Erratum: Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication.

[This corrects the article DOI: 10.1162/netn_a_00272.].

Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication.

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking.

Rise and shine: The use of polychromatic short-wavelength-enriched light to mitigate sleep inertia at night following awakening from slow-wave sleep.

Sleep inertia is the brief period of performance impairment and reduced alertness experienced after waking, especially from slow-wave sleep. We assessed the efficacy of polychromatic short-wavelength-enriched light to improve vigilant attention, alertness and mood immediately after waking from slow-wave sleep at night. Twelve participants (six female, 23.3 ± 4.2 years) maintained an actigraphy-confirmed sleep schedule of 8.5 hr for 5 nights, and 5 hr for 1 night prior to an overnight laboratory visit. In the laboratory, participants were awakened from slow-wave sleep, and immediately exposed to either dim, red ambient light (control) or polychromatic short-wavelength-enriched light (light) for 1 hr in a randomized crossover design. They completed a 5-min Psychomotor Vigilance Task, the Karolinska Sleepiness Scale, and Visual Analogue Scales of mood at 2, 17, 32 and 47 min after waking. Following this testing period, lights were turned off and participants returned to sleep. They were awakened from their subsequent slow-wave sleep period and received the opposite condition. Compared with the control condition, participants exposed to light had fewer Psychomotor Vigilance Task lapses (χ2 [1] = 5.285, p = 0.022), reported feeling more alert (Karolinska Sleepiness Scale: F1,77  = 4.955, p = 0.029; Visual Analogue Scalealert : F1,77  = 8.226, p = 0.005), and reported improved mood (Visual Analogue Scalecheerful : F1,77  = 8.615, p = 0.004). There was no significant difference in sleep-onset latency between conditions following the testing period (t10  = 1.024, p = 0.330). Our results suggest that exposure to polychromatic short-wavelength-enriched light immediately after waking from slow-wave sleep at night may help improve vigilant attention, subjective alertness, and mood. Future studies should explore the potential mechanisms of this countermeasure and its efficacy in real-world environments.

Supervision of a self-driving vehicle unmasks latent sleepiness relative to manually controlled driving.

Human error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had more involuntary transitions to sleep, had slower reaction times and more attentional failures, and showed substantial modifications in brain synchronization during and following an autonomous drive compared to a manually controlled drive. Our findings suggest that the introduction of partial self-driving capabilities in vehicles has the potential to paradoxically increase accident risk.

Systematic Gene-to-Phenotype Arrays: A High-Throughput Technique for Molecular Phenotyping.

We have developed a highly parallel strategy, systematic gene-to-phenotype arrays (SGPAs), to comprehensively map the genetic landscape driving molecular phenotypes of interest. By this approach, a complete yeast genetic mutant array is crossed with fluorescent reporters and imaged on membranes at high density and contrast. Importantly, SGPA enables quantification of phenotypes that are not readily detectable in ordinary genetic analysis of cell fitness. We benchmark SGPA by examining two fundamental biological phenotypes: first, we explore glucose repression, in which SGPA identifies a requirement for the Mediator complex and a role for the CDK8/kinase module in regulating transcription. Second, we examine selective protein quality control, in which SGPA identifies most known quality control factors along with U34 tRNA modification, which acts independently of proteasomal degradation to limit misfolded protein production. Integration of SGPA with other fluorescent readouts will enable genetic dissection of a wide range of biological pathways and conditions.

Fatigue Risk Management: The Impact of Anesthesiology Residents' Work Schedules on Job Performance and a Review of Potential Countermeasures.

