Skip to main content

Advertisement

  • Research
  • Open Access

Autonomic nervous alterations associated with daily level of fatigue

  • 1Email author,
  • 2,
  • 3,
  • 3,
  • 4,
  • 4,
  • 4,
  • 5,
  • 5 and
  • 1, 2
Behavioral and Brain Functions20117:46

https://doi.org/10.1186/1744-9081-7-46

©  Tanaka et al; licensee BioMed Central Ltd. 2011

  • Received: 17 July 2011
  • Accepted: 27 October 2011
  • Published:

Abstract

Background

Fatigue is a common symptom in both sick and healthy people. We examined autonomic nervous alterations associated with fatigue to clarify the mechanisms underlying fatigue.

Methods

The study group consisted of 19 healthy participants who performed a 2-back test for 30 min as a fatigue-inducing mental task session. Before and after the session, they completed the advanced trail making test (ATMT) for 30 min for mental fatigue evaluation, subjective scales to measure fatigue sensation, and underwent electrocardiography to allow assessment of autonomic nerve activities.

Results

After the fatigue-inducing task, the total error counts on the ATMT tended to increase (P = 0.076); the ATMT for total trial counts (P = 0.001), the subjective level of fatigue (P < 0.001), and the % low-frequency power (%LF) (P = 0.035) increased significantly; and the % high-frequency power (%HF) decreased compared with before the fatigue-inducing task although this did not reach the statistical significance (P = 0.170). Although LF measured in absolute units did not change significantly before and after the fatigue-inducing task (P = 0.771), and HF measured in absolute units decreased after the task (P = 0.020). The %LF and LF/HF ratio were positively associated with the daily level of fatigue evaluated using Chalder's fatigue scale. In addition, %HF was negatively associated with the fatigue score.

Conclusions

Increased sympathetic activity and decreased parasympathetic activity may be characteristic features of both acute and daily levels of fatigue. Our findings provide new perspectives on the mechanisms underlying fatigue.

Keywords

  • Advanced trail making test
  • 2-back Test
  • Parasympathetic nerve function
  • Selective attention
  • Sympathetic nerve function

Background

Many people experience fatigue after or during a prolonged period of activity [1]. Large community surveys have reported that up to half of the general adult population complains of fatigue [2, 3]. In Japan, more than half of the general adult population complains of fatigue, and more than one third of the population suffers from chronic fatigue [4]. Acute fatigue is a normal phenomenon that disappears after a period of rest; in contrast, chronic fatigue is sometimes irreversible and the compensation mechanisms that are useful in reducing acute fatigue are not effective [5]. Therefore, it is important to clarify the mechanisms underlying fatigue, and in particular, long-term fatigue.

Fatigue-related alterations of autonomic nerve activities have been reported in patients with chronic fatigue syndrome (CFS) [6–11], multiple sclerosis [12–14], and primary biliary cirrhosis [9, 15]. These reports suggest that changes in autonomic nerve activity are related to the mechanisms underlying fatigue. However, this relationship has been demonstrated only in patients with specific diseases and not in healthy subjects.

Recently, we demonstrated that decreased parasympathetic activity and increased sympathetic activity were induced in healthy volunteers following a 30-min fatigue-inducing mental task session [16]. As chronic or daily levels of fatigue can be evaluated using a paper-and-pencil questionnaire [17], the relationships between daily levels of fatigue and alterations of autonomic nerve activities may be identified. In addition, we can evaluate acute and daily levels of fatigue simultaneously in the same participants by using previously performed fatigue-inducing and fatigue-evaluating experiments [16]. The aim of the present study was to determine alterations in autonomic nerve activities associated with daily levels of fatigue as well as acute fatigue.

Methods

Participants

Nineteen healthy volunteers (mean age, 43.6 ± 10.1 years; 15 women and 4 men) were enrolled. None of the participants had a history of medical illness. Participants with a history of health problems, taking chronic medication or supplemental vitamins, and those who weighed < 40 kg [18–22] were excluded. Good health was assessed by physical examination, blood pressure, and heart rate. The protocol was approved by the Ethics Committee of Osaka City University, and all participants provided written informed consent.

