The impact of mental fatigue on brain activity: A comparative study between resting state and task state using EEG

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Mental fatigue has become a widespread sub-health condition, and has a serious impact on the cognitive function of the brain. However, seldom researches explore the differences of mental fatigue on electrophysiological activity between resting state and task state. In the present study, 20 healthy male individuals were recruited to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) data were collected before and after the task. The power and relative power of five EEG rhythms both in resting state and task state were analyzed statistically. Results: The results of brain topographies and statistical analysis indicated that mental arithmetic task can successfully induce mental fatigue in the enrolled subjects. The relative power index was more sensitive than the power index in response to mental fatigue, and the relative power for assessing mental fatigue was better in resting state than in task state. Furthermore, we found that it is of great physiological significance to divide alpha frequency band into alpha1 band and alpha2 band in fatigue related studies, and at the same time improve the statistical differences of sub-bands. Conclusions: Our current results suggested that the brain activity in mental fatigue state has great differences between resting state and task state, and it is imperative to select the appropriate state in EEG data acquisition and divide alpha band into alpha1 and alpha2 bands in mental fatigue related researches. Computational Neuroscience Developmental Neuroscience Mental fatigue EEG resting state task state Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Mental fatigue refers to a condition of low alertness and cognitive impairment [1]. Too much brain activity and stimulation can make a person feel mentally exhausted, and this feeling is akin to physical fatigue. Mental fatigue can give rise to numerous bad consequences, for example, making the uncomplicated tasks turn to be increasingly difficult or even impossible. Mental fatigue has become a popular subhealthy states in nowadays society, and affects nearly all aspects of cognitive functioning in humans [2], such as driving fatigue [3]. Concerning the effects of mental fatigue on daily life, it is important to reveal the differences of mental fatigue on brain activity between resting state and task state. Previous studies have been centered on the changes associated with task-related brain activity[4]. The fatigue-inducing mental tasks were widely used by researchers. The mental tasks that requiring different intensity of attention can differentiate the levels of mental fatigue, and their experimental duration could be distinct. The n- back task [5, 6] and psychomotor vigilance task [7, 8] (PVT) can be categorized as high-attention-demanding tasks, sleep deprivation [9] can be classified into low-attention-demanding tasks, meanwhile mental arithmetic task [10] and driving simulation task[11] fall into middle-attention-demanding tasks. However, among these three-type tasks, the middle-attention-demanding tasks are greatly in line with our daily working load. Therefore, we chose mental arithmetic task to induce mental fatigue. Historically, mental fatigue has been most prevalently studied with the neuroimaging technique of EEG on account of its high temporal resolution, low costs, and easy operation [12–14]. It has been widely proved that mental fatigue can lead to distinct changes in EEG[15]. Strijkstra has found that EEG during resting awake periods with eyes closed shows strong negative correlations of alpha power and positive correlations of theta power with subjective sleepiness[16]. With the mental fatigue increasing, the power spectrum density of alpha rhythm increases when eyes open and decreases when eyes closed[17]. These changes in EEG can be used to detect mental fatigue [10, 15], which is especially important and meaningful for driving fatigue estimation [7, 11]. From the above, we can conclude that EEG has become the most effective technical means for exploring the neuromechanism and detection of mental fatigue [18, 19]. The current study is also motivated by the studies which have divided the EEG bands into narrower bands. In mental fatigue related studies, some researchers divided alpha band into alpha1 (8–10Hz) and alpha2 (10–13Hz). Li has performed statistical analysis on the characteristics of alpha1 and alpha2 to estimate mental fatigue, and reported that alpha1 band is better for fatigue detection [10]. Sun has applied alpha1 frequency band for mental fatigue classification, and achieved a high prediction accuracy [20]. In the current study, we attempted to investigate the differences of mental fatigue on electrophysiological activity between resting state and task state. To this end, we administered a challenging sustained mental arithmetic math task for a group of young healthy male participants to induce mental fatigue, and EEG data for resting state and task state before and after the tasks were collected. Then the power and relative power of delta, theta, alpha1, alpha2, and beta were computed, and statistical analysis (analysis of variance, ANOVA) were carried on the results among different brain regions. Materials and Methods Participants Twenty male participants (age was 24.5±1.5 years, and body mass index was 20.7±1.8 kg/m 2 ) were recruited. Each subject should be right-handed, and should have a regular life, normal normal eyesight, and no brain diseases. Before the tests, every participant was required to do as follows: (1) not staying up late at night, (2) not drinking alcohol and drugs in one week preceding the EEG test, (3) not smoking and drinking coffee and tea in 8 hours before EEG data acquisition, and (4) washing their hair in 2 hours before the experiment. Every participant was informed the experimental procedures and the local Ethics Committee have approved this study. Each subject gained some monetary reimbursement to motivate their better performances during the tests. EEG data recording EEG data were recorded by a digital EEG apparatus (SYMTOP NT9200) at the following nineteen electrodes of the 10–20 systems: Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, T3, T4, T5, T6, Fz, Cz, and Pz (A1 and A2 were chosen as the reference electrodes, Fpz was specified as the grounding-electrode, sample frequency was 1000 Hz, electrode impedance was controlled under 5000 Ω). In order to induce mental fatigue, every subject was required to do a mental arithmetic task with 200 different problems for 100 minutes. The mental arithmetic problem was designed as: a random double-digit (between 60 and 90) plus another random double-digit (between 60 and 90) and then multiplied by a random single digit (between 6 and 9). Each math problem was designed to be done in 30 seconds determined by preceding pretests. As shown in Figure 1, the whole mental arithmetic task was equally divided into 4 tasks, and EEG was collected for both resting state and task state. Therefore, there were 5 times EEG data acquisition named as T0, T1, T2, T3 and T4 for the whole task. Besides, resting state means closing the eyes, being awake and relaxed, and subjects were required to concentrate their attention on the breath avoiding thinking about anything, whereas task state refers to keep the body still and do a mental arithmetic math problem, a three-digit subtracts a single digit continuously (keep same for every data recordings). All the mental arithmetic math problems were automatically displayed on the computer screen one by one. The whole test was carried on from 7 pm to 9 pm in a sound attenuated, and light, temperature, and humidity controlled room. EEG data preprocessing EEG signals from only eighteen subjects were analyzed for further analysis. The other two were excluded because of their big head movements when recording the EEG. In the current analysis, ten pieces of five seconds of artifact-free continuous EEG data (containing no eye blinks, no slow eye movements, no electrocardiogram artifacts (eliminated by Fast ICA), and no baseline drift (removed by baseline correction)) were selected from each condition by EEGLAB. These pieces of data were then down