sPACeMAN – Assessing Neurocognitive Performance and Electrocortical Activity Across Diverse Gravity Levels Using a Gamification Approach

sPACeMAN – Assessing Neurocognitive Performance and Electrocortical Activity Across Diverse Gravity Levels Using a Gamification Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article sPACeMAN – Assessing Neurocognitive Performance and Electrocortical Activity Across Diverse Gravity Levels Using a Gamification Approach Constance Badalì, Petra Wollseiffen, Lennart Puck, Stefan Schneider This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5136580/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract It is essential that astronauts maintain optimal cognitive function in order to successfully complete critical tasks in demanding environments. However, stress can impair executive functions and decision-making, which may ultimately affect mission success. Training and establishing routines can help ensure efficiency and may free up cognitive resources to handle unforeseen challenges effectively. To evaluate workload management in a demanding dual-task the study investigated behavioural data (Reaction Time and Error Rate), as well as neurophysiological parameters (event-related potentials and electrocortical activity) in Earth gravity, hypergravity and weightlessness in 25 consecutive parabolas through a parabolic flight. The data demonstrated no significant changes in electrocortical activity and reaction time between the different gravity levels. However, a notable increase in error rate was observed in microgravity when compared to hyper- and normal gravity. Electrophysiological data revealed a pronounced N1-P2 complex, indicating perceptual processing of the sound of the Oddball paradigm. The typical fronto-central N200 component was triggered by both sounds of the Oddball paradigm, although no differences were observed between the gravity levels. The similarity of the ERP responses to both oddball paradigm tones suggests that most cognitive resources were allocated to the primary task, with reduced discrimination of auditory stimuli. Furthermore, the presence of the N200 component, interpreted as mismatch negativity (MMN), indicates automatic neural responses to auditory deviations that are independent of cognitive load. This has important implications for astronauts performing complex tasks during space missions, where understanding cognitive workload and task prioritization is essential for mission success and safety. Further research is needed to explore cognitive workload management in such demanding environments. Biological sciences/Neuroscience Biological sciences/Physiology weightlessness hypergravity parabolic flight behavioural and neuronal parameters ERP EEG Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 INTRODUCTION Since space missions regularly require astronauts to perform complex, critical tasks in challenging environments, maintaining cognitive performance is of great importance. In situations of increased stress, cognitive processes of executive functions and decision-making can be negatively affected. Such impairment presents a notable risk to missions where the ability to perform complex procedures safely and efficiently is critical. The training and development of routines within such procedures are not only important for mission success but possibly allow astronauts to free up or reallocate cognitive resources to adequately cope with unexpected tasks. The relevance of monitoring and maintaining cognitive performance in space is also embedded in ESAs strategic roadmaps 1 ( https://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf ) and of major importance when designing and applying countermeasures to increase mission success and safety. It is advisable to combine physiological as well as psychological data to monitor the neuro-psychological status during a mission 2 and provide significant physical and mental crew health and performance data 3 . In the last decade, several studies have investigated human behaviour and neurocognitive performance in microgravity, e.g. during space flights or experimental parabolic flights 4 , 5 . Despite anecdotical reports of astronauts and cosmonauts, there seems to be a positive impact of weightlessness on cortical processing 6 , 7 . These results are in line with in vitro data from Sieber et al. (2014) reporting an increased excitability of neurons under microgravity 8 . Summarizing in vivo and in vitro experiments, Kohn and Ritzmann (2018) suggest a reduced membrane viscosity caused by increased lateral pressure on neurons in microgravity. This leads to a reduction in the open-state probability of ion channels, which results finally in a slightly depolarized resting membrane potential of the cell 8 . Studies already show that cells under external pressure tend to have reduced neuronal excitability 9 . It is therefore assumed, that the well-reported increase in blood volume to the brain during microgravity increases intracranial pressure in the brain and might be the cause for this cascade of physiological changes. The capacity of the human mind to perform cognitive tasks is contingent upon the ability to allocate the requisite and available brain resources efficiently and effectively to the tasks at hand. It has been demonstrated that the utilisation of available brain resources is dependent on the challenge presented by the tasks to be completed 10 , 11 . The term "cognitive workload" can be used to describe the concept of brain resource utilization 12 – 14 . A neurophysiological representation of this can be observed in the amplitude and latency of event-related potentials (ERP), with the amplitude of ERPs demonstrating a correlation with the amount of attentional resources allocated to a given task 15 . Recent results observed in microgravity show higher amplitudes of ERPs elicited by a discrete primary and secondary task in hypergravity without differences in behavioral data 16 . This is also true for the cognitive performance data under partial gravity (Moon/Mars) and for differences in ERP amplitude and latency, which could lead to the suggestion that there is a threshold for the influence of lower gravity on neurocognitive performance 17 . Despite these findings, the studies were limited by (1) the small sample size, (2) the limited number of experimental parabolas and (3) the use of a non-continuous primary task in interfering with a classical oddball paradigm. Accordingly, a continuous navigation task (Pac-Man) was selected as the primary task with a non-continuous classical auditive oddball paradigm in this study, as it provides a high level of intrinsic motivation (gamification). Given the game-like and more challenging character of the continuous primary task, it is hypothesized that performance under 0G is increased compared to 1G and 1.8G and that this is simultaneously mirrored by a reduction of the elicited ERP waves during the experiment. MATERIALS AND METHODS Participants and Procedure Parabolic flights take place on board the A310 ZeroG from Merignac International Airport in Bordeaux (F), led by the European Space Agency (ESA) and the German Aerospace Centre (DLR). Each parabola consists of four phases, characterised by shifts in gravity from Earth gravity to hypergravity, microgravity, back to hypergravity and returning to Earth gravity. Every campaign includes three flight days, with 30 experimental parabolas per day. Over three campaigns conducted from September 2023 to June 2024, data were collected from 18 participants (12 males, 6 females) who executed the experiment in normal gravity (1G), hypergravity (1.8G) and microgravity (0G). All participants and investigators underwent clinical examinations and provided informed consent. The study's experimental design was approved by the Research Ethics Committee of the German Sport University Cologne and the University of Caen following the Declaration of Helsinki. Experiment The neurocognitive task consisted of a continuous navigation task (PACMAN) and a classical auditory oddball task. While playing PACMAN participants heard randomised tones through wired noise-cancelling headphones (BOSE QuietComfort 20). These tones included either target tones (high tones) or standard tones (low tones). The low-pitched tones made up 70% of all tones and were to be disregarded, while the high-pitched tones, which made up 30% of all tones, prompted participants to quickly press the space bar with the left hand on a keyboard on their lap. PACMAN was played using the arrow keys with the right hand. Each trial lasted for 18 seconds, allowing it to integrate into the 1.8G and 0G phases of the flight. Each participant performed 15 parabolas, i.e. 15 trials in 1G, 1.8G and 0G. Participants were instructed to prioritize the PACMAN task, aiming for a high score and to consider the sounds of the oddball paradigm as secondary. All participants received Scopolamine (anti-nausea medication) right before the flight. The dose of the medication was calculated individually by the flight physicians taking into account the body weight and experience (novice or experienced flyer) of each participant. Throughout the flight, the participants were sitting and safely secured to an aircraft seat avoiding uncontrolled flying and loss of orientation, but allowing the participants to experience the sensation of microgravity. During the whole flight, the participants were observed by an operator to avoid external disturbances and to provide reassurance to the participants during the phases of altered gravity. All participants went through the experimental protocol 24 hours before the start as a familiarization process. EEG data collection Each participant wore a 32-channel EEG cap (actiCap-32Ch, Brain Products GmbH, Munich, Germany) that was custom-fitted to their unique head size and arranged according to the classic 10–20 configuration. To ensure a consistent data acquisition, each electrode was referenced to a reference electrode positioned within the triangle formed by FP1, FP2, and Fz, with the ground electrode placed adjacent to it. To facilitate optimal signal transmission, all electrodes were filled with Electro-Gel™ (Electro-Cap International, USA). To maintain impedance levels below ten kilo-Ohms [kΩ] throughout the flight, the electrodes were regularly refilled with gel. Before being stored, EEG data were subjected to analogue-to-digital conversion and amplification using Brain Vision amplifier and RecView software (Brain Products GmbH, Munich, Germany). Data analysis EEG data preprocessing and analysis were performed using Brain Vision Analyzer 2.2 (Brain Products GmbH, Munich, Germany). Data that provide information about the participants’ performance, such as error rate and reaction time, were analysed using self-created scripts in Python 3 (Python Software Foundation, https://www.python.org/ 18 ) in Jupyter Notebooks 19 . EEG Analysis After filtering the EEG signals with low-pass and high-pass techniques, a frequency range from 0.5 to 30 Hz was retained for the analyses (time constant of 0.318 s and 48 dB/octave). Individual channels exceeding 10 kΩ of impedance were interpolated using splines (order: 4, maximum degree of Legendre polynomials: 10, standard lambda: 1E-05). To detect and remove blinks and horizontal eye movements, independent component