Open Access

Effect of mental fatigue on the central nervous system: an electroencephalography study

  • Masaaki Tanaka1Email author,
  • Yoshihito Shigihara1,
  • Akira Ishii1,
  • Masami Funakura2,
  • Etsuko Kanai2 and
  • Yasuyoshi Watanabe1, 3
Behavioral and Brain Functions20128:48

https://doi.org/10.1186/1744-9081-8-48

Received: 19 March 2012

Accepted: 16 August 2012

Published: 6 September 2012

Abstract

Background

Fatigue can be classified as mental and physical depending on its cause, and eachtype of fatigue has a multi-factorial nature. We examined the effect of mentalfatigue on the central nervous system using electroencephalography (EEG) in eighteenhealthy male volunteers.

Methods

After enrollment, subjects were randomly assigned to two groups in a single-blinded,crossover fashion to perform two types of mental fatigue-inducing experiments. Eachexperiment consisted of four 30-min fatigue-inducing 0- or 2-back test sessions andtwo evaluation sessions performed just before and after the fatigue-inducingsessions. During the evaluation session, the participants were assessed using EEG.Eleven electrodes were attached to the head skin, from positions F3, Fz, F4, C3, Cz,C4, P3, Pz, P4, O1, and O2.

Results

In the 2-back test, the beta power density on the Pz electrode and the alpha powerdensities on the P3 and O2 electrodes were decreased, and the theta power density onthe Cz electrode was increased after the fatigue-inducing mental task sessions. Inthe 0-back test, no electrodes were altered after the fatigue-inducing sessions.

Conclusions

Different types of mental fatigue produced different kinds of alterations of thespontaneous EEG variables. Our findings provide new perspectives on the neuralmechanisms underlying mental fatigue.

Keywords

Central nervous system Electroencephalography Mental fatigue N-back Test

Background

Fatigue is a common symptom. In Japan, more than half of the general adult populationsuffers from fatigue [1]. Fatigue decreases efficiency in the performance of daily activities. Inaddition, fatigue is one of contributing factors for various medical conditions such ascardiovascular diseases [2], epileptic seizures [3], and Karoshi (death from overwork) [4]. It would thus be of great interest to clarify the mechanisms underlyingfatigue and to develop efficient methods for overcoming it. However, the neuralmechanisms of fatigue are not well understood.

Fatigue is classified as physical or mental. Physical fatigue is a bodily weakness thatcan occur because of repetitive muscle activity. In contrast, mental fatigue is observedas a reduced efficiency for mental tasks [5]. Recently, new methods of induction and evaluation of mental fatigue havebeen proposed [6]. In a mental-fatigue-inducing task session, participants performed 0- or2-back test trials [7]. The 0-back test was used to represent a lower mental-load task, which couldbe performed without use of working memory, while the 2-back test was used to representa higher mental-load task, which could not be performed without using working memory [8]. The advantage of using these tasks is in their ability to cause differenttypes of mental fatigue. Since mental fatigue is a multi-faceted problem [5], it is of great importance to cause mental fatigue using different types oftasks. As a fatigue evaluation mental task session, participants performed cognitivetasks, which are computer-based mental function tasks and the participants were requiredto use simple and conflict-controlling selective attention. After the 0- or 2-back testsessions, error rates of the evaluation tasks were increased, thus demonstrating adeterioration of the task performance. Task performances were used to assess mentalfatigue, and the reliability and validity of the evaluation tasks were satisfactory.

Although a variety of psychophysiological parameters have been used in previous researchdealing with fatigue, spontaneous electroencephalography (EEG) has been proposed as themost promising indicator of fatigue [9]. The electrical activity of the brain is classified according to rhythms,which are defined according to frequency bands, including beta, alpha, theta, and delta,and each frequency band is associated with specific internal information processing inthe central nervous system [10]. Therefore, alterations of resting-state EEG power induced by mental fatiguemay provide valuable clues to identify its neural mechanisms. The aim of our study wasthus to clarify the neural underpinnings of mental fatigue using EEG.

Methods

Participants

Eighteen healthy male volunteers [30.1 ± 10.8 years of age(mean ± SD)] were enrolled in this study. Current smokers,participants having a history of medical illness, taking chronic medications orsupplemental vitamins, or with a body weight less than 40 kg were excluded fromthe study based on our previous studies [1115]. The study protocol was approved by the Ethics Committee of Osaka CityUniversity, and all the participants provided written, informed consent.