sampled from 1000Hz to 256 Hz. And EEG rhythms (delta: 2–4 Hz; theta: 4–8 Hz; alpha1: 8–10 Hz; alpha2: 10–13 Hz; beta: 13–30 Hz) were extracted by digital FFT filtering. Computation of EEG indices In this study, the power and relative power of every EEG rhythms were explored. The frequency spectrum X( f) of EEG signal x( n) was obtained by means of FFT, and then the power spectrum P x( f) of EEG were gained with equation (1). The power E( h) and relative power R( h) were calculated through equation (2) and equation (3). Where, in equation (1), equation (2) and equation (3), N is the number of EEG signal x( n), , h represents the EEG rhythms (such as delta, theta, alpha1, alpha2, beta), f h and f l are the upper and lower frequencies of h rhythm respectively, E total is the total power of all EEG rhythms. Besides, all the calculated power spectrum are the average value of the selected 10-segment EEG signals for each condition. In order to study the differences of mental fatigue in different brain regions[21], we divided the whole brain region into five brain functional regions. As shown in table 1, the nineteen electrodes are also divided into five groups. And EEG indices are also computed based on the five brain functional regions. [Due to technical limitations, equations 1-3 are only available as a download in the supplemental files section.] Statistical analysis One-way ANOVA was carried out to distinguish the significant statistical differences between the five periods (T0, T1, T2, T3 and T4). This ANOVA analysis was performed on the power and relative power of EEG bands. Results are demonstrated as mean ± SD. Significant level is reported at p <0.05. Results Figure 2 and table 2 depict the results of EEG power, it has been found that the power of each rhythm in resting state and task state varies in the evolutionary process of mental fatigue, but there are few statistical differences. In resting state, the alpha1 rhythm power at frontal and temporal have a marked tendency to increase, and the alpha2 power at parietal has a significant reduction. In task state, only the beta power at parietal and occipital have obvious decrease. The reason for the insignificant statistical differences may be that the power of EEG rhythms is not sensitive to the mental fatigue, and the small changes of EEG power will be masked by individual differences and power spectrum fluctuations. Therefore, the other widely used EEG index, relative power, was analyzed in the study. Figure 3, figure 4 and table 3 show the results of EEG relative power in resting state. Figure 3 is the brain topography of the relative power for every rhythms. Figure 4 is the average relative power of all electrodes. Table 3 is the statistical results of EEG relative power in different brain regions. As shown in figure 3, figure 4 and table 3, the relative power of delta rhythm presents a monotonically decreasing trend throughout the whole brain, and has significant statistical differences across all brain regions. The results of theta rhythm indicate that only in the central region has a significant increasing trend, and there are no statistic difference in other brain regions. Whereas, both alpha1 rhythm and alpha2 rhythm have significant statistical differences among all the brain regions, and beta rhythm have significant statistical differences only in frontal, temporal, and parietal regions. But the changing regularities of alpha1, alpha2, and beta rhythms are not monotonous. Figure 5, figure 6 and table 4 show the results of EEG relative power in task state. Figure 5 is the brain topography of the relative power for every rhythms, figure 6 is the average relative power of all electrodes, and table 4 is the statistical results of EEG relative power in different brain regions. As shown in figure 5, figure 6 and table 4, the relative power of delta rhythm presents a decreasing trend throughout the whole brain, and has significant statistical differences in frontal, central, parietal, occipital regions. Both theta rhythm and alpha1 rhythm have a non-monotonic increasing trend for the results of relative power, but only in temporal and parietal regions for theta rhythm, and only in central and parietal regions for alpha1 rhythm that have significant statistical differences. Discussion In the present study, we analyzed the difference in spontaneous neural activities caused by performing prolonged fatigue-inducing mental arithmetic tasks between resting state and task state. Five EEG rhythms were evaluated among five brain regions in the two states. The delta rhythm power was 7.1±0.54 μV 2 in the resting state, and had the lowest proportion (10%) in all EEG rhythms; in the task state, the power was 6.1±0.34 μV 2 , but the proportion increased to 21.5%. This is mainly because Alpha1 and Alpha2 rhythms were significantly suppressed in task state (see figure 5), leading to a significant increase in the proportion of corresponding delta rhythm. The delta rhythm power had no statistical difference among T0, T1, T2, T3 and T4 both in resting state and task state (see table 1), which is consistent with its actual physiological meaning. Because delta rhythm is related to people’s deep sleep[22], and it usually appears in large quantities in adult’s deep sleep, anesthesia and hypoxia. As for the relative power of delta rhythm, it decreased significantly along with the accumulation of task time in both resting state and task state, which is in line with the results reported by Jap when researching driving fatigue[21]. Some literatures also have pointed out that the amplitude and relative power of delta rhythm increased under fatigue state[23]. However, in many fatigue evaluation studies, delta band was directly removed by researchers and technicians [22]. Because they believe that delta rhythm reflects the state of deep sleep, and general brain fatigue status does not show significant changes. Moreover, the frequencies of EEG artifacts (such as blink artifacts, eye movement artifacts, electrocardio artifacts, etc., except for power-frequency artifacts and myoelectricity artifacts) mainly coincide with the delta frequency band. The removal of the artifacts is highly subjective, and the removal effect varies from person to person. Therefore, the results of delta rhythm in this study will not be in too further discussion. The power and relative power results of theta rhythm were unanimous both in resting state and task state, demonstrating an increasing trend, which was consistent with the results of most fatigue studies [16, 21–23]. Generally, theta rhythm is considered to reflect the early state of sleepiness[24], which is related to brain fatigue[25] and has a sensitive response to fatigue[26]. As shown in table 3 and table 4, the response result of theta rhythm in the task state was slightly better than that in the resting state, because there were statistical differences in the temporal region and parietal region in the task state, while there were statistical differences only in the central region in the resting state. Alpha rhythm reflects the state of relaxation and wakefulness. When focusing attention, external stimulation or visual input, alpha rhythm will be blocked[27]. Alpha rhythm is considered to be the most sensitive indicator of brain fatigue [25, 26], which is consistent with the statistical analysis results of alpha1 and alpha2 showed in table 3 and table 4. In the increase of mental fatigue, the power and relative power of alpha rhythm were reported to be significantly increased [22, 23]. Several other researchers reported the opposite changing tendency [21]. However, it is now widely accepted that alpha rhythm intensifies as the brain transformed from normal into fatigue [28, 29] (see detailed statistical results of relevant studies in reference [27]). As shown in table 3 and table 4, the effect of alpha1 and alpha2 rhythm in depicting mental fatigue in resting state is better than that in task state In this study, alpha band was further divided into two sub-bands, alpha1 and alpha2, obtaining some meaningful results: the relative power of alpha1 rhythm increased significantly both in resting state and task state, while alpha2 rhythm decreased significantly in the resting state, but showed an increasing trend in the task state, which were consistent with