Evoked responses from the auditory cortex.
Evoked response from auditory cortex in cat in relation to local injury to cortex, anesthesia, and sleep
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Evoked response from auditory cortex in cat in relation to local injury to cortex, anesthesia, and sleep
EEG of pilot during orbital flight on Gemini VII used to study sleep cycles
EEG baselines covering wide range of states of wakefulness and sleep in astronaut candidates estimated by computation and pattern recognition techniques
Long-term space voyages pose numerous known and unknown health hazards, to the human immune system. Well-studied clinical examples of secondary immunodeficiencies created on Earth, lead one to predict that the conditions of prolonged space flight would weaken the human immune responses that normally hold infection and cancer in check. From evidence gathered from humans flown for prolonged periods in space and from human models of space flight studied on Earth it is reasonable to suspect that space travelers to the planet Mars would experience a weakening of immunity. Subtle defects of immune cell structure and function have been observed in astronauts, such as weakening of specific T-lymphocyte recall of specific antigens. Ground-based models also have demonstrated alterations of immune function, such as the elevation of neuroendocrine immune system messengers, interleukin-6, and soluble tumor necrosis factor-alpha receptor in sleep deprivation. Since severe immune compromise the clinical consequences of reactivation of latent virus infections and the development of cancer, has yet to be seen in space flight or in the Earth models, it is extremely important to begin to quantify early changes in immunity to predict the development of immune system collapse with poor clinical outcomes. This approach is designed to validate a number of surrogate markers that will predict trouble ahead. Inherent in this research is the development of countermeasures to reduce the risks of infection and cancer in the first humans going to Mars.
We find that a universal homogeneous scaling form describes the distribution of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.
Regulation of circadian period in humans was thought to differ from that of other species, with the period of the activity rhythm reported to range from 13 to 65 hours (median 25.2 hours) and the period of the body temperature rhythm reported to average 25 hours in adulthood, and to shorten with age. However, those observations were based on studies of humans exposed to light levels sufficient to confound circadian period estimation. Precise estimation of the periods of the endogenous circadian rhythms of melatonin, core body temperature, and cortisol in healthy young and older individuals living in carefully controlled lighting conditions has now revealed that the intrinsic period of the human circadian pacemaker averages 24.18 hours in both age groups, with a tight distribution consistent with other species. These findings have important implications for understanding the pathophysiology of disrupted sleep in older people.
The study was designed to determine if performance and mood impairments occur in bed-rested subjects, and if different exercise-training regimens modify or prevent them. Eighteen normal, healthy men were divided on the basis of age, peak oxygen uptake, and maximal isometric knee extension strength into three similar groups: no exercise (NOE), isotonic exercise (ITE), and isokinetic exercise (IKE). A 15-min battery of 10 performance tests and 8 mood and 2 sleep scales were administered daily during ambulatory control, 30 d of absolute bed rest (BR), and 4 d of ambulatory recovery. Performance test proficiency increased (p < 0.05) for all three groups during BR in 7 of 10 tests and there were no consistent significant differences between the three groups. However, during BR, the ITE group was distinguished from the other groups by a decline (p < 0.05) in the activation mood dimension and in two of its constituent scales (motivation and concentration), and by improvement (p < 0.05) in the trouble-falling-asleep and psychological-tension scales. Since few deleterious changes in performance and mood occurred in the three groups and did not exceed baseline ambulatory levels, we conclude that mood and performance did not deteriorate in response to prolonged BR and were not altered by exercise training. However, the decline in activation mood scales in the ITE group may reflect overtraining or excess total workload in this group.
The Psychomotor Vigilance Task (PVT) is considered the gold standard fatigue detection device and is used frequently in fatigue research. The purpose of this study was to compare a psychomotor vigilance task developed for use on touchscreen devices with the original PVT-192 in conditions of acute sleep loss and circadian desynchronization. Participants arrived in the lab approximately two hours after their habitual time and were asked to stay awake for up to 24 hrs and take 5-minute reaction time tests every 2 hours on two different devices: the original PVT-192 and NASA-PVT on an iPod. We found that the NASA-PVT and PVT-192 were sensitive to the 24 hrs of extended wakefulness.
There is a need for non-invasive, objective measures to forecast performance impairment arising from sleep loss and circadian misalignment, particularly in safety-sensitive occupations. Eye-tracking devices have been used in some operational scenarios, but such devices typically focus on eyelid closures and slow rolling eye movements and are susceptible to the intrusion of head movement artifacts. We hypothesized that an expanded suite of oculomotor behavior metrics, collected during a visual tracking task, would change according to circadian phase and time awake, and could be used as a marker of performance impairment.
