Changes in electroencephalographic microstates between evening and morning are associated with overnight sleep slow waves in healthy individuals.

STUDY OBJECTIVES: Microstates are semi-stable voltage topographies that account for most of electroencephalogram (EEG) variance. However, the impact of time of the day and sleep on microstates has not been examined. To address this gap, we assessed whether microstates differed between the evening and morning and whether sleep slow waves correlated with microstate changes in healthy participants. METHODS: Forty-five healthy subjects were recruited. Each participant underwent six minutes of resting state EEG recordings in the evening and morning, interleaved by sleep EEGs. Evening-to-morning changes in microstate duration, coverage, and occurrence were assessed. Furthermore, correlation between microstate changes and sleep slow-wave activity (SWA) and slow-wave density (SWD) were performed. RESULTS: Two-way ANOVAs with Microstate Class (A, B, C, and D) and Time (evening and morning) revealed significant Microstate Class*Time interaction for duration (F(44) = 5.571, p = 0.002), coverage (F(44) = 6.833, p = 0.001), and occurrence (F(44) = 5.715, p = 0.002). Post-hoc comparisons showed significant effects for microstate C duration (padj=0.048, Cohen's d = -0.389), coverage (padj=0.002, Cohen's d = -0.580), and occurrence (padj=0.002, Cohen's d= -0.606). Topographic analyses revealed inverse correlations between SWD, but not SWA, and evening-to-morning changes in microstate C duration (r = - 0.51, padj = 0.002), coverage (r = - 0.45, padj = 0.006), and occurrence (r = - 0.38, padj = 0.033). CONCLUSION: Microstate characteristics showed significant evening-to-morning changes associated with, and possibly regulated by, sleep slow-waves. These findings suggest that future microstate studies should control for time of day and sleep effects.

Natural Oscillatory Frequency Slowing in the Premotor Cortex of Early-Course Schizophrenia Patients: A TMS-EEG Study.

Despite the heavy burden of schizophrenia, research on biomarkers associated with its early course is still ongoing. Single-pulse Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) has revealed that the main oscillatory frequency (or "natural frequency") is reduced in several frontal brain areas, including the premotor cortex, of chronic patients with schizophrenia. However, no study has explored the natural frequency at the beginning of illness. Here, we used TMS-EEG to probe the intrinsic oscillatory properties of the left premotor cortex in early-course schizophrenia patients (<2 years from onset) and age/gender-matched healthy comparison subjects (HCs). State-of-the-art real-time monitoring of EEG responses to TMS and noise-masking procedures were employed to ensure data quality. We found that the natural frequency of the premotor cortex was significantly reduced in early-course schizophrenia compared to HCs. No correlation was found between the natural frequency and age, clinical symptom severity, or dose of antipsychotic medications at the time of TMS-EEG. This finding extends to early-course schizophrenia previous evidence in chronic patients and supports the hypothesis of a deficit in frontal cortical synchronization as a core mechanism underlying this disorder. Future work should further explore the putative role of frontal natural frequencies as early pathophysiological biomarkers for schizophrenia.

N-Acetylaspartate and Choline Metabolites in Cortical and Subcortical Regions in Clinical High Risk Relative to Healthy Control Subjects: An Exploratory 7T MRSI Study.

N-acetylaspartate (NAA) and choline (Cho) are two brain metabolites implicated in several key neuronal functions. Abnormalities in these metabolites have been reported in both early course and chronic patients with schizophrenia (SCZ). It is, however, unclear whether NAA and Cho's alterations occur even before the onset of the disorder. Clinical high risk (CHR) individuals are a population uniquely enriched for psychosis and SCZ. In this exploratory study, we utilized 7-Tesla magnetic resonance spectroscopic imaging (MRSI) to examine differences in total NAA (tNAA; NAA + N-acetylaspartylglutamate [NAAG]) and major choline-containing compounds, including glycerophosphorylcholine and phosphorylcholine [tCho], over the creatine (Cre) levels between 26 CHR and 32 healthy control (HC) subjects in the subcortical and cortical regions. While no tCho/Cre differences were found between groups in any of the regions of interest (ROIs), we found that CHR had significantly reduced tNAA/Cre in the right dorsal lateral prefrontal cortex (DLPFC) compared to HC, and that the right DLPFC tNAA/Cre reduction in CHR was negatively associated with their positive symptoms scores. No tNAA/Cre differences were found between CHR and HC in other ROIs. In conclusion, reduced tNAA/Cre in CHR vs. HC may represent a putative molecular biomarker for risk of psychosis and SCZ that is associated with symptom severity.

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson's disease.

