Frontiers in Human Neuroscience
Technical University of Berlin, Germany
University of Pennsylvania, United States
University of the Fraser Valley, Canada
The editor and reviewers’ affiliations are the latest provided on their Loop research profiles and may not reflect their situation at the time of review.
Expedition Cognition: A Review and Prospective of Subterranean Neuroscience With Spaceflight Applications
- 1 Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- 2 Department of Medicine, University of Udine, Udine, Italy
- 3 Department of Psychology, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- 4 Institute of Mountain Emergency Medicine, Eurac Research – Institute of Mountain Emergency Medicine, Bolzano, Italy
- 5 Directorate of Human and Robotics, Exploration, European Space Agency, Köln, Germany
- 6 Department of Psychology, Concordia University, Montreal, QC, Canada
Renewed interest in human space exploration has highlighted the gaps in knowledge needed for successful long-duration missions outside low-Earth orbit. Although the technical challenges of such missions are being systematically overcome, many of the unknowns in predicting mission success depend on human behavior and performance, knowledge of which must be either obtained through space research or extrapolated from human experience on Earth. Particularly in human neuroscience, laboratory-based research efforts are not closely connected to real environments such as human space exploration. As caves share several of the physical and psychological challenges of spaceflight, underground expeditions have recently been developed as a spaceflight analog for astronaut training purposes, suggesting that they might also be suitable for studying aspects of behavior and cognition that cannot be fully examined under laboratory conditions. Our objective is to foster a bi-directional exchange between cognitive neuroscientists and expedition experts by (1) describing the cave environment as a worthy space analog for human research, (2) reviewing work conducted on human neuroscience and cognition within caves, (3) exploring the range of topics for which the unique environment may prove valuable as well as obstacles and limitations, (4) outlining technologies and methods appropriate for cave use, and (5) suggesting how researchers might establish contact with potential expedition collaborators. We believe that cave expeditions, as well as other sorts of expeditions, offer unique possibilities for cognitive neuroscience that will complement laboratory work and help to improve human performance and safety in operational environments, both on Earth and in space.
Human space exploration has been limited to orbital space flight since 1972 (Apollo 17), but due to renewed interest by traditional government entities and the private sector, this trend is about to change. Engineering challenges are being overcome that will allow for a return to the Moon, and extend exploration to deep-space asteroids and to Mars (Salotti and Heidmann, 2014; Thronson et al., 2016). However, the difficulties of future missions for which we are least prepared may be those in the human domain (Kanas and Manzey, 2008; De La Torre et al., 2012; Bishop, 2013; Sgobba et al., 2017a). Separation from family and friends, delays in communications with Earth, distortion of audio and visual signals, and limited privacy and personal space are important factors for crewmembers of long-term space missions (Sandal et al., 2006). Even the most highly selected and trained individual is subject to limitations of human physiology and psychology. The isolated, confined, extreme and otherwise unusual physical and social environments of long-duration missions will approach these limits, and potentially result in catastrophic failure (for an overview of incidents related to human error in manned space missions, see Sgobba et al., 2017a).
Risks to human health and performance can be mitigated through selection, training, mission and equipment design, and countermeasures (Kanas and Manzey, 2008), and can be investigated in a variety of ways (Bishop, 2013). The human nervous system itself is studied primarily under laboratory conditions, using neuroimaging methods such as structural and functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) to observe the brain and the neural correlates of behavior non-invasively, and through comparisons between healthy and impaired systems by studying patient populations. It is also common to probe circuit, cellular, and molecular-level processes using animal models. While laboratory work is essential to establish a basis for interpreting field results and is generally less costly and less constrained than is research conducted in space, it also has limitations; it rarely looks at complex environments that are representative of real operational environments, and laboratory conditions cannot adequately simulate the unique conditions of spaceflight.
To better understand physiological and cognitive adaptations of the nervous system under conditions of microgravity, a series of studies using data collected in flight or pre- and post-flight has been conducted on postural reactions, eye movements, spatial orientation illusions, and cognitive responses (reviewed in Clément and Ngo-Anh, 2013). Some of the effects of microgravity on body fluid distribution (in addition to more physiological topics of bone density and muscle loss) can be simulated using bedrest studies in which the head is inclined downwards by about six degrees (a procedure that has negative consequences for mental status, Ishizaki et al., 2002), and by observing the changes in brain anatomy from pre- to post-flight (Roberts et al., 2017).
Aside from microgravity itself, the most relevant conditions of spaceflight for many other research questions about the nervous system can be found or devised on Earth. These “space analogs” may arise incidentally from other human activities, such as during Antarctic expeditions, or may be planned to simulate complex interactions of environmental, physical, physiological, and social aspects during space missions (Pagel and Choukèr, 2016). Space analogs can therefore offer platforms partway between the laboratory environment and the operational spaceflight context for the scientific study of psychology, cognition and neuroscience (Keeton et al., 2011). Neurocognitive changes, fatigue, circadian rhythm alterations, sleep problems, changes in stress hormone levels, and immune function have all been observed in situations that mimic some aspects of prospective human space missions (Pagel and Choukèr, 2016). A particularly valuable aspect of expedition-based analogs is that participants are in real, physically demanding and potentially dangerous situations with additional effects on stress, sleep, and team interactions.
In addition to informing future space mission design, space analog environments offer possibilities for neuroscientists to investigate brain function and behavioral performance in unique situations. Extending the study of human neuroscience outside the lab could lead to insights for basic research and benefits for safety-critical occupations (i.e., medical teams, shift-workers, firefighters, or air traffic controllers). However, opportunities for mutual exchange have yet to be fully exploited, likely due to limited contact between laboratory researchers and expedition experts, and because portable equipment for measuring neurophysiological signals has only recently reached a level of maturation necessary to make high quality measurements in situ.
Our objective here is to foster an exchange between cognitive neuroscientists, and cave expedition and space analog experts, by providing an overview of how laboratory and field research in neuroscience and related areas (i.e., cognition, cognitive psychology, neuropsychology) can be bridged, using caving expeditions as an exemplar space analog and expedition environment.
Scope and Terminology
We first discuss the properties of available space analogs and their evaluation and discuss the particular characteristics of caves that make them suitable for exerting the physical and psychological challenges of spaceflight, in order to assist researchers’ selection of missions appropriate for their research questions. We review work that pertains to human neuroscience and cognition conducted to date in caves, and then explore how the few focus areas of that early work can be broadened to a range of current topics. We then outline tools and techniques that are suitable for use in cave environments. Finally, we suggest how researchers might establish contact with organizations and teams that conduct expeditions.
Neuroscience, cognitive science, neuropsychology, and psychology are broad overlapping fields that may each study the same or related processes with numerous tools. We will not attempt to distinguish between the purviews of these fields here; research questions from any domain that concern environment-brain-behavior relationships that affect human performance are our focus. These topics at times overlap with human physiology, human factors, sports psychology, and social psychology. Although it makes little sense to study human performance in isolation from other physiological processes and from a physical and social context, other resources exist that have dealt specifically with these topics. For references on medical and physiological matters (i.e., bone loss, radiation, extravehicular activities, balance, motion sickness and nutrition), and for information on physiological and neurophysiological studies conduced to date on the ISS (see Buckey, 2006; Clément and Ngo-Anh, 2013). For space flight human factors research methods, accident analysis and prevention, and human-automation interaction (see Sgobba et al., 2017b; Kanki, 2018b; Marquez et al., 2018; Wilson, 2018). Psychology, mental heath, team performance and group interactions in space are reviewed in (Suedfeld and Steel, 2000; Manzey, 2004; Kanas and Manzey, 2008; Kanas, 2015; Salas et al., 2015; Pagel and Choukèr, 2016; Sandal, 2018). For a discussion of current knowledge on neuroplastic changes in the human central nervous system associated with spaceflight (actual or simulated) as measured by magnetic resonance imaging-based techniques (see Van Ombergen et al., 2017). Cognitive functions, human error, and workload and fatigue are relevant to expedition cognition and are amenable to study in the cave environment as discussed here; useful references for further reading include (De La Torre et al., 2012; Gore, 2018; Kanki, 2018a).
