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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Enhancement of Cognitive Processing by Multiple Sclerosis Patients Using Liquid Cooling Technology: A Case Study

Cognitive dysfunction is a common symptom in patients with multiple sclerosis (MS). This can have a significant impact on the quality of life of both the patient and of their primary care giver. This case study explores the possibility that liquid cooling therapy may be used to enhance the cognitive processing of MS patients in the same way that it provides temporary relief of some physical impairment. Two MS patients were presented a series of pattern discrimination tasks before and after being cooled with a liquid cooling garment for a one hour period. The subject whose ear temperature was reduced during cooling showed greater electroencephalographic (EEG) activity and scored much better on the task after cooling. The patient whose ear temperature was unaffected by cooling showed less EEG activity and degraded performance after the one hour cooling period.

Montgomery, Leslie D.↗
NASA NTRS2002

Letting Thoughts Take Wing

Scientists are conducting research into electroencephalograms (EEGs) of brainwave activity, and electromyography (EMG) of muscle activity, in order to develop systems which can control an aircraft with only a pilot's thoughts. This article describes some EEG and EMG signals, and how they might be analyzed and interpreted to operate an aircraft. The development of a system to detect and interpret fine muscle movements is also profiled in the article.

Jorgensen, Chuck↗
NASA NTRS2004

A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.

Bailey, Nathan R.↗
NASA NTRS2004

Kernel PLS Estimation of Single-trial Event-related Potentials

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Rosipal, Roman↗
NASA NTRS2003

Multimodal neuroelectric interface development

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

Evaluation Studies↗
NASA NTRS1997

Serotonergic modulation of hippocampal pyramidal cells in euthermic, cold-acclimated, and hibernating hamsters

Serotonergic fibers project to the hippocampus, a brain area previously shown to have distinctive changes in electroencephalograph (EEG) activity during entrance into and arousal from hibernation. The EEG activity is generated by pyramidal cells in both hibernating and nonhibernating species. Using the brain slice preparation, we characterized serotonergic responses of these CA1 pyramidal cells in euthermic, cold-acclimated, and hibernating Syrian hamsters. Stimulation of Shaffer-collateral/commissural fibers evoked fast synaptic excitation of CA1 pyramidal cells, a response monitored by recording population spikes (the synchronous generation of action potentials). Neuromodulation by serotonin (5-HT) decreased population spike amplitude by 54% in cold-acclimated animals, 80% in hibernating hamsters, and 63% in euthermic animals. The depression was significantly greater in slices from hibernators than from cold-acclimated animals. In slices from euthermic animals, changes in extracellular K+ concentration between 2.5 and 5.0 mM did not significantly alter serotonergic responses. The 5-HT1A agonist 8-hydroxy-2(di-n-propylamino)tetralin mimicked serotonergic inhibition in euthermic hamsters. Results show that 5-HT is a robust neuromodulator not only in euthermic animals but also in cold-acclimated and hibernating hamsters.

NASA Discipline Regulatory Physiology↗
NASA NTRS1996

Contribution of oxygen-sensitive neurons of the rostral ventrolateral medulla to hypoxic cerebral vasodilatation in the rat

1. We sought to determine whether hypoxic stimulation of neurons of the rostral ventrolateral reticular nucleus (RVL) would elevate regional cerebral blood flow (rCBF) in anaesthetized paralysed rats. 2. Microinjection of sodium cyanide (NaCN; 150-450 pmol) into the RVL rapidly (within 1-2 s), transiently, dose-dependently and site-specifically elevated rCBF1 measured by laser Doppler flowmetry, by 61.3 +/- 22.1% (P < 0.01), increased arterial pressure (AP; +30 +/- 8 mmHg; P < 0.01)1 and triggered a synchronized 6 Hz rhythm of EEG activity. 3. Following cervical spinal cord transection, NaCN and also dinitrophenol (DNP) significantly (P < 0.05) elevated rCBF and synchronized the EEG but did not elevate AP; the response to NaCN was attenuated by hyperoxia and deepening of anaesthesia. 4. Electrical stimulation of NaCN-sensitive sites in the RVL in spinalized rats increased rCBF measured autoradiographically with 14C iodoantipyrine (Kety method) in the mid-line thalamus (by 182.3 +/- 17.2%; P < 0.05) and cerebral cortex (by 172.6 +/- 15.6%; P < 0.05) regions, respectively, directly or indirectly innervated by RVL neurons, and in the remainder of the brain. In contrast regional cerebral glucose utilization (rCGU), measured autoradiographically with 14C-2-deoxyglucose (Sokoloff method), was increased in proportion to rCBF in the mid-line thalamus (165.6 +/- 17.8%, P < 0.05) but was unchanged in the cortex. 5. Bilateral electrolytic lesions of NaCN sensitive sites of RVL, while not altering resting rCBF or the elevation elicited by hypercarbia (arterial CO2 pressure, Pa,CO2, approximately 69 mmHg), reduced the vasodilatation elicited by normocapnic hypoxaemia (arterial O2 pressure, Pa,O2, approximately 27 mmHg) by 67% (P < 0.01) and flattened the slope of the Pa,O2-rCBF response curve. 6. We conclude that the elevation of rCBF produced in the cerebral cortex by hypoxaemia is in large measure neurogenic, mediated trans-synaptically over intrinsic neuronal pathways, and initiated by excitation of oxygen sensitive neurons in the RVL.