the power change trend shown in figure 2. In similar research results, it is also pointed out that alpha1 rhythm power increases with the increase of fatigue level [29–31], and alpha2 rhythm has the same changes in task state[29]. The change rule of alpha1 and alpha2 in the resting state is completely opposite, and that in the task state is consistent, indicating that it is essential to divide alpha frequency band into alpha1 and alpha2 sub-bands in brain fatigue research based EEG. Klimesch has emphasized that using narrower frequency band in the study can reduce the risk that the frequency effects are cancelled out or not discovered[32], which is well demonstrated in the results of alpha1 and alpha2 rhythms in this study. In addition, narrower frequency band division can enhance the physiological meaning of the sub-bands and make their statistical results more significant. The contrary change trend and significant statistical results of Alpha1 and Alpha2 rhythms in the resting state can prove this inference. Klimesch has pointed out through the analysis of event-related potential that alpha1 rhythm is related to attention, and its power will increase significantly when the attention task increases and the subjects are required to stay awake and not allow sleep and rest [32], which is consistent with the results of alpha1 rhythm in this study. As for alpha2 rhythm, Klimesch et al. have indicated that alpha2 desynchronization is positively correlated with brain long-term memory function by comparing the performance of subjects with different memory abilities in memory tasks[33]. In their subsequent studies, it has been further proved that alpha2 rhythm is correlated with memory [34–37] and cognitive behavior[38]. When the memory task increases, alpha2 rhythm (in the state of eye closure at the time of EEG data collection) shows synchronization [34, 35, 39], that is, the power decreases, which can explain the change trend of alpha2 rhythm in the resting state in this study. Further analysis of the brain topography in the fourth column of figure 3 and figure 5, we found that: (a) alpha2 rhythm power is mainly distributed in the occipital region, which is consistent with the results of topography given by Craig et al. [29]; (b) in resting state, alpha2 rhythm is very strong in all brain regions in the baseline state (referring to the T0 period), but when the brain enters the fatigue state (referring to the T1, T2, T3 and T4 periods), alpha2 rhythm is mainly concentrated in the occipital region; (c) in task state, alpha2 rhythm is mainly concentrated in occipital region, and tends to strengthen in the parietal region and right temporal region with the increase of tasks. The above results suggest that alpha2 rhythm is also closely related to visual information processing in the brain, as the occipital lobe is mainly responsible for visual functions. In the resting state, there is no visual information input in the brain, and the influence of memory task is dominant in the brain, so the brain is shown as de-synchronization [33], and the power and relative power are shown as decreased. In the task state, the brain has a large amount of visual information to be processed, then the neural centers in the occipital area and nearby brain areas are activated (manifested as increased energy of alpha2 rhythm) to complete the visual information transmission and processing tasks. The influence of visual information processing task is dominant, while the influence of memory task is covered. Under these two kinds of comprehensive effects make the alpha2 power has increasing trend, but no statistical difference. Under the combined action of these two influences, the power of alpha2 rhythm tends to increase, but there is no statistical difference. With the deepening of mental fatigue, the relative power of beta rhythm decreases significantly in both resting state and task state, which is consistent with the change trend of its power. Consistent research results have also been widely reported[21, 22]. Beta rhythm are usually associated with the excited state of the brain (e.g., mood and mental activity). When the brain converts from resting state to task state, it needs to maintain a high concentration to complete the tasks, and its beta proportion rises from 15% to 28%. According to the brain topography in the fifth column of figure 3 and figure 5, beta rhythm is mainly distributed in the temporal region, which is consistent with the results of the brain topography given by Jap et al. [21]. Based on the statistical results in table 3 and table 4, the effect of beta rhythm on depicting mental fatigue in resting state is slightly better than that in task state. Conclusions In the present study, a strictly controlled experiment was conducted to study the differences of mental fatigue on electrophysiological activity between resting state and task state. To this end, mental fatigue was induced by the mental arithmetic math task and EEG data was collected before and after the tasks. Then five EEG rhythms (delta, theta, alpha1, alpha2, and beta) were calculated and discussed between resting state and task state. The results suggested the following conclusions: firstly, mental arithmetic task can successfully induce mental fatigue in the enrolled subjects; secondly, the relative power index of each EEG rhythm is more sensitive than the power index in response to mental fatigue, indicating that relative power can be used to estimate brain fatigue level; thirdly, the relative power of each EEG rhythm is better at assessing mental fatigue in resting state than in task state; finally, it is of great physiological significance to divide alpha frequency band into alpha1 band and alpha2 band in fatigue related studies, and at the same time improve the statistical differences of sub-bands. Abbreviations EEG: electroencephalogram; ANOVA: analysis of variance; EEG DAQ: EEG data acquisition. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Shandong University, and written informed consent was obtained from each participant. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no conflict of interest. Funding This work was partly supported by the National Natural Science Foundation of China (No. 51575497), Zhejiang Provincial Natural Science Foundation of China (No. LQ19E050011), and the Zhejiang Provincial Public Welfare Technology Application Research Foundation of China (No. LGF19G010005). These funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing and publishing the manuscript. Authors’ contributions LG: conception and design, experimental procedures, analysis and interpretation of the results, writing the article. JY and JW: conception and design, analysis and interpretation of the results. 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Brain region Electrode name Frontal Fp1, Fp2, F3, F4, F7, F8, Fz Temporal T3, T4, T5, T6 Central C3, Cz, C4 Parietal P3, Pz, P4 Occipital O1, O2 Table 2: ANOVA results of EEG power in different brain regions in resting state and task state. State Region Delta Theta Alpha1 Alpha2 Beta Resting state Whole brain 0.118 0.792 0.403 0.572 0.710 Frontal 0.366 0.819 0.044 0.372 0.656 Temporal 0.135 0.574 0.011 0.221 0.078 Central 0.513 0.887 0.119 0.114 0.273 Parietal 0.141 0.735 0.203 4.3E-4 0.112 Occipital 0.492 0.796 0.914 0.159 0.089 Task state Whole brain 0.760 0.507 0.212 0.673 0.103 Frontal 0.833 0.728 0.735 0.390 0.684 Temporal 0.106 0.179 0.765 0.903 0.193 Central 0.965 0.845 0.434 0.743 0.195 Parietal 0.644 0.426 0.059 0.057 8.9E-7 Occipital 0.223 0.724 0.757 0.324 0.013 Table 3: ANOVA results of EEG relative power in different brain regions in resting state. Region Delta Theta Alpha1 Alpha2 Beta Whole brain 1.5E-5 0.955 1.4E-15 7.1E-11 0.079 Frontal 2.2E-5 0.664 3.4E-15 4.5E-20 0.038 Temporal 0.025 0.727 2.3E-4 0.012 7.3E-5 Central 2.0E-4 0.005 1.7E-6 2.1E-9 0.117 Parietal 1.8E-4 0.309 5.5E-4 1.2E-5 0.043 Occipital 0.015 0.950 0.004 0.002 0.750 Table 4: ANOVA results of EEG relative power in different brain regions in task state. Region Delta Theta Alpha1 Alpha2 Beta Whole brain 0.109 0.044 0.056 0.311 0.060 Frontal 0.003 0.114 0.115 0.526 0.1966 Temporal 0.406 0.001 0.225 0.084 0.015 Central 0.004 0.424 7.7E-5 0.859 0.326 Parietal 0.006 0.021 3.6E-4 0.164 0.103 Occipital 0.037 0.579 0.076 0.540 0.238 Supplementary Files eq13.jpg 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. 