Experimental design

After enrollment, the participants were randomly assigned to two groups in asingle-blinded, crossover fashion to perform two types of fatigue-inducingexperiments on separate days (Figure 1A). The time intervalbetween each experiment was approximately 1 week. Each experiment consisted offour 30-min mental-fatigue-inducing task sessions and two evaluation sessionsperformed just before and after the fatigue-inducing sessions (Figure 1B). During the evaluation session, subjects were evaluated using EEG andelectrocardiography (ECG) with their eyes closed for 1 min sitting quietly.Subjects performed cognitive task trials for 9 min, and were then asked to ratetheir subjective level of fatigue on a Visual analogue scale (VAS) from 0 (minimum)to 100 (maximum) [16]. Saliva samples were collected. This study was conducted in a room atOsaka City University Graduate School of Medicine under quiet, temperature- andhumidity-controlled conditions. For 1 day before each session, subjectsrefrained from intense mental and physical activities, consumed a normal diet andbeverages (excluding caffeinated beverages), and maintained normal sleeping hours.They had breakfast just before the session.
Figure 1

Experimental design (A) and procedures during experimental sessions (B). Participants were randomly assigned to two groups in a crossover fashion toperform two types of fatigue-inducing n-back test experiments on separate days.The time interval between each experiment was 1 week. Each experimentconsisted of four 30-min fatigue-inducing mental task sessions and twoevaluation sessions performed just before and after the four fatigue-inducingsessions.

Fatigue-inducing mental task sessions

Participants performed a 0-back or 2-back test for 30 min four times asfatigue-inducing mental task sessions [7]. During this task, one of four letters was presented for 1 s on adisplay of a personal computer every 3 s. In the 0-back test trial,participants were asked to press the right button with their right middle finger ifthe target letter (shown beside the personal computer) was presented at the center ofthe screen. If any other letters appeared, they were to press the left button withtheir right index finger. In the 2-back test trial, they had to judge whether thetarget letter presented at the center of the screen was the same as the one that hadappeared two presentations before. If it was the same, they were to press the rightbutton with their right middle finger. If it was not the same, they were to press theleft button with their right index finger. They were instructed to perform the tasktrials as quickly and as correctly as possible. The result of each n-back trial, thatis, a correct response or error, was continuously presented on the display of thepersonal computer.

Cognitive tasks

The cognitive task presentation consisted of traffic lights (placed on a lettercorresponding to blue or red in Japanese) and traffic signs for walkers (right orleft) and turns (right or left) shown on a personal computer screen. Participantsperformed Task 1 for 3 min and Task 2 for 6 min. In Task 1, participantswere told to press the right button with their right middle finger if the bluetraffic light was presented (placed on a letter corresponding to blue in Japanese)regardless of traffic signs for walkers or turns. If the red traffic light waspresented, participants were told to press the left button with their right indexfinger. In Task 2, subjects had to judge whether the target letter presented at thecenter of a traffic light was blue or red. If the letter meant blue inJapanese, regardless of the color of the traffic light or traffic signs forwalkers or turns, they were to press the right button with their right middle finger;otherwise, they were to press the left button with their right index finger. TheStroop trial (mismatching the color of the traffic light with the letter) and thenon-Stroop trial (matching the color of the traffic light with the letter) occurredequally. In these tasks, each trial was presented 100 ms after pressing eitherof the buttons. During the task period, blue or red trials and traffic signs forwalkers (right or left) and turns (right or left) were given randomly, and theoccurrence of each color and type of sign was equal. Subjects were instructed toperform the task trials as quickly and as correctly as possible. The result of eachcognitive task trial, that is, a correct response or error, was continuouslypresented on the display of the personal computer.

Electroencephalography

EEG was performed using an EEG system (Neurofax μ EEG-9100; Nihon KohdenCorporation, Tokyo, Japan). Eleven electrodes (Ag/AgCl) were attached to the headskin, from positions F3, Fz, F4, C3, Cz, C4, P3, Pz, P4, O1, and O2; andelectrooculography (EOG) was also measured to evaluate ocular artifacts. All theelectrodes were referenced to linked earlobes. Electrode impedance was maintainedbelow 5 kΩ during the experiment. The EEG was amplified with a 0.3-s timeconstant and a 120-Hz low-pass filter, and sampled at 500 Hz. Prior tofrequency analysis, all EEG data were divided into each epoch, with a duration of1 s. The recorded data were visually inspected and data segments containingpossible residual artifacts were eliminated. EEG larger than +50 μV wererejected as artifact. EOG artifact was also removed by using EOG signals aspredictors of the artifact voltages at each EEG electrode. After artifact detection,the data were subjected to a fast Fourier transform, and after averaging, the powerwas determined in four frequency bands, beta (13–25 Hz), alpha(8–13 Hz), theta (4–8 Hz), and delta (1–4 Hz),for each participant, electrode, and epoch. The average power densities in thesefrequency bands were log-transformed (ln) for normalization [17].