Experimental design

The day before the experiment, participants finished dinner by 9:00 pm and then fasted overnight. The following morning, they had breakfast before the visit. At 10:00 a.m., after the visit, they started the experiment. Before the start of the experiment, a paper-and-pencil questionnaire was distributed to participants to evaluate their daily level of fatigue. As a fatigue-inducing mental task session, participants performed 2-back test [23] trials for 30 min [24], and as a fatigue-evaluating mental task, they performed the advanced trail making test (ATMT; [25]) for 30 min [24] before and after the fatigue-inducing task session. Just before and after the fatigue-inducing session, they recorded their subjective sensation of fatigue on a visual analogue scale (VAS) from 0 (no fatigue) to 100 (complete exhaustion) [26] and underwent electrocardiography (ECG) with their eyes closed for 1 min while sitting on a chair. VAS and ECG recordings were performed before the ATMT trials. This study was conducted in a quiet, temperature- and humidity-controlled environment. For 1 day before the visit, participants refrained from intense mental and physical activities and caffeinated beverages, consumed a normal diet, and maintained normal sleeping hours.

Questionnaire

A paper-and-pencil questionnaire was distributed to participants. The severity of daily level of fatigue was measured using Chalder's fatigue scale (Chalder et al. 1993), which has been previously used in Japanese participants [27]. The reliability and validity of the Japanese version of Chalder's fatigue scale to evaluate the severity of daily fatigue have been previously confirmed [27]. The fatigue scale consists of 11 questions using a 4-point (0-3) Likert scale that allows the following responses: 0 = less than usual; 1 = no more than usual; 2 = more than usual; 3 = much more than usual during the past several weeks. The total score for the 11-item fatigue scale ranges from 0 to 33, with higher scores indicating a greater degree of daily fatigue.

Fatigue-inducing mental task

As a fatigue-inducing mental task, participants performed the 2-back test for 30 min [24]. During this task, one of four letters was presented on a display of a personal computer every 3 sec, and they had to judge whether the target letter presented at the center of the screen was the same as the one that had appeared 2 presentations before. If it was, they were to press the right mouse button with their right middle finger; if it was not, they were to press the left mouse button with their right index finger. They were instructed to perform the task trials as quickly and as correctly as possible. The results of each 2-back trial, that is, a correct response or error, were continuously presented on the display of the personal computer.

Fatigue-evaluating mental task

As a fatigue-evaluating mental task, participants performed the ATMT for 30 min [24]. In this test, circles numbered from 1 to 25 were randomly placed on the display of a personal computer, and participants were required to use a computer mouse to touch these circles in sequence, starting with number 1. Tasks A, B, and C all ended when they touched the 25th target. They continued directly with the next Tasks B, C, and A, in that order, on and on for 30 min. The number of hits counted and the time were counted. In task A of the ATMT, when they touched a target circle, it remained in the same position, but the color changed from black to yellow. The positions of the other circles remained the same. In task B of the ATMT, when they touched the first target circle, it disappeared, and circle number 26 appeared in a different position on the screen. The positions of the other circles remained the same. For example, touching circles 2, 3, and 4 resulted in their disappearance and the addition of circles 27, 28, and 29 on the screen, so that there were always 25 circles on the screen. In task C of the ATMT, when they touched the first target circle, it disappeared and circle number 26 appeared in a different position on the screen and the position of all other circles changed at random. As in task B, there were always 25 circles on the screen. Participants performed tasks A, B, and C consecutively. They were instructed to perform all task trials as quickly and as correctly as possible.