Space Analogs and Assessment of Suitability
The National Aeronautics and Space Administration (NASA), European Space Agency (ESA), Roscosmos State Corporation for Space Activities, Canadian Space Agency (CSA), and other space exploration organizations have created a variety of terrestrial and aquatic space analogs, as well as simulated missions. Each analog simulates a subset of space or extra-terrestrial conditions. Those analogs which are predominantly used to test equipment, validate procedures, and gain an understanding of system-wide technical and communication challenges emphasize the equivalence of physical factors, such as terrain, reduced gravity and communications delays; those with natural sciences foci might emphasize geological and biological properties of the analog (e.g., the yearly NASA/ESA–funded Arctic Mars Analog Svalbard Expedition in Norway is used for testing astrobiological hypotheses).
Other analogs have a human focus or mixed scientific uses including human research. For the purposes of human activities, the relevant conditions for a particular topic of interest may include additional factors that affect a crew member’s ability to carry out their work efficiently and safely. An important principle for assessing the relevance of various extreme environments as viable analogs for space or providing the basis for cross-comparison is that it is the experience of the environments rather than the environments themselves that must be considered (Suedfield, 1991; Bishop, 2013). Thus, an environment may provide an excellent analog for spaceflight without physically resembling it, provided that many of the stressors exerted upon human participants are paralleled. For example, as in space, the external environment in the Antarctic winter requires specialized equipment, planning, and procedures in order to safely conduct operations outside the habitat. Morphew enumerated the stressors of (long-duration) spaceflight (see Table 1; Morphew, 2001).
Table 1. Stressors of long duration space flights (Morphew, 2001).
In Antarctica, McMurdo Antarctic Research Station (population > 1,000) is used by NASA as a Mars analog because of terrain, temperature, and taxing conditions comparable to those of Mars’ surface (Morris and Holt, 1983). Psychiatric studies at McMurdo station have provided evidence that prolonged isolation can increase the risk for mental health disorders (Kanas, 2015). ESA collaborates with the smaller Franco-Italian Antarctic base Concordia (population
15) (Tafforin, 2009), at which some human research is conducted, for example on sleep quality and adaptation to high altitude conditions (Tellez et al., 2014). Although aquatic environments are not precise models for the physical conditions of asteroid, moon, or planetary exploration, underwater missions do mimic the stressors associated with safety, communication, and technological logistics related to long-term spaceflight and exploration. The NASA Extreme Environment Mission Operations (NEEMO) is an underwater research lab where crews are sent on missions up to 2 weeks long to focus on testing equipment and procedures for future spacewalks (Todd and Reagan, 2004), and the Pavillion Lake Research Project (PLRP; CSA/NASA) uses remotely operated, autonomous, and human explorers to investigate microbiology and remnants of early life.
Simulated missions provide a similar physical environment to a spacecraft or base habitat, as well as activities and schedules resembling those of astronauts. One of the most ambitious of such projects in recent history (2007, 2011) was Mars500 (ESA/Russian Institute for Biomedical Problems). In the longer of two experiments, six volunteers were confined in a mock-up spacecraft for over a year and a half in order to simulate a complete Mars mission. Mars500 included a number of experiments on human brain function and behavior whose results have been published. Research topics included the effect of exercise on prefrontal cortex activity (Schneider et al., 2013); circadian heart rate variability during isolation (Vigo et al., 2013); and the relationships between cortisol levels on brain activity, sleep architecture, and emotional states (Gemignani et al., 2014); sleeping patterns (Basner et al., 2013); and the relationship between feelings of loneliness and cognitive functions (Van Baarsen et al., 2012). Other recent/ongoing projects are exploring perception of time, sleep quality, concentration, and their biological clocks over periods of weeks (Lunares, Poland), and crew selection, team processes, self-guided stress management and resilience training, crew communications and autonomous behavioral countermeasures for spaceflight in missions of several months (Hawaii Space Exploration Analog and Simulation; HI-SEAS; NASA/University of Hawaii).
Training courses that are designed as space analogs have also been proposed as suitable environments in which to conduct human research. ESA’s Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES) program, in which astronauts conduct scientific and exploration tasks in subterranean environments, is one such possibility (Strapazzon et al., 2014). NASA uses the National Outdoor Leadership School (NOLS) to tests the ability of astronauts and candidates to work together in a challenging outdoor setting (Alexander, 2016). For more information about space analogs, please refer to Keeton et al. (2011), Lia Schlacht et al. (2016), Pagel and Choukèr (2016), and Kanki (2018b).
In order to categorize the wide variety of earth-space analogs, NASA created an Analog Assessment Tool (described in NASA/TP−2011-216146, Keeton et al., 2011) that helps investigators select an analog based on study goals. Initially, the tool arranges the analogs based on importance weightings where the research characteristics (such as team size or degree of physical isolation) and utility characteristics (such as relevance of the crew’s tasks or the cost of the study) are proposed. Fidelity weightings are calculated for each proposed analog based on the research and utility characteristics including the degree of their isolation, hostility, confinement, risk, prior knowledge (the accessibility of information about the environment that the mission crew has access to prior to expedition), natural lighting, logistics difficulty, remote communications, science opportunity, similarity to planet surface, and sensitivity (susceptibility to damage by humans of the environment). Both sets of weightings are combined to produce an overall ranking for all proposed analogs according to the goals of the mission (Keeton et al., 2011). ESA has also analyzed facilities that are suitable to be used as lunar analogs (Hoppenbrouwers, 2016). Table 2 presents a synthesis of the criteria commonly used to evaluate terrestrial space analogs against a research project’s goals.
Table 2. Summary of criteria for evaluating terrestrial space analogs.
Caves as Space Analogs
Approximately 20% of Earth’s landmass is karstic, i.e., consisting of topography formed from the dissolution of soluble rocks such as limestone, dolomite, and gypsum, and characterized by sinks, ravines, caves, and underground streams (Ford and Williams, 2007). Only a small portion has been explored, but many sites attract people for recreational and scientific purposes. It is estimated that at least 2,000,000 people in the US alone visit caves each year (Hooker and Shalit, 2000) and members of national speleological societies (e.g., approximately 10,000 members in the US National Speleological Society and about 7,000 in the French Federation of Speleology, gleaned from their websites) suggest that the number of people likely to be involved in rigorous expeditions worldwide is in the range of tens of thousands. Caves are, in fact, interesting to a variety of scientific disciplines, including geology, hydrogeology, and biology, but they also represent unusual challenges for the people who work, explore, rescue, and temporarily live within them. The majority of deaths of cave explorers are caused by falls related to human error, followed by rock falls, drowning, and hypothermia (Stella-Watts et al., 2012; Stella et al., 2015). Science conducted on cave expeditions therefore has the potential to significantly increase research to the benefit of spacefarers, and to improve safety in a widely practiced activity.
Caves have been identified as a naturalistic space analog for training purposes (Bessone et al., 2013; Strapazzon et al., 2014; Pagel and Choukèr, 2016). As space analogs, caves feature many logistic challenges and stressors (e.g., isolation and confinement, risk and reliance on technical equipment for safety, limited prior knowledge of the environment, unusual lighting and sensory conditions, communication and supply difficulties). The spaceflight stressors highlighted in Table 1 (in bold, italics) indicate those spaceflight stressors which are frequently present in caves conditions. Although speleological expeditions may vary in their coverage according to mission, team, and environmental properties, strong overlap is observed. Critically, cave expeditions (as well as some aquatic and polar analogs) fulfill the important psychological factor of being somewhat risky and safety-critical environments in which participants are reliant on equipment and teammates, with limited and slow rescue options (Stella-Watts et al., 2012; Bessone et al., 2013). Perceived risk is likely to cause neurophysical changes that affect many aspects of brain and behavior, from interpersonal interactions to sleep and cognitive function (Pagel and Choukèr, 2016). Cave exploration also requires discipline, teamwork, technical skills and a great deal of behavioral adaptation (Bessone et al., 2013). Martian caves and lava tubes have been proposed as suitable locations in which to construct habitats on Mars, due to thermal stability and shielding from radiation and micrometeorites (Moses and Bushnell, 2016), which would further increase the similarity of the model’s physical environment.