Electrocardiography

ECG was recorded using active tracer AC301 (Global Medical Solution Inc., Tokyo,Japan), and the ECG was analyzed using MemCalc for Windows (Global Medical SolutionInc.). Data were analyzed offline after analogue-to-digital conversion at250 Hz. R-R wave variability was measured as an indicator of autonomic nerveactivity. For frequency domain analyses of the R-R wave intervals, low-frequencypower (LF) was calculated as the power within the frequency range of 0.04 to0.15 Hz, high-frequency power (HF) was calculated as that within the frequencyrange of 0.15 to 0.4 Hz. LF and HF were measured in normalized units.Normalization was performed by dividing the absolute power by the total variance thenmultiplying by 100. The %HF is vagally mediated [1820], but the %LF originates from a variety of sympathetic and vagal mechanisms [19, 21]. The LF/HF ratio is considered an index of sympathetic nervous systemactivity [22].

Saliva sample analyses

We measured saliva cortisol level in order to examine whether the n-back testsessions cause stress response. Saliva samples for the analysis of cortisol werecollected in a tube (Salivette; Sarstedt, Rommelsdorf, Germany) and kept on ice untilcentrifuged at 1700 g for 5 min at 4°C. These supernatants werestored at −80°C until analyzed. The assay for cortisol level was performedby Special Reference Laboratories (SRL; Tokyo, Japan).

Statistical analyses

The paired t-test was used to evaluate the significance of differencesbetween the two conditions. All P values were two-tailed, and values less than 0.05were considered to be statistically significant. Statistical analyses were performedusing the SPSS 17.0 software package (SPSS, Chicago, IL).

Results

Subjective levels of fatigue, cognitive task performances, ECG parameters and salivacortisol levels for the fatigue-inducing n-back test sessions are summarized in Table1. VAS scores of general and mental fatigue were significantlyincreased after the 0- and 2-back test sessions. As for the cognitive task performances,error rates of Task 2 were significantly increased after the 0- and 2-back testsessions. As for the ECG variables, the LF/HF ratio was increased after the 2-back testsessions although this ratio was not altered after the 0-back test sessions. Salivacortisol levels were not altered after the 0- or 2-back test sessions.
Table 1

Measurements before and after the fatigue-inducing mental task sessions

 

0-back test

2-back test

 

Before

After

Before

After

VAS for fatigue

    

General fatigue

15.8 ± 11.2

53.2 ± 24.2a

14.5 ± 10.4

47.8 ± 23.0a

Mental fatigue

15.2 ± 9.9

50.9 ± 27.5a

13.2 ± 10.0

47.0 ± 26.0a

Cognitive tasks

    

Error rate of Task 1

2.4 ± 1.9

3.4 ± 3.3

2.6 ± 2.1

3.7 ± 3.7

Error rate of Task 2

4.4 ± 3.3

6.8 ± 4.9a

5.1 ± 4.0

7.1 ± 5.2a

ECG

    

LF/HF

2.8 ± 5.2

3.7 ± 2.4

1.7 ± 1.0

4.2 ± 3.8b

%LF (%)

32.3 ± 16.7

43.2 ± 17.8

34.8 ± 14.9

40.0 ± 23.2

%HF (%)

32.0 ± 25.0

18.3 ± 13.6b

26.2 ± 14.1

18.2 ± 17.2

Saliva cortisol (nmol/l)

9.4 ± 4.5

9.4 ± 4.5

8.7 ± 3.3

7.2 ± 3.3

Data are presented as mean ± SD.

VAS, visual analogue scale; LF, low-frequency power; HF high-frequencypower.

aP < 0.01,bP < 0.05, significantly different from thecorresponding values before the fatigue-inducing mental task sessions (pairedt-test).

The spontaneous EEG beta power densities before and after the fatigue-inducing mentaltask sessions are shown in Figure 2. In the 2-back test, the betapower density on the Pz electrode was significantly decreased after the fatigue-inducingmental task sessions. In the 0-back test, the beta power densities were not altered onany of the electrodes after the fatigue-inducing task sessions.
Figure 2

Electroencephalographic beta power densities before (open columns) and after(closed columns) 2- (A) and 0-back (B) test sessions and Gaussian distributionsof the power densities on the Pz electrode before (solid line) and after(dotted line) 2-back test session (C). Data are presented as mean and SD.aP < 0.05, significantly different from thecorresponding values before the fatigue-inducing sessions (pairedt-test).

