Chapter 9 Performance and Brain Electrical Activity During Prolonged Confinement

Chapter 9

PERFORMANCE AND BRAIN ELECTRICAL ACTIVITY DURING PROLONGED CONFINEMENT

Bernd Lorenz, Jurgen Lorenz, and Dietrich Manzey I. Introduction . . . . . . . . . . . . . . . . . . . . . . 11. Methodological Aspects . . . . . . . . . . . . . . . . A. S u b j e c t s . . . . . . . . . . . . . . . . . . . . . . B. PerformanceTasks . . . . . . . . . . . . . . . . C. Electroencephalographic Recording and Analysis D. Procedure . . . . , . . . . . . . . . . . . . . . . E. Statistical Evaluation of Single-Subject Data . . 111. Results . . . . . . . . . . . . . . . . . . . . . . . . . A. Performance . . . . . . . . . . . . . . . . . . . B. Electroencephalography . . . . . . . . . . . . .

Advances in Space Biology and Medicine Volume 5, pages 157-183 Copyright 0 1996 by JAI Press h c . All rights of reproductionin any form reserved. ISBN: 1-5593897&2

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158 159 159 160 161 162 162 163 163 168

BERND LORENZ, JURGEN LORENZ, and DIETRICH MANZEY

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,176 B. Electroencephalogram . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Conclusions and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .I79

IV. Discussion

A. Performance

V.

1. INTRODUCTION Living and working in space involves exposure to several different stresson. The most important stressor is microgravity,causing various physiological changes like body fluid shifts, as well as clinical syndromes such as space motion sickness.’ Other stresson are: confinement, sleep disturbances, high workload, and specific Exposure environmental conditions caused by the artificial life support to this multi-stressor environment may have detrimental effects on the operational capacity of astronauts. Hence it appears to be widely accepted that in-flight monitoring of the mental state of astronauts is important for the conduct of long-duration manned space mission^^^^ However, opinions differ as to which behavioral measures should be chosen to provide a comprehensive assessment of changes in individual performance status under exposure to environmental stress6 Human factors research in space is faced by a lack of applicable models of task behavior that could guide the selection of space relevant performance indicators. The variety of methodological approachesadopted by the investigators involved in the ISEMSI and EXEMSI projects reflects to some extent this problem. Some investigators monitor performance by means of highly structured laboratory tasks:-* whereas others prefer more complex task scenarios’ (see also Gushin, et al.”). In addition, sampling of performance measures inherent in the actual operational tasks has been suggested for performance state evaluation.” The weakness of using comparatively simple laboratory tasks is their poor operational fidelity. On the other hand, more complex or realistic tasks are often associated with unknown measurement problems that may lead to serious deficiencies in reaching adequate interpretations.’*Apart from these shortcomings, there are practical constraints in the design of a performance study in a space mission or a space simulation study. The most critical limitation is the small number of subjects which does not allow the application of techniques proposed to counteract the threats to the various types of validity generally encountered in field settings.13 The aim of the present study was twofold: (1) the application of an integrated monitoring device for the assessment of the individual psychophysiological state. In particular, we were interested in the feasibility of self-administration and the quality of performance and physiological data which can be obtained under these conditions and (2) the experiment was to provide data about human performance changes under conditionsof confinement, lack of privacy, and experimental work-

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load. These data are to serve as reference data for the evaluation of possible performance changes during long-term space flights. In view of the methodological constraints mentioned above, we decided to rely on standardized laboratory tasks with (1) a background in human information-processing theory and (2) empirical evidence of suitability for repeated app1i~ation.l~ The advantages of such an approach are twofold. First, repeated sequential testing is required for monitoring the time course of adaptational processes. Secondly, standardization guarantees a comparability of results with other field-experiments focusing on the effects of environmental stressors on human performance in space Precise guidelines for a battery of or in a space simulating performance tasks which fulfill these requirements have been published recently by the Advisory Group for Aerospace Research and Development (AGARD).” A subset of the AGARD battery of Standardized Tests for Research with Environmental Stressors (STRES),including Sternberg memory search, grammatical reasoning, unstable tracking, and a dual task, was applied during an 8-day mission in the Russian orbital station MIR.Decrements in tracking and dual-task efficiency were observed.” A further study using the same tasks was used to examine the effects of high ambient pressure on task performance during a 3Oday deep-dive simulation (450 meter) in a hyperbaric complex.16 A slowing down of general performance at maximum depths was the main type of deterioration observed in this study. A recent study of the effects of sleep deprivation on performance in the AGARD battery showed stronger impairment of single-task tracking than of dual-task tracking.” These divergent patterns of performance changes associated with suboptimal internal and external conditions are difficult to integrate into a single dimension of inadequate arousal level. They support the assumption of multidimensional activation states underlying task Physiological indicators may help in assessing changes in state of alertness and effort, which are not reflected in performance data. A recent review by Kramer 21 suggests that the continuously recorded electroencephalogram(EG).particularly frontal theta rhythm2”” and alpha attenuation,z is a useful physiological indicator of changes in alertness and effort.

II. METHODOLOGICAL ASPECTS A. Subjects

The study involved two groups of subjects: (1) the chamber crew consisting of three males and one female, who worked and lived for 60 days in the EXEMSI isolation facility and (2) the ground control crew of two males and three females, who were not confined. The average age of the chamber crew was 29 years with a range of 26 to 34 years, that of the ground crew was 33 years with a range of 29 to 39 years. Subjects had different nationalities: France (2), Italy (2). Austria (l), Canada (l), Great Britain (l), the Netherlands (I), and Sweden (1). They were

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BERND LORENZ, JURGENLORENZ, and DIETRICH MANZEY

submitted to a thorough medical and psychological screening. Operational aptitude was tested by methods chosen from those used for ESA astronaut selection for which a normative database was available.26

B.