For these reasons, the European Space Agency (ESA) has carried out training activities in the subterranean environment since 2008. The multidisciplinary mission known as CAVES is used for training astronauts of the International Space Station (ISS) Partner Space Agencies (USA, Russia, Japan, Canada, and Europe) (Bessone et al., 2013; Strapazzon et al., 2014). During the 6-day mission, astronauts conduct exploration and scientific activities under similar scheduling and mission conditions as they will later experience in space as a means of eliciting and coaching behavioral competences (Bessone et al., 2008). The science program includes environmental and air circulation monitoring, mineralogy, microbiology, chemical composition of waters, and search for life forms adapted to the cavern environment, and increasingly, human experiments.
As CAVES participants are highly selected astronauts-in-training whose objectives are to explore and conduct scientific studies, it lies toward the higher-fidelity end of the spectrum of cave analog possibilities, and of possible experimental control. However, its capacity to support multiple experiments is limited by tight personnel scheduling. Expeditions of other organizations may therefore be more suitable for a given research question, taking into consideration the specific expedition’s space analog suitability (for recent examples of cave-based human research and a description of the cave conditions and mission, see Stenner et al., 2007; Antoni et al., 2017; Pinna et al., 2017). Cave expeditions may vary due to differences in cave environments (temperature, presence of water, remoteness and access, difficulty level, etc.), mission (duration, objectives, group size, group composition), organization (scientific, exploration, amateur), and the demographics of participants (age, sex, training, culture, language). These factors affect the nature of the data collection that is possible as well as its quality and applicability to other groups. In the section entitled “Connection to in-field study experts and cave community” we list some of the main speleological meetings and organizations through which expeditions appropriate to a research program might be found.
A Brief History of Early Neuroscientific Work Conducted in Caves
Health outcomes of humans living in isolation have been studied over the last 80 years. In the 1960s, researchers began to investigate how biological rhythms were affected when living underground, without “zeitgebers” (i.e., environmental cues that can alter the internal clock, the study of which is now included in the field of chronobiology). Early studies involving isolation in subterranean conditions are listed in Table 3, along with their findings. These studies, as well as those later studies found in Table 4, were identified by a literature search of life science electronic databases (Medline: 1966-Present, NASA Technical Reports Server: 1915-Present, Google Scholar: Present, Worldcat: 1971-Present, OPAC: 1831-Present, and PubMed: 1997-Present). Search terms included “cave/s,” “cave” AND “isolation” AND “human,” “free-running isolation,” “potholing/ers,” “caving,” “social isolation,” ‘subterranean” AND “isolation,” “spelunking,” and “underground environment.” Because many early studies were only reported in their original language, we additionally searched for Italian: “grotta/e,” “isolamento in grotto,” “isolamento spazio temporale,” and “Montalbini” (author); French: “grotte,” “sejours souterrain,” “Siffre” (author); and Spanish: “cueva,” “aisolamento in cueva,” “permanecer bajo tierra,” and “spelunka.” All studies reporting results from human subjects in subterranean environments with a neuroscience or cognitive component were retained (16 reports).
Table 3. Subterranean studies reported from 1938 to 1974.
Table 4. Subterranean studies reported from 1974 to 1994.
Reports from the early to mid 1900s on the effects of isolation on the human body are limited in their sample size and lack standardized methodology (Halberg et al., 1970). One of the first peer-reviewed studies to examine chronobiology was performed by Mills, who analyzed chronobiological aspects of his subject throughout 105 days in subterranean isolation (Mills, 1964). From the 1960s to the mid-1970s, similar studies documented renal rhythms, sleep-wakefulness cycles, time estimation, internal temperature, heart rate, and even menstrual cycles of their subjects as biomarkers for changes of their internal clocks (see Table 3). The majority of these earlier studies using basic physiological measures found that a rest-activity cycle persisted in the absence of any environmental synchronizer or deliberate scheduling, although it appeared to be slightly desynchronized/longer than 24 h (
24.5 h). These findings were interpreted as evidence that the internal clock does not need external cues such as intense light to regulate its biological rhythm (Halberg, 1965). Social cues (e.g., subjects sleeping in the same underground conditions nearby one another, subjects eating meals together) were also shown to affect circadian rhythm, as those of subjects isolated together tended to align (Apfelbaum, 1969).
Although some of the studies in Table 3 were able to look at physiological parameters such as the effects of isolation on vision, measures were mostly implemented prior to and after isolation as opposed to within the cave environment itself. During the expedition, circadian rhythms were observed using core body temperature, sleep-wake cycles, and subjective estimation of time.
Electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG) are techniques that are used to record electrical activity in the brain, skeletal muscles, and eye movements, respectively. Due to advances in electrophysiological tools in the mid 1970s, it became possible to make physiological and neurophysiological measurements during subterranean isolation studies. One of the first cave research studies using EEG and EMG was performed by Chouvet et al. (1974), who characterized sleep architecture during isolation (i.e., the pattern of rapid eye-movement or REM sleep; light sleep or stages 1 and 2; and deep or slow-wave sleep, SWS, that occurs over a nights’ rest). From the mid-1970s to the 1990s, similar studies documented the effects of isolation with limited external time cues on circadian rhythms using EEG, EMG, and EOG, in addition to the previously mentioned physiological measures. These studies are listed in Table 4, along with their main findings.
The studies presented in Tables 3, 4 represent pioneering efforts investigating circadian rhythms in the absence of an externally imposed day-night cycle. Early observations that humans have endogenous rhythmicity in biological processes and alertness levels that can be modified by external cues stimulated further research on human circadian rhythms and sleep cycles which have grown into fields of scientific study with implications for health and disease (Kirsch, 2011). Many of these studies are noteworthy for their pioneering efforts, ingenuity of design, and commitment of their subjects; isolating individuals for long periods would now be considered highly unusual (if not unethical; although causality certainly cannot be inferred, one of the subjects isolated alone for 3 months later died by suicide Hillman et al., 1994b). However, today the data generated by these studies are primarily of interest for historical reasons; the very small sample sizes and lack of experimental control and methodological standardization between studies limit the interpretability and generalizability of the findings, and the tools and practices of measurement of human psychology and physiology have evolved considerably in the interim. Later work showed that some of the findings reported above were likely caused by the experimental procedures. Most notably, many studies in Tables 3, 4 suggested that the endogenous human circadian cycle is closer to 25 than 24 h. This was later attributed to phase shift due to exposure to bright artificial light that subjects were allowed to use while awake; in the absence of bright light, the intrinsic pacemaker is in fact very close to 24 h (Czeisler et al., 1999).
Research Topics: Opportunities, Considerations, and Collaborations
Studies in caves to date have only concerned themselves with a few of the topics for which the cave environment makes a good space analog (i.e., isolation, lighting). Figure 1 presents some of the (interrelated) topics within neuroscience, cognition, and psychology that could be usefully studied in cave expeditions, and might benefit from an intermediate research platform between the laboratory environment and space itself.
Figure 1. Potential topics in psychology, cognition, and neuroscience that could benefit from study in subterranean and expedition environments. Caves could also be a useful context within which to evaluate and optimize the effects of equipment interfaces and operational protocols on human cognition and performance, as well as within which to test the effectiveness of countermeasures.