analysis was implemented after a visual inspection of the data set. Current cortical density After the initial segmentation into 1G and the respective gravity level, followed by division into 4s intervals, an automatic artefact rejection was conducted (gradient < 50 µV; max/min amplitude − 200 to 200 µV; lowest allowed activity in intervals 0.5µV). As scalp potentials vary in volume, based on reference location, the data was converted into reference-free current source density (CSD) maps for every participant (order of splines: 4; maximum degree of Legendre polynomials: 10; lambda 1e-5). The CSD consists of the voltage values of individual electrodes in addition to the current source density recorded at these electrodes. Using the integrated LORETA module in the Brain Vision Analyzer 20 , 21 , cortical current densities in the frontal, parietal, and occipital lobes and the region supplied by the middle cerebral artery (MCA) were determined across each 4-second recording interval. Cortical current density is defined as the electric current triggered by neural activity per unit area of cross-section. In general, the unit is microvolts per square millimetre (electrical current in a 2-dimensional area) but in a voxel-based analysis, this value needs to be squared so that the unit is squared microvolts per millimetre to the power of 4. Event-related potentials ERPs not only reflect how sensory information is perceived and processed but also indicate higher cognitive processes 22 . In the field of behavioural control processes, which encounters stimuli evaluation, selective attention, and conscious perception, two ERP components, N200 and P300, are important 23 , 24 . The appearance of ERPs is dependent on the occurrence of a specific stimulus, whether it be sensory, visual, or auditory, unlike that of spontaneous EEG. Due to that time-specific character, the data set was segmented based on the relevant stimulus, which was the appearance of target and standard tones of the oddball paradigm from − 200 to 800 ms. Following that segmentation, data were corrected for artefacts (gradient < 50 µV; max/ min amplitude − 250 to 250 µV; lowest allowed activity in intervals 0.5 µV) and baseline corrected (-200 to 0 ms). On average, there were around 84 stimuli for the target sound, and around 360 stimuli for the standard sound for each participant. Subsequently, the averaged ERPs for all participants under both, the 1G and partial gravity conditions and across all electrodes were computed and a reference-free CSD map was obtained from all ERP waveforms using spline interpolation (order of splines: 4, maximum degree of Legendre polynomials: 10, default lambda: 1e-5). To determine the temporal occurrence (latency) and magnitude of the ERP amplitude, a peak algorithm was applied to the data sets. The time window for determining the parameters was 90–200 ms for the first negative wave. 100–250 ms for the consecutive negative wave and 150–300 ms for the negative wave over the fronto-central part. Statistics Statistics were performed using self-written scripts in R (2022.12.0, Posit Software, PBC). All data sets were tested for normality using the Shapiro-Wilk test before further statistical calculation. Further statistical evaluation was carried out with two-way repeated measures analysis of variance (RM ANOVA) or the corresponding, non-parametric procedure (Friedman test), depending on the outcome of the Shapiro-Wilk test. Comparisons of reaction time (RT) was performed using either the Friedman test or a one-way repeated measures ANOVA with the within-group factors of gravity (1G/1.8G/0G). Comparison of the accuracy/percentage of errors (ER) was performed using either the Friedman test or a two-way repeated measures ANOVA with the within-group factors of gravity (1G/1.8G/0G) and experiment (target or standard sound of the Oddball paradigm). Where appropriate, a post hoc analysis with Bonferroni correction was carried out. Additionally, as this study was conducted with a small sample size and the observation of outlier, the non-parametric version of a two-factorial repeated measures ANOVA, the ld.f2 function with Wald-type (WTS) of the nparLD package in R, was used 25 – 27 . This package refers to the results of the studies by Akritas and Brunner 28 . Here, the relative treatment effects are defined in relation to the distributions of the variables measured in the experiment. This was the case for the statistical calculation of the electrocortical activity with the within-factors gravity and Regions of Interest (ROI) . If this package provided a significant main effect of either one factor or an interaction effect of both factors, a Wilcoxon test was performed as a post-hoc test with Bonferroni correction. To statistically examine the amplitude and latency of the observed event-related potentials, the data were evaluated with a two-factor analysis of variance (ANOVA) or the corresponding, non-parametric procedure (ld.f2 function with Wald-type). If statistical significance was determined by the procedures, a post hoc test with Bonferroni correction was carried out. The level of significance was set to p < 0.05. Data in this manuscript are presented as mean and standard deviation. Results The data for the electrocortical activity were not normally distributed and therefore the ld.f2 model with the Wald-type (WTS) was calculated and showed no significant interaction effect of the factors ROI and gravity (Statistic = 4.665, p = .587, Fig. 2 , Fig. 3 , Fig. 4 , Table 1 ). Table 1 Cortical current density averaged over 25 parabolas for each gravity level. Displayed are means ± standard deviation. FRONT frontal lobe, PAR parietal lobe, OCC occipital lobe, MCA middle cerebral artery Electrocortical Activity FRONT PAR OCC MCA 0G 0.016 ± 0.011 0.034 ± 0.030 0.048 ± 0.035 0.018 ± 0.010 1G 0.014 ± 0.010 0.027 ± 0.017 0.041 ± 0.024 0.015 ± 0.008 1.8G 0.014 ± 0.011 0.024 ± 0.019 0.040 ± 0.032 0.017 ± 0.013 Statistical test Ld.f2 model with Wald test p-value n.s. The Friedman test regarding the participants' reaction time did not show a significant outcome (χ 2 : 4.333, p = .115, Fig. 5 , Table 2 ). Table 2 Behavioural Performance like reaction time of the answers for the target sound for the oddball. Error Rate for the target and standard sound of the oddball. Displayed are means ± standard deviation. Behavioural Performance Error Rate [%] Reaction Time [ms] Target Sound Standard Sound Target Sound 0G 26.863 ± 17.703 2.271 ± 1.370 592.015 ± 116.923 1G 16.406 ± 11.146 1.811 ± 1.421 577.985 ± 115.775 1.8G 19.722 ± 12.286 2.595 ± 1.264 576.434 ± 115.226 Statistical test Repeated measure ANOVA Friedman Test p-value Interaction Effect of Gravity and Error Rate : p = .003 * n.s. (χ² = 4.333, p = .115) Post-hoc (t-test with Bonferroni correction) Target Sound : 0G vs. 1.8G : p = .028 * 0G vs. 1G : p = .009 ** The two-way repeated measures ANOVA for the participants' accuracy showed a significant interaction effect between the different gravity levels and the Oddball paradigm on the error rate of the participants (F (34,2) = 8.986, p = .003, Fig. 6 , Table 2 ). Therefore, the effect of gravity was analysed for the different sounds of the Oddball paradigm. The effect of gravity was significant for 0G compared to 1.8G (p = .009) and 1G (p = .028). The standard and target tones of the auditory oddball paradigm elicited a negative and a consecutive positive wave under the posterior electrode P7 and a negative wave over the fronto-central part, which was most pronounced under electrode C3. A two-way repeated measure ANOVA was conducted to evaluate the effect of different gravity levels for the different sounds of an auditive Oddball paradigm on the amplitude of the observed N1-P2 complex. The data was not normally distributed and therefore the ld.f2 model with the Wald-type (WTS) was calculated and showed no significant interaction effect of the factors Experiment and Gravity (Statistic: 3.543, p = .170, Fig. 7 , Fig. 8 , Table 3 ). Table 3 Amplitude of the N1-P2 complex of event-related potentials for the Oddball paradigm. Displayed are means ± standard deviation. Event-Related Potentials N1-P2 complex Standard Sound Target Sound Amplitude [µV] Amplitude [µV] 0G 20.843 ± 14.642 23.924 ± 11.193 1.8G 16.966 ± 12.390 22.316 ± 12.066 1G 19.535 ± 16.540 24.727 ± 11.713 Statistical test Ld.f2 model with Wald test p-value n.s Table 4 Amplitude and Latency of the event-related potential N200 for the Oddball paradigm. Displayed are means ± standard deviation. Event-Related Potentials N200 Latency [ms] Amplitude [µV] Standard Sound Target Sound Standard Sound Target Sound 0G 203.333 ± 27.233 206.889 ± 26.887 -7.502 ± 7.125 -8.604 ± 5.434 1.8G 208.000 ± 19.060 202.556 ± 26.584 -8.085 ± 7.442 -8.904 ± 6.569 1G 201.667 ± 24.841 210.889 ± 30.910 -8.300 ± 8.688 -8.524 ± 5.461 Statistical test Ld.f2 model with Wald test Ld.f2 model with Wald test p-value n.s n.s Discussion This study examines the impact of different gravity levels on neurocognitive performance and electrocortical activity while executing a dual-task with a continuous primary task. The investigation was conducted under three different gravity conditions: 1G (representative of Earth's gravity), 1.8G (hypergravity), and 0G (weightlessness). The analysis of electrocortical activity revealed no statistically significant differences between the gravity levels in all four brain lobes and especially not in the frontal lobe, which is known to be responsible for executive function and cognitive evaluation. This result is in contrast to previous studies that showed a significant reduction in brain activity in microgravity when two discrete tasks were combined in a dual task 29 . However, the results are consistent with those from hypergravity and partial gravity, which showed no statistically significant reduction in brain activity in the frontal lobe 16 , 17 Despite no gravity-dependent changes in reaction time could be observed, the error rate was found to be significantly higher in 0G compared to 1.8G and 1G. These observations diverge from those of previous studies that employed a discrete primary task. In these studies, the reaction time was observed to be shorter in microgravity, while the error rate remained unaltered 6 . In contrast, no differences were observed in the behavioural data in a discrete primary task in hypergravity and partial weightlessness 16 , 17 . The electrophysiological data from the current study demonstrated a pronounced negative peak after approximately 100 ms, followed by a positive deflection after around 200 ms. This phenomenon is known as the N1-P2 complex and has been previously described by Wollseiffen et al. (2016), who observed it in conjunction with a cognitive task comprising a single discrete component 7 . The absence of the P300 component, which typically occurs in dual tasks with a discrete primary task, is noteworthy. This absence may be indicative of the fact that the continuous task employed in the current study was more demanding than the mental arithmetic task that had been previously investigated 16 , 17 , 29 . It is possible that this was perceived as a single, uninterrupted task. Here, the N1-P2 complex may be classified as an early event-related potential (ERP) which is closely associated with perceptual processing. In contrast, later ERPs, such as the