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Human Behavior and Performance Support for ISS Operations and Astronaut Selections: NASA Operational Psychology for Six-Crew Operations

The Behavioral Health and Performance group at NASA Johnson Space Center provides psychological support services and behavioral health monitoring for ISS astronauts and their families. The ISS began as an austere outpost with minimal comforts of home and minimal communication capabilities with family, friends, and colleagues outside of the Mission Control Center. Since 1998, the work of international partners involved in the Space Flight Human Behavior and Performance Working Group has prepared high-level requirements for behavioral monitoring and support. The "buffet" of services from which crewmembers can choose has increased substantially. Through the process of development, implementation, reviewing effectiveness and modifying as needed, the NASA and Wyle team have proven successful in managing the psychological health and well being of the crews and families with which they work. Increasing the crew size from three to six brought additional challenges. For the first time, all partners had to collaborate at the planning and implementation level, and the U.S. served as mentor to extrapolate their experiences to the others. Parity in available resources, upmass, and stowage had to be worked out. Steady progress was made in improving off-hours living and making provisions for new technologies within a system that has difficulty moving quickly on certifications. In some respect, the BHP support team fell victim to its previous successes. With increasing numbers of crewmembers in training, requests to engage our services spiraled upward. With finite people and funds, a cap had to placed on many services to ensure that parity could be maintained. The evolution of NASA BHP services as the ISS progressed from three- to six-crew composition will be reviewed, and future challenges that may be encountered as the ISS matures in its assembly-complete state will be discussed.

VanderArk, Steve

Implications of Weak-Link Behavior on the Performance of Mo/Au Bilayer Transition-Edge Sensors

Understanding the physical properties of the superconducting-to-normal transition is fundamental for optimizing the design and performance of transition-edge sensors (TESs). Recent critical current measurements of Mol Au bilayer test structures show that they act as weak superconducting links, exhibiting oscillatory, Fraunhofer-like behavior with applied magnetic field. In this paper we investigate the implications of this behavior for TES X-ray detectors, under operational bias conditions. These devices include normal metal features used for absorber attachment and unexplained noise suppression, which result in modifications to the previously reported critical current behavior. We present measurements of the logarithmic resistance sensitivity with temperature, a, and current, b, as a function of applied magnetic field and bias point within the resistive transition. Results show that these important device parameters exhibit similar oscillatory behavior with applied magnetic field, which in turn affects the signal responsivity and noise, and hence the energy resolution. These results show the significance of the critical current in determining the performance of TESs and hold promise to improve future.

Smith, Stephen J.

Cognitive Behavioral Training and Education for Spaceflight Operations

Cognitive behavioral-training (CBT) is an evidence-based practice commonly used to help treat insomnia, and is part of NASA's countermeasure regimen for Fatigue Management. CBT addresses the life style and habits of individuals that are maladaptive to managing stress and fatigue. This includes addressing learned behavioral responses that may cause stress and lead to an increased sense of fatigue. While the initial cause of onset of fatigue in the individual may be no longer present, the perception and engrained anticipation of fatigue persist and cause an exaggerated state of tension. CBT combined with relaxation training allows the individual to unlearn the maladaptive beliefs and behaviors and replace them with routines and techniques that allow cognitive restructuring and resultant relief from stress. CBT allows for elimination in individuals of unwanted ruminating thoughts and anticipatory anxiety by, for example, training the individuals to practice stressful situations in a relaxed state. As a result of CBT, relaxation can be accomplished in many ways, such as progressive muscle relaxation, meditation and guided imagery. CBT is not therapy, but rather the synthesis of behavioral countermeasures. CBT utilizes progressive relaxation as a means of reinforcing educational and cognitive countermeasures. These countermeasures include: masking, elimination of distracting thoughts, anxiety control, split attention, cognitive restructuring and other advanced psychological techniques.