Circadian Rhythm and Sleep
Sleep quantity and quality, circadian rhythm, and resulting alertness levels and performance proficiency are often altered in spaceflight for environmental and operational reasons (Mallis and DeRoshia, 2005). Due to logistic challenges with sleep measurements in the spaceflight environment, only a few astronauts have been studied using polysomnography (PSG), the gold-standard method for evaluating sleep. According to astronauts’ subjective reports and objective recordings of neurophysiology (i.e., EEG, PSG) and of activity levels (i.e., actigraphy; wrist-worn accelerometers) human sleep has been reported to be shorter and shallower during various missions including Skylab missions (Frost et al., 1975, 1976), space shuttle missions (Monk et al., 1998; Dijk et al., 2001), Mir missions (Gundel et al., 1997), and ISS Expeditions from 2006 to 2011 (Barger et al., 2014), compared to sleep on the ground. Barger and colleagues additionally found that the use of sleep-promoting drugs, which are known to alter sleep architecture and cognitive performance, were pervasive during spaceflight; the authors argued for the need to develop effective countermeasures to restore normal sleep in space (Barger et al., 2014).
The degree to which spaceflight sleep problems are caused by altered physiology due to the effects of microgravity itself or other factors such as isolation and confinement, noise, changes in physical activity, long or unusual sleep-wake and crew shift-work schedule, over-excitation, demographics, rapid succession of light and dark exposure, and ambient temperature is not yet known (Gundel et al., 1997; Pandi-Perumal and Gonfalone, 2016). However, results from space analogs also report significant changes in sleep patterns during Antarctic overwintering (Steinach et al., 2016) and during extended confined isolation (Basner et al., 2013), respectively, suggesting that sleep disturbance can be usefully studied in space analog conditions. In caves, mission-like levels of activity and scheduling, psychological pressures relating to factors such as risk and interpersonal interaction, new surroundings, temperature, humidity, and noise can all affect sleep timing, duration, and quality. Cave expedition constraints can also introduce circadian disturbances; for example, it is not uncommon for cave exploration activities to involve extended periods of wakefulness and near-continuous activity (>24 h and even up to 40 h), when sleeping within the cave is logistically difficult or impossible. These extended periods of wakefulness parallel those in spaceflight which can occur for operational requirements for example rendezvous and docking procedures, and in emergencies. Some cave expeditions may last weeks and require crew to adapt to sleeping and working conditions, providing a situation analogous to longer mission phases. Even when a normal sleep-wake cycle is maintained, important zeitgebers are absent or altered in caves, as in space exploration.
Inadequate sleep can affect daytime alertness levels, response time, vigilant attention, and error rates, learning, complex task performance, emotional evaluation, risk assessment, and fatigue; however, effects differ according to the type of task and degree of its complexity, characteristics of the individual, and the nature of the sleep deprivation (i.e., acute deprivation, or chronic restriction; Wickens et al., 2015; Bermudez et al., 2016; Havekes and Abel, 2017; Krause et al., 2017). In meta-analyses, mental fatigue was shown to also have some effect on physical and athletic performance (Van Cutsem et al., 2017; McMorris et al., 2018), which has relevance for more physically strenuous expedition activities such as climbing or extravehicular activities. Hypnotics (i.e., drugs used to treat insomnia) reduce sleep latency and increase sleep duration, but the resulting sleep shows abnormal sleep architecture (Cojocaru et al., 2017) and does not entirely restore impaired cognitive performance (Verster et al., 2016). Because sleep architecture is important to learning and memory consolidation (Diekelmann and Born, 2010; Ros et al., 2010), these effects are especially undesirable wherever learning is required, as it is during exploration and spatial navigation. People are not always good at assessing their own performance levels; devising means of assessing readiness to perform safety-critical tasks is important, as is knowing how well self-reported alertness levels accurately reflect subsequent cognitive performance (Boardman et al., 2017), and how well performance can be improved in the short term. Caffeine can mitigate some of the next-day cognitive performance effects of reduced sleep in a somewhat predictable fashion (Ramakrishnan et al., 2015). Interestingly, an individual’s performance impairments due to sleep restriction, or enhancement due to stimulants like caffeine, may not translate directly into group performance impairments and improvements, due to mediating factors of group dynamics (Faber et al., 2017), which would also be useful processes to understand under expedition conditions.
In addition to inadequate sleep quality and duration, sleep timing affects performance. Recent progress on the molecular-genetic basis of circadian rhythms indicates that they affect cognition, learning and memory, mood, and metabolism directly, in addition to indirectly through their influence on sleep (Kyriacou and Hastings, 2010). The effect of sleep restriction and circadian misalignment is a topic of concern in occupations that involve shift-work like emergency medicine, in which short-term cognitive deficits have been related to shift work schedules (Machi et al., 2012).
Sensation and Perception
Caves offer unusual sensory inputs that affect waking behavioral performance. In caves as in enclosed artificial environments such as spacecraft, olfactory input is monotonous sometimes negative (i.e., body odors), contributing to habitability and comfort issues. Noise is pervasive in artificial environments, and is known to cause annoyance, disturb sleep and daytime sleepiness, and to negatively affect patient outcomes and staff performance (in hospitals), increase the occurrence of hypertension and cardiovascular disease, and impair cognitive performance (Stansfeld and Matheson, 2003; Basner et al., 2014a). Operational limits on both continuous and intermittent noise exposure have been established for spaceflight, in order to provide an acceptable environment for voice communications and for restful sleep (Allen et al., 2018). However, recent evidence suggests that even low levels of noise, within the established limits, can cause neurophysiological changes that negatively affect health, learning, and memory performance (studied in rodents Cheng et al., 2011). In humans, noise increases the cognitive load associated with understanding speech and communicating, and the ability to do more than one task simultaneously (Rönnberg et al., 2010). Many cave environments have continuous background noise from wind and water movement that could be used to study its effect on individual stress levels, concentration, cognitive performance, fatigue, workload, communication, and interpersonal interaction.
Lighting in caves is produced by headlamps, which create partial, focal illumination of complex three-dimensional spaces and complicates movement and navigation. These perceptual conditions are likely to increase cognitive load and contribute to dual-task performance decrements, including communication and teamwork. The type and distribution of lighting on the exterior of spacecraft affects human visual performance and is an important factor in spacecraft design, particularly for extravehicular activities (Rajulu, 2018). Future extra-terrestrial cave/lava tube exploration may create related challenges.
Higher-level perceptual skills are also relevant for spaceflight. Visuo-spatial orientation skills refer to the ability of individuals to make use of information available in the environment to efficiently orient and navigate. This function relies on cognitive processes such as memory, attention, perception, mental imagery, and decision-making skills (Ekstrom and Isham, 2017). It allows individuals to become familiar with the environment and to integrate information about self-position and orientation into a spatial mental representation of the surroundings, known as a cognitive map (Tolman, 1948; Arnold et al., 2013). Cognitive maps allow any target location from anywhere within the environment to be reached, even by following novel routes when a known pathway is unavailable (Epstein et al., 2017). An accurate mental representation of the environment is crucial for a variety of cognitive tasks in near-space, such as those that involve reaching and grasping objects from a given location within the environment or directing attention to elements in space that are not necessarily within our focal vision. These skills are necessary for maneuvering safely in microgravity, during extra-vehicular activities, and for exploration of planet surfaces (Clément and Reschke, 2008).
The ability to form accurate mental representations of the environment implies the integrity of a complex extended network in the brain (Ekstrom and Isham, 2017; Ekstrom et al., 2017). Within this network, regions in the medial temporal lobe (i.e., hippocampus and parahippocampal cortex) are involved in the learning and memory aspects of orienting and navigating through the environment (Epstein et al., 2005; Iaria et al., 2007). Interestingly, these networks are among those implicated in sleep-related processes of memory consolidation, notably of memory involving spatial and contextual elements (Diekelmann and Born, 2010). Other brain regions used while moving throughout the environment and locating elements within it include the posterior parietal cortex, which is critical for integrating different sensory information processed through our visual, vestibular, somatosensory, and proprioceptive systems (Posner et al., 1984; Andersen, 1997); and the frontal and prefrontal cortex which are necessary for executive functions such as planning, mental imagery, and working memory (Owen et al., 1990; Petrides and Baddeley, 1996). Recent studies have shown that even a minimal functional alteration (not damage per se) of the neural networks described above is associated with impairments of spatial processing (He et al., 2007; Iaria et al., 2014; Kim et al., 2015). As with many complex skills, maintaining expertise in spatial orientation and navigation also requires consistent practice; reliance on GPS technology for example, which offloads the cognitive demands of navigation, is associated with lower navigational expertise (Ishikawa et al., 2008) and lower hippocampal volume and connectivity (Maguire et al., 2000; Iaria et al., 2014). Spatial orientation and navigation are a clear example of a cognitive process in which one must “use it or lose it” (Shors et al., 2012).