P300 component, are associated with cognitive processes 22 , 30 . It is hypothesised that the continuous primary task in the study may have limited the cognitive processing of the different tones of the oddball paradigm, indicating the absence of a P300 component. This suggests that the secondary auditory stimuli were not fully processed. The use of cognitive resources, known as cognitive workload, is based on two theories, the limited capacity theory and the multiple resource theory, and emphasises that the human brain only has a limited capacity to absorb and process information. They explain the relationship between the complexity of a task and performance, which decreases as the task becomes more complex. A notable finding of this study is that both sounds of the oddball paradigm elicited the same ERP components in the current dual task, which is in contrast with the results of studies that employed a discrete primary task 6 , 16 , 17 . It leads to the suggestion, that the majority of cognitive resources were allocated to the PACMAN game and that the auditory stimuli of the oddball paradigm were no longer perceived in a differentiated manner. It may therefore be the case that the secondary task of the dual task was not adequately assessed, either because it was ignored or it was processed with limited cognitive resources. Prior research, including that of Allison and Polich (2008), has demonstrated that dual tasks typically necessitate a substantial allocation of cognitive resources and that the additional demand of a second task is challenging to quantify. It is frequently challenging to ascertain which element of the dual task participants are concentrating on 31 . The reduced amplitude values of the event-related potentials observed in this study in comparison to the results of Wollseiffen et al. (2016) may be indicative of the PACMAN task being perceived as more complex and demanding than the discrete mental arithmetic task. Another crucial element of this study is the observation of the N200 component, which may be interpreted as a Mismatch Negativity (MMN), described by Näätänen et al. 32 – 34 in a dichotomic-listening study. The MMN is hypothesised to reflect an automatic neural mismatch process occurring between the input of a deviant stimulus and a sensory memory trace. Similarly, Folstein et al. (2018) distinguished the visual N2 from the auditory MMN, noting that the MMN responds to auditory deviants even when there is no focal attention to the stimuli 35 . It also appears to occur independently of task complexity and cognitive load 36 , 37 . The combination of the results suggests that a continuous primary task in the context of a discrete secondary task requires a higher cognitive workload than a discrete primary task. This results in fewer resources being available for the secondary task. Understanding how the human brain allocates available cognitive resources, especially during dual-task situations, is of major importance to astronauts and ground personnel who are responsible for prioritising the relevant tasks during space missions. Generally, people under stress often find themselves in situations where they have to perform two tasks simultaneously, or are faced with a critical situation and have to perform and react to a sudden secondary task. For example, during the docking manoeuvre of the Soyuz capsule to the ISS. The astronauts must be able to manually dock the capsule to the ISS with six degrees of freedom and at the same time react to sounds from the spacecraft. Overall, the present study shows that examining ERPs in the context of dual-task performance can provide valuable insights into cognitive processing and workload management. The results highlight the need for further research into cognitive workload and attentional focus during dual-task performance in complex environments to improve overall performance and safety. Declarations Competing Interests: All authors declare no financial or non-financial competing interests. Consent to participate: Informed consent was obtained from all individual participants included in the study. Ethical Standards: The study's experimental design was approved by the Research Ethics Committee of the German Sport University Cologne and the University of Caen in accordance with the Declaration of Helsinki. Author contributions: All authors contributed to the study's conception and design. Experiment preparation, data collection and analysis were performed by C.B, P.W., L.P. and S.S. The first draft was written by C.B. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgement We would like to thank NOVESPACE for their great support on Earth and in space as well as the participants for their valuable time. The study was funded by the German Aerospace Center DLR (50WB2020). Data Availability Statement: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References ESA. Roadmaps. Available at https://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf . (2022). Genik, R. J., Green, C. C., Graydon, F. X. & Armstrong, R. E. Cognitive avionics and watching spaceflight crews think: generation-after-next research tools in functional neuroimaging. Aviation, space, and environmental medicine 76, B208-12 (2005). Carey, W. Exploration of the moon as preparation for mars - the human robotic partnership (Noordwijk, 2012). Koppelmans, V. et al. Study protocol to examine the effects of spaceflight and a spaceflight analog on neurocognitive performance: extent, longevity, and neural bases. BMC neurology 13, 205; 10.1186/1471-2377-13-205 (2013). Kozlovskaya, I. B., Kreidich, Y., Oganov, V. S. & Koserenko, O. P. Pathophysiology of motor functions in prolonged manned space flights. Acta astronautica 8, 1059–1072; 10.1016/0094-5765(81)90079-5 (1981). Wollseiffen, P. et al. Neurocognitive performance is enhanced during short periods of microgravity-Part 2. Physiology & behavior 207, 48–54; 10.1016/j.physbeh.2019.04.021 (2019). Wollseiffen, P. et al. Neuro-cognitive performance is enhanced during short periods of microgravity. Physiology & behavior 155, 9–16; 10.1016/j.physbeh.2015.11.036 (2016). Sieber, M., Hanke, W. & Kohn, F. P. M. Modification of Membrane Fluidity by Gravity. OJBIPHY 04, 105–111; 10.4236/ojbiphy.2014.44012 (2014). Kohn, F. P. M. & Ritzmann, R. Gravity and neuronal adaptation, in vitro and in vivo-from neuronal cells up to neuromuscular responses: a first model. European biophysics journal: EBJ 47, 97–107; 10.1007/s00249-017-1233-7 (2018). Isreal, J. B., Chesney, G. L., Wickens, C. D. & Donchin, E. P300 and tracking difficulty: evidence for multiple resources in dual-task performance. Psychophysiology 17, 259–273; 10.1111/j.1469-8986.1980.tb00146.x (1980). Kasper, R. W., Cecotti, H., Touryan, J., Eckstein, M. P. & Giesbrecht, B. Isolating the neural mechanisms of interference during continuous multisensory dual-task performance. Journal of cognitive neuroscience 26, 476–489; 10.1162/jocn_a_00480 (2014). Baldwin, C. L. Auditory Cognition and Human Performance (CRC Press, 2016). Basil, M. D. Multiple Resource Theory. In Encyclopedia of the Sciences of Learning , edited by N. M. Seel (Springer US, Boston, MA, 2012), pp. 2384–2385. Wickens, C. D. The Structure of Attentional Resources. In Attention and Performance , edited by Nickerson R.S. 1st ed. (New York, 1981). Luck, S. J. (ed.). The Oxford handbook of event-related potential components . 1st ed. (Oxford Univ. Press, Oxford, 2013). Badalì, C., Wollseiffen, P. & Schneider, S. Under pressure-the influence of hypergravity on electrocortical activity and neurocognitive performance. Experimental brain research 241, 2249–2259; 10.1007/s00221-023-06677-8 (2023). Badalì, C., Wollseiffen, P. & Schneider, S. Shades of gravity - effects of planetary gravity levels on electrocortical activity and neurocognitive performance. Brain structure & function 229, 1265–1277; 10.1007/s00429-024-02803-6 (2024). van Rossum, G. & Drake, F. L. Python 3. Reference manual (SohoBooks, United States, 2009). Kluyver, T. et al. Jupyter Notebooks – a publishing format for reproducible computational workflows. Positioning and Power in Academic Publishing: Players, Agents and Agendas. (2016). Grech, R. et al. Review on solving the inverse problem in EEG source analysis. Journal of neuroengineering and rehabilitation 5, 25; 10.1186/1743-0003-5-25 (2008). Pascual-Marqui, R. D. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods and findings in experimental and clinical pharmacology 24 Suppl D, 5–12 (2002). Duncan, C. C. et al. Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 120, 1883–1908; 10.1016/j.clinph.2009.07.045 (2009). Helfrich, R. F. & Knight, R. T. Cognitive neurophysiology: Event-related potentials. Handbook of clinical neurology 160, 543–558; 10.1016/B978-0-444-64032-1.00036 – 9 (2019). Patel, S. H. & Azzam, P. N. Characterization of N200 and P300: selected studies of the Event-Related Potential. International journal of medical sciences 2, 147–154; 10.7150/ijms.2.147 (2005). Brunner, E. & Langer, F. Nichtparametrische Analyse longitudinaler Daten . 2014th ed. (Oldenbourg Wissenschaftsverlag, Berlin, Boston, 1998). Feys, J. Nonparametric Tests for the Interaction in Two-way Factorial Designs Using R. The R Journal 8, 367; 10.32614/RJ-2016-027 (2016). Noguchi, K., Gel, Y. R., Brunner, E. & Konietschke, F. nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments. J. Stat. Soft. 50; 10.18637/JSS.V050.I12 (2012). Akritas, M. G. & Brunner, E. A unified approach to rank tests for mixed models. Journal of Statistical Planning and Inference 61, 249–277; 10.1016/S0378-3758(96)00177-2 (1997). Klein, T. et al. The influence of microgravity on cerebral blood flow and electrocortical activity. Experimental brain research 237, 1057–1062; 10.1007/s00221-019-05490-6 (2019). Solís-Marcos, I. & Kircher, K. Event-related potentials as indices of mental workload while using an in-vehicle information system. Cogn Tech Work 21, 55–67; 10.1007/s10111-018-0485-z (2019). Allison, B. Z. & Polich, J. Workload assessment of computer gaming using a single-stimulus event-related potential paradigm. Biological psychology 77, 277–283; 10.1016/j.biopsycho.2007.10.014 (2008). Näätänen, R., Gaillard, A. W. & Mäntysalo, S. Early selective-attention effect on evoked potential reinterpreted. Acta psychologica 42, 313–329; 10.1016/0001-6918(78)90006-9 (1978). Näätänen, R., Pakarinen, S., Rinne, T. & Takegata, R. The mismatch negativity (MMN): towards the optimal paradigm. Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 115, 140–144; 10.1016/j.clinph.2003.04.001 (2004). Alho, K., Sams, M., Paavilainen, P., Reinikainen, K. & Näätänen, R. Event-related brain potentials reflecting processing of relevant and irrelevant stimuli during selective listening. Psychophysiology 26, 514–528; 10.1111/j.1469-8986.1989.tb00704.x (1989). Folstein, J. R. & van Petten, C. Influence of cognitive control and mismatch on the N2 component of the ERP: a review. Psychophysiology 45, 152–170; 10.1111/j.1469-8986.2007.00602.x (2008). Muller-Gass, A., Macdonald, M., Schröger, E., Sculthorpe, L. & Campbell, K. Evidence for the auditory P3a reflecting an automatic process: elicitation during highly-focused continuous visual attention. Brain research 1170, 71–78; 10.1016/j.brainres.2007.07.023 (2007). Ghani, U., Signal, N., Niazi, I. K. & Taylor, D. ERP based measures of cognitive workload: A review. Neuroscience and biobehavioral reviews 118, 18–26; 10.1016/j.neubiorev.2020.07.020 (2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5136580","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":404515896,"identity":"3be9c95d-8ec4-428c-a99d-9c5ad2ff940e","order_by":0,"name":"Constance Badalì","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYFACHhCy4OFnSGAD8hIYGNghgoS0SPBINsC0MBOphcHgALFa+Bt4D354UyMhY3w8/dnDHwxpcvzMvAcY3lTg1iJxgC9Zcs4xCR6zM2/MjXkYcowlm/kSGOecwa3FgIHHQJqHDajlRg6bNOO/isQNh3kMmHnb8Gox/s3zT4LHeEb6M8kfDBWJ+8Fa/uHVYibN2ybBYyCRYCYBdFjiBmaQlgY8fjnMl2Y5t0+CR+LMGzNpHoY0YwmgLQfnHMOthb+99/CNN99s7PnbwQ5LluNv7zF88KYGtxZwLGCAA3g0jIJRMApGwSggAgAAFsRCRGNVxgMAAAAASUVORK5CYII=","orcid":"","institution":"German Sport University Cologne","correspondingAuthor":true,"prefix":"","firstName":"Constance","middleName":"","lastName":"Badalì","suffix":""},{"id":404515897,"identity":"3d067ff0-b519-4953-b186-8c398bdffbb0","order_by":1,"name":"Petra Wollseiffen","email":"","orcid":"","institution":"German Sport University Cologne","correspondingAuthor":false,"prefix":"","firstName":"Petra","middleName":"","lastName":"Wollseiffen","suffix":""},{"id":404515898,"identity":"bfa355ca-90cd-402e-8473-02db599debc3","order_by":2,"name":"Lennart Puck","email":"","orcid":"","institution":"FZI Research Centre for Information Technology","correspondingAuthor":false,"prefix":"","firstName":"Lennart","middleName":"","lastName":"Puck","suffix":""},{"id":404515899,"identity":"d56f1318-124a-4263-bdb5-99d3d3cc7285","order_by":3,"name":"Stefan Schneider","email":"","orcid":"","institution":"German Sport University Cologne","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Schneider","suffix":""}],"badges":[],"createdAt":"2024-09-23 08:50:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5136580/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5136580/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75488328,"identity":"04dca459-e4c5-4b24-97c7-97fec5889329","added_by":"auto","created_at":"2025-02-05 06:51:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46872,"visible":true,"origin":"","legend":"\u003cp\u003eThe neurocognitive task involved the traditional PACMAN game in combination with a classical auditory oddball paradigm, which participants had to perform simultaneously during 1G, 1.8G and 0G phases of a parabolic flight. This task was repeated in 25 consecutive parabolas for each of the specified gravity levels on a single flight day.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/156594bfcbc7ebb66a1e3b50.jpg"},{"id":75487791,"identity":"117baac7-30b3-4b96-92d1-5ecabb7ba7f5","added_by":"auto","created_at":"2025-02-05 06:43:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40851,"visible":true,"origin":"","legend":"\u003cp\u003eCortical current density averaged over 25 parabolas for each gravity level in 0G, 1.8G and 1G. Displayed are means ± standard deviation. FRONT frontal lobe, PAR parietal lobe, OCC occipital lobe, MCA middle cerebral artery\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/80c46e5d72c9cced73cbc991.jpg"},{"id":75487793,"identity":"2c0e8e6c-b364-4bca-80f0-78f80cd4d135","added_by":"auto","created_at":"2025-02-05 06:43:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":110116,"visible":true,"origin":"","legend":"\u003cp\u003eTopographical map in steps of 20 ms ranging from 60 ms – 380 ms after the occurrence of a standard sound in an auditory oddball paradigm over the scalp for 1G, 1.8G and 0G.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/141898a51e2e2ba2f0f30afa.jpg"},{"id":75489464,"identity":"e6d8bd67-0352-47a2-88f6-03104194fd9a","added_by":"auto","created_at":"2025-02-05 06:59:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":116195,"visible":true,"origin":"","legend":"\u003cp\u003eTopographical map in steps of 20 ms ranging from 60 ms – 380 ms after the occurrence of a target sound in an auditory oddball paradigm over the scalp for 1G, 1.8G and 0G.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/0398eb998b521a89089df291.jpg"},{"id":75487797,"identity":"b5ca8052-f4f4-4d8d-a4e6-7ea02c72d600","added_by":"auto","created_at":"2025-02-05 06:43:49","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":17528,"visible":true,"origin":"","legend":"\u003cp\u003eReaction Time for the target sound for the Oddball paradigm in 0G, 1.8G and 1G. Displayed are means ± standard deviation\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/353bf1f5a8187b46c4b865f4.jpg"},{"id":75488332,"identity":"37264d0e-6f6e-4c2e-a19d-a910b81a85d2","added_by":"auto","created_at":"2025-02-05 06:51:49","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":19352,"visible":true,"origin":"","legend":"\u003cp\u003eError Rate for the standard and target sound for the Oddball paradigm in 0G, 1.8G and 1G. Displayed are means ± standard deviation\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/f6b4500d9006695d2f3923dd.jpg"},{"id":75488331,"identity":"14e722fe-9f2d-4f53-87b5-83ba4ea3be78","added_by":"auto","created_at":"2025-02-05 06:51:49","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":34226,"visible":true,"origin":"","legend":"\u003cp\u003eAmplitude of the N1-P2 complex, elicited by the standard and target sound of the Oddball paradigm in 0G, 1.8G and 1G. Displayed are means ± standard deviation.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/14e55eb3676093113d44b0e2.jpg"},{"id":75487810,"identity":"4d88f2df-22bb-4f52-9153-39496e1a03a0","added_by":"auto","created_at":"2025-02-05 06:43:50","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":56663,"visible":true,"origin":"","legend":"\u003cp\u003eAveraged N1-P2 complex across electrode P7 after the occurrence of a target sound (a) and standard sound (b) of an auditory Oddball paradigm.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/9b6fef57947a30f63d7f7345.jpg"},{"id":75487795,"identity":"04d7f052-9a6f-4598-b812-a653700ae388","added_by":"auto","created_at":"2025-02-05 06:43:49","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":52373,"visible":true,"origin":"","legend":"\u003cp\u003eLatency (a) and Amplitude (b) of the negative event-related potential, elicited by the standard and target sound of the Oddball paradigm in 0G, 1.8G and 1G. Displayed are means ± standard deviation.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/d90e9f22be20b1d42e5281c1.jpg"},{"id":75487799,"identity":"4748fca5-2bdc-484e-b6b6-929542a4d7b4","added_by":"auto","created_at":"2025-02-05 06:43:49","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":49249,"visible":true,"origin":"","legend":"\u003cp\u003eAveraged negative event-related potential across electrode C3 after the occurrence of a target sound (a) and standard sound (b) of an auditory Oddball paradigm.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/a39e9febb36827b82a299df7.jpg"},{"id":82107629,"identity":"eac02aea-4d0f-4c17-a36b-5397bd9ac360","added_by":"auto","created_at":"2025-05-06 22:16:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1373619,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5136580/v1/3ac84f9d-6a36-4297-816e-af282529d8fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"sPACeMAN – Assessing Neurocognitive Performance and Electrocortical Activity Across Diverse Gravity Levels Using a Gamification Approach","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSince space missions regularly require astronauts to perform complex, critical tasks in challenging environments, maintaining cognitive performance is of great importance. In situations of increased stress, cognitive processes of executive functions and decision-making can be negatively affected. Such impairment presents a notable risk to missions where the ability to perform complex procedures safely and efficiently is critical. The training and development of routines within such procedures are not only important for mission success but possibly allow astronauts to free up or reallocate cognitive resources to adequately cope with unexpected tasks. The relevance of monitoring and maintaining cognitive performance in space is also embedded in ESAs strategic roadmaps \u003csup\u003e1\u003c/sup\u003e(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf\u003c/span\u003e\u003cspan address=\"https://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and of major importance when designing and applying countermeasures to increase mission success and safety. It is advisable to combine physiological as well as psychological data to monitor the neuro-psychological status during a mission\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e and provide significant physical and mental crew health and performance data\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the last decade, several studies have investigated human behaviour and neurocognitive performance in microgravity, e.g. during space flights or experimental parabolic flights \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Despite anecdotical reports of astronauts and cosmonauts, there seems to be a positive impact of weightlessness on cortical processing \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese results are in line with in vitro data from Sieber et al. (2014) reporting an increased excitability of neurons under microgravity\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Summarizing in vivo and in vitro experiments, Kohn and Ritzmann (2018) suggest a reduced membrane viscosity caused by increased lateral pressure on neurons in microgravity. This leads to a reduction in the open-state probability of ion channels, which results finally in a slightly depolarized resting membrane potential of the cell\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Studies already show that cells under external pressure tend to have reduced neuronal excitability\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. It is therefore assumed, that the well-reported increase in blood volume to the brain during microgravity increases intracranial pressure in the brain and might be the cause for this cascade of physiological changes.\u003c/p\u003e \u003cp\u003eThe capacity of the human mind to perform cognitive tasks is contingent upon the ability to allocate the requisite and available brain resources efficiently and effectively to the tasks at hand. It has been demonstrated that the utilisation of available brain resources is dependent on the challenge presented by the tasks to be completed\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The term \"cognitive workload\" can be used to describe the concept of brain resource utilization\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. A neurophysiological representation of this can be observed in the amplitude and latency of event-related potentials (ERP), with the amplitude of ERPs demonstrating a correlation with the amount of attentional resources allocated to a given task\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent results observed in microgravity show higher amplitudes of ERPs elicited by a discrete primary and secondary task in hypergravity without differences in behavioral data\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This is also true for the cognitive performance data under partial gravity (Moon/Mars) and for differences in ERP amplitude and latency, which could lead to the suggestion that there is a threshold for the influence of lower gravity on neurocognitive performance \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite these findings, the studies were limited by (1) the small sample size, (2) the limited number of experimental parabolas and (3) the use of a non-continuous primary task in interfering with a classical oddball paradigm.