Performance Tasks

Three tasks were selected for this study from the AGARD-STRES batter^:'^ Memory Search Task (two levels of memory load), Unstable Tracking Task, and Dual Task (two levels of memory load). In addition a SubjectiveState Questionnaire was completed. Memory Search Task

This task is based on the experimental paradigm proposed by Sterx~berg~~ for evaluating short-term memory function. First, a set of letters, the “memory set,” has to be memorized. Then a single probe letter is presented, and the subject has to indicate whether or not the probe letter belongs to the memory set by pressing an appropriateresponsekey. Immediately after the response the probe letter disappears from the screen, and a new probe letter appers after a 1-secondresponse-stimulus interval (RSI). Letters belonging to the memory set (targets) and letters not belonging to the memory set (distractors) are randomly selected from all 20 consonants of the alphabet. In deviation from the AGARD standard, the vowels A, E, I, 0, and U were excluded from the memory set in order to avoid the effect of verbalizing on memorizing the set. The memory load was varied by presenting memory sets of two or four letters in separate test runs. Reaction times and errors were recorded for each probe. Unstable Tracking Task

This task requires fine manual control: a horizontally moving cursor has to be centered by means of a joystick within a fixed target in the center of the screen. The instability results from a positive feedback loop that drives the cursor to the left or right edge of the screen at a velocity proportional to (a) the tracking error and (b) a divergent element determined by the parameter “lambda.”28When the cursor reaches the boundary lines, a “control loss” is recorded. The difficulty of the task is essentiallydetermined by the value of lambda. When this was kept at a subcritical value of 2, control loss usually did not occur after sufficient training. The perforrnance measure, the root-mean-square tracking error (RMSE), was integrated over 1-second blocks, and the total number of control losses were recorded. Dual Task

This is a combination of the Unstable Tracking Task and the Memory Search Task. Two levels were used, one with a 2-letter memory set, the other with aCletter

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memory set in the Memory Search Task. The subject was instructed to pay equal attention to both tasks, i.e., not to neglect one in favor of the other. Subjective State Questionnaire

Subjective mood of the subject was assessed by means of a Subjective State Questionnaire. Fourteen mood attributes were presented sequentiallyon the screen, and subjects were instructed to rate each on a 5-point scale ranging from 0 “absolutely inappropriate”to 5 “absolutely appropriate.” The attributes were: fresh, sad, strained, fatigued, nervous, happy, interested, balanced, aggressive, carefree, distracted, bored, concentrated,relaxed. Computerization

All tasks were computerized using a commercially available code generating ~ystem.2~ Presentation of tasks, recording of reaction times and tracking errors were controlled by an IBM-286 compatible personal computer (Dell” 2 10). Responses in the Memory Search Task were given with non-dominant hand via the standard AGARD 4-button key-pad. The tracking tasks were controlled with the dominant hand using a joystick. Operation of the battery was programmed in a standard menu-driven format to facilitate self-administration.Task duration was fixed at 5 min for each task, 2 min more than proposed by AGARD in order to improve the reliability of the frequency estimates derived from the analysis of heart rate variability (not reported here). The intertask interval could be set by the subject between 20 s and 1 min. Completion of the battery took 60 min with and 35 min without physiological data acquisition. Task sequence was always: Memory Search TasWZletter set, Memory Search TasWCletterset, Unstable Tracking Task, Dual TasW2-letterset, Dual TasW4-letter set. and Subjective State Questionnaire. Randomization of the task sequence was not performed in view of the small number of subjects. C. Electroencephalographic Recording and Analysis

Biosignals were recorded from the midline sites Fz, Cz, and Pz according to the international 10-20 system.30Ag-AgCI electrodes were used with the left mastoid as the reference site. An additional electrode positioned half way between Fz and Cz served as the ground. To permit correction for eye movement artifacts, an electro-oculogram (EOG) was recorded from two electrodespositioned above and beside the subjects’ right eye . Electrode impedance was kept below 5 KOhm. EEG and EOG were amplified by means of a portable amplifier (VITAPORT”) with a 5-s time constant. Biosignals were recorded continuously throughout the session and stored on line by an APPLE LC” microcomputer after 8-bit A/D-conversion at a sampling rate of 128 Hz. Frequency analysis was based on 2-s periods that were filtered by a Hanning window algorithm and then subjected to Fourier

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BERND LORENZ, JURGENLORENZ, and DIETRICH MANZEY

transformation. This provided an analysis of the power spectrum between 1 and 20 Hz with a frequency resolution of 0.5 Hz.Periods containingocular artefacts(criterion: +/- 50 microvolt) or movement artifacts were excluded from the analysis. D. Procedure