Stress, Decision-Making, and Risk-Taking Behavior
Factors affecting physiological and psychological well-being like increased social isolation, confinement, altered sleep, and higher stress levels are also known to affect cognitive skills. For example, visuo-spatial orientation and its neural correlates (Glasauer and Mittelstaedt, 1998; Stranahan et al., 2006; Lukavský, 2014; Valera et al., 2016). Poor quality sleep leads to slower performance and more errors navigating a newly-learned environment (Valera et al., 2016), and chronic stress is known to produce spatial orientation deficits (Mizoguchi et al., 2000; Kleen et al., 2006), likely by perturbing the neurochemistry of supporting networks (Conrad, 2008, 2010; Li et al., 2015). Spatial confinement may also have more direct effects on spatial orientation, for instance, Lukavský (2014) identified a marked difference in scene memory in the six participants of the Mars500 project. Relative to controls, these individuals developed a greater bias toward “boundary extension” while viewing distant scenes, i.e., falsely recalling a wider field of view or more distant perspective from these visual stimuli. Lukavský hypothesized that the lack of interaction with distal objects and scenes due to extended stays in a relatively confined environment will result in the deterioration of the perception and strategy use within larger environments.
The hippocampus and prefrontal cortex have a well-documented sensitivity to some of the negative factors associated with subterranean explorations. Rodents housed in confined, isolated, or simple environments have smaller hippocampi, comprised of fewer neurons (Kempermann et al., 1997) with fewer dendritic spines (Leggio et al., 2005), less neurogenesis (Olson et al., 2006), and poorer spatial abilities (Nilsson et al., 1999; Leggio et al., 2005). While the typical experiences of a lab rodent differ from that of an average human, these findings are generally supported by human research (Gianaros et al., 2007; Lupien et al., 2007; Ganzel et al., 2008; Prince and Abel, 2013). The prefrontal cortex is vulnerable to both acute and chronic stressors, with acute stress producing notable impairments in spatial working memory (Arnsten, 2009), as well as reducing the capacity to problem-solve and think flexibly. Paralleling the effects seen in the hippocampus, long-term exposure to stressors produces lower prefrontal cortex volumes (Cerqueira et al., 2007), reduced dendrite length and branching (Holmes and Wellman, 2009), and detriments to spatial memory (Cerqueira et al., 2007; Arnsten, 2009), vulnerabilities that appear to worsen with aging (McEwen and Morrison, 2013). Cave environments offer challenging three-dimensional environments in which to move and explore, simulating the challenging perceptual and mission conditions of spaceflight; they may also offer unique opportunities to contribute to knowledge of hippocampal function, dysfunction, and plasticity as it relates to sleep, stress, and confinement.
The perceived risk and danger aspect of expedition environments offers another set of research opportunities with spaceflight relevance. Communication with the outside world may be very limited. Though teams often set up a telephone line between an external base and a main cave base camp for extended expeditions, difficult terrain may still require hours or even days of movement before communication can be established, and rescue attempts could take much longer. In future long-duration space missions to Mars and for permanent stays on the Martian surface, transmissions between ground and space may be delayed up to 40 min or even blocked, and short-term rescue may be impossible; lack of a visual link to Earth will add to the feelings of isolation and autonomy (Horneck and Comet, 2006; Strapazzon et al., 2014). Under uncertain conditions, stress impacts decision-making and risk-taking behavior (reviewed in Morgado et al., 2015). These effects appear to be mediated by stress-related release of neurotransmitters that lead to alterations in neural firing, and if stress is chronic, to architectural changes in frontal lobe areas involved in higher-level cognition (Arnsten, 2015). The stress associated with risk and danger also affects interpersonal interactions and group dynamics, potentially leading to feedback cycles in communication that foment crew conflict (Kalish et al., 2015).
Interpersonal Interactions and Teamwork
The interaction of stressors that challenge cave and space explorers with interpersonal dynamics is a critical component of mission success (Bishop et al., 1999; Sandal, 2018). Although teamwork, team cohesion, team effectiveness, and resilience have been identified as knowledge gaps and are current topics of investigation for space exploration, there have been relatively few studies in extreme environments and space-analogs (for a summary, see Salas et al., 2015; Sandal, 2018), and studies within caves are scarce (for examples, see Bishop et al., 1999; MacNeil and Brcic, 2017).
The empirical study of team characteristics and processes has non-standard, evolving theoretical constructs and methodology (Cronin et al., 2011; Alliger et al., 2015; Kozlowski, 2015). Common techniques include behavioral observation (during simulations or training; in person, or by reviewing recordings) and self-report by surveys (during pauses in activity, or retroactively) (Brannick et al., 1997). These methods may require an uninvolved observer, rely on team members’ ability and desire for introspection, and may not capture how the team dynamically reacts and interacts to changing situations. Wearable physiological and neurophysiological measurement devices have been proposed as a means of unobtrusively tracking team dynamics, assessing the quality of teams’ performance in real time, and adaptively rearranging team or task components (Stevens et al., 2011; Salas et al., 2015; Santoro et al., 2015; Lederman et al., 2017). These promising approaches are in early development phases, and could be tested in cave environments.
Evaluating Interfaces and Countermeasures
As well as observing and characterizing the behavioral and neurophysiological correlates of environmental stressors (Alonso et al., 2015), (neuro) physiological indices of attention, workload, and emotional state can be used to measure how people interact with technology, for the purposes of evaluating equipment interfaces (Liapis et al., 2015) and to validate brain-computer interface (BCI) systems. Passive BCIs use these signals to adapt the behavior and functionality of highly complex and safety critical systems accordingly to the user’s actual mental state in real time, without requiring effort. They are promising means of optimizing interaction with technology for spaceflight applications as well as in various Earth-based applications (Coffey et al., 2010; Aricò et al., 2016; Arico et al., 2017). In cave exploration, interaction and supervision of swarms of robotic agents is a possible application (Fink et al., 2015; Kolling et al., 2016).
The cave environment could be used to test the feasibility and effectiveness of countermeasures. In a recent meta-analysis, mindfulness-based meditation was shown to reduce stress, depression, anxiety and distress, and improve quality of life in healthy individuals (Khoury et al., 2015). Neurofeedback, in which users are given a visual or auditory representation of certain features of their brain’s ongoing activity such that they can learn to modulate it (e.g., based on the amplitude of different frequency bands measured with EEG), might be tested as a means of maintaining function during expeditions. In a review of about 30 controlled studies, EEG-neurofeedback showed evidence of performance gains on sustained attention, orienting and executive attention, memory, spatial rotation, reaction time, complex psychomotor skills, implicit procedural memory, recognition memory, perceptual binding, intelligence, mood and well-being (Gruzelier, 2014).
Slow oscillations present in deep sleep can be enhanced using a method known as auditory closed-loop stimulation. Short bursts of quiet broadband noise are played to the user, precisely timed to the ascending phase of ongoing slow oscillations (Ngo et al., 2013). The brain’s reaction to the sounds strengthens the slow oscillations and improves some types of memory (i.e., hippocampus-dependent declarative memory; Arnal et al., 2017; Besedovsky et al., 2017). Another new method of enhancing learning is known as targeted memory reactivation (TMR), in which an olfactory or auditory stimulus is associated with a learning event. In the subsequent sleep period, the stimulus is repeated, presumably reactivating the memory and increasing the strength with which it is consolidated (learned) (Schouten et al., 2017). Although these methods are new and have shown improvements on only basic tasks that are far removed from those performed in the operational environment, further developments may make them usable to optimize learning in expedition environments; these could be tested in caves.