\u003c/p\u003e \u003cp\u003eAccordingly, a continuous navigation task (Pac-Man) was selected as the primary task with a non-continuous classical auditive oddball paradigm in this study, as it provides a high level of intrinsic motivation (gamification). Given the game-like and more challenging character of the continuous primary task, it is hypothesized that performance under 0G is increased compared to 1G and 1.8G and that this is simultaneously mirrored by a reduction of the elicited ERP waves during the experiment.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Procedure\u003c/h2\u003e \u003cp\u003eParabolic flights take place on board the A310 ZeroG from Merignac International Airport in Bordeaux (F), led by the European Space Agency (ESA) and the German Aerospace Centre (DLR). Each parabola consists of four phases, characterised by shifts in gravity from Earth gravity to hypergravity, microgravity, back to hypergravity and returning to Earth gravity. Every campaign includes three flight days, with 30 experimental parabolas per day. Over three campaigns conducted from September 2023 to June 2024, data were collected from 18 participants (12 males, 6 females) who executed the experiment in normal gravity (1G), hypergravity (1.8G) and microgravity (0G). All participants and investigators underwent clinical examinations and provided informed consent. The study's experimental design was approved by the Research Ethics Committee of the German Sport University Cologne and the University of Caen following the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperiment\u003c/h3\u003e\n\u003cp\u003eThe neurocognitive task consisted of a continuous navigation task (PACMAN) and a classical auditory oddball task. While playing PACMAN participants heard randomised tones through wired noise-cancelling headphones (BOSE QuietComfort 20). These tones included either target tones (high tones) or standard tones (low tones). The low-pitched tones made up 70% of all tones and were to be disregarded, while the high-pitched tones, which made up 30% of all tones, prompted participants to quickly press the space bar with the left hand on a keyboard on their lap. PACMAN was played using the arrow keys with the right hand.\u003c/p\u003e \u003cp\u003eEach trial lasted for 18 seconds, allowing it to integrate into the 1.8G and 0G phases of the flight. Each participant performed 15 parabolas, i.e. 15 trials in 1G, 1.8G and 0G.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e Participants were instructed to prioritize the PACMAN task, aiming for a high score and to consider the sounds of the oddball paradigm as secondary. All participants received Scopolamine (anti-nausea medication) right before the flight. The dose of the medication was calculated individually by the flight physicians taking into account the body weight and experience (novice or experienced flyer) of each participant. Throughout the flight, the participants were sitting and safely secured to an aircraft seat avoiding uncontrolled flying and loss of orientation, but allowing the participants to experience the sensation of microgravity. During the whole flight, the participants were observed by an operator to avoid external disturbances and to provide reassurance to the participants during the phases of altered gravity. All participants went through the experimental protocol 24 hours before the start as a familiarization process.\u003c/p\u003e\n\u003ch3\u003eEEG data collection\u003c/h3\u003e\n\u003cp\u003eEach participant wore a 32-channel EEG cap (actiCap-32Ch, Brain Products GmbH, Munich, Germany) that was custom-fitted to their unique head size and arranged according to the classic 10\u0026ndash;20 configuration. To ensure a consistent data acquisition, each electrode was referenced to a reference electrode positioned within the triangle formed by FP1, FP2, and Fz, with the ground electrode placed adjacent to it. To facilitate optimal signal transmission, all electrodes were filled with Electro-Gel\u0026trade; (Electro-Cap International, USA). To maintain impedance levels below ten kilo-Ohms [kΩ] throughout the flight, the electrodes were regularly refilled with gel. Before being stored, EEG data were subjected to analogue-to-digital conversion and amplification using Brain Vision amplifier and RecView software (Brain Products GmbH, Munich, Germany).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eEEG data preprocessing and analysis were performed using Brain Vision Analyzer 2.2 (Brain Products GmbH, Munich, Germany). Data that provide information about the participants\u0026rsquo; performance, such as error rate and reaction time, were analysed using self-created scripts in Python 3 (Python Software Foundation, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.python.org/\u003c/span\u003e\u003cspan address=\"https://www.python.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003csup\u003e18\u003c/sup\u003e) in Jupyter Notebooks\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEEG Analysis\u003c/h3\u003e\n\u003cp\u003eAfter filtering the EEG signals with low-pass and high-pass techniques, a frequency range from 0.5 to 30 Hz was retained for the analyses (time constant of 0.318 s and 48 dB/octave). Individual channels exceeding 10 kΩ of impedance were interpolated using splines (order: 4, maximum degree of Legendre polynomials: 10, standard lambda: 1E-05). To detect and remove blinks and horizontal eye movements, independent component analysis was implemented after a visual inspection of the data set.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCurrent cortical density\u003c/h2\u003e \u003cp\u003eAfter the initial segmentation into 1G and the respective gravity level, followed by division into 4s intervals, an automatic artefact rejection was conducted (gradient\u0026thinsp;\u0026lt;\u0026thinsp;50 \u0026micro;V; max/min amplitude \u0026minus;\u0026thinsp;200 to 200 \u0026micro;V; lowest allowed activity in intervals 0.5\u0026micro;V). As scalp potentials vary in volume, based on reference location, the data was converted into reference-free current source density (CSD) maps for every participant (order of splines: 4; maximum degree of Legendre polynomials: 10; lambda 1e-5). The CSD consists of the voltage values of individual electrodes in addition to the current source density recorded at these electrodes. Using the integrated LORETA module in the Brain Vision Analyzer \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, cortical current densities in the frontal, parietal, and occipital lobes and the region supplied by the middle cerebral artery (MCA) were determined across each 4-second recording interval. Cortical current density is defined as the electric current triggered by neural activity per unit area of cross-section. In general, the unit is microvolts per square millimetre (electrical current in a 2-dimensional area) but in a voxel-based analysis, this value needs to be squared so that the unit is squared microvolts per millimetre to the power of 4.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEvent-related potentials\u003c/h3\u003e\n\u003cp\u003eERPs not only reflect how sensory information is perceived and processed but also indicate higher cognitive processes \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In the field of behavioural control processes, which encounters stimuli evaluation, selective attention, and conscious perception, two ERP components, N200 and P300, are important \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The appearance of ERPs is dependent on the occurrence of a specific stimulus, whether it be sensory, visual, or auditory, unlike that of spontaneous EEG. Due to that time-specific character, the data set was segmented based on the relevant stimulus, which was the appearance of target and standard tones of the oddball paradigm from \u0026minus;\u0026thinsp;200 to 800 ms. Following that segmentation, data were corrected for artefacts (gradient\u0026thinsp;\u0026lt;\u0026thinsp;50 \u0026micro;V; max/ min amplitude \u0026minus;\u0026thinsp;250 to 250 \u0026micro;V; lowest allowed activity in intervals 0.5 \u0026micro;V) and baseline corrected (-200 to 0 ms). On average, there were around 84 stimuli for the target sound, and around 360 stimuli for the standard sound for each participant. Subsequently, the averaged ERPs for all participants under both, the 1G and partial gravity conditions and across all electrodes were computed and a reference-free CSD map was obtained from all ERP waveforms using spline interpolation (order of splines: 4, maximum degree of Legendre polynomials: 10, default lambda: 1e-5). To determine the temporal occurrence (latency) and magnitude of the ERP amplitude, a peak algorithm was applied to the data sets. The time window for determining the parameters was 90\u0026ndash;200 ms for the first negative wave. 100\u0026ndash;250 ms for the consecutive negative wave and 150\u0026ndash;300 ms for the negative wave over the fronto-central part.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eStatistics were performed using self-written scripts in R (2022.12.0, Posit Software, PBC). All data sets were tested for normality using the Shapiro-Wilk test before further statistical calculation. Further statistical evaluation was carried out with two-way repeated measures analysis of variance (RM ANOVA) or the corresponding, non-parametric procedure (Friedman test), depending on the outcome of the Shapiro-Wilk test.\u003c/p\u003e \u003cp\u003eComparisons of reaction time (RT) was performed using either the Friedman test or a one-way repeated measures ANOVA with the within-group factors of \u003cem\u003egravity\u003c/em\u003e (1G/1.8G/0G). Comparison of the accuracy/percentage of errors (ER) was performed using either the Friedman test or a two-way repeated measures ANOVA with the within-group factors of \u003cem\u003egravity\u003c/em\u003e (1G/1.8G/0G) and \u003cem\u003eexperiment\u003c/em\u003e (target or standard sound of the Oddball paradigm). Where appropriate, a post hoc analysis with Bonferroni correction was carried out.\u003c/p\u003e \u003cp\u003eAdditionally, as this study was conducted with a small sample size and the observation of outlier, the non-parametric version of a two-factorial repeated measures ANOVA, the ld.f2 function with Wald-type (WTS) of the nparLD package in R, was used\u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This package refers to the results of the studies by Akritas and Brunner\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Here, the relative treatment effects are defined in relation to the distributions of the variables measured in the experiment. This was the case for the statistical calculation of the electrocortical activity with the within-factors \u003cem\u003egravity\u003c/em\u003e and \u003cem\u003eRegions of Interest (ROI)\u003c/em\u003e. If this package provided a significant main effect of either one factor or an interaction effect of both factors, a Wilcoxon test was performed as a post-hoc test with Bonferroni correction.