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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-6414","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":177467,"identity":"5b5922fb-28ef-4165-81b3-fbfbbc6a75c3","order_by":1,"name":"Gang Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBACPmYwZcPA2ECsFjaIljRStECow8S7i4GNnf3i54Jf5+2ZZ/cYMPzcQZTDeIqlZ/bdZmacc8aAsfcMcVoSpHl7brMxzsgxYGZsI05L8m/ennM8pGhhPybN8+OABEm2sFnzNiQbMM5IKzjYS4wWfv7jj2/z/LGzN5yRvPHBT2K0MDDwGDCA3GPYwMBwgCgNDAzsDxgY/jAwyBOpfBSMglEwCkYgAABehS3LLd5A6AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-1957-471X","institution":"Zhejiang Normal University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Li","suffix":""},{"id":177468,"identity":"7ee2df90-b4ea-467f-93a0-d1e8cccaffb1","order_by":2,"name":"Youdong Luo","email":"","orcid":"","institution":"zhejiang normal university","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Youdong","middleName":"","lastName":"Luo","suffix":""},{"id":177469,"identity":"1330c3c4-f773-49aa-9eda-ae3bf7b31d23","order_by":3,"name":"Weidong Jiao","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weidong","middleName":"","lastName":"Jiao","suffix":""},{"id":177470,"identity":"b9f7370e-f244-461c-b870-f54566af9d0c","order_by":4,"name":"Yonghua Jiang","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yonghua","middleName":"","lastName":"Jiang","suffix":""},{"id":177471,"identity":"0b503095-5deb-4bf5-8036-e9d846df1d91","order_by":5,"name":"Zhao Gao","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhao","middleName":"","lastName":"Gao","suffix":""},{"id":177472,"identity":"b6710b83-8244-469a-b5e7-95bb5e689020","order_by":6,"name":"Shan Huang","email":"","orcid":"","institution":"Zhejiang Normal NUniversity","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shan","middleName":"","lastName":"Huang","suffix":""},{"id":177473,"identity":"79ae409f-7882-4790-ac8c-023b1bc7c866","order_by":7,"name":"Jianhua Zhang","email":"","orcid":"","institution":"Zhejiang Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jianhua","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2019-10-02 19:31:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.15754/v1","doiUrl":"https://doi.org/10.21203/rs.2.15754/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":117148,"identity":"3229a2f4-7171-4a1c-af18-28d03834ef38","added_by":"auto","created_at":"2019-10-09 18:57:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62613,"visible":true,"origin":"","legend":"EEG data acquisition (EEG DAQ) procedures. C1 means resting state and C2 means task state.","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 1.jpg"},{"id":117150,"identity":"df863ff6-1b0e-4145-a668-470395751ff4","added_by":"auto","created_at":"2019-10-09 18:57:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88410,"visible":true,"origin":"","legend":"The power of EEG rhythms over the whole brain region at different time periods. (a) Resting state, (b) Task state.","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 2.jpg"},{"id":117151,"identity":"bd2400f9-5eed-4aa7-ad92-72238f5f8322","added_by":"auto","created_at":"2019-10-09 18:57:23","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":257579,"visible":true,"origin":"","legend":"Brain topography of the relative power of EEG rhythms in resting state. In the figure, all the relative power values are normalized to 0-1.","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 3.jpg"},{"id":117152,"identity":"2af21e96-bcd3-4ff7-b69d-837cf433bf08","added_by":"auto","created_at":"2019-10-09 18:57:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":50466,"visible":true,"origin":"","legend":"The average relative power of EEG rhythms over the whole brain region at different time periods in resting state.","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 4.jpg"},{"id":117153,"identity":"c7d989c0-6482-4f4f-ad48-3719f9d4320a","added_by":"auto","created_at":"2019-10-09 18:57:23","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":269523,"visible":true,"origin":"","legend":"Brain topography of the relative power of EEG rhythms in task state. In the figure, all the relative power values are normalized to 0-1.","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 5.jpg"},{"id":117154,"identity":"f6da7310-0fb0-4995-ad06-6453f6d02dbf","added_by":"auto","created_at":"2019-10-09 18:57:23","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":51983,"visible":true,"origin":"","legend":"The average relative power of EEG rhythms over the whole brain region at different time periods in task state.","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/Fig 6.jpg"},{"id":13475193,"identity":"53b89884-cbcc-45d4-85ad-eb31180efa51","added_by":"auto","created_at":"2021-09-16 21:24:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":832183,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6414/v1/27359dd8-4ff2-456b-9975-dbc82b8b8df4.pdf"},{"id":117147,"identity":"13223e6d-c666-4a13-922b-4e779866ca76","added_by":"auto","created_at":"2019-10-09 18:57:22","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":10121,"visible":true,"origin":"","legend":"","description":"","filename":"eq13.jpg","url":"https://assets-eu.researchsquare.com/files/758a5674-ef9a-449c-a3fd-392a2824b3b4/v1/eq1-3.jpg"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe impact of mental fatigue on brain activity: A comparative study between resting state and task state using EEG\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMental fatigue refers to a condition of low alertness and cognitive impairment [1]. Too much brain activity and stimulation can make a person feel mentally exhausted, and this feeling is akin to physical fatigue. Mental fatigue can give rise to numerous bad consequences, for example, making the uncomplicated tasks turn to be increasingly difficult or even impossible. Mental fatigue has become a popular subhealthy states in nowadays society, and affects nearly all aspects of cognitive functioning in humans [2], such as driving fatigue [3]. Concerning the effects of mental fatigue on daily life, it is important to reveal the differences of mental fatigue on brain activity between resting state and task state.\u003c/p\u003e\n\n\u003cp\u003ePrevious studies have been centered on the changes associated with task-related brain activity[4]. The fatigue-inducing mental tasks were widely used by researchers. The mental tasks that requiring different intensity of attention can differentiate the levels of mental fatigue, and their experimental duration could be distinct. The \u003cem\u003en-\u003c/em\u003eback task [5, 6] and psychomotor vigilance task [7, 8] (PVT) can be categorized as high-attention-demanding tasks, sleep deprivation [9] can be classified into low-attention-demanding tasks, meanwhile mental arithmetic task [10] and driving simulation task[11] fall into middle-attention-demanding tasks. However, among these three-type tasks, the middle-attention-demanding tasks are greatly in line with our daily working load. Therefore, we chose mental arithmetic task to induce mental fatigue.\u003c/p\u003e\n\n\u003cp\u003eHistorically, mental fatigue has been most prevalently studied with the neuroimaging technique of EEG on account of its high temporal resolution, low costs, and easy operation [12–14]. It has been widely proved that mental fatigue can lead to distinct changes in EEG[15]. Strijkstra has found that EEG during resting awake periods with eyes closed shows strong negative correlations of alpha power and positive correlations of theta power with subjective sleepiness[16]. With the mental fatigue increasing, the power spectrum density of alpha rhythm increases when eyes open and decreases when eyes closed[17]. These changes in EEG can be used to detect mental fatigue [10, 15], which is especially important and meaningful for driving fatigue estimation [7, 11]. From the above, we can conclude that EEG has become the most effective technical means for exploring the neuromechanism and detection of mental fatigue [18, 19].