The study comprised four phases: training, pre-isolation baseline data collection, isolation and post-isolation. Training sessions: These focused on handling of the hardware as well as performance of the whole task battery (all tasks in sequence). This provided sufficient knowledge for dealing with the main hardware and software components and an introduction to typical sources of EEG contaminating artefacts (neck and face muscle tension, movements and eye blinks). All subjects completed the performance battery four times for practice. During that phase they received feedbackabout their performance. These sessions were conducted without acquisition of physiological data. Pre-isolationbaseline data collection: This comprised two sessions, which were run as a joint experimental session with another experiment involving EEG recording.3’ Isolation period: The sessions started on day 10 for subjects B and G, and on day 11 for subjects D and H, and were then repeated at weekly intervals for a total of 16 sessions per subject. The tests for subjects B and H always started at 11:OO am, those for subjects D and G at 2:OO pm. Posr-isolafionsessions: These took place five and seven days after leaving the isolation facility. A confrolgroup, consisting of the ground control crew, was included to obtain further experience with the single-subject experimentation technique (see below) adopted in this study. The control group completed a total of 12 sessions in their normal ofice. Only the two members, who served as “back-ups” during the pre-isolation phase, performed the same number of 16sessions as the chamber crew. The control group sessions could not be synchronized with those of the chamber crew, since they had to be scheduled during the ground control crew’s spare time with intersession intervals ranging from 2 to 6 days, and without control over the time of day. No physiological data were recorded for the control group, another important difference in the overall workload between the two groups. E. Statistical Evaluation of Single-Subject Data

The statisticalanalysis of response latencies was based on responserates obtained by reciprocal transformation. This was done to reduce the skewness usually found in the distribution of reaction times and to improve homogeneity of variances.

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Response rates as well as the RMSE-data from the Unstable Tracking Task were averaged over 10-s blocks, providing 30 performance scores per 5-minute trial. Response rates from false responses were not included in block averaging. For the chamber crew this procedure resulted in a sequence of 360 performance values obtained for all 12 sessions in each task and each subject. The training sessions were not included in the analysis. For the control group 240 performance values were obtained. Performance differences between sessions were statistically evaluated by analysis of variance (ANOVA) with the experimental sessions as the independent variable. The ANOVAs were performed separately for each individual subject. Significant effects of session were analyzed in more detail by pairwise comparison of averagepre-isolationperformance with all other means (two-tailed non-orthogonal, a priori contrasts with Bonferroni adjusted p = O.OS/number of comparison^^^). In these an,alyses,the series of ANOVA residuals was used for estimation of error variance. Such an approach is justified when a series represents independent successive observations (white noise), i.e., does not show significant autocorrelations. Positive autocorrelations, which may cause a substantial inflation of F-scores,must be regarded as critical when ANOVAis applied to ~ingle-casedata.~~ Our analyses revealed that positive autocorrelations found in the sequence of ANOVA residuals of all reaction time data disappeared after removal of a linear trend within each 5-minute trial. In the tracking task data autocorrelation was evident because of the inherent dynamics of the task. Here, data aggregation across 10-s intervals was sufficient to obtain negligible departures from white noise. This means that sometimes negative autocorrelations were present at unsystematic lags, which resulted in a bias towards a conservative significance test. To correct for possible speed-accuracy trade-offs, which could be confused with effects of response rates, between-session differences in error rates for the memory search data were evaluated by simple X*-statistics.

111. RESULTS This section first presents the results of the single-subject analyses of the performance data. Secondly, results of the EEG frequency analyses are presented, and finally, an attempt is made to integrate behavioral and physiological sources of data for a diagnosisof operator state. Results obtained from one subject will be presented in more detail. A. Performance Memory Search

Figure 1 presents the individual sequences of mean response rates in the Memory Search Task (left panel Chamber Crew, right panel Ground Control Crew) under

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Table 1. Distribution of Results Obtained by the Planned Comparison Tests in the MEMORY SEARCH TASK Chamber Crew

GroundControl Crew

+

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abs. no. perceflt

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Notes: Values based on single-subject ANOVAs of chamber crew and ground control crew. For each offour task load levels the following number of comparisons were computed: chamber crew 10 + 10 + 10 + 9 = 39; ground control crew: 10 + 10 + 6 + 6 + 6 = 38. Column headings: + significant increases, 0 non-significant changes, significant decreases in mean response rate, Z sum of values in previous three columns. Comparisons represent tests between session averages relative to pre-isolation baseline levels.

-

different levels of task load (from top to bottom: single mode -memory set 2, single mode - memory set 4, dual mode - memory set 2, dual mode - memory set 4). Visual inspection reveals only a slight tendency for increasing speed with test repetition. This was interrupted by occasional drops spread over the entire period without a clear systematic pattern. This general pattern applies to subjects of both groups and was more or less present under all levels of task load. All ANOVAs performed on each single sequence revealed significant F-values for the main effect of the session (p < 0.01). This supports the impression of a lack of performance stability between sessions. To provide a more detailed insight into the pattern of changes that occurred in both groups, results obtained by the total number of t-tests (156 for the chamber crew, 152 for the ground control crew) were divided into three categories: significant increases, insignificant changes, and significant decreases in mean response rates. Table 1 contains the absolute numbers and relative percentages of these categories obtained in each group. The results are separated for all four levels of task load. It is evident that in both groups the main source of the significant session

BERND LORENZ, JURGENLORENZ, and DIETRICH MANZEY

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main effects was due to increases in mean response rates (25.6% increases in the chamber crew, 32.2% increases in the ground control crew). Task load had a different effect among groups. Whereas the ground control group had much more frequent speed increases under single task conditions (ground control crew: 44.7%, chamber crew: 21.8%), irrespectiveof memory load, an oppositetendency emerged under dual task conditions. Here, the chamber crew displayed more speed increases (29.5%) and less decreases (5.1%) than the ground control crew (19.7% increases,

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17.1% decreases).Error percentages were generally not different between the levels of memory load and between sessions and were kept well below 10%by all subjects. Only one subject of the ground control group (C), and one subject of the chamber crew (B) committed significantly more errors towards the endof themission: under the task load condition singlehigh memory-load B had x2 (df = 11) = 24.71, p < 0.01; and C had x2 (df = 11) = 22.16, p = 0.02). Under the condition dualhigh memory-load significant error-rate differences were found again in subject C: x2 (df = 11) = 24.57, p < 0.01. and also in subject K of the ground control group: x2 (df = 7) = 16.78, p = 0.02. Unstable Tracking