Moonmaw, Ronald

Behavioral Mapless Navigation Using Rings

This paper presents work on the development and implementation of a novel approach to robotic navigation. In this system, map-building and localization for obstacle avoidance are discarded in favor of moment-by-moment behavioral processing of the sonar sensor data. To accomplish this, we developed a network of behaviors that communicate through the passing of rings, data structures that are similar in form to the sonar data itself and express the decisions of each behavior. Through the use of these rings, behaviors can moderate each other, conflicting impulses can be mediated, and designers can easily connect modules to create complex emergent navigational techniques. We discuss the development of a number of these modules and their successful use as a navigation system in the Trinity omnidirectional robot.

Monroe, Randall P.

Damage Tolerance Behavior of Friction Stir Welds in Aluminum Alloys

Friction stir welding is a solid state welding process used in the fabrication of various aerospace structures. Self-reacting and conventional friction stir welding are variations of the friction stir weld process employed in the fabrication of cryogenic propellant tanks which are classified as pressurized structure in many spaceflight vehicle architectures. In order to address damage tolerance behavior associated with friction stir welds in these safety critical structures, nondestructive inspection and proof testing may be required to screen hardware for mission critical defects. The efficacy of the nondestructive evaluation or the proof test is based on an assessment of the critical flaw size. Test data describing fracture behavior, residual strength capability, and cyclic mission life capability of friction stir welds at ambient and cryogenic temperatures have been generated and will be presented in this paper. Fracture behavior will include fracture toughness and tearing (R-curve) response of the friction stir welds. Residual strength behavior will include an evaluation of the effects of lack of penetration on conventional friction stir welds, the effects of internal defects (wormholes) on self-reacting friction stir welds, and an evaluation of the effects of fatigue cycled surface cracks on both conventional and selfreacting welds. Cyclic mission life capability will demonstrate the effects of surface crack defects on service load cycle capability. The fracture data will be used to evaluate nondestructive inspection and proof test requirements for the welds.

McGill, Preston

Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.

Zaal, Peter M. T.

Crack Growth Behavior in the Threshold Region for High Cycle Fatigue Loading

The research results described in this paper presents a new understanding of the behavior of fatigue crack growth in the threshold region. It is believed by some crack growth experts that the ASTM load shedding test method does not produce true or valid threshold properties. The concern involves the observed fanning of threshold region da/dN data plots for some materials in which the low R-ratio data fans out or away from the high R-ratio data. This data fanning or elevation of threshold values is obviously caused by an increase in crack closure in the low R-ratio tested specimens. This increase in crack closure is assumed by some investigators to be caused by a plastic wake on the crack surfaces that was created during the load shedding test phase. This study shows that the increase in crack closure is the result of an extensive occurrence of crack bifurcation behavior in some materials, particularly in aluminum alloys, when the crack tip cyclic yield zone size becomes less than the grain size of the alloy. This behavior is related to the high stacking fault energy (SFE) property of aluminum alloys which results in easier slip characteristics. Therefore, the particular fanning behavior in aluminum alloys is a function of intrinsic dislocation property of the materials and that the fanned data represents valid material properties. However, for corrosion sensitive steel alloys used in this study the fanning was caused by a build-up of iron oxide at the crack tip from fretting corrosion.

Forman, Royce G.

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Game Theory

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.

Individualized Behavioral Health Monitoring Tool

Behavioral health risks during long-duration space exploration missions are among the most difficult to predict, detect, and mitigate. Given the anticipated extended duration of future missions and their isolated, extreme, and confined environments, there is the possibility that behavior conditions and mental disorders will develop among astronaut crew. Pulsar Informatics, Inc., has developed a health monitoring tool that provides a means to detect and address behavioral disorders and mental conditions at an early stage. The tool integrates all available behavioral measures collected during a mission to identify possible health indicator warning signs within the context of quantitatively tracked mission stressors. It is unobtrusive and requires minimal crew time and effort to train and utilize. The monitoring tool can be deployed in space analog environments for validation testing and ultimate deployment in long-duration space exploration missions.