\u003c/p\u003e\n\n\u003cp\u003eThe current study is also motivated by the studies which have divided the EEG bands into narrower bands. In mental fatigue related studies, some researchers divided alpha band into alpha1 (8–10Hz) and alpha2 (10–13Hz). Li has performed statistical analysis on the characteristics of alpha1 and alpha2 to estimate mental fatigue, and reported that alpha1 band is better for fatigue detection [10]. Sun has applied alpha1 frequency band for mental fatigue classification, and achieved a high prediction accuracy [20].\u003c/p\u003e\n\n\u003cp\u003eIn the current study, we attempted to investigate the differences of mental fatigue on electrophysiological activity between resting state and task state. To this end, we administered a challenging sustained mental arithmetic math task for a group of young healthy male participants to induce mental fatigue, and EEG data for resting state and task state before and after the tasks were collected. Then the power and relative power of delta, theta, alpha1, alpha2, and beta were computed, and statistical analysis (analysis of variance, ANOVA) were carried on the results among different brain regions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch1\u003eParticipants\u003c/h1\u003e\n\u003cp\u003eTwenty male participants (age was 24.5±1.5 years, and body mass index was 20.7±1.8 kg/m\u003csup\u003e2\u003c/sup\u003e) were recruited. Each subject should be right-handed, and should have a regular life, normal normal eyesight, and no brain diseases. Before the tests, every participant was required to do as follows: (1) not staying up late at night, (2) not drinking alcohol and drugs in one week preceding the EEG test, (3) not smoking and drinking coffee and tea in 8 hours before EEG data acquisition, and (4) washing their hair in 2 hours before the experiment. Every participant was informed the experimental procedures and the local Ethics Committee have approved this study. Each subject gained some monetary reimbursement to motivate their better performances during the tests.\u003c/p\u003e\n\n\u003ch1\u003eEEG data recording\u003c/h1\u003e\n\u003cp\u003eEEG data were recorded by a digital EEG apparatus (SYMTOP NT9200) at the following nineteen electrodes of the 10–20 systems: Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, T3, T4, T5, T6, Fz, Cz, and Pz (A1 and A2 were chosen as the reference electrodes, Fpz was specified as the grounding-electrode, sample frequency was 1000 Hz, electrode impedance was controlled under 5000 Ω). In order to induce mental fatigue, every subject was required to do a mental arithmetic task with 200 different problems for 100 minutes. The mental arithmetic problem was designed as: a random double-digit (between 60 and 90) plus another random double-digit (between 60 and 90) and then multiplied by a random single digit (between 6 and 9). Each math problem was designed to be done in 30 seconds determined by preceding pretests. As shown in Figure 1, the whole mental arithmetic task was equally divided into 4 tasks, and EEG was collected for both resting state and task state. Therefore, there were 5 times EEG data acquisition named as T0, T1, T2, T3 and T4 for the whole task. Besides, resting state means closing the eyes, being awake and relaxed, and subjects were required to concentrate their attention on the breath avoiding thinking about anything, whereas task state refers to keep the body still and do a mental arithmetic math problem, a three-digit subtracts a single digit continuously (keep same for every data recordings). All the mental arithmetic math problems were automatically displayed on the computer screen one by one. The whole test was carried on from 7 pm to 9 pm in a sound attenuated, and light, temperature, and humidity controlled room.\u003c/p\u003e\n\n\u003ch1\u003eEEG data preprocessing\u003c/h1\u003e\n\u003cp\u003eEEG signals from only eighteen subjects were analyzed for further analysis. The other two were excluded because of their big head movements when recording the EEG. In the current analysis, ten pieces of five seconds of artifact-free continuous EEG data (containing no eye blinks, no slow eye movements, no electrocardiogram artifacts (eliminated by Fast ICA), and no baseline drift (removed by baseline correction)) were selected from each condition by EEGLAB. These pieces of data were then down sampled from 1000Hz to 256 Hz. And EEG rhythms (delta: 2–4 Hz; theta: 4–8 Hz; alpha1: 8–10 Hz; alpha2: 10–13 Hz; beta: 13–30 Hz) were extracted by digital FFT filtering.\u003c/p\u003e\n\n\u003ch1\u003eComputation of EEG indices\u003c/h1\u003e\n\u003cp\u003eIn this study, the power and relative power of every EEG rhythms were explored. The frequency spectrum \u003cem\u003eX(\u003c/em\u003e\u003cem\u003ef)\u003c/em\u003e of EEG signal \u003cem\u003ex(\u003c/em\u003e\u003cem\u003en)\u003c/em\u003e was obtained by means of FFT, and then the power spectrum \u003cem\u003eP\u003csub\u003ex(\u003c/sub\u003e\u003c/em\u003e\u003cem\u003ef)\u003c/em\u003e of EEG were gained with equation (1). The power \u003cem\u003eE(\u003c/em\u003e\u003cem\u003eh)\u003c/em\u003e and relative power\u003cem\u003e R(\u003c/em\u003e\u003cem\u003eh)\u003c/em\u003e were calculated through equation (2) and equation (3). Where, in equation (1), equation (2) and equation (3), \u003cem\u003eN\u003c/em\u003e is the number of EEG signal \u003cem\u003ex(\u003c/em\u003e\u003cem\u003en),\u003c/em\u003e, \u003cem\u003eh \u003c/em\u003erepresents the EEG rhythms (such as delta, theta, alpha1, alpha2, beta), \u003cem\u003ef\u003csub\u003eh\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003ef\u003csub\u003el \u003c/sub\u003e\u003c/em\u003eare the upper and lower frequencies of \u003cem\u003eh\u003c/em\u003e rhythm respectively, \u003cem\u003eE\u003csub\u003etotal\u003c/sub\u003e\u003c/em\u003e is the total power of all EEG rhythms. Besides, all the calculated power spectrum are the average value of the selected 10-segment EEG signals for each condition. In order to study the differences of mental fatigue in different brain regions[21], we divided the whole brain region into five brain functional regions. As shown in table 1, the nineteen electrodes are also divided into five groups. And EEG indices are also computed based on the five brain functional regions.\u003c/p\u003e\n\u003cp\u003e[Due to technical limitations, equations 1-3 are only available as a download in the supplemental files section.]\u003c/p\u003e\n\u003ch1\u003eStatistical analysis\u003c/h1\u003e\n\u003cp\u003eOne-way ANOVA was carried out to distinguish the significant statistical differences between the five periods (T0, T1, T2, T3 and T4). This ANOVA analysis was performed on the power and relative power of EEG bands. Results are demonstrated as mean ± SD. Significant level is reported at \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure 2 and table 2 depict the results of EEG power, it has been found that the power of each rhythm in resting state and task state varies in the evolutionary process of mental fatigue, but there are few statistical differences. In resting state, the alpha1 rhythm power at frontal and temporal have a marked tendency to increase, and the alpha2 power at parietal has a significant reduction. In task state, only the beta power at parietal and occipital have obvious decrease. The reason for the insignificant statistical differences may be that the power of EEG rhythms is not sensitive to the mental fatigue, and the small changes of EEG power will be masked by individual differences and power spectrum fluctuations. Therefore, the other widely used EEG index, relative power, was analyzed in the study.\u003c/p\u003e\n\n\u003cp\u003eFigure 3, figure 4 and table 3 show the results of EEG relative power in resting state. Figure 3 is the brain topography of the relative power for every rhythms. Figure 4 is the average relative power of all electrodes. Table 3 is the statistical results of EEG relative power in different brain regions. As shown in figure 3, figure 4 and table 3, the relative power of delta rhythm presents a monotonically decreasing trend throughout the whole brain, and has significant statistical differences across all brain regions. The results of theta rhythm indicate that only in the central region has a significant increasing trend, and there are no statistic difference in other brain regions. Whereas, both alpha1 rhythm and alpha2 rhythm have significant statistical differences among all the brain regions, and beta rhythm have significant statistical differences only in frontal, temporal, and parietal regions. But the changing regularities of alpha1, alpha2, and beta rhythms are not monotonous.