Non-NASA Center↗
NASA NTRS1995

Biocybernetic system evaluates indices of operator engagement in automated task

A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.

Cerebral Cortex/physiology↗
NASA NTRS2003

Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component

The present study examined the effects of an electroencephalographic- (EEG-) based system for adaptive automation on tracking performance and workload. In addition, event-related potentials (ERPs) to a secondary task were derived to determine whether they would provide an additional degree of workload specificity. Participants were run in an adaptive automation condition, in which the system switched between manual and automatic task modes based on the value of each individual's own EEG engagement index; a yoked control condition; or another control group, in which task mode switches followed a random pattern. Adaptive automation improved performance and resulted in lower levels of workload. Further, the P300 component of the ERP paralleled the sensitivity to task demands of the performance and subjective measures across conditions. These results indicate that it is possible to improve performance with a psychophysiological adaptive automation system and that ERPs may provide an alternative means for distinguishing among levels of cognitive task demand in such systems. Actual or potential applications of this research include improved methods for assessing operator workload and performance.

Task Performance and Analysis↗
NASA NTRS2016

Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation

Attention-related human performance limiting states (AHPLS) can cause pilots to lose airplane state awareness (ASA), and their detection is important to improving commercial aviation safety. The Commercial Aviation Safety Team found that the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness, and that distraction of various forms was involved in all of them. Research on AHPLS, including channelized attention, diverted attention, startle / surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors has been implemented to simultaneously measure their physiological markers during high fidelity flight simulation human subject studies. Pilot participants were asked to perform benchmark tasks and experimental flight scenarios designed to induce AHPLS. Pattern classification was employed to distinguish the AHPLS induced by the benchmark tasks. Unimodal classification using pre-processed electroencephalography (EEG) signals as input features to extreme gradient boosting, random forest and deep neural network multiclass classifiers was implemented. Multi-modal classification using galvanic skin response (GSR) in addition to the same EEG signals and using the same types of classifiers produced increased accuracy with respect to the unimodal case (90 percent vs. 86 percent), although only via the deep neural network classifier. These initial results are a first step toward the goal of demonstrating simultaneous real time classification of multiple states using multiple sensing modalities in high-fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Harrivel, Angela R.↗
NASA NTRSDate not supplied

Perturbations in Brain Functional Connectivity Patterns After Waking From Slow Wave Sleep Under Different Cognitive States

Sleep inertia refers to the state of transition between sleep and wake characterized by impaired alertness, confusion, and reduced cognitive and behavioral performance. While the behavioral symptoms of sleep inertia are well described, the neurological changes that lead to this state remain elusive. Here, to understand the state of sleep inertia and the reorganization that the brain undergoes, we took a graph theoretical approach and compared the EEG derived brain connectivity patterns before sleep and after waking up while participants (n = 10) performed multiple tasks that differed in cognitive complexities. We focused on how the degree and the clustering coefficient of brain regions (EEG sensors) change immediately after participants wake up from slow wave sleep. During a psychomotor vigilance task (PVT), designed to assess vigilant attention, we find that the brain regions with strong network connectivity (degree) before sleep show a reduction in connectivity after waking. In contrast, those with low connectivity before sleep have greater connectivity after waking. The regions that undergo these changes are specific to each participant and these findings are unique to the beta frequency range, which plays a key role in sensorimotor functioning and preserving the current state of the brain. Moreover, in tasks that required inhibitory control and arithmetic reasoning, we found that only regions with weak connectivity before sleep exhibited more connections after waking, but regions with high connectivity prior to sleeping remained unchanged, highlighting task specific effects. Furthermore, we find that during the PVT, the clustering coefficient within low frequency oscillations of the brain is reduced upon waking while it remains unchanged during other tasks. These results suggest that the connections between regions that are lost after abrupt awakening can be reallocated to other regions in order to renormalize the brain. However, this response may only be evident during specific cognitive states and may be more nuanced during complex task performance.

sleep inertia↗