Mollicone, Daniel

Analyzing the Operational Behavior of the Alignment and Phasing System of the Thirty Meter Telescope using SysML

The Alignment and Phasing System (APS) of the Thirty Meter Telescope (TMT) is responsible for positioning individual segments of the primary mirror, as well as the secondary and tertiary mirrors. Given its essential role, understanding the as-speci ed behavior and verifying related requirements is vital to the correct operation of the TMT. Analyzing the behavior of APS is challenging due to the variety of interactions with other subsystems. This paper presents results from developing an integrated system model that captures the structure, behavior, and requirements in a formal modeling language to enable automated veri cation using appropriate solvers. Speci cally, demonstrated and discussed are the results of applying a Systems Modeling Language (SysMLTM) based approach in which operational modes, behavior speci cations and use case scenarios are used for the purpose of verifying requirements on timing, power, and pointing error through system-level simulation using a single, integrated model.

Troy, Mitchell

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS: Teams Risk

BACKGROUNDThe Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogsof the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.METHODSWe followed best practices for data harmonization. Characteristics of each research setting were assessed for harmonization potential, and we deemed NEK-SIRIUS 17 as inappropriate due to study aims, length, and data quality. Common variables of interest were identified. Study characteristics and key variables with which datafiles could be merged were defined as “meta-data.” HFBP-EM data from all settings were processed under a common format. We then created a harmonized team-level database designed to facilitate analyses that address HRP research gaps related to HRP’s Team risk. In this database, team cohesion, processes, performance, psychological safety, and group living were operationalized as the team mean of the crew responses for each data collection (e.g., on mission day 7). Data collected on the International Space Station (ISS) included a subset of scale items administered to participants. Data collected from ISS team members within +/- 7 days of the first data collection and every following 30 +/-4 days were aggregated to the team level. We generated figures that display the mean and variability of team constructs across research settings. We also generated plots of changes in team constructs with mission day and with percentage of the mission completed. Where possible, we compared data from spaceflight analogs with data from astronauts aboard the ISS. RESULTS AND DISCUSSIONThe team-level harmonized database was structured such that each row represents data for a team on a specific mission day. Team constructs (e.g., team cohesion) were included as columns (i.e., wide format) with repeated measures across mission days given in rows (i.e., long format). The database included data from 18 crews: five, 4-person American crews in HERA C4, four 4-person American crews in HERA C5, one 6-person multinational crew in NEK-SIRIUS 19, and eight, 2–11-person multinational crews aboard the ISS. Results provide insights into mission and campaign differences in team functioning and performance. For example, between campaign differences were observed for team processes—the interdependent team actions that orchestrate taskwork in pursuit of the team’s goals [1]. Greater between-team variability on team processes was detected during HERA C4 than during C5, and a downward trend was observed over the duration of C4, but not C5 or SIRIUS 19. This may be due to the campaign-level differences such as the sleep deprivation implemented during C4. Responses on the subset of team process items administered on the ISS indicate between-crew variability more like those observed in C4 than C5 and NEK, with some, but not all ISS crews demonstrating a downward trend over time. Additional findings will be presented. REFERENCESMarks, M. A., et al (2001) Academy of Management Review, 26(3), 356-376.

S T Bell

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS Teams Risk

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogs of the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.

S T Bell

Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks

Unreinforced woven fabrics are widely employed in various high-performance applications, including parachute deployment systems, airbags, and ballistic armor. The analysis of such materials is inherently complex due to the multiscale structure of these materials, and the dependence of macroscale behavior on changes that occur at lower scales. Previously, NASA’s Multiscale Analysis Tool (NASMAT) showed its capability in predicting unreinforced fabric behavior at the macroscale by capturing finite rotations that occur at the mesoscale. Though effective, the tool can face high computational cost for large, complex problems, motivating the need for the development of a surrogate model that can capture the same behavior. A recurrent neural network (RNN) was developed and trained on virtual NASMAT data to mimic the physics-based solutions while improving the computational runtime. The architecture of the RNN to best simulate the fabric behavior was carefully crafted based on heuristic knowledge of predicting physics-based temporal data, manual hyperparameter case studies, and Hyperband optimization.. The resultant model was able to predict a variety of stress-strain curves for fabrics with different mesoscale geometries, and was further validated by comparing to experimental data for the K706 style Kevlar plain-weave fabric, demonstrating the ability of the model to effectively capture the geometric changes in the fabric without explicitly calculating them, as is done in NASMAT. Furthermore, the tool showed its ability to improve on the runtime by a factor of 10 for fabric solutions compared to the multiscale tool, which would further enable the simulation of complex loading scenarios on unreinforced fabrics.