Figure 2 presents the time courses of the average root mean square tracking error (RMSE) for both groups. It is apparent that in three subjects of the chamber crew tracking errors increased several times during confinement under all three levels of task load. Whereas the groups did not differ at the second pre-isolation baseline session, no subject of the ground control crew displayed similar performance decrements in the subsequent sessions. The main feature in the ground control crew was performance stabilization,as was supported by the pattern of results obtained by the t-tests (Table 2). In the chamber crew 50 of the total number of 117 (42.7%) comparisonswith pre-isolation baseline values indicated aperformance decrement. Table 2. Distributionof Results Obtained by the Played Comparisons in the UNSTABLE TRACKING TASK Chamber Crew

Ground Control Crew

+

0

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0

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abs. no. percent

12 30.8

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39

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12 30.8

11 28.2

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7 17.9

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39

32 84.2

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Notes: Values are based on single-subject ANOVAs of chamber crew and ground control crew. For each of the three levels of task load the following number of comparisons were computed: chambercrew lO+lO+lO+9=39;groundcontrolcrew:lO+lO+6+6+6=38. Column headings: + significant increases, 0 non-significant changes, - significant decreases in mean RMSE, X sum of values in previous three columns. Comparisons represent tests between session averages relative to pre-isolation baseline levels.

BERND LORENZ, JURGEN LORENZ, and DIETRICH MANZEY

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Table 3. Subjective Fatigue Ratings from Eight Sessions During Isolation Period Experimental Session

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Decrements became more frequent with higher task load. In the ground control crew only 6 of 113 (5.3%) comparisons revealed reduced tracking accuracy. Subjective State

Evaluation of the subjective ratings given after completion of the task battery generally did not indicate any mood disturbancesin either group. Table 3 contains the individual fatigue ratings of both groups. The chamber crew shows a tendency towards higher fatigue than the ground control crew for the entire isolation period: F(1,7)=4.12; p=O.O8. In summary, analyses of the memory search task and the unstable tracking task revealed that there was no difference in performance of memory recognition, speed and accuracy between the two groups. However, the chamber crew showed a lower performance in tracking under all levels of task load, and a tendency toward higher subjective fatigue ratings. B. Electroencephalography

The EEG results will be described under three headings: (1) task-related spectral changes, (2) relation between time spent in isolation and alpha and theta changes, .ressed by single-subject analysis of one subject, and (3) correlation of behavJral, subjective, and EEG changes in this subject.

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Task-Related Changes

For the evaluation of task-related effects, the EEG power spectra were averaged across all sessions for each of the five task conditions. Figure 3 shows the average power spectra obtained over the Pz lead (upper part) and over the Fz lead (lower part) from each member of the chamber crew. Reliable EEG alpha waves (8-12 Hz) and theta waves (5-7 Hz) were observed only in subjects G and H. The EEG of subjects B and D was mainly characterized by desynchronized traces. Alpha power in G and H was greatest over Pz and differed between tasks with higher values during both memory-load levels of the Memory Search Task compared to the Unstable Tracking Task, Dual Task, set 2, and Dual Task, set 4. In addition, subject H showed a shift in the alpha center frequency depending on the task condition. A peak at 9.5 Hz was observed under both memory load levels of single memory search. The peak shifted to 10.5 Hz when tracking was performed under single as well as dual-task conditions. Theta power predominated over Fz and exhibited a tendency to be higher during the Memory Search Task than during the Unstable Tracking Task. Relation Between Time Spent in Isolation and Alpha and Theta Changes

The statistical significance of task- and session-related Pz-alpha and Fz-theta waves was determined by performing single-subject analyses on thedata for subject G. For subject H the first three sessions were contaminated by excessive eye-blink artefacts, which left too few data for a quantative single-subject analysis. The data for subject G had 151 (10.1%) missing values due to artefacts, but no complete session needed to be excluded from analysis. According to the procedure described for the performance data, the power density estimates were averaged across 10-s blocks, yielding 30 spectra per 5-minute task and 150 spectra for the entire session. The following band widths were defined for subject G on the basis of his individual power spectra: Fz-Theta: 5.5-7.5 Hz; Pz-Alpha: 8.0-1 1 .O Hz. Separate two-way ANOVAs were computed on the Fz-theta and Pz-alpha series of 1500spectral density estimates (30 blocks of 10 s, 5 tasks, 10 sessions)with TASK and SESSION as experimental factors. The source of the between-task difference was furtherexamined by computing four orthogonal aposferiori contrasts. The first and second contrasts, c l and c2, compared the effects of low and high memory loads for the single and dual Memory Search Tasks. The third contrast,c3, compared the averagesingleMemory Search Task with the averagedual Memory Search Task. The fourth, c4, compared all Memory Search Task levels with the single Unstable Tracking Task. Thus, the first three contrasts represented comparisons between the experimental levels of the memory task, whereas the fourth compared conditions

