cohort of 63 patients were used (41% with a diagnosis of insomnia/depression, 35% with insomnia/obstructive sleep apnea, and 17.5% with all three). The between-night stability of abnormal sleep biomarkers was determined by comparing each night's data to normative reference values., Results: The mean overall interscorer agreements between the 5 technologists were 75.9%, and the mean kappa score was 0.70. After visual review, the mean kappa score between the autostaging and five raters was 0.67, and staging agreed with a majority of scorers in at least 80% of the epochs for all stages except stage N1. Sleep spindles, autonomic activation, and stage N3 exhibited the least between-night variability ( P < .0001) and strongest between-night stability. Antihypertensive medications were found to have a significant effect on sleep quality biomarkers ( P < .02)., Conclusions: A strong agreement was observed between the automated sleep staging and human-scored PSG. One night's recording appeared sufficient to characterize abnormal slow wave sleep, sleep spindle activity, and heart rate variability in patients, but a 2-night average improved the assessment of all other sleep biomarkers., Commentary: Two commentaries on this article appear in this issue on pages 771 and 773., (© 2017 American Academy of Sleep Medicine)

Background: Sleep disordered breathing (SDB) is emerging as a significant health condition for children. The purpose of this study is to evaluate SDB symptoms in childhood cancer survivors and identify associations with quality of life (QOL) and psychological symptoms., Procedure: A sample of 62 survivors aged 8-18 years were recruited during routine survivorship visits. All subjects and their parents completed questionnaires to evaluate sleep, QOL and psychological symptoms; scales included were: Pediatric Sleep Questionnaire, Sleep Disordered Breathing Subscale (PSQ-SDBS), Pediatric Quality of Life Inventory (PedsQL) and Depression Anxiety Stress Scale (DASS-21). Continuous data were used for all scales and a threshold score of >0.33 on the PSA-SDBS was used to identify risk of SDB. The relationships between measures of sleep and independent variables were examined using Pearson correlations and multiple linear regression models for significant associations., Results: Of the 62 subjects enrolled, underlying diagnoses included 29 leukemias, 30 solid tumors and 3 non-malignant diseases. Nineteen percent of subjects were identified as having SDB risk on the PSQ-SDBS. The lowest mean PedsQL subscale score for parent and child ratings were school QOL; Parent mean 73(±SD 19) and Child mean 71(±SD 20). The severity of SDB per the PSQ was significantly associated with reduced total and school QOL which remained significant after adjusting for stress., Conclusions: Symptoms suggestive of SDB are common in childhood cancer survivors with negative implications for overall quality of life and school performance., (© 2015 Wiley Periodicals, Inc.)

In this study, we used the Pittsburgh Sleep Quality Index to divide the subjects into two groups, good sleepers and bad sleepers. We computed sleep behavioral (macro-sleep architectural) features and sleep spectral (micro-sleep architectural) features in order to observe if the annotated EEG data can be used to distinguish between good and bad sleepers in a more quantitative manner. Specifically, the macro-sleep features were defined by sleep stages and included sleep transitions, percentage of time spent in each sleep stage, and duration of time spent in each sleep stage. The micro-sleep features were obtained from the power spectrum of the EEG signals by computing the total power across all channels and all frequencies, as well as the average power in each sleep stage and across different frequency bands. We found that while the scoring-independent micro features are significantly different between the two groups, the macro features are not able to significantly distinguish the two groups. The fact that the macro features computed from the scoring files cannot pick up the expected difference in the EEG signals raises the question as to whether human scoring of EEG signals is practical in assessing sleep quality.

HIV patients are often plagued by sleep disorders and suffer from sleep deprivation. However, there remains a wide gap in our understanding of the relationship between HIV status, poor sleep, overall function and future outcomes; particularly in the case of HIV patients otherwise well controlled on cART (combined anti-retroviral therapy). In this study, we compared two groups: 16 non-HIV subjects (seronegative controls) and 12 seropositive HIV patients with undetectable viral loads. We looked at sleep behavioral (macro-sleep) features and sleep spectral (micro-sleep) features obtained from human-scored overnight EEG recordings to study whether the scored EEG data can be used to distinguish between controls and HIV subjects. Specifically, the macro-sleep features were defined by sleep stages and included sleep transitions, percentage of time spent in each sleep stage, and duration of time spent in each sleep stage. The micro-sleep features were obtained from the power spectrum of the EEG signals by computing the total power across all channels and frequencies, as well as the average power in each sleep stage and across different frequency bands. While the macro features do not distinguish between the two groups, there is a significant difference and a high classification accuracy for the scoring-independent micro features. This spectral separation is interesting because evidence suggests a relationship between sleep complaints and cognitive dysfunction in HIV patients stable on cART. Furthermore, there are currently no biomarkers that predict the early development of cognitive decline in HIV patients. Thus, a micro-sleep architectural approach could serve as a biomarker to identify HIV patients vulnerable to cognitive decline, providing an avenue to explore the utility of early intervention.