\u003c/p\u003e \u003cp\u003eTo statistically examine the amplitude and latency of the observed event-related potentials, the data were evaluated with a two-factor analysis of variance (ANOVA) or the corresponding, non-parametric procedure (ld.f2 function with Wald-type). If statistical significance was determined by the procedures, a post hoc test with Bonferroni correction was carried out. The level of significance was set to p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data in this manuscript are presented as mean and standard deviation.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe data for the electrocortical activity were not normally distributed and therefore the ld.f2 model with the Wald-type (WTS) was calculated and showed no significant interaction effect of the factors \u003cem\u003eROI\u003c/em\u003e and \u003cem\u003egravity\u003c/em\u003e (Statistic\u0026thinsp;=\u0026thinsp;4.665, p\u0026thinsp;=\u0026thinsp;.587, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCortical current density averaged over 25 parabolas for each gravity level. Displayed are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. \u003cem\u003eFRONT\u003c/em\u003e frontal lobe, \u003cem\u003ePAR\u003c/em\u003e parietal lobe, \u003cem\u003eOCC\u003c/em\u003e occipital lobe, \u003cem\u003eMCA\u003c/em\u003e middle cerebral artery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eElectrocortical Activity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFRONT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePAR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOCC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMCA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.016\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u0026thinsp;\u0026plusmn;\u0026thinsp;0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048\u0026thinsp;\u0026plusmn;\u0026thinsp;0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.027\u0026thinsp;\u0026plusmn;\u0026thinsp;0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u0026thinsp;\u0026plusmn;\u0026thinsp;0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.8G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.040\u0026thinsp;\u0026plusmn;\u0026thinsp;0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatistical test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eLd.f2 model with Wald test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Friedman test regarding the participants' reaction time did not show a significant outcome (χ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e: 4.333, p\u0026thinsp;=\u0026thinsp;.115, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBehavioural Performance like reaction time of the answers for the target sound for the oddball. Error Rate for the target and standard sound of the oddball. Displayed are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eBehavioural Performance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eError Rate [%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eReaction Time [ms]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTarget Sound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard Sound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTarget Sound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.863\u0026thinsp;\u0026plusmn;\u0026thinsp;17.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.271\u0026thinsp;\u0026plusmn;\u0026thinsp;1.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e592.015\u0026thinsp;\u0026plusmn;\u0026thinsp;116.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.406\u0026thinsp;\u0026plusmn;\u0026thinsp;11.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.811\u0026thinsp;\u0026plusmn;\u0026thinsp;1.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e577.985\u0026thinsp;\u0026plusmn;\u0026thinsp;115.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.8G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.722\u0026thinsp;\u0026plusmn;\u0026thinsp;12.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.595\u0026thinsp;\u0026plusmn;\u0026thinsp;1.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e576.434\u0026thinsp;\u0026plusmn;\u0026thinsp;115.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatistical test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eRepeated measure ANOVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFriedman Test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eInteraction Effect of \u003cem\u003eGravity and Error Rate\u003c/em\u003e: p\u0026thinsp;=\u0026thinsp;.003 *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003en.s. (χ\u0026sup2; = 4.333, p\u0026thinsp;=\u0026thinsp;.115)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost-hoc (t-test with Bonferroni correction)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTarget Sound\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e0G vs. 1.8G : p\u0026thinsp;=\u0026thinsp;.028 *\u003c/p\u003e \u003cp\u003e0G vs. 1G : p\u0026thinsp;=\u0026thinsp;.009 **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe two-way repeated measures ANOVA for the participants' accuracy showed a significant interaction effect between the different gravity levels and the Oddball paradigm on the error rate of the participants (F\u003csub\u003e(34,2)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;8.986, p\u0026thinsp;=\u0026thinsp;.003, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Therefore, the effect of gravity was analysed for the different sounds of the Oddball paradigm. The effect of gravity was significant for 0G compared to 1.8G (p\u0026thinsp;=\u0026thinsp;.009) and 1G (p\u0026thinsp;=\u0026thinsp;.028).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe standard and target tones of the auditory oddball paradigm elicited a negative and a consecutive positive wave under the posterior electrode P7 and a negative wave over the fronto-central part, which was most pronounced under electrode C3.\u003c/p\u003e \u003cp\u003eA two-way repeated measure ANOVA was conducted to evaluate the effect of different gravity levels for the different sounds of an auditive Oddball paradigm on the amplitude of the observed N1-P2 complex. The data was not normally distributed and therefore the ld.f2 model with the Wald-type (WTS) was calculated and showed no significant interaction effect of the factors Experiment and Gravity (Statistic: 3.543, p\u0026thinsp;=\u0026thinsp;.170, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAmplitude of the N1-P2 complex of event-related potentials for the Oddball paradigm. Displayed are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eEvent-Related Potentials\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eN1-P2 complex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eStandard Sound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eTarget Sound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAmplitude [\u0026micro;V]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eAmplitude [\u0026micro;V]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.843\u0026thinsp;\u0026plusmn;\u0026thinsp;14.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.924\u0026thinsp;\u0026plusmn;\u0026thinsp;11.193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.8G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.966\u0026thinsp;\u0026plusmn;\u0026thinsp;12.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.316\u0026thinsp;\u0026plusmn;\u0026thinsp;12.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.535\u0026thinsp;\u0026plusmn;\u0026thinsp;16.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.727\u0026thinsp;\u0026plusmn;\u0026thinsp;11.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatistical test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eLd.f2 model with Wald test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAmplitude and Latency of the event-related potential N200 for the Oddball paradigm. Displayed are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eEvent-Related Potentials\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eN200\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLatency [ms]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAmplitude [\u0026micro;V]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eStandard Sound\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eTarget Sound\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eStandard Sound\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eTarget Sound\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203.333\u0026thinsp;\u0026plusmn;\u0026thinsp;27.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206.889\u0026thinsp;\u0026plusmn;\u0026thinsp;26.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7.502\u0026thinsp;\u0026plusmn;\u0026thinsp;7.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-8.604\u0026thinsp;\u0026plusmn;\u0026thinsp;5.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.8G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208.000\u0026thinsp;\u0026plusmn;\u0026thinsp;19.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202.556\u0026thinsp;\u0026plusmn;\u0026thinsp;26.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.085\u0026thinsp;\u0026plusmn;\u0026thinsp;7.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-8.904\u0026thinsp;\u0026plusmn;\u0026thinsp;6.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201.667\u0026thinsp;\u0026plusmn;\u0026thinsp;24.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210.889\u0026thinsp;\u0026plusmn;\u0026thinsp;30.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.300\u0026thinsp;\u0026plusmn;\u0026thinsp;8.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-8.524\u0026thinsp;\u0026plusmn;\u0026thinsp;5.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatistical test\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLd.f2 model with Wald test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eLd.f2 model with Wald test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examines the impact of different gravity levels on neurocognitive performance and electrocortical activity while executing a dual-task with a continuous primary task. The investigation was conducted under three different gravity conditions: 1G (representative of Earth's gravity), 1.8G (hypergravity), and 0G (weightlessness).