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with involvement of memory with the condition of single-task tracking, i.e., a condition without involvement of memory. As described for the performance data, ANOVA residuals were evaluated for autocorrelation. Alpha changes were studied by means of residual analysis. A strong autocorrelation was found in the sequences of alpha power density estimates. Therefore, hypotheses were evaluated by means of the general linear ARIMA (Auto-Regressive Integrated Moving Average) approach.34Computations were carried out with the statistical software package SPSS-Trendsm(151 missing values were replaced by session means). The main effects of session and task load and their interaction, including the above specified contrasts, were tested by using an appropriate coding scheme for the generation of the necessary set of dummy variables (0/1 coding for the session effect, orthogonal contrast coding for the task load effect). Figure 4 presents the time course of the alpha power density estimates found in subject G (light solid line) and the fit of a general linear model (dark solid line) including parameters for the ANOVA model and a highly significant parameter for a first order autoregressive process (AR[11 = 0.18; p c 0.0001). The mean level of alpha was highest in the pre-baseline session and attenuated significantly in all subsequent sessions including post-baseline (p < 0.0001 for all parameters for the session main effect).The lowest levels were observed in isolation weeks 2,3,4, and 8, and at the post-isolation session. Thus, alpha was lowest during the first half and at the end of the isolation period. Alpha attenuation in these sessions, except for the session in week 3, was stronger for single-task than for dual-task memory search, as revealed by the corresponding parameters of the sessiodtask load interaction (p < 0.005). Obviously, the involvement of tracking provoked a decline in alpha that dominated over the influence of the environmental condition. A comparable effect is found for the influence of task load. Higher memory load decreased alpha under single-task mode (cl: p c 0.005) but only slightly under dual-task mode (c2: p > 0.05). As argued above for the impact of the environmental condition on alpha power attenuation, it appears that the involvement of tracking also reduced alpha to an extent that no further effect of memory load was detectable. The single-dual comparison showed the strongest contribution to the overall task-load effect in terms of an alpha attenuation upon changing from single- to dual-task operation (c3: p c 0.0001). However, as can clearly be inferred from Figure 4, the drop in alpha power occurred on starting single-task tracking, which was the main source for the significanceof the fourth contrast (c4:p c 0.01). Them changes showed a behavior differing from that of the alpha changes. The series of 10-s estimates of Fz-theta power density displayed uncorrelated (white noise) ANOVA residuals. Therefore, significancetests using the ordinary ANOVA method were accepted. Figure 5 shows the series of the Fz-theta power density estimate observed in subject G, presented in the same manner as described above for Pz-alpha. Among the above specified contrasts only c4 reached significance (p c 0.05),revealing lower theta under single-task tracking compared to all levels of memory search. Alarge amount of variance in the series of subject G was accounted

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for by a highly significant between-session main effect. Only the mean theta at the session in week 4 of isolation was at the pre-isolation baseline level. Theta was enhanced in all other sessions, including the post-isolation session, relative to the pre-isolation baseline level (p < 0.001). The most striking theta increase occurred in week 6. Figure 6 shows the power spectra obtained over Fz, Cz, and Pz and demonstrates that the theta peak at about 7 Hz over Fz occurred independently from simultaneous alpha activity peaking at 9.5 Hz over Cz and Pz. Thus, this 7-Hz frontal rhythm can most likely be attributed to theta rather than to the slow alpha. This point is considered further in the discussion section. Correlation ofBehavioral, Subjective, and EEG Changes

The data for subject G were chosen for a study of the correlation between behavioral, subjective,and physiological changes. The series of mean performance scores (response rate, RMSE) of all ten sessions for which the EEG was evaluated and the respective mean alpha and theta values were z-transformed in order to obtain a common metric. Between-task differences are not considered. All seven performance z-scores were averaged to provide one global performance score per session. From the Subjective State Questionnaire only the ratings for the items

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week

CONFINEMENT

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Figure 7. Covariance of performance (dashed), Pz - alpha power.(solid);Fz - theta power (dotted),andwbjective state (“fatigue”:hatched bar; “concentrated“:open bar) in subject G as a function of length of isolation. “fatigue” and “concentrated” were selected (no SSQ ratings were obtained at the pre-isolation baseline session). The result of this analysis is presented in Figure 7. Alpha reduction displayed a good correlation with the subjective fatigue state as both prevailed during the first half of isolation and at the post-isolation session. Of particular interest is the performance and subjectivestate at session 5 after six weeks of isolation where the described marked increase in fronto-central theta O C C U K ~ ~ . At this session subject G achieved the best performance of the whole isolation period. The subjective rating of a low value in the item “fatigue” and a high value in the item “concentrated” agrees with good performance eaciency at this session.

IV. DISCUSSION During the ground-based simulation EXEMSI four crew members worked and lived for 60 days under conditions of confinement and isolation analogous to a long-term space mission. Our experiment focused on intra-individual changes in basic cognitive and psychomotor performance as a function of time spent under these environmental conditions. A subset of the AGARD-STRES battery of tests was repeatedly performed before, during, and after isolation. Results were derived from thorough single-subject analyses.