Background: Parkinson's disease (PD) represents a major public health challenge that will only grow in our aging population. Understanding the connection between PD and associated prodromal conditions, such as rapid eye movement sleep behavioral disorder (RBD), is critical to identifying prevention strategies. However, the relationship between RBD and severity of motor findings in early PD is unknown. This study aims to examine this relationship., Methods: The study population consisted of 418 PD patients who completed the Movement Disorders Society-United Parkinson's Disease Rating Scale (MDS-UPDRS) and rapid eye movement sleep (REM) disorder questionnaires at the baseline visit of the Michael J. Fox's Parkinson's Progression Markers Initiative (PPMI). Cross-sectional analysis was carried out to assess the association between REM Sleep Behavior Screening Questionnaire score and MDS UPDRS-3 (motor) score categories. Correlation with a higher score category was described as "worse motor findings". A score of 5 on the REM disorder questionnaire was defined as predictive of RBD., Results: Out of the 418 PD patients, 113 (27.0%) had RBD. With univariate logistic regression analysis, individuals with scores predictive of RBD were 1.66 times more likely to have worse motor findings (p = 0.028). Even with age, gender, and Geriatric Depression Scale scores taken into account, individuals with scores predictive of RBD were 1.69 times more likely to have worse motor findings (p = 0.025)., Discussion: PD patients with RBD symptoms had worse motor findings than those unlikely to have RBD. This association provides further evidence for the relationship between RBD and PD.

Study Objectives: Prior studies using positron emission tomography (PET) or single-photon emission computed tomography techniques have reported inconsistent findings regarding differences between patients with restless legs syndrome (RLS) and control patients in the striatal dopamine-2 receptor (D2R) binding potentials (BP). D2R-BP does reflect receptor-ligand interactions such as receptor affinity (K(d)) and density (β(max)) or neurotransmitter synaptic concentrations. Thus, differences in D2R-BP reflect changes in these primary factors. PET techniques are currently available to estimate D2R β(max) and K(d)., Design: Separate morning and evening PET scans were performed. The D2R-BP were measured in basal ganglia using [(11)C]raclopride., Setting: Academic medical center., Patients or Participants: Thirty-one patients with primary RLS and 36 age- and sex-matched control patients completed the study., Measures and Results: Patients with RLS had lower D2R-BP in putamen and caudate but not the ventral striatum. A subgroups analysis of those RLS patients who had not previously taken dopaminergic medications continued to show a significantly lower D2R-BP in the posterior putamen. D2R-BP did not differ between night and day for either group. D2R β(max) and K(d) did not differ significantly between patients with RLS and control patients but did show a strong and significant increase at night in the ventral striatum. Primary and secondary clinical measures of disease status failed to show any relation to D2R in any brain region., Conclusions: Given the lack of any difference in either β(max) or K(d) and the prior studies supporting an increase in presynaptic dopaminergic activity, the current changes found in D2R-BP likely reflect an increase in synaptic dopamine.