\u003c/p\u003e \u003cp\u003eThe analysis of electrocortical activity revealed no statistically significant differences between the gravity levels in all four brain lobes and especially not in the frontal lobe, which is known to be responsible for executive function and cognitive evaluation. This result is in contrast to previous studies that showed a significant reduction in brain activity in microgravity when two discrete tasks were combined in a dual task \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. However, the results are consistent with those from hypergravity and partial gravity, which showed no statistically significant reduction in brain activity in the frontal lobe \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite no gravity-dependent changes in reaction time could be observed, the error rate was found to be significantly higher in 0G compared to 1.8G and 1G. These observations diverge from those of previous studies that employed a discrete primary task. In these studies, the reaction time was observed to be shorter in microgravity, while the error rate remained unaltered \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In contrast, no differences were observed in the behavioural data in a discrete primary task in hypergravity and partial weightlessness \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe electrophysiological data from the current study demonstrated a pronounced negative peak after approximately 100 ms, followed by a positive deflection after around 200 ms. This phenomenon is known as the N1-P2 complex and has been previously described by Wollseiffen et al. (2016), who observed it in conjunction with a cognitive task comprising a single discrete component \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The absence of the P300 component, which typically occurs in dual tasks with a discrete primary task, is noteworthy. This absence may be indicative of the fact that the continuous task employed in the current study was more demanding than the mental arithmetic task that had been previously investigated \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. It is possible that this was perceived as a single, uninterrupted task. Here, the N1-P2 complex may be classified as an early event-related potential (ERP) which is closely associated with perceptual processing. In contrast, later ERPs, such as the P300 component, are associated with cognitive processes \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. It is hypothesised that the continuous primary task in the study may have limited the cognitive processing of the different tones of the oddball paradigm, indicating the absence of a P300 component. This suggests that the secondary auditory stimuli were not fully processed.\u003c/p\u003e \u003cp\u003eThe use of cognitive resources, known as cognitive workload, is based on two theories, the limited capacity theory and the multiple resource theory, and emphasises that the human brain only has a limited capacity to absorb and process information. They explain the relationship between the complexity of a task and performance, which decreases as the task becomes more complex. A notable finding of this study is that both sounds of the oddball paradigm elicited the same ERP components in the current dual task, which is in contrast with the results of studies that employed a discrete primary task \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. It leads to the suggestion, that the majority of cognitive resources were allocated to the PACMAN game and that the auditory stimuli of the oddball paradigm were no longer perceived in a differentiated manner. It may therefore be the case that the secondary task of the dual task was not adequately assessed, either because it was ignored or it was processed with limited cognitive resources.\u003c/p\u003e \u003cp\u003ePrior research, including that of Allison and Polich (2008), has demonstrated that dual tasks typically necessitate a substantial allocation of cognitive resources and that the additional demand of a second task is challenging to quantify. It is frequently challenging to ascertain which element of the dual task participants are concentrating on \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The reduced amplitude values of the event-related potentials observed in this study in comparison to the results of Wollseiffen et al. (2016) may be indicative of the PACMAN task being perceived as more complex and demanding than the discrete mental arithmetic task.\u003c/p\u003e \u003cp\u003eAnother crucial element of this study is the observation of the N200 component, which may be interpreted as a Mismatch Negativity (MMN), described by N\u0026auml;\u0026auml;t\u0026auml;nen et al. \u003csup\u003e\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e in a dichotomic-listening study. The MMN is hypothesised to reflect an automatic neural mismatch process occurring between the input of a deviant stimulus and a sensory memory trace. Similarly, Folstein et al. (2018) distinguished the visual N2 from the auditory MMN, noting that the MMN responds to auditory deviants even when there is no focal attention to the stimuli \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. It also appears to occur independently of task complexity and cognitive load \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe combination of the results suggests that a continuous primary task in the context of a discrete secondary task requires a higher cognitive workload than a discrete primary task. This results in fewer resources being available for the secondary task. Understanding how the human brain allocates available cognitive resources, especially during dual-task situations, is of major importance to astronauts and ground personnel who are responsible for prioritising the relevant tasks during space missions. Generally, people under stress often find themselves in situations where they have to perform two tasks simultaneously, or are faced with a critical situation and have to perform and react to a sudden secondary task. For example, during the docking manoeuvre of the Soyuz capsule to the ISS. The astronauts must be able to manually dock the capsule to the ISS with six degrees of freedom and at the same time react to sounds from the spacecraft.\u003c/p\u003e \u003cp\u003eOverall, the present study shows that examining ERPs in the context of dual-task performance can provide valuable insights into cognitive processing and workload management. The results highlight the need for further research into cognitive workload and attentional focus during dual-task performance in complex environments to improve overall performance and safety.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting Interests:\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eAll authors declare no financial or non-financial competing interests.\u003c/p\u003e \u003ch2\u003eConsent to participate:\u003c/h2\u003e \u003cp\u003e Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical Standards:\u003c/h2\u003e \u003cp\u003e The study's experimental design was approved by the Research Ethics Committee of the German Sport University Cologne and the University of Caen in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAuthor contributions:\u003c/strong\u003e \u003cp\u003eAll authors contributed to the study's conception and design. Experiment preparation, data collection and analysis were performed by C.B, P.W., L.P. and S.S. The first draft was written by C.B. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e \u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank NOVESPACE for their great support on Earth and in space as well as the participants for their valuable time. The study was funded by the German Aerospace Center DLR (50WB2020).\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eESA. Roadmaps. Available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf\u003c/span\u003e\u003cspan address=\"https://esamultimedia.esa.int/docs/edu/ESA_roadmaps_public.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGenik, R. J., Green, C. C., Graydon, F. X. \u0026amp; Armstrong, R. E. Cognitive avionics and watching spaceflight crews think: generation-after-next research tools in functional neuroimaging. Aviation, space, and environmental medicine 76, B208-12 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarey, W. \u003cem\u003eExploration of the moon as preparation for mars - the human robotic partnership\u003c/em\u003e (Noordwijk, 2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoppelmans, V. \u003cem\u003eet al.\u003c/em\u003e Study protocol to examine the effects of spaceflight and a spaceflight analog on neurocognitive performance: extent, longevity, and neural bases. \u003cem\u003eBMC neurology\u003c/em\u003e 13, 205; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2377-13-205\u003c/span\u003e\u003cspan address=\"10.1186/1471-2377-13-205\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKozlovskaya, I. B., Kreidich, Y., Oganov, V. S. \u0026amp; Koserenko, O. P. Pathophysiology of motor functions in prolonged manned space flights. Acta astronautica 8, 1059\u0026ndash;1072; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0094-5765(81)90079-5\u003c/span\u003e\u003cspan address=\"10.1016/0094-5765(81)90079-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1981).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWollseiffen, P. \u003cem\u003eet al.\u003c/em\u003e Neurocognitive performance is enhanced during short periods of microgravity-Part 2. Physiology \u0026amp; behavior 207, 48\u0026ndash;54; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.physbeh.2019.04.021\u003c/span\u003e\u003cspan address=\"10.1016/j.physbeh.2019.04.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWollseiffen, P. \u003cem\u003eet al.\u003c/em\u003e Neuro-cognitive performance is enhanced during short periods of microgravity. Physiology \u0026amp; behavior 155, 9\u0026ndash;16; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.physbeh.2015.11.036\u003c/span\u003e\u003cspan address=\"10.1016/j.physbeh.2015.11.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSieber, M., Hanke, W. \u0026amp; Kohn, F. P. M. Modification of Membrane Fluidity by Gravity. OJBIPHY 04, 105\u0026ndash;111; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4236/ojbiphy.2014.44012\u003c/span\u003e\u003cspan address=\"10.4236/ojbiphy.2014.44012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKohn, F. P. M. \u0026amp; Ritzmann, R. Gravity and neuronal adaptation, in vitro and in vivo-from neuronal cells up to neuromuscular responses: a first model. European biophysics journal: EBJ 47, 97\u0026ndash;107; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00249-017-1233-7\u003c/span\u003e\u003cspan address=\"10.1007/s00249-017-1233-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsreal, J. B., Chesney, G. L., Wickens, C. D. \u0026amp; Donchin, E. P300 and tracking difficulty: evidence for multiple resources in dual-task performance. Psychophysiology 17, 259\u0026ndash;273; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1469-8986.1980.tb00146.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1469-8986.1980.tb00146.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1980).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKasper, R. W., Cecotti, H., Touryan, J., Eckstein, M. P. \u0026amp; Giesbrecht, B. Isolating the neural mechanisms of interference during continuous multisensory dual-task performance. Journal of cognitive neuroscience 26, 476\u0026ndash;489; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1162/jocn_a_00480\u003c/span\u003e\u003cspan address=\"10.1162/jocn_a_00480\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaldwin, C. L. \u003cem\u003eAuditory Cognition and Human Performance\u003c/em\u003e (CRC Press, 2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasil, M. D. Multiple Resource Theory. In \u003cem\u003eEncyclopedia of the Sciences of Learning\u003c/em\u003e, edited by N. M. Seel (Springer US, Boston, MA, 2012), pp. 2384\u0026ndash;2385.