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A. Performance

No deterioration of short-term memory functions was found during and after the 60-day isolation period. Occasional performance decrements that occurred during isolation were also present in the non-isolated control group. Similar results were obtained with a short-term memory task during the 28-day isolation period of the ISEMSI study' and during a short-term mission to the Russian orbital station MIR.'' In the latter study the authors applied the same AGARD tasks twice a day and performed the same type of single-case analysis as in the present study. After a training period of 29 sessions each task was performed 23 times (6 pre-flight, 13 in-flight, 4 post-flight sessions). Comparisons of in-flight performance with preflight and post-flight baseline sessions revealed the following pattern of effects: (1) Speed and accuracy of short-term memory retrieval and logical reasoning remained unimpaired during the stay in space, (2) Clear disturbances of unstable tracking were found at the beginning and at the end of the mission, and (3) Time-sharing performance was impaired throughout the stay in space. Significant decrements of tracking performance were also observed in two subjects (B and G) in the present study. The time course of tracking accuracy followed in both subjects a distinct triphasic pattern with an initial deterioration, an intermediate recovery to pre-isolation baseline level after the first half of the isolation period, and a second deterioration at the end of isolation. An initial drop in tracking performance, though masked by the effects of further practice, could also be detected in the data from a third subject (H). Nearly equal decrements in tracking performance consistently emerged in single-task mode and dual-task mode. A weakness of the present study is that the five tasks were performed serially. Hence, accumulating fatigue towards the end of the session, rather than a specific impact of isolation on fine manual control, may be responsible for the observed decrements in tracking. This explanation is supported by the findings of Mecklinger, et al?' during the EXEMSI project. Their 34-min auditory classification task always preceded the present experiment and demanded a high level of sustained vigilance. They found decreased P300 amplitudes and increased reaction times elicited by rare tones in the chamber crew, which were not observed in their control group and which became more pronounced towards the end of the experimental session. Moreover, this time-on-task effect became stronger at the end of the EXEMSI mission. It is likely that in both experiments fatigue caused a suboptimal state of attention. An important difference in the MIR space study is that under real spaceflight conditions increased interference between tracking and concurrent memory search ~ccurred.'~ These findings suggest that the mechanisms involved in tracking deterioration appear to be different during adaptation to weightlessness than during a state of fatigue. It is likely that fine manual control disturbed by weightlessness causes a more profound re-structuring of the dual-task that also involves an impact on memory resource allocation. The AGARD-STRES battery was also applied in

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a study of the effects of sleep deprivation.I8The authors reported an even stronger effect in the single-task tracking test than in the dual-task tracking test. They concluded that “concurrent memory search maintained vigilance at a level sufficient to temper the effects of sleep deprivation on tracking.”” The same task battery was also applied to assess the impact on four professional saturation divers of a 30-day stay under a high ambient pressure environment reaching the equivalent of a depth of 450 meters below sea level.16The pattern of results was quite different from that obtained in space, isolation, and sleep deprivation. The most prominent feature was a general slowing of performance during the first 11 days, which included the compression phase and the bottom phase, with subsequent recovery to pre-dive baseline levels during the long return-to-surface period. Tracking was slightly impaired during the two days of the compression phase. Accuracy of memory retrieval and dual-task efficiency remained unimpaired. These different patterns of performance changes obtained with the AGARD tests under various kinds of suboptimal internal and external conditions are difficult to integrate into a single dimension of inadequate arousal level. They seem to support the assumption that multidimensional activation states are underlying task perf~rmance.’’*~~ B. Electroencephalogram

Two crew members of the confined crew displayed a consistent relationship between task demands and EEG power spectral activity of the alpha wave over Pz and, to a much weaker extent, of the theta wave over Fz.Alpha was markedly lower during tracking and both levels of the dual-task than during single memory search. Statistical confirmation of this observation was obtained by computing the power spectra of one subject over EEG segmentsof 10-sduration.The resulting time series were analyzed with the same technique of single-subject analysis as applied to the performance data. Changes in alpha power typically behave inversely to task difficulty, a less demanding task yielding a higher alpha power. This has been proven for simple laboratory tasks as well as for rather complex tasks such as during flight performance with varying mission complexity.21The attenuation of alpha power found in subjects transferring from a single-task to a dual-task has also been reported?’ The appearance of the alpha wave is obviously accompanied by a state of relaxed wakefulness, where mental activity is uncoupled from sensory inputs?6 Therefore, alpha attenuation on the transfer from single-task to dual-task may be due to an extension of perceptual cue utilization, which obviously takes place when continuous tracking is involved. The hypothesis of a link between alpha attenuation and perceptual cue utilization is further supported by the observation that a decrease in alpha power already emerges under single-task tracking, when continuous visuo-motor coordination is required. The same two subjects, who generated reliable alpha waves under task load, displayed a higher fronto-central theta wave during memory performance than during tracking. The effect could be substantiated statistically only in one subject

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by a single-subject analysis. In this particular subject a 7-Hz theta wave had a clear Fz topography accompanied by an alpha wave that peaked at 9.5 Hz over Cz and Pz. Because of the presence of slow alpha activity at the latter electrode sites it seems unlikely that the 7-Hz activity belonged to slow alpha. Thus, we suggest that this rhythm corresponds to a type of frontal theta activity that is associated with mental task engagement described in the literature. Gundel and Wilson22found an increased theta power with higher memory-load in a Stemberg memory search task with acoustically presented probes. Mecklinger, Kramer, and Strayerz3also found an increased power in the theta band as a function of memory load in a semantic memory search task. Similar appearances of fronto-midline theta during mental task performance were described by Mizuki, Takii, Nishijima, and Inanaga3’ and were attributed to concentrated attention. In a deep-sea diving simulation, Lorenz, Lorenz, and Heineke24observed a correlation between theta power and memory load in a memory search task, which also used letter stimuli. The effect increased markedly during the 33-day dive to a simulated depth of 450 meters. This suggests a synergistic effect of task load and suboptimal environmentalconditions.The most striking theta increases occurred during the mid decompression phase, where performance deteriorations had already recovered. Thus, in accordance with the present study, Fz-theta was accompanied with an efficient rather than a degraded performance during the dive. The correlation with the high subjectively reported level of concentration in the present study further supports the assumption that mental effort is linked to the generation of the frontal theta wave.