\u003c/p\u003e\n\n\u003cp\u003eFigure 5, figure 6 and table 4 show the results of EEG relative power in task state. Figure 5 is the brain topography of the relative power for every rhythms, figure 6 is the average relative power of all electrodes, and table 4 is the statistical results of EEG relative power in different brain regions. As shown in figure 5, figure 6 and table 4, the relative power of delta rhythm presents a decreasing trend throughout the whole brain, and has significant statistical differences in frontal, central, parietal, occipital regions. Both theta rhythm and alpha1 rhythm have a non-monotonic increasing trend for the results of relative power, but only in temporal and parietal regions for theta rhythm, and only in central and parietal regions for alpha1 rhythm that have significant statistical differences.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we analyzed the difference in spontaneous neural activities caused by performing prolonged fatigue-inducing mental arithmetic tasks between resting state and task state. Five EEG rhythms were evaluated among five brain regions in the two states. The delta rhythm power was 7.1±0.54 μV\u003csup\u003e2\u003c/sup\u003e in the resting state, and had the lowest proportion (10%) in all EEG rhythms; in the task state, the power was 6.1±0.34 μV\u003csup\u003e2\u003c/sup\u003e, but the proportion increased to 21.5%. This is mainly because Alpha1 and Alpha2 rhythms were significantly suppressed in task state (see figure 5), leading to a significant increase in the proportion of corresponding delta rhythm. The delta rhythm power had no statistical difference among T0, T1, T2, T3 and T4 both in resting state and task state (see table 1), which is consistent with its actual physiological meaning. Because delta rhythm is related to people’s deep sleep[22], and it usually appears in large quantities in adult’s deep sleep, anesthesia and hypoxia. As for the relative power of delta rhythm, it decreased significantly along with the accumulation of task time in both resting state and task state, which is in line with the results reported by Jap when researching driving fatigue[21]. Some literatures also have pointed out that the amplitude and relative power of delta rhythm increased under fatigue state[23]. However, in many fatigue evaluation studies, delta band was directly removed by researchers and technicians [22]. Because they believe that delta rhythm reflects the state of deep sleep, and general brain fatigue status does not show significant changes. Moreover, the frequencies of EEG artifacts (such as blink artifacts, eye movement artifacts, electrocardio artifacts, etc., except for power-frequency artifacts and myoelectricity artifacts) mainly coincide with the delta frequency band. The removal of the artifacts is highly subjective, and the removal effect varies from person to person. Therefore, the results of delta rhythm in this study will not be in too further discussion.\u003c/p\u003e\n\n\u003cp\u003eThe power and relative power results of theta rhythm were unanimous both in resting state and task state, demonstrating an increasing trend, which was consistent with the results of most fatigue studies [16, 21–23]. Generally, theta rhythm is considered to reflect the early state of sleepiness[24], which is related to brain fatigue[25] and has a sensitive response to fatigue[26]. As shown in table 3 and table 4, the response result of theta rhythm in the task state was slightly better than that in the resting state, because there were statistical differences in the temporal region and parietal region in the task state, while there were statistical differences only in the central region in the resting state.\u003c/p\u003e\n\n\u003cp\u003eAlpha rhythm reflects the state of relaxation and wakefulness. When focusing attention, external stimulation or visual input, alpha rhythm will be blocked[27]. Alpha rhythm is considered to be the most sensitive indicator of brain fatigue [25, 26], which is consistent with the statistical analysis results of alpha1 and alpha2 showed in table 3 and table 4. In the increase of mental fatigue, the power and relative power of alpha rhythm were reported to be significantly increased [22, 23]. Several other researchers reported the opposite changing tendency [21]. However, it is now widely accepted that alpha rhythm intensifies as the brain transformed from normal into fatigue [28, 29] (see detailed statistical results of relevant studies in reference [27]). As shown in table 3 and table 4, the effect of alpha1 and alpha2 rhythm in depicting mental fatigue in resting state is better than that in task state\u003c/p\u003e\n\n\u003cp\u003eIn this study, alpha band was further divided into two sub-bands, alpha1 and alpha2, obtaining some meaningful results: the relative power of alpha1 rhythm increased significantly both in resting state and task state, while alpha2 rhythm decreased significantly in the resting state, but showed an increasing trend in the task state, which were consistent with the power change trend shown in figure 2. In similar research results, it is also pointed out that alpha1 rhythm power increases with the increase of fatigue level [29–31], and alpha2 rhythm has the same changes in task state[29]. The change rule of alpha1 and alpha2 in the resting state is completely opposite, and that in the task state is consistent, indicating that it is essential to divide alpha frequency band into alpha1 and alpha2 sub-bands in brain fatigue research based EEG. Klimesch has emphasized that using narrower frequency band in the study can reduce the risk that the frequency effects are cancelled out or not discovered[32], which is well demonstrated in the results of alpha1 and alpha2 rhythms in this study. In addition, narrower frequency band division can enhance the physiological meaning of the sub-bands and make their statistical results more significant. The contrary change trend and significant statistical results of Alpha1 and Alpha2 rhythms in the resting state can prove this inference.\u003c/p\u003e\n\n\u003cp\u003eKlimesch has pointed out through the analysis of event-related potential that alpha1 rhythm is related to attention, and its power will increase significantly when the attention task increases and the subjects are required to stay awake and not allow sleep and rest [32], which is consistent with the results of alpha1 rhythm in this study. As for alpha2 rhythm, Klimesch et al. have indicated that alpha2 desynchronization is positively correlated with brain long-term memory function by comparing the performance of subjects with different memory abilities in memory tasks[33]. In their subsequent studies, it has been further proved that alpha2 rhythm is correlated with memory [34–37] and cognitive behavior[38]. When the memory task increases, alpha2 rhythm (in the state of eye closure at the time of EEG data collection) shows synchronization [34, 35, 39], that is, the power decreases, which can explain the change trend of alpha2 rhythm in the resting state in this study.\u003c/p\u003e\n\n\u003cp\u003eFurther analysis of the brain topography in the fourth column of figure 3 and figure 5, we found that: (a) alpha2 rhythm power is mainly distributed in the occipital region, which is consistent with the results of topography given by Craig et al. [29]; (b) in resting state, alpha2 rhythm is very strong in all brain regions in the baseline state (referring to the T0 period), but when the brain enters the fatigue state (referring to the T1, T2, T3 and T4 periods), alpha2 rhythm is mainly concentrated in the occipital region; (c) in task state, alpha2 rhythm is mainly concentrated in occipital region, and tends to strengthen in the parietal region and right temporal region with the increase of tasks. The above results suggest that alpha2 rhythm is also closely related to visual information processing in the brain, as the occipital lobe is mainly responsible for visual functions. In the resting state, there is no visual information input in the brain, and the influence of memory task is dominant in the brain, so the brain is shown as de-synchronization [33], and the power and relative power are shown as decreased. In the task state, the brain has a large amount of visual information to be processed, then the neural centers in the occipital area and nearby brain areas are activated (manifested as increased energy of alpha2 rhythm) to complete the visual information transmission and processing tasks. The influence of visual information processing task is dominant, while the influence of memory task is covered. Under these two kinds of comprehensive effects make the alpha2 power has increasing trend, but no statistical difference. Under the combined action of these two influences, the power of alpha2 rhythm tends to increase, but there is no statistical difference.