Reporting and monitoring are important facets of a comprehensive Fatigue Risk Management System. As part of efforts to reduce fatigue risks, we partnered with an international airline to study 44 (4 Female) volunteer pilots over a 4 week period that included baseline earlymiddaylate flight days and rest days off. All study procedures were approved by an IRB and participants provided written informed consent prior to beginning the study. Reduced sleep duration was associated with both early and late duties. Performance was influenced by duty timing, time of day and time awake. TLX ratings were highest for mental and effort demands, while ATC and weather were the most identified hassle factors. Melatonin analysis revealed individual variations in circadian shift over the study period. The study results highlight the value of FRMS monitoring in airline operations. Ongoing crew education should emphasize individual variation and effective mitigation strategies. Further study could focus on workload and time of day scheduling factors.
Light is the predominant signal for the human circadian clock to synchronize to the solar 24-h day through an active process called entrainment. Modern light profiles are characterized by exposure to both natural daylight and artificial lighting. A mismatch between these self-selected light profiles and the solar day-night alternation can disrupt the circadian system, resulting in acute and chronic effects for health and safety. In this chapter, we describe (i) how entrainment works in the real world, illustrating the major role of light for this process; (ii) ways in which the circadian system can be disrupted by (external) factors such as irregular sleep, shift work, daylight saving time, and longitudinal position in a time zone; and (iii) how field studies have used light interventions to reduce direct and indirect effects of circadian disruption in ecological settings.
Abstract Background An integrated score that globally assesses perioperative pain experience and rationally weights each component has not yet been developed. Methods A development dataset specific to adult Chinese patients undergoing orthopaedic surgery was obtained from PAIN OUT (1985 qualified patients of 2244). A more recent validation dataset obeying the same conditions was obtained from the Chinese Anaesthesia Shared‐database Platform (1004 qualified patients of 1032). Outcomes were assessed using the International Pain Outcomes Questionnaire (IPO‐Q), which comprises key patient‐level outcomes of perioperative pain management, including pain experience and perceptions of care. Using principal component analysis and regression models, a composite score (CS) was inferred to integrate pain experience. The discrimination of the CS for dissatisfaction and desire for more pain treatment was compared with that of the worst pain score. Results A CS was developed from the 12 items of the IPO‐Q regarding pain experience. The weight for calculating the CS was worst pain 11, least pain 17, time spent in severe pain 11, interference with activity in bed 9, interference with breathing deeply or coughing 10, interference with sleep 9, anxiety 12, helplessness 12, nausea 0, drowsiness 2, itch 5 and dizziness 2. In external validation, the CS indicated superior discrimination to the worst pain in predicting dissatisfaction ( p < 0.001) and desire for more pain treatment ( p < 0.001). Conclusions This study introduced a methodology to integrate outcomes regarding perioperative pain experience into a CS, which was based on the weight of each item. Significance This novel methodology sheds additional light on the riveting issue of carefully integrating several measures into a composite endpoint, which may be useful for quality improvement purposes when addressing the impact of a change in clinical practice.
Suicide is a leading cause of death worldwide, and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium. The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via mtCOJO, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders and other known risk factors. Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.
Protozoan parasites represent a severe threat to global human health as they are responsible for infection in Malaria, and a range of Neglected Tropical Diseases (NTDs) including Chagas disease, leishmaniasis and African sleeping sickness. Often treatments for protozan parasites are limited in their efficacy and drug resistance is an emerging problem. The current efforts to develop new treatments for the aforementioned diseases have been met with limited success and as such novel compound classes for development are being actively sought. Peptoids are peptidomimetics that have showed promise as antimicrobial agents but their application in the field of vector-borne parasitic diseases is highly underdeveloped. Herein, a library of over 50 peptoids containing a wide variety of chemical functionalities has been prepared and biologically evaluated against a range of protozoan parasitic targets. Selected members of the peptoid library were found to have potent anti-parasitic activity and good selectivity indices (SI). For example, peptoid 29 [NamyNspeNspe)(NhArgNspeNspe)]2 had an IC50 of 0.05 μM against Plasmodium falciparum and a SI > 100.