V. CONCLUSIONS AND SUMMARY A subset of the AGARD-STRESbattery including memory search, unstable tracking, and a combination of both tasks (dual-task), was applied repeatedly to the four chamber crew members before, during, and after the 60-day isolation period of EXEMSI. Five ground control group members served as a control group. A subjective state questionnaire was also included. The results were subjected to a quantitative single-subject analysis. Electroencephalograms (Em)were recorded to permit correlation of changes in task performance with changes in the physiological state. Evaluation of the EEG focused on spectral parameters of spontaneous EEG waves. No physiological data were collected from the control group., Significant decrements in tracking ability were observed in the chamber crew. The time course of these effects followed a triphasic pattern with initial deterioration, intermediaterecovery to pre-isolation baseline scores after the first half of the isolation period, and a second deterioration towards the end. None of the control group subjects displayed such an effect. Memory search (speed and accuracy) was only occasionally impaired during isolation, but the control group displayed a similar pattern of changes. It is suggested that a state of decreased alertness causes tracking deterioration,which leads to a reduced efficiency of sustained cue utiliza-

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tion. The assumption of low alertness was further substantiated by higher fatigue ratings by the chamber crew compared to those of the control group, Analysis of the continuous EEG recordings revealed that only two subjects produced reliable alpha wave activity (8-12 Hz) over Pz and, to a much smaller extent, Fz-theta wave activity (5-7 Hz) during task performance. In both subjects Pz-alpha power decreased consistently under task conditions involving single-task and dual-task tracking. Fz-theta activity was increased more by single-task and dual-task memory search than by single-task tracking. The alpha attenuation appears to be associated with an increasing demand on perceptual cue utilization required by the tracking performance. In one subject marked attenuation of alpha power occurred during the first half of the confinement period, where he also scored the highest fatigue ratings. A striking increase in fronto-central theta activity was observed in the same subject after six weeks of isolation. This change was associated with an efficient rather than a degraded task performance, and a high rating of the item “concentrated” and a low rating of the item “fatigued.” This finding supports the hypothesis that the activation state associated with increased fronto-central theta activity accompanies efficient performance of demanding mental tasks. The usefulness of standardized laboratory tasks as monitoring instruments is demonstrated by the direct comparability with results of studies obtained fromother relevant research applications using the same tasks. The feasibility of a self-administered integrated psychophysiological assessment of the individual state was illustrated by the nearly completecollection of data. The large number of individual data collected over the entire period permitted application of quantitative singlesubject analysis, allowing reliable determination of changes in the individual state in the course of time. It thus appears that this assessment technique can be adapted for in-flight monitoring of astronauts during prolonged spaceflights. Parallel EEG recording can provide relevant supplementary information for diagnosing the individual activation state associated with task performance. The existenceof large individual differences in the generation of task-sensitive EEG rhythms forms an important issue for further studies.

REFERENCES 1. Thornton, W.E., Moore, T.P., Pool. S.L., Vanderploeg, J. Clinical Characterization and Etiology

of Space Motion Sickness. Aviation. Space, and Environmental Medicine, ss(9, Suppl.):A I-AS.

1987. 2. Christensen, J.M., Talbot, J.M. A Review of the Psychological Aspects of Space Flight. Aviarion. Space, and Environmental Medicine, sI:203-212. 1986. 3. Kanas, N. Psychosocial Factors Affecting Simulated and Actual Space Missions. Aviation, Space, and Environmental Medicine, 56:806-811, 1985. 4. Gushin, V.I., Kholin, EE. Ivanovsky, Y.R. Soviet Psychophysiological Investigations of Simulated Isolation: some results and prospects. In: Advances in Space Biology and Medicine, vol. 3 (S.L. Bonting. Ed.), pp. 5-14. JAI Press, Greenwich. CT.1993.

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5. Holland, A.W. NASA Investigations of Isolated and Confined Environments. In: Advances in Space Biology and Medicine, vol. 3 (S.L. Bonting. Ed.), pp. 15-21. JAI Press, Greenwich. Cr, 1993. 6. Hockey. G.R.J. Changes in Operator Efficiency as a Function of Environmental Stress, Fatigue, and Circadian Rhythms. In: Handbook of Perception and Human Performance, vol. 2. (K.R. Boff, L. Kaufman, and J.P. Thomas, Eds.). pp. 44-14-49, Wiley. New York, 1986. 7. Vsmes, R.J., Bergan. T., Lindrup, A., Hammerborg. D., Wamcke. M. Mental Performance. In: Advances in Space Biology and Medicine, vo1.3 (S.L. Bonting, Ed.), pp. 121-137, JAI Press, Greenwich, CT. 1993. Peru. A. Attention during Isolation and Confinement. In: Advances in Space Biology 8. Riuolatti, G., and Medicine, vol. 3 (S.L. Bonting, Ed.), pp. 151-162, JAI Press, Greenwich, Cr,1993. 9. Hockey, G.R.J., Wiethoff, M. Cognitive Fatigue in Complex Decision Making. In: Advances in Space Biology and Medicine, vol: 3 (S.L. Bonting, Ed.), pp. 139-150, JAI Press, Greenwich, CT, 1993. 10. Gushin. V.1.. Efimov. V.A., Smimova. T.M. Joy-Test Investigation of Dynamic Changes of Work

Capability under Isolation. In: Advances in Space Biology and Medicine. vol. 5 (S.L. Bonting, Ed.), pp. xx-xx. JAI Press, Greenwich, Cr,1995. 11. Gaillard A.W.K. Integral Monitoring In Space. In: Exploratory Studies Programmefor the Future European Mnnned Spncelnfrastructure (ESA - Long Term Programme Office), Space Psychology Days 2,2427 March, Villefranche-sur-Mer, LTPO-SR-92-01, France, 1992. 12. Kantowitz, B.H. Selecting Measures for Human Factors Research. Human Factors, 34:387-398,