Thus, as early twentieth century researchers deduced, cave environments are useful for studying sleep and circadian processes. Though early studies only took advantage of the isolation and the absence of zeitgebers found in caves, a much larger set of questions can be asked during modern expeditions: of sleep and circadian rhythm, but also about sensation and perception, spatial navigation, interpersonal interactions and teamwork, human factors design, stress, and the impact of these stressors on wellbeing and performance. In the following section, we discuss several considerations for conducting human research in cave environments.
Methodological Considerations for Conducting Research in Caves
Because of the long planning time for many space and analog missions and because of the difference in the scale of research investment, the pace of progress is generally more rapid in mainstream neuroscience. The focus of analog research is likely to be establishing and characterizing phenomena under expedition conditions and assessing the effect of interventions, whereas a laboratory approach can investigate finer-grained mechanisms, in tightly controlled paradigms that isolate specific phenomena, possibly using highly specialized equipment. Both are valuable; to maximize the advantages of each, researchers might choose to include a lab-based control group for comparison, test subjects before an expedition in the lab to serve as a baseline, complement field studies with investigations of the same phenomenon using their full lab suite, or carefully validate field equipment and procedures against laboratory standards, according to the research question.
Scientists only familiar with the traditional academic research side may find the collection Space Safety and Human Performance Sgobba et al. (2018), as well as Clément and Ngo-Anh (2013) to be useful starting points to review studies conducted in space or space analogs to date. It can be helpful to obtain first- or second-hand knowledge of the cave expedition environment prior to planning experiments, such that environmental and mission constraints that could introduce problems, confounds, or poor quality data can be avoided. In field studies, in fact, we often have poor control over confounding environmental factors (Brugger et al., 2018), but choosing the right “cave setting” can offer a certain level of standardization.
Expedition or medical experts who might wish to add neuroscience questions to their programs may discover too late that their results are unpublishable. For example, in auditory cognitive neuroscience, it is considered essential to confirm that subjects have normal hearing thresholds such that experimental findings can be attributed to some condition of interest and not a hearing deficit. Norms and best practices such as this have evolved in each specialized sub-field in order to guard against artifacts and confounds, and ensure replicability and generalizability of findings, but may not be obvious to operations personnel. There are often means of satisfying such requirements, once they are known. In this example, the researcher could conduct a basic audiogram on-site or arrange (with the subject’s permission) to obtain equivalent information via previous medical reports. A more problematic issue concerns sample size and statistical validity of the proposed research design; (i) case studies or very small sample sizes are unlikely to be well regarded by many peers in neuroscience; (ii) small sample sizes (
Oléron, G., Fraisse, P., Siffre, M., and Zuili, N. (1970). Les Variations Circadiennes du Temps de Reaction et du Tempo Spontane au Cours d’une Experience “Hors du Temps.” Annee Psychol. 70, 347–356.
Olson, A. K., Eadie, B. D., Ernst, C., and Christie, B. R. (2006). Environmental enrichment and voluntary exercise massively increase neurogenesis in the adult hippocampus via dissociable pathways. Hippocampus 16, 250–260. doi: 10.1002/hipo.20157
Owen, A. M., Downes, J. J., Sahakian, B. J., Polkey, C. E., and Robbins, T. W. (1990). Planning and spatial working memory following frontal lobe lesions in man. Neuropsychologia 28, 1021–1034. doi: 10.1016/0028-3932(90)90137-D
Pagel, J. I., and Choukèr, A. (2016). Effects of isolation and confinement on humans-implications for manned space explorations. J. Appl. Physiol. 120, 1449–1457. doi: 10.1152/japplphysiol.00928.2015
Pandi-Perumal, S. R., and Gonfalone, A. A. (2016). Sleep in space as a new medical frontier: the challenge of preserving normal sleep in the abnormal environment of space missions. Sleep Sci. 9, 1–4. doi: 10.1016/j.slsci.2016.01.003
Pattyn, N., Migeotte, P.-F., Morais, J., Soetens, E., Cluydts, R., and Kolinsky, R. (2009). Crew performance monitoring: putting some feeling into it. Acta Astronaut. 65, 325–329. doi: 10.1016/J.ACTAASTRO.2009.01.063
Petrides, M., and Baddeley, A. (1996). Specialized Systems for the Processing of Mnemonic Information within the Primate Frontal Cortex [and Discussion]. Philos. Trans. R. Soc. B Biol. Sci. 351, 1455–1462. doi: 10.1098/rstb.1996.0130
Pinna, V., Magnani, S., Sainas, G., Ghiani, G., Vanni, S., Olla, S., et al. (2017). Physical capacity and energy expenditure of cavers. Front. Physiol. 8:1067. doi: 10.3389/fphys.2017.01067
Pinti, P., Aichelburg, C., Lind, F., Power, S., Swingler, E., Merla, A., et al. (2015). Using Fiberless, Wearable fNIRS to monitor brain activity in real-world cognitive tasks. J. Vis. Exp. 106, 1–13. doi: 10.3791/53336
Polackova Solcova, I., Lačev, A., and Šalcová, I. (2014). Study of individual and group affective processes in the crew of a simulated mission to Mars: positive affectivity as a valuable indicator of changes in the crew affectivity. Acta Astronaut. 100, 57–67. doi: 10.1016/j.actaastro.2014.03.016
Posner, M. I., Walker, J. A., Friedrich, F. J., and Rafal, R. D. (1984). Effects of Pareital Injury on Covert Orienting of Attention 1. J. Neurosci. 4, 1863–1874. doi: 10.1136/jnnp.72.1.73
Prince, T. M., and Abel, T. (2013). The impact of sleep loss on hippocampal function. Learn. Mem. 20, 558–569. doi: 10.1101/lm.031674.113
Rajulu, S. (2018). “Human factors and safety in EVA,” in Space Safety and Human Performance, eds T. Sgobba, B. G. Kanki, J.-F. Clervoy, and G. Sandal (Butterworth-Heinemann), 469–500. doi: 10.1016/B978-0-08-101869-9.00011-X
Ramakrishnan, S., Laxminarayan, S., Wesensten, N. J., Balkin, T. J., and Reifman, J. (2015). “Can we predict cognitive performance decrements due to sleep loss and the recuperative effects of caffeine?,” in Proceedings of the HFM-254 Symposium on Health Surveillance and Informatics in Missions: Multidisciplinary Approaches and Perspectives (Paris), 1–20.
Reinberg, A., Halberg, F., and Ghata, J. S. M (1966). Spectre thermique d’une femme adulte avant, pendant et apres son isolement souterrain de trois mois. C.R. Acad. Sci. Hebd. Seances Acad. Sci. D. 262, 782–785.