The energy-saving potential of occupancy-centric smart thermostats has been extensively explored in simulations but lacked field testing for energy savings quantification and sensor performance assessment in real buildings. This paper presents a long-term field study conducted in a single-family home in Texas, U.S. to evaluate the performance of occupancy-centric controls (OCC) of HVAC (heating, ventilation, and air-conditioning) system in terms of energy savings, sensor accuracy, and impact on electric peak demand. The test site was equipped with a commercial off-the-shelf (COTS) smart thermostat and multiple occupancy presence sensors for OCC implementation. Additionally, a sub-metering system was installed to monitor electricity consumption of various end-use equipment, including the HVAC system. A supplementary device was installed to track the ground-truth occupancy for the accuracy evaluation of the occupancy presence sensor. Scenarios of baseline and OCC controls were alternated weekly over the 20-month testing period. The results indicated an effective OCC execution, as evidenced by indoor temperature profiles. During the 2023 cooling season, OCC achieved total energy savings of 1,958 kWh, corresponding to a 17.6% energy savings ratio. Under certain conditions, daily HVAC energy savings reached as high as 17 kWh, with a savings ratio of 35%. Sensor performance showed an overall accuracy of 83.8%, a False Positive Rate (FPR) of 12.8%, and a False Negative Rate (FNR) of 47.4%. A key limitation was the sensor’s inability to detect stationary occupants during sleep, leading to a midnight FNR of nearly 100% and significantly compromising thermal comfort. Additionally, the implementation of OCC resulted in extended periods of high electricity demand on summer afternoons, affecting occupant’s thermal comfort and posing potential challenges to community-level grid operations if OCC were widely adopted. Furthermore, this study addresses a critical research gap by empirically investigating energy-saving potential and occupancy sensor performance in residential buildings. Through a comprehensive field-testing study, the research examines the interrelationship between sensor accuracy, energy savings, and thermal comfort, an area that has received limited attention in the current literature.
When learning, the brain modifies individual synaptic connections to reach a desired behavior. Animal and human brains have been shown to be incredibly capable of learning complex and varied functions across a wide variety of tasks. In recent years, artificial neural networks, inspired by human and animal brains, have shown great capabilities in learning a wide variety of difficult tasks. However, artificial neural networks primarily teach themselves through the use of backpropagation, a learning method which has no clear analogue within the brain. Additionally, Artificial Neural Networks primarily use continuous activation functions, which differ significantly from the spiking neuronal behavior present in the brain. In this paper, we discuss and demonstrate a biologically plausible learning method that approximates backpropagation through two techniques on Spiking Neural Networks. First, we show that the local temporal derivatives that are necessary for backpropagation can be approximately recovered through reconstruction using spike timings. Second, we show that through learning during a sleep phase, inspired by neuroscience research into memory replay, the localized parallel feedback path can learn to approximate the derivative through the forward path weight matrix, thus solving the weight transport problem. Lastly, we demonstrate that the combination of these two methods can approach or exceed the accuracy of backpropagation-based methods for a variety of neuromorphic vision tasks while maintaining biological plausibility.
Multivariate autoregressive (MVAR) model estimation enables assessment of causal interactions in brain networks. However, accurately estimating MVAR models for high-dimensional electrophysiological recordings is challenging due to the extensive data requirements. Hence, the applicability of MVAR models for study of brain behavior over hundreds of recording sites has been very limited. Prior work has focused on different strategies for selecting a subset of important MVAR coefficients in the model to reduce the data requirements of conventional least-squares estimation algorithms. Here we propose incorporating prior information, such as resting state functional connectivity derived from functional magnetic resonance imaging, into MVAR model estimation using a weighted group least absolute shrinkage and selection operator (LASSO) regularization strategy. The proposed approach is shown to reduce data requirements by a factor of two relative to the recently proposed group LASSO method of Endemann et al (Neuroimage 254:119057, 2022) while resulting in models that are both more parsimonious and more accurate. The effectiveness of the method is demonstrated using simulation studies of physiologically realistic MVAR models derived from intracranial electroencephalography (iEEG) data. The robustness of the approach to deviations between the conditions under which the prior information and iEEG data is obtained is illustrated using models from data collected in different sleep stages. This approach allows accurate effective connectivity analyses over short time scales, facilitating investigations of causal interactions in the brain underlying perception and cognition during rapid transitions in behavioral state.
Sleeping sickness is a fatal disease caused by the protozoan parasite Trypanosoma brucei (Tb). Inosine-5’-monophosphate dehydrogenase (IMPDH) has been proposed as a potential drug target, since it maintains the balance between guanylate deoxynucleotide and ribonucleotide levels that is pivotal for the parasite. Here we report the structure of TbIMPDH at room temperature utilizing free-electron laser radiation on crystals grown in living insect cells. The 2.80 Å resolution structure reveals the presence of ATP and GMP at the canonical sites of the Bateman domains, the latter in a so far unknown coordination mode. Consistent with previously reported IMPDH complexes harboring guanosine nucleotides at the second canonical site, TbIMPDH forms a compact oligomer structure, supporting a nucleotide-controlled conformational switch that allosterically modulates the catalytic activity. The oligomeric TbIMPDH structure we present here reveals the potential of in cellulo crystallization to identify genuine allosteric co-factors from a natural reservoir of specific compounds.