Electrocardiographic analyses

ECG was recorded using active tracer AC301 (Global Medical Solution Inc., Tokyo, Japan), and the ECG was analyzed using MemCalc for Windows (Global Medical Solution Inc.). Data were analyzed offline after analogue-to-digital conversion at 250 Hz. R-R wave. Irregularities in the ECG recordings were excluded from the analyses. Variability was measured as an indicator of autonomic nerve activity. For frequency domain analyses of the R-R wave intervals, the percent of low-frequency power (LF) was calculated as the power within the frequency range of 0.04 to 0.15 Hz, and the percent of high-frequency power (HF) was calculated as that within the frequency range of 0.15 to 0.4 Hz. LF and HF were measured in absolute and normalized units; normalization was performed by dividing the absolute power by the total variance and then multiplying by 100. The %HF is vagally mediated [28–30], but the %LF originates from a variety of sympathetic and vagal mechanisms [28, 31]. The LF/HF ratio represents the sympathetic to parasympathetic balance [32].

Statistical analysis

Values are shown as mean ± SD unless otherwise noted. Paired t-tests were used to evaluate the differences before and after the mental fatigue-inducing task as for the ATMT performances and VAS scores and Wilcoxon's signed rank tests as for the indices of the heart rate variability. Pearson's correlation analyses were conducted to evaluate relationships between two variables. All P values were 2-tailed, and P values less than 0.05 were considered statistically significant. Statistical analyses were performed using SPSS 17.0 software package (SPSS Inc., Chicago, IL).

Results

Task performances, subjective level of fatigue, and ECG variables before and after the fatigue-inducing mental task are shown in Table 1. After the fatigue-inducing task, the total error counts of the ATMT during the fatigue-evaluating mental task tended to increase compared with before the fatigue-inducing task, although differences did not reach statistical significance (P = 0.076). In addition, after the fatigue-inducing task, the total trial counts (sum of the counts to touch the circles in sequence) of the ATMT (P = 0.001) indicating that they became faster after the fatigue-inducing task, subjective level of fatigue (P < 0.001), and %LF (P = 0.035) increased significantly, whereas %HF decreased although this did not reach statistical significance (P = 0.170). Although LF measured in absolute units did not change significantly before and after the fatigue-inducing task (P = 0.771), HF measured in absolute units decreased after the task (P = 0.020). The LF/HF ratio did not change significantly before and after the fatigue-inducing task (P = 0.805).
Table 1

Effect of acute mental fatigue on various parameters

 

Before

After

P value

ATMT for total error counts

16 ± 19

20 ± 26

0.076

ATMT for total trial counts

305 ± 53

325 ± 45

0.001

VAS for fatigue

21 ± 13

47 ± 20

< 0.001

ECG variables

   

   %LF

38 ± 16

48 ± 18

0.035

   %HF

40 ± 20

33 ± 17

0.170

   LF/HF

3.4 ± 7.1

3.0 ± 3.8

0.396

Data are mean ± SD.

ATMT, advanced trail making test; VAS, visual analogue scale; ECG, electrocardiography; %LF, % low-frequency power; %HF, % high-frequency power.

Relationships between Chalder's fatigue scale score and task performances on the ATMT before the fatigue-inducing mental task are shown in Figure 1. The total error and trial counts were not associated with the Chalder's fatigue scale score.
Figure 1
Figure 1

Relationships between Chalder's fatigue scale score and task performances. The task performances were assessed using total error counts (a) and total trial counts (b) of the fatigue-evaluating mental task. Linear regression lines, Pearson's correlation coefficients (R), and P values are shown.

Relationships between Chalder's fatigue scale score and ECG variables before the fatigue-inducing mental task are shown in Figure 2. %LF and LF/HF ratio were positively associated with the Chalder's fatigue scale score, and %HF was negatively associated with the fatigue score.
Figure 2
Figure 2

Relationships between Chalder's fatigue scale score and autonomic nerve activities. Autonomic nerve activities were evaluated using the % low-frequency power (%LF; a), % high-frequency power (%HF; b), and LF/HF ratio (c) obtained on R-R wave interval analyses using electrocardiography. Linear regression lines, Pearson's correlation coefficients (R), and P values are shown.

Discussion

The present study showed that, after an acute fatigue-inducing mental task, subjective levels of fatigue, %LF, and total error counts on the ATMT (tendency) increased and %HF decreased (although this did not reach statistical signigicance) compared with before the fatigue-inducing task. In addition, %LF and LF/HF ratio were positively, and %HF was negatively associated with the Chalder's fatigue scale score.