Roberts, D. R., Albrecht, M. H., Collins, H. R., Asemani, D., Chatterjee, A. R., Spampinato, M. V., et al. (2017). Effects of spaceflight on astronaut brain structure as indicated on MRI. N. Engl. J. Med. 377, 1746–1753. doi: 10.1056/NEJMoa1705129
Rönnberg, J., Rudner, M., Lunner, T., and Zekveld, A. (2010). When cognition kicks in: working memory and speech understanding in noise. Noise Heal. 12:263. doi: 10.4103/1463-1741.70505
Ros, T., Munneke, M. A. M., Ruge, D., Gruzelier, J. H., and Rothwell, J. C. (2010). Endogenous control of waking brain rhythms induces neuroplasticity in humans. Eur. J. Neurosci. 31, 770–778. doi: 10.1111/j.1460-9568.2010.07100.x
Roy, R. N., Charbonnier, S., Campagne, A., and Bonnet, S. (2016). Efficient mental workload estimation using task-independent EEG features. J. Neural Eng. 13:026019. doi: 10.1088/1741-2560/13/2/026019
Sahayadhas, A., Sundaraj, K., and Murugappan, M. (2012). Detecting driver drowsiness based on sensors: a review. Sensors 12, 16937–16953. doi: 10.3390/s121216937
Salas, E., Tannenbaum, S. I., Kozlowski, S. W. J., Miller, C. A., Mathieu, J. E., and Vessey, W. B. (2015). Teams in space exploration: a new frontier for the science of team effectiveness. Curr. Dir. Psychol. Sci. 24, 200–207. doi: 10.1177/0963721414566448
Salotti, J. M., and Heidmann, R. (2014). Roadmap to a human Mars mission. Acta Astronaut. 104, 558–564. doi: 10.1016/j.actaastro.2014.06.038
Sanchez da la Pena, S., Halberg, F., Galvagno, A., Montalbini, M., Follini, S., Wu, J., et al. (1989). “Circadian and circaseptan (about-7-day) free-running physiologic rhythms of a woman in social isolation,” in Second Annual IEEE Symposium on Computer-Based Medical Systems, 273–278.
Sandal, G. M. (2001). Crew tension during a space station simulation. Environ. Behav. 33, 134–150. doi: 10.1177/00139160121972918
Sandal, G. M. (2018). “Psychological resilience,” in Space Safety and Human Performance, eds T. Sgobba, B. G. Kanki, J.-F. Clervoy, and G. Sandal (Butterworth-Heinemann), 183–237. doi: 10.1016/B978-0-08-101869-9.00006-6
Sandal, G. M., Leon, G. R., and Palinkas, L. (2006). Human challenges in polar and space environments. Rev. Environ. Sci. Bio Technol. 5, 281–296. doi: 10.1007/s11157-006-9000-8
Sandal, G. M., Vaernes, R., and Ursin, H. (1995). Interpersonal relations during simulated space missions. Aviat. Space. Environ. Med. 66, 617–624.
Santoro, J. M., Dixon, A. J., Chang, C.-H., and Kozlowski, S. W. J. (2015). “Measuring and monitoring the dynamics of team cohesion: methods, emerging tools, and advanced technologies,” in eds E. Salas, W. B. Vessey, and A. X. Estrada (Bingley: Emerald Group Publishing Limited), 115–145. doi: 10.1108/S1534-085620150000017006
Santy, P. A., Kapanka, H., Davis, J. R., and Stewart, D. F. (1988). Analysis of sleep on Shuttle missions. Aviat. Sp. Environ. Med. 59, 1094–1097.
Sawyer, B. D., Hancock, P. A., Deaton, J., and Suedfeld, P. (2012). Finding the team for Mars: a psychological and human factors analysis of a Mars Desert Research Station crew. Work 41 (Suppl. 1), 5481–5484. doi: 10.3233/WOR-2012-0859-5481
Schneider, S., Abeln, V., Popova, J., Fomina, E., Jacubowski, A., Meeusen, R., et al. (2013). The influence of exercise on prefrontal cortex activity and cognitive performance during a simulated space flight to Mars (MARS500). Behav. Brain Res. 236, 1–7. doi: 10.1016/J.BBR.2012.08.022
Schneider, S., Brümmer, V., Carnahan, H., Kleinert, J., Piacentini, M. F., Meeusen, R., et al. (2010). Exercise as a countermeasure to psycho-physiological deconditioning during long-term confinement. Behav. Brain Res. 211, 208–214. doi: 10.1016/j.bbr.2010.03.034
Schneider, T. M., Bregani, R., Stopar, R., Krammer, J., Göksu, M., Müller, N., et al. (2016). Medical and logistical challenges of trauma care in a 12-day cave rescue: a case report. Injury 47, 280–283. doi: 10.1016/j.injury.2015.09.005
Schouten, D. I., Pereira, S. I. R., Tops, M., and Louzada, F. M. (2017). State of the art on targeted memory reactivation: sleep your way to enhanced cognition. Sleep Med. Rev. 32, 123–131. doi: 10.1016/J.SMRV.2016.04.002
Sgobba, T., Kanki, B., Canepa, G., and Ferrante, M. (2017a). “Introduction,” in Space Safety and Human Performance, eds T. Sgobba, B. G. Kanki, J.-F. Clervoy, and G. Sandal (Oxford, UK; Cambridge, MA: Butterworth-Heinemann), 1–16. doi: 10.1016/B978-0-08-101869-9.00001-7
Sgobba, T., Kanki, B. G., Clervoy, J.-F., and Sandal, G. M. (eds.). (2018). “Copyright.” in Space Safety and Human Performance. Oxford, UK; Cambridge, MA: Butterworth-Heinemann.
Sgobba, T., Leveson, N., Wilde, P., and Barr, S. (2017b). “System safety and accident prevention,” in Space Safety and Human Performance, eds T. Sgobba, B. G. Kanki, J.-F. Clervoy, and G. Sandal (Oxford, UK; Cambridge, MA: Butterworth-Heinemann), 273–353. doi: 10.1016/B978-0-08-101869-9.00008-X
Shahid, A., Wilkinson, K., Marcu, S., and Shapiro, C. M. (eds.). (2011). “ZOGIM-A (Alertness Questionnaire),” in STOP, THAT and One Hundred Other Sleep Scales, (New York, NY: Springer), 405–406. doi: 10.1007/978-1-4419-9893-4_102
Shapiro, C. M., Auch, C., Reimer, M., Kayumov, L., Heslegrave, R., Huterer, N., et al. (2006). A new approach to the construct of alertness. J. Psychosom. Res. 60, 595–603. doi: 10.1016/j.jpsychores.2006.04.012
Shors, T. J., Anderson, M. L., Curlik, D. M., and Nokia, M. S. (2012). Use it or lose it: how neurogenesis keeps the brain fit for learning. Behav. Brain Res. 227, 450–458. doi: 10.1016/j.bbr.2011.04.023
Siffre, M. (1987). “Rythmes biologiques, sommeil et vigilance en confinement prolonge,” in Proceedings of a Colloquium on ‘Space & Sea’ (Marseille), 53–68.
Siffre, M., Reinberg, A., Halberg, F., Ghata, J., and Perdriel, G. S. R (1966). L’isolement souterrain prolonge. Presse Med. 74, 915–919.