Fabric

An Investigation Into Some Important Aspects of Droplet Breakup/Vaporization Behavior Caused By a Gas Flow (Both Nonreacting & Detonative Combustion) in a Shock Tube

As a part of the rotating detonation engine (RDE) technology enablement project at NASA Glenn Research Center (GRC), an effort was undertaken to extend our current computational capabilities of OpenNCC in some important ways with the implementation of a modeling approach to account for the droplet breakup caused by a shock-induced gas motion, & a vaporization model valid over a wide range of pressure conditions encountered in multiphase detonation. With the modified code, a study was undertaken to investigate the individual droplet behavior followed by the passage of a shock front. The study is carried out by tracking a sparse group of droplets to gain some understanding of shock induced droplet behavior under various shock strengths & fuel injector conditions. The study also looks into the effect of randomization involved in determining the droplet breakup outcomes. Over a wide range of sub-critical conditions examined, larger droplets are observed to undergo significant changes in droplet behavior following their breakup. However, smaller droplets (10 µm or less ) remain unaffected by any shock induced breakup. In a follow-on work, we investigated the impact of shock and droplet interaction in a detonation study involving both gaseous as well as gas/liquid (droplet clouds) fuel/air stoichiometric mixtures in a simple 3D shock-tube configuration. The droplet clouds are made up of different initial droplet sizes of either 6, 10, or 30 µm. We also investigated the individual droplet behavior followed by the passage of a detonation front. The results represent conditions that lead to both overdriven and C-J (ChapmanJouguet) detonations. Under both test conditions, most of the droplet vaporization is completed within a short distance (duration) behind the detonation front & well within the region of complete combustion observed in a corresponding equivalent gas-phase fuel/air mixture. The impact of the shock-induced droplet breakup is found to be significant in the calculations involving the 30-µm droplets. Subsequent to the breakup, the drop sizes vary from 1 to 10 µm. Another factor that contributed to the observed rapid vaporization is the result of vaporization taking place under supercritical conditions. The overall detonation properties of various droplet clouds (made up of different initial sizes) are similar to those observed in a corresponding gaseous fuel/air mixture. In the calculation involving a gaseous fuel, the calculated C-J detonation velocity is 1822 m/s involving Jet-A/air and φ = 1. In the overdriven detonation, it is 2044 m/s. In the calculations involving droplet clouds, the corresponding detonation velocities are lower. The impact of increased droplet size is primarily seen in a higher reduction in the detonation velocity.

shock/droplet interaction

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, and Psychosocial Adaptions within a Team

The Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team (the Team Risk) is primarily performance-focused, with a secondary emphasis on behavioral health outcomes resulting from team performance and interpersonal interactions. Monitoring tools, measures, and countermeasures are aimed at enhancing team processes and team composition configurations to optimize team performance and functioning. Long-duration exploration missions (LDEMs) will include major challenges that could affect team performance, including social isolation, physical confinement, a small and diverse crew, communication delays between crew and ground, limited or no crew rotation or evacuation options, limited or no resupply, and a high-consequence environment. Each of these conditions will affect the crew’s coordination, cooperation, psychological well-being, and performance. Although the International Space Station (ISS) remains important for studies that require spaceflight testing and validation, the current conditions on the ISS do not adequately mimic the exploration environment that is required for National Aeronautics and Space Administration (NASA) teams research, and thus access to terrestrial or ground-based analogs of LDEM conditions is paramount. The emphasis on analogs for research is reflected in this updated evidence review of the Team Risk, and includes data from studies conducted at isolated, confined, extreme (ICE) environments (e.g., Antarctic stations), and from several mission simulation analogs such as the Human Exploration Research Analog (HERA) (HERA Experiment Information Package, 2014), also known as isolated, confined, controlled (ICC) environments. These studies have characterized many team factors regarding LDEMs, and the Team Risk has now matured from risk characterization to focusing more on countermeasure development. Because spaceflight evidence for team-level research is lacking, no reliable data is available to quantify the impact of team-level variables on individual and team-level outcomes during spaceflight missions. Until recently, no systematic attempt had been undertaken to measure the performance effects of team cohesion, team composition, team training, or team-related psychosocial adaptation during spaceflight. The Team Risk is a relatively young research area for NASA, with substantial growth only since the 2000s, and with limited access to spaceflight performance data. As a result, spaceflight evidence is lacking to identify specifically what team composition, level of training, amount of cohesion, or quality of psychosocial adaptation is necessary to reduce the risk of performance errors in space. However, astronaut journals and interviews and reports from spaceflight subject matter experts (SMEs) provide testimonies that team performance during spaceflight is important for mission success and to maintain crew health. Team spaceflight data is now being collected as part of the Spaceflight Standard Measures task (Clement, 2021)—a set of core measurements related to many human spaceflight risks that are collected from astronauts before, during, and after long-duration missions. The team-related standard measures focus on team cohesion, team performance, group living, team climate, and team processes. Collection of standard measures data is ongoing and published data is not yet available. Finally, although spaceflight evidence is lacking, evidence gleaned from ground studies and spaceflight analog studies will help close the gaps outlined in the Team Risk. Ground-based studies provide quantitative evidence for team functioning in ICE environments. Academic research on teams has produced dozens of meta-analyses that can be used to understand the general relationships among team inputs (e.g., team member characteristics and skills, job context), team processes, and emergent states (e.g., coordination, communication, cooperation, cohesion, trust, shared cognition), and team outcomes (e.g., effectiveness, errors, adaptation). Teams are complex, incorporating individual characteristics of team members, but also existing at a level that is greater than the sum of its parts. Therefore, the Team Risk must be integrated with other individual-focused NASA Human Research Program (HRP) risks, including Behavioral Medicine (BMed), Sleep, and Human-Systems Integration Architecture (HSIA), and emerging research indicates more integration may needed between the Team Risk and the physiologically oriented risks. Much of this integration occurs through the Human Systems Risk Board (HSRB). A lack of team functioning may be a stressor in some circumstances, but the team often acts as a countermeasure. For example, support for team leaders and teammates can facilitate individual functioning and encourage psychological and physically healthy behaviors and attitudes. However, more research is needed regarding teams during LDEMs and the remaining gaps in the research are described in the current report.

Lauren Blackwell Landon

Changes in Cognitive Performance and Behavior Induced by Space-like Environment

Exposure to space radiation is a principal consideration of spaceflight missions as risk is leveraged as time and dose—both expected to increase with future missions to the Moon, Mars, and beyond. Previous mission exposure levels, galactic cosmic radiation (GCR) and solar particle events (SPE), have been characterized as increased compared to those natural to Earth and are predicted to cause robust deficits at higher doses and longer durations. The cognitive health implications of this critical difference are understood as risks to mission and crew operations. We examined potential radiation-induced disruptions on brain health through resting-state in-cage behavior. 23–24-week-old male and female mice were exposed to 0 cGy (Sham), 5 cGy, 15 cGy, and 50 cGy via Five-Ion GCR Simulation (H, Si, He, O, Fe) at the NASA Space Radiation Lab in Brookhaven National Labs. Behavioral and cognitive performance were evaluated via frequency/duration of digging, rearing, and grooming within the 72-hour (acute) and 91-day (delayed) period following irradiation. Additionally, during this time we evaluated nestlet building using a 5-stage Deacon score, rating shredding and shelter assembly of cotton material from untouched (1) to shredded and formed into a crater shape (5). We have observed differences in behavior frequency and duration differences among the 15 cGy subset within the acute observation window. There were no significant differences in behavior frequencies nor duration during the delayed observation period. These experimental design aspects that allot for gender-inclusivity is supportive of the diversification of future space travel mission plans. Investigating gender differences is an element under our main objective of determining radiation dose-response curves. In brief, these studies identified a space-relevant radiation dose of 15 cGy that that can be utilized for future standardized ground studies on the nervous system.

O. Siu

Effects of a 33-Ion Sequential Beam Galactic Cosmic Ray Analog on Male Mouse Behavior and Evaluation of CDDO-EA as a Radiation Countermeasure

In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a ‘vehicle’ formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/ during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures.

Space radiation