Introduction: Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson's disease (PD). FOG detection is possible using acceleration data from wearable sensors, and a convolutional neural network (CNN) is often used to determine the presence of FOG epochs. We compared the performance of a standard CNN for the detection of FOG with two more complex networks, which are well suited for time series data, the MiniRocket and the InceptionTime. Methods: We combined acceleration data of people with PD across four studies. The final data set was split into a training (80%) and hold-out test (20%) set. A fifth study was included as an unseen test set. The data were windowed (2 s) and five-fold cross-validation was applied. The CNN, MiniRocket, and InceptionTime models were evaluated using a receiver operating characteristic (ROC) curve and its area under the curve (AUC). Multiple sensor configurations were evaluated for the best model. The geometric mean was subsequently calculated to select the optimal threshold. The selected model and threshold were evaluated on the hold-out and unseen test set. Results: A total of 70 participants (23.7 h, 9% FOG) were included in this study for training and testing, and in addition, 10 participants provided an unseen test set (2.4 h, 11% FOG). The CNN performed best (AUC = 0.86) in comparison to the InceptionTime (AUC = 0.82) and MiniRocket (AUC = 0.76) models. For the CNN, we found a similar performance for a seven-sensor configuration (lumbar, upper and lower legs and feet; AUC = 0.86), six-sensor configuration (upper and lower legs and feet; AUC = 0.87), and two-sensor configuration (lower legs; AUC = 0.86). The optimal threshold of 0.45 resulted in a sensitivity of 77% and a specificity of 58% for the hold-out set (AUC = 0.72), and a sensitivity of 85% and a specificity of 68% for the unseen test set (AUC = 0.90). Conclusion: We confirmed that deep learning can be used to detect FOG in a large, heterogeneous dataset. The CNN model outperformed more complex networks. This model could be employed in future personalized interventions, with the ultimate goal of using automated FOG detection to trigger real-time cues to alleviate FOG in daily life.

Examining First Night Effect on Sleep Parameters with hd-EEG in Healthy Individuals.

Difficulty sleeping in a novel environment is a common phenomenon that is often described as the first night effect (FNE). Previous works have found FNE on sleep architecture and sleep power spectra parameters, especially during non-rapid eye movement (NREM) sleep. However, the impact of FNE on sleep parameters, including local differences in electroencephalographic (EEG) activity across nights, has not been systematically assessed. Here, we performed high-density EEG sleep recordings on 27 healthy individuals on two nights and examined differences in sleep architecture, NREM (stages 2 and 3) EEG power spectra, and NREM power topography across nights. We found higher wakefulness after sleep onset (WASO), reduced sleep efficiency, and less deep NREM sleep (stage 3), along with increased high-frequency NREM EEG power during the first night of sleep, corresponding to small to medium effect sizes (Cohen's d ≤ 0.5). Furthermore, study individuals showed significantly lower slow-wave activity in right frontal/prefrontal regions as well as higher sigma and beta activities in medial and left frontal/prefrontal areas, yielding medium to large effect sizes (Cohen's d ≥ 0.5). Altogether, these findings suggest the FNE is characterized by less efficient, more fragmented, shallower sleep that tends to affect especially certain brain regions. The magnitude and specificity of these effects should be considered when designing sleep studies aiming to compare across night effects.

The Effects of Augmented Reality Visual Cues on Turning in Place in Parkinson's Disease Patients With Freezing of Gait.

Background: Turning in place is particularly bothersome for patients with Parkinson's disease (PD) experiencing freezing of gait (FOG). Cues designed to enforce goal-directed turning are not yet available. Objectives: Assess whether augmented reality (AR) visual cues improve FOG and turning in place in PD patients with FOG. Methods: Sixteen PD patients with FOG performed a series of 180° turns under an experimental condition with AR visual cues displayed through a HoloLens and two control conditions (one consisting of auditory cues and one without any cues). FOG episodes were annotated by two independent raters from video recordings. Motion data were measured with 17 inertial measurement units for calculating axial kinematics, scaling, and timing of turning. Results: AR visual cues did not reduce the percent time frozen (p = 0.73) or the number (p = 0.73) and duration (p = 0.78) of FOG episodes compared to the control condition without cues. All FOG parameters were higher with AR visual cues than with auditory cues [percent time frozen (p = 0.01), number (p = 0.02), and duration (p = 0.007) of FOG episodes]. The AR visual cues did reduce the peak angular velocity (visual vs. uncued p = 0.03; visual vs. auditory p = 0.02) and step height (visual vs. uncued p = 0.02; visual vs. auditory p = 0.007), and increased the step height coefficient of variation (visual vs. uncued p = 0.04; visual vs. auditory p = 0.01) and time to maximum head-pelvis separation (visual vs. uncued p = 0.02; visual vs. auditory p = 0.005), compared to both control conditions. Conclusions: The AR visual cues in this study did not reduce FOG, and worsened some measures of axial kinematics, and turn scaling and timing. Stimulating goal-directed turning might, by itself, be insufficient to reduce FOG and improve turning performance. Trial Registration: This study was registered in the Dutch trial registry (NTR6409; 2017-02-16).