The EEG alpha power densities before and after the fatigue-inducing mental task sessionsare shown in Figure 3. In the 2-back test, the alpha powerdensities on the P3 and O2 electrodes were significantly decreased after thefatigue-inducing mental task sessions.
Figure 3

Electroencephalographic alpha power densities before (open columns) and after(closed columns) 2- (A) and 0-back (B) test sessions and Gaussian distributionsof the power densities on the P3 (C) and O2 (D) electrodes before (solid lines)and after (dotted lines) 2-back test session. Data are presented as meanand SD. aP < 0.05, significantly different from thecorresponding values before the fatigue-inducing sessions (pairedt-test).

The EEG theta power densities before and after the fatigue-inducing mental task sessionsare shown in Figure 4. In the 2-back test, the theta power densityon the Fz electrode was significantly increased after the fatigue-inducing mental tasksessions. In the 0-back test, the theta power densities were not altered on any of theelectrodes after the fatigue-inducing task sessions.
Figure 4

Electroencephalographic theta power densities before (open columns) and after(closed columns) 2- (A) and 0-back (B) test sessions and Gaussian distributionsof the power densities on the Fz electrode before (solid line) and after(dotted line) 2-back test session (C). Data are presented as mean and SD.cP < 0.05, significantly different from thecorresponding values before the fatigue-inducing sessions (pairedt-test).

The theta/beta and theta/alpha ratios before and after the fatigue-inducing mental tasksessions are also evaluated. In the 2-back test, the theta/beta ratios on the Fz(before, 1.89 ± 0.55, after, 2.26 ± 1.11;P = 0.044), Pz (before, 1.62 ± 0.46, after,1.97 ± 0.95; P = 0.047), and O1 (before,1.47 ± 0.49, after, 1.75 ± 0.82;P = 0.011) electrodes were significantly increased after thefatigue-inducing mental task sessions, although the theta/alpha ratio did not show anyalterations. In the 0-back test, the theta/beta and theta/alpha ratios were not alteredon any of the electrodes after the fatigue-inducing task sessions.

Finally, the EEG delta power densities before and after the fatigue-inducing mental tasksessions are shown in Figure 5. In the 0- and 2-back tests, thedelta power densities were not altered on any of the electrodes after thefatigue-inducing task sessions.
Figure 5

Electroencephalographic delta power densities before (open columns) and after(closed columns) 2- (A) and 0-back (B) test sessions. Data are presented asmean and SD.

Discussion

We found that in the 2-back test, the beta power density on the Pz electrode and thealpha power densities on the P3 and O2 electrodes were decreased, and the theta powerdensity on the Cz electrode was increased after the fatigue-inducing mental tasksessions, while in the 0-back test, no electrodes were altered after thefatigue-inducing sessions.

To confirm that the participants were actually fatigued as a result of performing n-backtest trials, they performed cognitive task trials and rated their subjective level offatigue just before and after the n-back test sessions. After the n-back test sessions,error rates of Tasks 2 were increased (Table 1). These findingsare consistent with those of our previous studies [6, 23]. In addition, the VAS scores for general and mental fatigue were increasedafter the sessions (Table 1). These findings demonstrate that theparticipants were markedly fatigued after the n-back test sessions, and also demonstratethe validity of using the n-back test sessions as fatigue-inducing. No alterations ofthe saliva cortisol levels demonstrate that the n-back test sessions induced fatiguewithout or minimum influence of stress or stress response.

The theta power density on the Fz electrode was increased after 2-back task sessions.This finding is consistent with the results of the previous studies, in which fatiguewas caused by performing a monotonous simulation driving task [24] or Stroop neuropsychological test [25] for 90 min without any break: In these studies, the theta power densityon the frontal EEG electrode site was increased after the mental fatigue-inducing tasktrials. It has been reported that the theta power density is positively related tosleepiness [26, 27]. Thus, alteration of the theta power density in our study may be caused bysleepiness. In fact, the subjective level of sleepiness was increased after thefatigue-inducing mental task sessions (data not shown). Since sleep is one of the mostefficient strategies to recover from fatigue, the sleepiness caused by mental fatiguemay reflect internal processes designed to meet the demand to recover from mentalfatigue. Alternatively, since theta oscillations arising from predominantlyfronto-central sources are increased by working memory load [10, 28], alteration of the theta power density may be caused just by working memoryload caused by performing 30-min 2-back test trials.