Long duty periods and overnight call shifts impair physicians' performance on measures of vigilance, psychomotor functioning, alertness, and mood. Anesthesiology residents typically work between 64 and 70 hours per week and are often required to work 24 hours or overnight shifts, sometimes taking call every third night. Mitigating the effects of sleep loss, circadian misalignment, and sleep inertia requires an understanding of the relationship among work schedules, fatigue, and job performance. This article reviews the current Accreditation Council for Graduate Medical Education guidelines for resident duty hours, examines how anesthesiologists' work schedules can affect job performance, and discusses the ramifications of overnight and prolonged duty hours on patient safety and resident well-being. We then propose countermeasures that have been implemented to mitigate the effects of fatigue and describe how training programs or practice groups who must work overnight can adapt these strategies for use in a hospital setting. Countermeasures include the use of scheduling interventions, strategic naps, microbreaks, caffeine use during overnight and extended shifts, and the use of bright lights in the clinical setting when possible or personal blue light devices when the room lights must be turned off. Although this review focuses primarily on anesthesiology residents in training, many of the mitigation strategies described here can be used effectively by physicians in practice.

Oculometric Assessment of Sensorimotor Impairment Associated with TBI.

PURPOSE: Diffuse tissue damage from impact or blast traumatic brain injury (TBI) degrades information processing throughout the brain, often resulting in impairments in sensorimotor function. We have developed an eye-movement assessment test, consisting of a simple, appropriately randomized, radial tracking task together with a broad set of oculometric measures that can be combined to yield a sensitive overall indicator of sensorimotor functional status. We show here that this multidimensional method can be used to detect and characterize sensorimotor deficits associated with TBI. METHODS: To compare dynamic visuomotor processing of TBI subjects (n = 34) with a separate control population (n = 41), we used the Comprehensive Oculometric Behavioral Response Assessment (COBRA) method (Liston & Stone, J Vision. 14:12, 2014) to quantify 10 performance metrics for each subject. Each TBI subject's set of oculometrics was then combined to compute a single TBI impairment vector whose magnitude we refer to as the impairment index. RESULTS: In our TBI population, several individual oculometrics were significantly degraded, including pursuit latency, initial pursuit acceleration, pursuit gain, catch-up saccade amplitude, proportion smooth tracking, and speed responsiveness. Furthermore, the TBI impairment index discriminated TBI subjects from controls with an 81% probability that increased with self-reported TBI severity; although the 9 subjects self-reporting "little-to-no" residual impairment were statistically indistinguishable from controls (58% probability), the remaining 25 subjects were easily detectable (91% probability). Given the demonstrated link between higher-order visual perception/cognition and eye movements, we interpret the observed TBI-related impairments as degradations in the speed, accuracy, and precision of information processing within cortical circuits supporting higher-order visual processing and sensorimotor control, not just low-level brainstem motor deficits. CONCLUSIONS: We conclude that multidimensional oculometric testing could be used as a sensitive screen for subtle neurological signs of subclinical neurological insults, to quantify functional impairment, to monitor deterioration or recovery, and to evaluate treatment efficacy.

Beyond Agar: Gel Substrates with Improved Optical Clarity and Drug Efficiency and Reduced Autofluorescence for Microbial Growth Experiments.

Agar, a seaweed extract, has been the standard support matrix for microbial experiments for over a century. Recent developments in high-throughput genetic screens have created a need to reevaluate the suitability of agar for use as colony support, as modern robotic printing systems now routinely spot thousands of colonies within the area of a single microtiter plate. Identifying optimal biophysical, biochemical, and biological properties of the gel support matrix in these extreme experimental conditions is instrumental to achieving the best possible reproducibility and sensitivity. Here we systematically evaluate a range of gelling agents by using the yeast Saccharomyces cerevisiae as a model microbe. We find that carrageenan and Phytagel have superior optical clarity and reduced autofluorescence, crucial for high-resolution imaging and fluorescent reporter screens. Nutrient choice and use of refined Noble agar or pure agarose reduce the effective dose of numerous selective drugs by >50%, potentially enabling large cost savings in genetic screens. Using thousands of mutant yeast strains to compare colony growth between substrates, we found no evidence of significant growth or nutrient biases between gel substrates, indicating that researchers could freely pick and choose the optimal gel for their respective application and experimental condition.