The Beneficial Effects of Conventional Visual Cues Are Retained When Augmented Reality Glasses Are Worn.

Wearing smart glasses may be distracting and thus annihilate the beneficial effects of cues on freezing of gait in Parkinson's disease. Furthermore, augmented reality cues might be effective in reducing FOG specifically in cueing-responsive patients. We present a single-patient study in which a patient with Parkinson's disease traversed a doorway under different cueing conditions. Wearing augmented reality (AR) glasses did not deteriorate FOG nor affect the beneficial effects of cues. The AR visual cues did not improve FOG. This single-patient study implies that the current design of AR glasses does not stand in the way of the development of augmented reality visual cues. However, the effectivity of augmented reality visual cues remains to be proven.

Assessing the exposure-response relationship of sleep disturbance and vibration in field and laboratory settings.

Exposure to nocturnal freight train vibrations may impact sleep, but exposure-response relationships are lacking. The European project CargoVibes evaluated sleep disturbance both in the field and in the laboratory and provides unique data, as measures of response and exposure metrics are comparable. This paper therefore provides data on exposure-response relationships of vibration and sleep disturbance and compares the relationships evaluated in the laboratory and the field. Two field studies (one in Poland and one in the Netherlands) with 233 valid respondents in total, and three laboratory studies in Sweden with a total of 59 subjects over 350 person-nights were performed. The odds ratios (OR) of sleep disturbance were analyzed in relation to nighttime vibration exposure by ordinal logit regression, adjusting for moderating factors common for the studies. Outcome specific fractions were calculated for eleven sleep outcomes and supported comparability between the field and laboratory settings. Vibration exposure was significantly associated with sleep disturbance, OR = 3.51 (95% confidence interval 2.6-4.73) denoting a three and a half times increase in the odds of sleep disturbance with one unit increased 8 h nighttime log10 Root Mean Square vibration. The results suggest no significant difference between field and laboratory settings OR = 1.37 (0.59-3.19). However, odds of sleep disturbance were higher in the Netherlands as compared to Sweden, indicating unexplained differences between study populations or countries, possibly related to cultural and contextual differences and uncertainties in exposure assessments. Future studies should be carefully designed to record explanatory factors in the field and enhance ecological validity in the laboratory. Nevertheless, the presented combined data set provides a first set of exposure response relationships for vibration-induced sleep disturbance, which are useful when considering public health outcomes among exposed populations.

Aviation Noise Impacts: State of the Science.

Noise is defined as "unwanted sound." Aircraft noise is one, if not the most detrimental environmental effect of aviation. It can cause community annoyance, disrupt sleep, adversely affect academic performance of children, and could increase the risk for cardiovascular disease of people living in the vicinity of airports. In some airports, noise constrains air traffic growth. This consensus paper was prepared by the Impacts of Science Group of the Committee for Aviation Environmental Protection of the International Civil Aviation Organization and summarizes the state of the science of noise effects research in the areas of noise measurement and prediction, community annoyance, children's learning, sleep disturbance, and health. It also briefly discusses civilian supersonic aircraft as a future source of aviation noise.

Usability of Three-dimensional Augmented Visual Cues Delivered by Smart Glasses on (Freezing of) Gait in Parkinson's Disease.

External cueing is a potentially effective strategy to reduce freezing of gait (FOG) in persons with Parkinson's disease (PD). Case reports suggest that three-dimensional (3D) cues might be more effective in reducing FOG than two-dimensional cues. We investigate the usability of 3D augmented reality visual cues delivered by smart glasses in comparison to conventional 3D transverse bars on the floor and auditory cueing via a metronome in reducing FOG and improving gait parameters. In laboratory experiments, 25 persons with PD and FOG performed walking tasks while wearing custom-made smart glasses under five conditions, at the end-of-dose. For two conditions, augmented visual cues (bars/staircase) were displayed via the smart glasses. The control conditions involved conventional 3D transverse bars on the floor, auditory cueing via a metronome, and no cueing. The number of FOG episodes and percentage of time spent on FOG were rated from video recordings. The stride length and its variability, cycle time and its variability, cadence, and speed were calculated from motion data collected with a motion capture suit equipped with 17 inertial measurement units. A total of 300 FOG episodes occurred in 19 out of 25 participants. There were no statistically significant differences in number of FOG episodes and percentage of time spent on FOG across the five conditions. The conventional bars increased stride length, cycle time, and stride length variability, while decreasing cadence and speed. No effects for the other conditions were found. Participants preferred the metronome most, and the augmented staircase least. They suggested to improve the comfort, esthetics, usability, field of view, and stability of the smart glasses on the head and to reduce their weight and size. In their current form, augmented visual cues delivered by smart glasses are not beneficial for persons with PD and FOG. This could be attributable to distraction, blockage of visual feedback, insufficient familiarization with the smart glasses, or display of the visual cues in the central rather than peripheral visual field. Future smart glasses are required to be more lightweight, comfortable, and user friendly to avoid distraction and blockage of sensory feedback, thus increasing usability.