In the 2-back test, the beta power density on the Pz electrode and the alpha powerdensities on the P3 and O2 electrodes were decreased after the fatigue-inducing mentaltask sessions. Our results of the decreased beta and alpha power densities areconsistent with the results of previous studies: The beta power density was decreased byperforming a monotonous simulation driving task for 90 min without break [24]; while the alpha power density was decreased by keeping awake and activeovernight [29]. While local synchronization in the brain during information processingevolved in the gamma frequency range, synchronization between neighboring corticesduring multi-modal information processing evolved in the beta frequency range, and longrange interactions during high-level information processing such as visuospatialattention evolved in the alpha frequency range [30]. Since multi-modal and high-level information processing are associated withthe beta and alpha power densities, respectively, decreased beta and alpha powerdensities under conditions of mental fatigue indicate deterioration of multi-modal andhigh-level information processing in the central nervous system. Our results for thecognitive tasks (Table 1) support this speculation.

Different types of mental fatigue produced different styles of the alterations of theEEG variables: in the 2-back test, the beta power density on the Pz electrode and thealpha power densities on the P3 and O2 electrodes were decreased, and the theta powerdensity on the Fz electrode was increased. In the 0-back test,no electrodes were alteredafter the fatigue-inducing sessions. The 0-back test was used to represent a lowermental-load task, which could be performed without working memory use, while the 2-backtest was used to represent a higher mental-load task, which could not be performedwithout working memory use [7]. Most of the locations that showed changes of beta and alpha power densitiesare located close to the visual areas (P3, Pz, and O2) in the 2-back test. Higher mentalload to perform 2-back test may need more visual memory and implies more visual work indifferent visual areas to develop the fatigue-related alterations of EEG power densitiesin the posterior areas related to visual processing. Higher mental load thus may triggerprocesses designed to bring about deterioration of multi-modal and high-levelinformation processing, while lower mental load may induce fewer alterations.

In addition to EEG, different types of mental fatigue produced different styles of thealterations of the ECG variables. The LF/HF ratio was increased after the 2-back testsessions although this ratio was not altered after the 0-back test sessions. Sinceincreased LF/HF ratio during mental fatigue-inducing task session was reported to beassociated with the mental effort or motivation [23], the different results of the LF/HF ratio between the 0- and 2-back testsessions might result from the difference of the mental effort or motivation between thesessions. The brain network, including the prefrontal cortex (PFC) and anteriorcingulate cortex (ACC), has been shown to play an important role in the regulation ofautonomic nervous activities [31]. Abnormalities in these brain regions have been shown to be associated withfatigue [32, 33]. Because impaired selective attention assessed by increased error rates incognitive task trials were observed after the fatigue-inducing mental task sessions, andthe selective attention process activates the PFC and ACC [3437], the higher mental load required for the 2-back test sessions might introducetemporary dysfunctions in the PFC and ACC to cause decreased parasympathetic andincreased sympathetic activities, while lower mental load necessary for performing the0-back test sessions might induce fewer alterations of the ECG variables.

Limitations

While the results of the present study are suggestive of causal relationships betweeninformation load and mental fatigue, only a limited number of participants weretested. The ratio of fatigue was similar between men and women in the society [38]. However, it is not clear whether the findings in our study can beconsidered to be the same in women. To generalize our results, studies involving alarger number of participants will be needed.

Conclusions

We identified mental fatigue-related changes in spontaneous EEG variables. In the 2-backtest, the beta power density on the Pz electrode and the alpha power densities on the P3and O2 electrodes were decreased, and the theta power density on the Cz electrode wasincreased after the fatigue-inducing mental task sessions, while in the 0-back test, noelectrodes were altered after the fatigue-inducing sessions. Our findings provide newperspectives on the neural mechanisms underlying mental fatigue.

Abbreviations

ACC: 

Anterior cingulate cortex

ECG: 

Electrocardiography

EEG: 

Electroencephalography

HF: 

High-frequency power LF, low-frequency power

PFC: 

Prefrontal cortex

VAS: 

Visualanalogue scale.

Declarations

Acknowledgements

We thank Forte Science Communications for editorial help with the manuscript. Thiswork was supported in part by the Ministry of Health, Labour and Welfare of the Japanand by the Grant-in-Aid for Scientific Research B (KAKENHI: 23300241) from Ministryof Education, Culture, Sports, Science and Technology (MEXT) of Japan and by thegrant from Ministry of Health, Labor and Welfare of Japan. The funders had no rolesin study design, data collection and analysis, decision to publish, or preparation ofthe manuscript.

Authors’ Affiliations

(1)
Department of Physiology, Osaka City University Graduate School of Medicine
(2)
Degital & Network Technology Development Center, Panasonic Corporation
(3)
Center for Molecular Imaging Science, RIKEN

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