Background: Poor sleep has adverse affects on heath, yet few studies have addressed the goal of improving sleep among hospitalized patients. We evaluated the effectiveness of a sleep-promoting intervention on the quality and quantity of sleep among inpatients., Methods: This study was conducted on a neurological ward in a large, tertiary care hospital. Sleep quality, quantity, and disruptors were assessed using questionnaires completed by patients during their hospital stay and Press Ganey surveys completed retrospectively. Room noise was also measured using noise meters. Data from each of 4 chronological phases of the study (baseline, basic intervention, "washout," and deluxe intervention) were analyzed. In the intervention phases, nurses conducted "Sleep Rounds" at bedtime, during which sleep-promoting practices were implemented, including lights out, television off, temperature adjustment, and a final restroom usage., Results: Patients reported 5 (interquartile range [IQR] 3) hours of sleep per night, awoke 3 (IQR 3) times nightly, and reported a median sleep latency of 11 to 15 minutes. Pain, staff interruptions, and roommates were the most significant barriers to good sleep. Noise levels were adequately low (35-40 dB) at night but were not positively impacted by our sleep-promoting interventions. Patients perceived noise on the unit to be worse during phases of the study in which there was no intervention., Conclusions: Patient perception of sleep experience improved during the phases in which Sleep Rounds were implemented, despite the fact that there was no measurable improvement in sleep or sleep-disrupting factors., (Copyright © 2012 Society of Hospital Medicine.)

Study Objectives: Prior studies, all using SPECT techniques, failed to find any differences for dopamine transporter (DAT) in restless legs syndrome (RLS) subjects. The distinct pharmacokinetic properties associated with SPECT-determined DAT along with rapid biodynamic changes in DAT may, however, have missed membrane-bound DAT differences. The current studies assessed real-time DAT binding potentials (BP) in striatum of RLS patients using (11)C-methylphenidate and PET techniques., Design: RLS medications were stopped at least 11 days prior to the PET study. Clinical severity of RLS was also assessed. PET scans were performed at 2 different times of day (starting at 08:30 and 19:30) in separate groups of subjects. The primary outcome measure was total striatal DAT BP., Participants: Thirty-six patients with primary RLS and 34 age- and gender-matched controls., Results: RLS subjects had significantly lower DAT binding in the striatum compared to controls on both the Day and the Night scans. DAT was decreased in putamen and caudate but not the ventral striatum of RLS subjects. There were no diurnal differences in DAT for the total group or for control and RLS separately. DAT BP did not correlate with any clinical measures of RLS., Conclusion: The current study found a significant decrease in DAT BP in two independent studies. These results when viewed along with prior RLS SPECT and autopsy studies of DAT, and cell culture studies with iron deficiency and DAT, suggest that membrane-bound striatal DAT, but not total cellular DAT, may be decreased in RLS.

Background and Purpose: Restless Legs Syndrome (RLS) is a common sensorimotor disorder often associated with significant chronic sleep loss. Previous studies looking at the effects of sleep loss on daytime function in RLS individuals, using subjective reporting techniques have yielded mixed results. In this study we used more objective measures of alertness and compared RLS subjects who are off treatments and chronically sleep restricted to chronic sleep-restricted controls., Subjects and Methods: The final sample consisted of 20 RLS subjects (10 male and 10 female) and 13 sleep-restricted controls (seven male and six female). Thirteen controls underwent a 14-day chronic partial sleep-restriction protocol in order to closely match the degree of chronic sleep loss reportedly experienced by untreated RLS patients. On the final day of the protocol each subject performed a morning and evening Suggested Immobilization Test (SIT) which served as a modified Maintenance of Wakefulness Test (MWT). RLS and control groups were compared for differences in alertness as measured objectively by the sleep latency on the morning and evening SITs., Results: The RLS subjects had a longer sleep latency on the morning and evening SIT than controls (t=3.80, p=0.001, U=31.0, p<0.001, respectively). Even after controlling for the potential arousal impact associated with increased leg activity, RLS individuals still demonstrated a higher degree of objective alertness (p=0.023, p=0.006, Fisher's exact test)., Conclusions: RLS subjects, despite having, if anything, greater sleep loss, displayed greater sustained alertness than sleep-restricted controls. Thus, the heightened degree of alertness demonstrated by RLS patients may be in contrast to the perceived impairment in mood, vigor, and vigilance commonly reported in previous studies.

The onset of sleep is associated with a variety of changes in both behavioral and physiologic states. Sleep is not a uniform state either: it has different stages that affect different areas of the brain and body. Nonrapid eye movement sleep stages are as different from rapid eye movement sleep as is wakefulness. Circadian rhythms of physiologic systems also impact wake, sleep, sleepiness, and alertness. There are characteristic changes in both sleep patterns and circadian rhythm that occur with aging. The cardiovascular, respiratory, endocrine and gastrointestinal systems also undergo changes with sleep onset. This article reviews the aspects of normal sleep, physiologic changes that occur in the human body with sleep, and how sleep changes over the lifespan.