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWickens, C. D. The Structure of Attentional Resources. In \u003cem\u003eAttention and Performance\u003c/em\u003e, edited by Nickerson R.S. 1st ed. (New York, 1981).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuck, S. J. (ed.). \u003cem\u003eThe Oxford handbook of event-related potential components\u003c/em\u003e. 1st ed. (Oxford Univ. Press, Oxford, 2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBadal\u0026igrave;, C., Wollseiffen, P. \u0026amp; Schneider, S. Under pressure-the influence of hypergravity on electrocortical activity and neurocognitive performance. Experimental brain research 241, 2249\u0026ndash;2259; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00221-023-06677-8\u003c/span\u003e\u003cspan address=\"10.1007/s00221-023-06677-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBadal\u0026igrave;, C., Wollseiffen, P. \u0026amp; Schneider, S. Shades of gravity - effects of planetary gravity levels on electrocortical activity and neurocognitive performance. Brain structure \u0026amp; function 229, 1265\u0026ndash;1277; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00429-024-02803-6\u003c/span\u003e\u003cspan address=\"10.1007/s00429-024-02803-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Rossum, G. \u0026amp; Drake, F. L. \u003cem\u003ePython 3. Reference manual\u003c/em\u003e (SohoBooks, United States, 2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKluyver, T. \u003cem\u003eet al.\u003c/em\u003e Jupyter Notebooks \u0026ndash; a publishing format for reproducible computational workflows. Positioning and Power in Academic Publishing: Players, Agents and Agendas. (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrech, R. \u003cem\u003eet al.\u003c/em\u003e Review on solving the inverse problem in EEG source analysis. \u003cem\u003eJournal of neuroengineering and rehabilitation\u003c/em\u003e 5, 25; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1743-0003-5-25\u003c/span\u003e\u003cspan address=\"10.1186/1743-0003-5-25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePascual-Marqui, R. D. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. \u003cem\u003eMethods and findings in experimental and clinical pharmacology\u003c/em\u003e 24 Suppl D, 5\u0026ndash;12 (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuncan, C. C. \u003cem\u003eet al.\u003c/em\u003e Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. \u003cem\u003eClinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology\u003c/em\u003e 120, 1883\u0026ndash;1908; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clinph.2009.07.045\u003c/span\u003e\u003cspan address=\"10.1016/j.clinph.2009.07.045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHelfrich, R. F. \u0026amp; Knight, R. T. Cognitive neurophysiology: Event-related potentials. Handbook of clinical neurology 160, 543\u0026ndash;558; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/B978-0-444-64032-1.00036\u0026thinsp;\u0026ndash;\u0026thinsp;9\u003c/span\u003e\u003cspan address=\"10.1016/B978-0-444-64032-1.00036\u0026thinsp;\u0026ndash;\u0026thinsp;9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel, S. H. \u0026amp; Azzam, P. N. Characterization of N200 and P300: selected studies of the Event-Related Potential. International journal of medical sciences 2, 147\u0026ndash;154; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7150/ijms.2.147\u003c/span\u003e\u003cspan address=\"10.7150/ijms.2.147\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrunner, E. \u0026amp; Langer, F. \u003cem\u003eNichtparametrische Analyse longitudinaler Daten\u003c/em\u003e. 2014th ed. (Oldenbourg Wissenschaftsverlag, Berlin, Boston, 1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeys, J. Nonparametric Tests for the Interaction in Two-way Factorial Designs Using R. The R Journal 8, 367; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.32614/RJ-2016-027\u003c/span\u003e\u003cspan address=\"10.32614/RJ-2016-027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoguchi, K., Gel, Y. R., Brunner, E. \u0026amp; Konietschke, F. nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments. J. Stat. Soft. 50; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18637/JSS.V050.I12\u003c/span\u003e\u003cspan address=\"10.18637/JSS.V050.I12\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkritas, M. G. \u0026amp; Brunner, E. A unified approach to rank tests for mixed models. Journal of Statistical Planning and Inference 61, 249\u0026ndash;277; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0378-3758(96)00177-2\u003c/span\u003e\u003cspan address=\"10.1016/S0378-3758(96)00177-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein, T. \u003cem\u003eet al.\u003c/em\u003e The influence of microgravity on cerebral blood flow and electrocortical activity. Experimental brain research 237, 1057\u0026ndash;1062; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00221-019-05490-6\u003c/span\u003e\u003cspan address=\"10.1007/s00221-019-05490-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSol\u0026iacute;s-Marcos, I. \u0026amp; Kircher, K. Event-related potentials as indices of mental workload while using an in-vehicle information system. Cogn Tech Work 21, 55\u0026ndash;67; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10111-018-0485-z\u003c/span\u003e\u003cspan address=\"10.1007/s10111-018-0485-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllison, B. Z. \u0026amp; Polich, J. Workload assessment of computer gaming using a single-stimulus event-related potential paradigm. Biological psychology 77, 277\u0026ndash;283; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biopsycho.2007.10.014\u003c/span\u003e\u003cspan address=\"10.1016/j.biopsycho.2007.10.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eN\u0026auml;\u0026auml;t\u0026auml;nen, R., Gaillard, A. W. \u0026amp; M\u0026auml;ntysalo, S. Early selective-attention effect on evoked potential reinterpreted. Acta psychologica 42, 313\u0026ndash;329; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0001-6918(78)90006-9\u003c/span\u003e\u003cspan address=\"10.1016/0001-6918(78)90006-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1978).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eN\u0026auml;\u0026auml;t\u0026auml;nen, R., Pakarinen, S., Rinne, T. \u0026amp; Takegata, R. The mismatch negativity (MMN): towards the optimal paradigm. Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 115, 140\u0026ndash;144; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clinph.2003.04.001\u003c/span\u003e\u003cspan address=\"10.1016/j.clinph.2003.04.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlho, K., Sams, M., Paavilainen, P., Reinikainen, K. \u0026amp; N\u0026auml;\u0026auml;t\u0026auml;nen, R. Event-related brain potentials reflecting processing of relevant and irrelevant stimuli during selective listening. Psychophysiology 26, 514\u0026ndash;528; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1469-8986.1989.tb00704.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1469-8986.1989.tb00704.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1989).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFolstein, J. R. \u0026amp; van Petten, C. Influence of cognitive control and mismatch on the N2 component of the ERP: a review. Psychophysiology 45, 152\u0026ndash;170; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1469-8986.2007.00602.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1469-8986.2007.00602.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuller-Gass, A., Macdonald, M., Schr\u0026ouml;ger, E., Sculthorpe, L. \u0026amp; Campbell, K. Evidence for the auditory P3a reflecting an automatic process: elicitation during highly-focused continuous visual attention. Brain research 1170, 71\u0026ndash;78; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.brainres.2007.07.023\u003c/span\u003e\u003cspan address=\"10.1016/j.brainres.2007.07.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhani, U., Signal, N., Niazi, I. K. \u0026amp; Taylor, D. ERP based measures of cognitive workload: A review. Neuroscience and biobehavioral reviews 118, 18\u0026ndash;26; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neubiorev.2020.07.020\u003c/span\u003e\u003cspan address=\"10.1016/j.neubiorev.2020.07.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"weightlessness, hypergravity, parabolic flight, behavioural and neuronal parameters, ERP, EEG","lastPublishedDoi":"10.21203/rs.3.rs-5136580/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5136580/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIt is essential that astronauts maintain optimal cognitive function in order to successfully complete critical tasks in demanding environments. However, stress can impair executive functions and decision-making, which may ultimately affect mission success. Training and establishing routines can help ensure efficiency and may free up cognitive resources to handle unforeseen challenges effectively. To evaluate workload management in a demanding dual-task the study investigated behavioural data (Reaction Time and Error Rate), as well as neurophysiological parameters (event-related potentials and electrocortical activity) in Earth gravity, hypergravity and weightlessness in 25 consecutive parabolas through a parabolic flight.\u003c/p\u003e\n\u003cp\u003eThe data demonstrated no significant changes in electrocortical activity and reaction time between the different gravity levels. However, a notable increase in error rate was observed in microgravity when compared to hyper- and normal gravity. Electrophysiological data revealed a pronounced N1-P2 complex, indicating perceptual processing of the sound of the Oddball paradigm. The typical fronto-central N200 component was triggered by both sounds of the Oddball paradigm, although no differences were observed between the gravity levels. The similarity of the ERP responses to both oddball paradigm tones suggests that most cognitive resources were allocated to the primary task, with reduced discrimination of auditory stimuli. Furthermore, the presence of the N200 component, interpreted as mismatch negativity (MMN), indicates automatic neural responses to auditory deviations that are independent of cognitive load. This has important implications for astronauts performing complex tasks during space missions, where understanding cognitive workload and task prioritization is essential for mission success and safety. Further research is needed to explore cognitive workload management in such demanding environments.\u003c/p\u003e","manuscriptTitle":"sPACeMAN – Assessing Neurocognitive Performance and Electrocortical Activity Across Diverse Gravity Levels Using a Gamification Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-05 06:43:45","doi":"10.21203/rs.3.rs-5136580/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14f81e93-df87-40c6-986c-289cc4db01a7","owner":[],"postedDate":"February 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43123313,"name":"Biological sciences/Neuroscience"},{"id":43123314,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-05-06T22:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-05 06:43:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5136580","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5136580","identity":"rs-5136580","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}