\u003c/p\u003e\n\n\u003cp\u003eWith the deepening of mental fatigue, the relative power of beta rhythm decreases significantly in both resting state and task state, which is consistent with the change trend of its power. Consistent research results have also been widely reported[21, 22]. Beta rhythm are usually associated with the excited state of the brain (e.g., mood and mental activity). When the brain converts from resting state to task state, it needs to maintain a high concentration to complete the tasks, and its beta proportion rises from 15% to 28%. According to the brain topography in the fifth column of figure 3 and figure 5, beta rhythm is mainly distributed in the temporal region, which is consistent with the results of the brain topography given by Jap et al. [21]. Based on the statistical results in table 3 and table 4, the effect of beta rhythm on depicting mental fatigue in resting state is slightly better than that in task state.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn the present study, a strictly controlled experiment was conducted to study the differences of mental fatigue on electrophysiological activity between resting state and task state. To this end, mental fatigue was induced by the mental arithmetic math task and EEG data was collected before and after the tasks. Then five EEG rhythms (delta, theta, alpha1, alpha2, and beta) were calculated and discussed between resting state and task state. The results suggested the following conclusions: firstly, mental arithmetic task can successfully induce mental fatigue in the enrolled subjects; secondly, the relative power index of each EEG rhythm is more sensitive than the power index in response to mental fatigue, indicating that relative power can be used to estimate brain fatigue level; thirdly, the relative power of each EEG rhythm is better at assessing mental fatigue in resting state than in task state; finally, it is of great physiological significance to divide alpha frequency band into alpha1 band and alpha2 band in fatigue related studies, and at the same time improve the statistical differences of sub-bands.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEEG: electroencephalogram; ANOVA: analysis of variance; EEG DAQ: EEG data acquisition.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Shandong University, and written informed consent was obtained from each participant.\u003c/p\u003e\n\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was partly supported by the National Natural Science Foundation of China (No. 51575497), Zhejiang Provincial Natural Science Foundation of China (No. LQ19E050011), and the Zhejiang Provincial Public Welfare Technology Application Research Foundation of China (No. LGF19G010005). These funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing and publishing the manuscript.\u003c/p\u003e\n\n\u003ch2\u003eAuthors’ contributions\u003c/h2\u003e\n\u003cp\u003eLG: conception and design, experimental procedures, analysis and interpretation of the results, writing the article. JY and JW: conception and design, analysis and interpretation of the results. LY and GZ: perform and analyze experiments, and interpret results. HS and ZJ: interpretation of the results, critical revision of the article. All authors have read and approved the final manuscript.\u003c/p\u003e\n\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"Reference","content":"\u003cp\u003e1.Boksem MAS, Tops M: Mental fatigue: Costs and benefits. 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Cognitive Brain Research 1997, 6(2):83–94.\u003c/p\u003e"},{"header":"Tables","content":"\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"font-size: 14px; line-height: 150%; font-family: Verdana, Geneva, sans-serif; color: rgb(0, 0, 0);\"\u003eTable 1: Division of the brain regions and their included electrode.\u003c/span\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eBrain region\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eElectrode name\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eFrontal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eFp1, Fp2, F3, F4, F7, F8, Fz\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTemporal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eT3, T4, T5, T6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eCentral\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eC3, Cz, C4\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eParietal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eP3, Pz, P4\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:85.05pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"39.92932862190813%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eOccipital\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:127.55pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"60.07067137809187%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eO1, O2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\n \u003cbr\u003e\n \u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTable 2: ANOVA results of EEG power in different brain regions in resting state and task state.\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"width:97.36%;border-collapse:collapse;border:none;\" width=\"97%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:12.42%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"12.631578947368421%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eState\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:18.9%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"18.94736842105263%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eRegion\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.72%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eDelta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTheta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eBeta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width:12.42%;border:none;border-bottom:solid windowtext 1.0pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"12.631578947368421%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eResting state\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:18.9%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"18.94736842105263%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eWhole brain\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.72%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.118\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.792\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.403\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.572\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"13.68421052631579%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.710\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:18.9%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"21.686746987951807%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eFrontal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.72%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.366\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.819\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.044\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.372\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.656\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:18.9%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"21.686746987951807%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTemporal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.72%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.135\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.574\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.011\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp 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rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.059\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.057\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e8.9E-7\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:18.9%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"21.686746987951807%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eOccipital\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.72%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.223\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.724\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.757\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.324\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:13.74%;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"15.662650602409638%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.013\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;text-indent:24.0pt;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTable 3: ANOVA results of EEG relative power in different brain regions in resting state.