Sonnenfeld, G., Measel, J., Loken, M. R., Degioanni, J., Follini, S., Galvagno, A., et al. (1992). Effects of isolation on interferon production and hematological and immunological parameters. J. Interferon. Res. 12, 75–81. doi: 10.1089/jir.1992.12.75
Stansfeld, S. A., and Matheson, M. P. (2003). Noise pollution: non-auditory effects on health. Br. Med. Bull. 68, 243–257. doi: 10.1093/bmb/ldg033
Steinach, M., Kohlberg, E., Maggioni, M. A., Mendt, S., Opatz, O., Stahn, A., et al. (2016). Sleep quality changes during overwintering at the German antarctic stations neumayer II and III: The gender factor. PLoS ONE 11:e0150099. doi: 10.1371/journal.pone.0150099
Stella, A. C., Priyanka Vakkalanka, J., Holstege, C. P., and Charlton, N. P. (2015). The Epidemiology of Caving Fatalities in the United States. Wilderness Environ. Med. 26, 436–437. doi: 10.1016/j.wem.2015.01.007
Stella-Watts, A. C., Holstege, C. P., Lee, J. K., and Charlton, N. P. (2012). The epidemiology of caving injuries in the United States. Wilderness Environ. Med. 23, 215–222. doi: 10.1016/j.wem.2012.03.004
Stenner, E., Gianoli, E., Piccinini, C., Biasioli, B., Bussani, A., and Delbello, G. (2007). Hormonal responses to a long duration exploration in a cave of 700 m depth. Eur. J. Appl. Physiol. 100, 71–78. doi: 10.1007/s00421-007-0408-9
Stevens, R. H., Galloway, T., Berka, C., and Wang, P. (2011). “Developing systems for the rapid modeling of team neurodynamics,” in International Conference on Foundations of Augmented Cognition (Berlin: Heidelberg: Springer), 356–365. doi: 10.1007/978-3-642-21852-1_42
Stranahan, A. M., Khalil, D., and Gould, E. (2006). Social isolation delays the positive effect of running on adult neurogenesis. Nat. Neurosci. 9, 526–533. doi: 10.1038/nn1668
Strangman, G. E., Sipes, W., and Beven, G. (2014). Human cognitive performance in spaceflight and analogue environments. Aviat. Space. Environ. Med. 85, 1033–1048. doi: 10.3357/ASEM.3961.2014
Strapazzon, G., Pilo, L., Bessone, L., and Barratt, M. R. (2014). CAVES as an environment for astronaut training. Wilderness Environ. Med. 25, 244–245. doi: 10.1016/j.wem.2013.12.003
Stroop, J. R. (1992). Studies of interference in serial verbal reactions. J. Exp. Psychol. Gen. 121, 15–23. doi: 10.1037/0096-34126.96.36.199
Suedfeld, P., and Steel, G. D. (2000). The environmental psychology of capsule habitats. Annu. Rev. Psychol. 51, 227–253. doi: 10.1146/annurev.psych.51.1.227
Suedfield, P. (1991). “Groups in isolation and confinement: environments and experiences,” in From Antarctica to Outer Space (New York, NY: Springer), 135–146. doi: 10.1007/978-1-4612-3012-0_14
Tafforin, C. (2009). Life at the Franco-Italian Concordia Station in Antarctica for a Voyage to Mars: ethnological study and anthropological perspectives. Antrocom 5, 67–72.
Taylor, R. M. (1990). “Situational Awareness Rating Technique (SART): the development of a tool for aircrew systems design,” in Situational Awareness in Aerospace Operations (AGARD-CP-478). Neuilly-sur-Seine: NATO – AGARD.
Tellez, H. F., Mairesse, O., Macdonald-Nethercott, E., Neyt, X., Meeusen, R., and Pattyn, N. (2014). Sleep-related periodic breathing does not acclimatize to chronic hypobaric hypoxia: a 1-year study at high altitude in Antarctica. Am. J. Respir. Crit. Care Med. 190, 114–116. doi: 10.1164/rccm.201403-0598LE
Thayer, J. F., Åhs, F., Fredrikson, M., Sollers, J. J., and Wager, T. D. (2012). A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neurosci Biobehav Rev. 36, 747–756. doi: 10.1016/j.neubiorev.2011.11.009
Thronson, H. A., Baker, J., Beaty, D., Carberry, C., Craig, M., Davis, R. M., et al. (2016). Continuing to Build a Community Consensus on the Future of Human Space Flight: Report of the Fourth Community Workshop on Achievability and Sustainability of Human Exploration of Mars (AM IV). Monrovia.
Todd, B., and Reagan, M. (2004). “The NEEMO Project: A Report on How NASA Utilizes the “ Aquarius” Undersea Habitat as an Analog for Long-Duration Space Flight,” in Engineering, Construction, and Operations in Challenging Environments (Reston, VA: American Society of Civil Engineers), 751–758. doi: 10.1061/40722(153)103
Tolman, E. C. (1948). Cognitive maps in rats and man. Psychol. Rev. 55, 189–208.
Valera, S., Guadagni, V., Slone, E., Burles, F., Ferrara, M., Campbell, T., et al. (2016). Poor sleep quality affects spatial orientation in virtual environments. Sleep Sci. 9, 225–231. doi: 10.1016/j.slsci.2016.10.005
Van Baarsen, B. F, Ferlazzo, D., Ferravante, J., Smit, J., and van der Pligt, M. van D. (2012). “The effects of extreme isolation on loneliness and cognitive control processes: analyses of the Lodgead data obtained during the Mars105 and the Mars520 studies,” in Proceedings, 63th International Astronautical Congress, Vol. 20 (Naples), 1–5.
Van Cutsem, J., Marcora, S., De Pauw, K., Bailey, S., Meeusen, R., and Roelands, B. (2017). The effects of mental fatigue on physical performance: a systematic review. Sport. Med. 47, 1569–1588. doi: 10.1007/s40279-016-0672-0
Van Ombergen, A., Laureys, S., Sunaert, S., Tomilovskaya, E., Parizel, P. M., and Wuyts, F. L. (2017). Spaceflight-induced neuroplasticity in humans as measured by MRI: what do we know so far? npj Microgravity 3:2. doi: 10.1038/s41526-016-0010-8
Verster, J., Peters, L. V., Aurora van de, L., Bouwmeester, H., Tiplady, B., Alford, C., et al. (2016). Abstracts. J. Sleep Res. 25, 5–377. doi: 10.1111/jsr.12446
Vigo, D. E., Ogrinz, B., Wan, L., Bersenev, E., Tuerlinckx, F., Van den Bergh, O., et al. (2012). Sleep-wake differences in heart rate variability during a 105-day simulated mission to mars. Aviat. Sp. Environ. Med. 83, 125–130. doi: 10.3357/ASEM.3120.2012
Vigo, D. E., Tuerlinckx, F., Ogrinz, B., Wan, L., Simonelli, G., Bersenev, E., et al. (2013). Circadian rhythm of autonomic cardiovascular control during mars500 simulated mission to mars. Aviat. Sp. Environ. Med. 84, 1023–1028. doi: 10.3357/ASEM.3612.2013
Wang, D., Chen, Z., Yang, C., Liu, J., Mo, F., and Zhang, Y. (2015). Validation of the Mobile Emotiv Device Using a Neuroscan Event-Related Potential System. J. Med. Imaging Heal. Informatics 5, 1553–1557. doi: 10.1166/jmihi.2015.1563
Watson, D., Clark, L. A., and Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54, 1063–1070. doi: 10.1037/0022-35188.8.131.523
Wickens, C. D., Hutchins, S. D., Laux, L., and Sebok, A. (2015). The Impact of Sleep Disruption on Complex Cognitive Tasks. Hum. Factors J. Hum. Factors Ergon. Soc. 57, 930–946. doi: 10.1177/0018720815571935
Wilhelm, O., Hildebrandt, A., and Oberauer, K. (2013). What is working memory capacity, and how can we measure it? Front. Psychol. 4:433. doi: 10.3389/fpsyg.2013.00433
Wilson, K. A. (2018). “Human factors mishap investigation,” in Space Safety and Human Performance, eds T. Sgobba, B. G. Kanki, J.-F. Clervoy, and G. Sandal (Butterworth-Heinemann), 809–831. doi: 10.1016/B978-0-08-101869-9.00018-2
Wolf-Meyer, M. (2013). Where have all our naps gone? Or Nathaniel Kleitman, the consolidation of sleep, and the historiography of emergence. Anthropol. Conscious. 24, 96–116. doi: 10.1111/anoc.12014
Yorubaland, C., Usman, A., and Fink, A. (1999). “The survey,” in The Survey Handbook, Vol. 1, ed A. Fink (Thousand Oaks, CA: Sage), 59–65.
Keywords: spaceflight, space analog, astronauts, neuroscience, cognition, psychology, human factors, wearable measurement
Citation: Mogilever NB, Zuccarelli L, Burles F, Iaria G, Strapazzon G, Bessone L and Coffey EBJ (2018) Expedition Cognition: A Review and Prospective of Subterranean Neuroscience With Spaceflight Applications. Front. Hum. Neurosci. 12:407. doi: 10.3389/fnhum.2018.00407
Received: 05 June 2018; Accepted: 21 September 2018;
Published: 30 October 2018.
Klaus Gramann, Technische Universität Berlin, Germany
Jelena Brcic, University of the Fraser Valley, Canada
Mathias Basner, University of Pennsylvania, United States
Copyright © 2018 Mogilever, Zuccarelli, Burles, Iaria, Strapazzon, Bessone and Coffey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.