Ocular and visual disorders in Parkinson's disease: Common but frequently overlooked.

Patients with Parkinson's disease (PD) often compensate for their motor deficits by guiding their movements visually. A wide range of ocular and visual disorders threatens the patients' ability to benefit optimally from visual feedback. These disorders are common in patients with PD, yet they have received little attention in both research and clinical practice, leading to unnecessary - but possibly treatable - disability. Based on a literature search covering 50 years, we review the range of ocular and visual disorders in patients with PD, and classify these according to anatomical structures of the visual pathway. We discuss six common disorders in more detail: dry eyes; diplopia; glaucoma and glaucoma-like visual problems; impaired contrast and colour vision; visuospatial and visuoperceptual impairments; and visual hallucinations. In addition, we review the effects of PD-related pharmacological and surgical treatments on visual function, and we offer practical recommendations for clinical management. Greater awareness and early recognition of ocular and visual problems in PD might enable timely instalment of tailored treatments, leading to improved patient safety, greater independence, and better quality of life.

The clinical heterogeneity of drug-induced myoclonus: an illustrated review.

A wide variety of drugs can cause myoclonus. To illustrate this, we first discuss two personally observed cases, one presenting with generalized, but facial-predominant, myoclonus that was induced by amantadine; and the other presenting with propriospinal myoclonus triggered by an antibiotic. We then review the literature on drugs that may cause myoclonus, extracting the corresponding clinical phenotype and suggested underlying pathophysiology. The most frequently reported classes of drugs causing myoclonus include opiates, antidepressants, antipsychotics, and antibiotics. The distribution of myoclonus ranges from focal to generalized, even amongst patients using the same drug, which suggests various neuro-anatomical generators. Possible underlying pathophysiological alterations involve serotonin, dopamine, GABA, and glutamate-related processes at various levels of the neuraxis. The high number of cases of drug-induced myoclonus, together with their reported heterogeneous clinical characteristics, underscores the importance of considering drugs as a possible cause of myoclonus, regardless of its clinical characteristics.

Personal and situational variables associated with wind turbine noise annoyance.

The possibility that wind turbine noise (WTN) affects human health remains controversial. The current analysis presents results related to WTN annoyance reported by randomly selected participants (606 males, 632 females), aged 18-79, living between 0.25 and 11.22 km from wind turbines. WTN levels reached 46 dB, and for each 5 dB increase in WTN levels, the odds of reporting to be either very or extremely (i.e., highly) annoyed increased by 2.60 [95% confidence interval: (1.92, 3.58), p < 0.0001]. Multiple regression models had R(2)'s up to 58%, with approximately 9% attributed to WTN level. Variables associated with WTN annoyance included, but were not limited to, other wind turbine-related annoyances, personal benefit, noise sensitivity, physical safety concerns, property ownership, and province. Annoyance was related to several reported measures of health and well-being, although these associations were statistically weak (R(2 )< 9%), independent of WTN levels, and not retained in multiple regression models. The role of community tolerance level as a complement and/or an alternative to multiple regression in predicting the prevalence of WTN annoyance is also provided. The analysis suggests that communities are between 11 and 26 dB less tolerant of WTN than of other transportation noise sources.

Feasibility of external rhythmic cueing with the Google Glass for improving gait in people with Parkinson's disease.

New mobile technologies like smartglasses can deliver external cues that may improve gait in people with Parkinson's disease in their natural environment. However, the potential of these devices must first be assessed in controlled experiments. Therefore, we evaluated rhythmic visual and auditory cueing in a laboratory setting with a custom-made application for the Google Glass. Twelve participants (mean age = 66.8; mean disease duration = 13.6 years) were tested at end of dose. We compared several key gait parameters (walking speed, cadence, stride length, and stride length variability) and freezing of gait for three types of external cues (metronome, flashing light, and optic flow) and a control condition (no-cue). For all cueing conditions, the subjects completed several walking tasks of varying complexity. Seven inertial sensors attached to the feet, legs and pelvis captured motion data for gait analysis. Two experienced raters scored the presence and severity of freezing of gait using video recordings. User experience was evaluated through a semi-open interview. During cueing, a more stable gait pattern emerged, particularly on complicated walking courses; however, freezing of gait did not significantly decrease. The metronome was more effective than rhythmic visual cues and most preferred by the participants. Participants were overall positive about the usability of the Google Glass and willing to use it at home. Thus, smartglasses like the Google Glass could be used to provide personalized mobile cueing to support gait; however, in its current form, auditory cues seemed more effective than rhythmic visual cues.