\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:78.0pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"18.772563176895307%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eRegion\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eDelta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTheta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.5pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eBeta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:78.0pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"18.772563176895307%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eWhole brain\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e1.5E-5\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.955\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e1.4E-15\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e7.1E-11\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.5pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.079\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:78.0pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"18.772563176895307%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eFrontal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e2.2E-5\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 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150%;\"\u003e0.950\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.004\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.45pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.002\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:67.5pt;border:none;border-bottom:solid windowtext 1.5pt;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.24548736462094%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.750\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;text-indent:24.0pt;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTable 4: ANOVA results of EEG relative power in different brain regions in task state.\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style=\"margin:0in;margin-bottom:.0001pt;text-align:justify;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:70.9pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"17.117117117117118%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eRegion\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eDelta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTheta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eAlpha2\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border-top:solid windowtext 1.5pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eBeta\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:70.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"17.117117117117118%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eWhole brain\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.109\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.044\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.056\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.311\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.060\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:70.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"17.117117117117118%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eFrontal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cstrong\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.003\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.114\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.115\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.526\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003e0.1966\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:70.9pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"17.117117117117118%\"\u003e\n \u003cp style=\"margin:0in;margin-bottom:.0001pt;text-align:center;font-size:14px;font-family:\u0026quot;Calibri\u0026quot;,sans-serif;line-height:150%;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-size: 14px;\"\u003e\u003cspan style=\"font-family: Verdana,Geneva,sans-serif;\"\u003e\u003cspan style=\"line-height: 150%;\"\u003eTemporal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:68.85pt;border:none;padding:0in 5.4pt 0in 5.4pt;\" width=\"16.576576576576578%\"\u003e\n \u003cp 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Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mental fatigue, EEG, resting state, task state","lastPublishedDoi":"10.21203/rs.2.15754/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.15754/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Mental fatigue is usually caused by long-term cognitive activities, mainly manifested as drowsiness, difficulty in concentrating, decreased alertness, disordered thinking, slow reaction, lethargy, reduced work efficiency, error-prone and so on. Mental fatigue has become a widespread sub-health condition, and has a serious impact on the cognitive function of the brain. However, seldom researches explore the differences of mental fatigue on electrophysiological activity between resting state and task state. In the present study, 20 healthy male individuals were recruited to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) data were collected before and after the task. The power and relative power of five EEG rhythms both in resting state and task state were analyzed statistically. \u003c/p\u003e\u003cp\u003eResults: The results of brain topographies and statistical analysis indicated that mental arithmetic task can successfully induce mental fatigue in the enrolled subjects. The relative power index was more sensitive than the power index in response to mental fatigue, and the relative power for assessing mental fatigue was better in resting state than in task state. Furthermore, we found that it is of great physiological significance to divide alpha frequency band into alpha1 band and alpha2 band in fatigue related studies, and at the same time improve the statistical differences of sub-bands. \u003c/p\u003e\u003cp\u003eConclusions: Our current results suggested that the brain activity in mental fatigue state has great differences between resting state and task state, and it is imperative to select the appropriate state in EEG data acquisition and divide alpha band into alpha1 and alpha2 bands in mental fatigue related researches.\u003c/p\u003e","manuscriptTitle":"The impact of mental fatigue on brain activity: A comparative study between resting state and task state using EEG","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2019-10-09 18:57:21","doi":"10.21203/rs.2.15754/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":"c2d0eaff-c217-435c-9643-ca0f390a1f9d","owner":[],"postedDate":"October 9th, 2019","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30664,"name":"Computational Neuroscience"},{"id":30665,"name":"Developmental Neuroscience"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2019-10-09 18:57:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6414","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-6414","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}