1992. 13. Cook, T.D., Campbell, D.T. Quasi-Everimentation: Design andAnalysisIssuesfor FieldSenings, Rand McNally, Chicago, 1979. 14. Bitmer, A.C. Jr., Carter, R.C.. Kennedy, R.S.. Harbeson, M.M., Krause, M. Performance Evaluation Tests for Environmental Research (PETER): Evaluation of 114 Measures. Perceptual and Motor Skills. 63683-708. 1986. 15. Manzey. D., Schiewe, A.. Lorenz, B., Finell, G.Monitoring of Cognitive and Psychomotor Performance during Space Flight. Paper presented at the 10th IAA Man in Space Symposium, Tokyo, April 19-23,1993. 16. Lorenz, B., Brooke. S.T., Holmes. C., Lorern, J., Finell. G.Cognitive and psychomotor performance monitoring during the AURORA '93 450-meter simulated saturation dive. In: AURORA '93 Dive Report, vol. 2. (National Hyperbaric Centre, Ed.),pp. 21-37, Aberdeen, 1993. 17. AGARDOgraph No. 308. Human Perf-ance Assessment Methods. AMP Working Group 12 and AGARD Lecture Series 163, AGARD, Neuilly-Sur-Seine. 1989. 18. Batejat. D.. Lagarde. D. Evaluation of the Sensitivity to Seven Psychomotor Tests during Prolonged Sleep Deprivation. Journal of Sleep Researrh (supplement).1:16. 1992. 19. Hockey, G.R.J., Hamilton, P. The Cognitive Patterning of Stress States. In: Stress and Fatigue in Human Performance (G.R.J. Hockey, Ed.), pp. 331-362, Wiley, New York, 1983. 20. Sanders,A.F. Towards a Model of Stress and Human Performance. Acta Ps)rhologica. 53:61-97, 1983. 21. Kramer, A.F. Physiological Memcs of Mental Workload A Review of Recent Progress. In: Multiple Task Performance (D.L. Damos. Ed.),pp. 279-328. Taylor & Francis, London, 1991. 22. GundeL A., Wilson. G.Topograph~calchanges in the ongoing EEG related to the difficulty of mental tasks. Brain Topography, 517-25,1992. 23. Mecklinger, A., Kramer. A.F.. Strayer, D.L. Event-Related Potentials and EEG Components in a Semantic Memory Search Task. Psychophysiology. 2 9 104-1 19,1992. 24. Lorem. J., Lorenz. B.. Heineke, M. Effect of Mental Task Load on Frontc&mral Theta Activity in a Deep Saturation Dive to 450 msw. Undersea Biomedical Research, 19243-262, 1992.

Performance and Brain Electrical Activity 25. Van Winsum, W.. Sergeant, J., G e m . R. The Functional Significance of Event-Related D

181

~ chronisation of Alpha Rhythm in Attentional and Activating Tasks. Electroencephalography a d Clinical Neurophysiology. 58519-524. 1984. 26. Fassbender. C.. Goeters. K. Definition of Psychological Testing of Astronaut Candidatesfor Columbus Missions. Technical report, ESA-8730/90NL/TW, DLR. Hamburg, 1991. 27. Stemberg. S. High Speed Scanning in Human Memory. Science, 153:652454,1966. 28. Jex. H.R.. McDonnell, J.D., Phatak. A.V. A"Critical"TrackingTaskfor ManualControl Research. IEEE Transactions on Human Factors irr Electronics, 7: 138-144. 1966. 29. Beringer, J. Entwutf einer Anwendersprache zur Steuerung psychologischer Reaktionszeitexperimente (Concept of a User-Language for Programming Psychological Reaction lime Experiments), Lang, FrankfurtfMain, 1993. 30. Jaspers. H.H. The Ten-?\verity Electrode System of the International Federation. Electroencephalography and Clinical Neurophysiology, 20:37 1-375. 1958. 31. Mecklinger. A., Friederici, A,, Giissow, T. Attention and Mental Performance in Confinement: Evidence from Cognitive Psychophysiology. In: Advances in Space Biology and Medicine, vol. 5 (S.L. Bonting, Ed.), pp. xx-xx. JAI Press, Greenwich, C l ' , 1995. 32. Kirk, R.E. Experimental Design, 2nd ed., Brooks/Cole, Belmont. 1982. 33. Hibbs, D.A. Jr. Problem of Statistical Estimation and Casual Inference in Time-Series Regression Models. In: Sociological Methodology (H.C. Cosmer, Ed.), pp. 252-308, Jossey-Bass. San Francisco, 1974. 34. Glass. G.V., Willson, V.L. Gottman, Y.M. Design and Analysis of lime-Series Experiments, Boulder, Associated University Press, 1975. 35. Sirevaag. E., Kramer. A., de Jong. R.. Mecklinger, A. A Psychophysiological Analysis of MultiTask Processing Demands. Psychophpiology. 25(Suppl.):482, 1988. 36. Bhel. R. Langsames Alpha im EEG-Powerspektrum als Indikator fiir konzeptuelle Beanspruchung (Slow Alpha in the EEG Power Spectrum as Indicator for Conceptual Load). Zeitschrifr fur experimentelle und angewandte Psychologie, 3372-395, 1992. Nishijima, H., Inanaga, K.The Relationship between the Appearance of 37. Mizuki, Y.. Takii. 0.. Frontal Midline Theta Activity and Memory Function. Electroencephalography and Clinical Neurophysiology. 56.56, 1983.

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