These findings are consistent with the results of our previous report [27], in which decreased parasympathetic and increased sympathetic activities were caused after a 30-min fatigue-inducing mental task. The brain network, including the prefrontal cortex (PFC) and anterior cingulate cortex (ACC), has been shown to play an important role in the regulation of autonomic nervous activities [33]. Decreased parasympathetic activity and increased sympathetic activity are interpreted as a state of autonomic hypervigilance [34, 35], and sympathoexcitatory subcortical circuits are normally under the inhibitory control of the PFC [34–36]. In addition, the ACC is related to the regulation of parasympathetic activity [37, 38]. Because impaired selective attention assessed by increased error counts of the ATMT [24] was observed after the fatigue-inducing task, and the selective attention process activates the PFC and ACC [39–42], acute mental load might introduce temporary dysfunctions in the PFC and ACC to cause decreased parasympathetic and increased sympathetic activities.

Decreased parasympathetic nerve activity and increased sympathetic activity have also been observed in patients with CFS [10, 11, 43]. Because bilateral reduction of grey-matter volume in the PFC [44] and decreased cerebral blood flow [45] and reduction of serotonin transporters [46] in the ACC were reported in the patients with CFS, decreased parasympathetic and increased sympathetic activities may be induced by the chronic anatomical and/or functional alterations in the PFC and ACC in these patients. Hence, chronic fatigue is characterized as decreased parasympathetic and increased sympathetic activities, and the pathophysiological background may be explained by chronic alterations in the PFC and ACC.

Limitations

The present study has several limitations. First, the study included a small number of participants. In addition, we did not obtain the information as for such as smoking habit or lifestyles, and a great majority of women was included maybe because we recruited the participants via advertisement. Studies involving a larger number of participants and more detailed information regarding the participants are needed to allow for generalization of these results. Second, conclusions about cause-and-effect relationships cannot be made due to the cross-sectional nature of the data. Third, heart variability indices are measures of autonomic modulation of the sinus node-not autonomic tone. Heart rate variability indices must be interpreted in light of the heart rate itself. Finally, the daily level of fatigue was evaluated using self-reports, and as such, was subjective. An objective biomarker for daily level of fatigue has been developed [47]. The number of saliva human herpesvirus (HHV)-6 DNA copies was decreased after holidays for approximately 1 week [47]. The reliability and validity of the results of this study should be confirmed using this biomarker.

Conclusions

The present results provide evidence that increased sympathetic activity and decreased parasympathetic activity are associated with both the acute and daily level of fatigue. Because increased sympathetic activity and decreased parasympathetic activity have been reported in patients with CFS [10, 11, 43], these alterations of the autonomic nerve activities may be common characteristics of fatigue. Based on these findings, transitional mechanisms from acute fatigue to chronic fatigue and chronic fatigue to chronic fatigue-associated disease might be clarified. Our findings provide new perspectives on the mechanisms underlying fatigue.

List of abbreviations

ACC: 

Anterior cingulate cortex

ATMT: 

Advanced trail making test

CFS: 

chronic fatigue syndrome

ECG: 

Electrocardiography

HF: 

High-frequency power

HHV: 

Human herpesvirus

LF: 

Low-frequency power

PFC: 

Prefrontal cortex

VAS: 

Visual analogue scale.

Declarations

Acknowledgements

We thank Dr. Laini Dubach for editorial assistance with the manuscript. This work was supported in part by the Ministry of Health, Labour and Welfare of the Japan and by the Grant-in-Aid for Scientific Research B (KAKENHI: 23300241) from Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Authors’ Affiliations

(1)
Department of Physiology, Osaka City University Graduate School of Medicine, 1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
(2)
Molecular Probe Dynamics Laboratory, RIKEN Center for Molecular Imaging Science, 6-7-3 Minatojima-minamimachi, Chuo-ku, Hyogo 650-0047, Japan
(3)
Department of Health Science, Faculty of Health Science for Welfare, Kansai University of Welfare Sciences, 3-11-1 Asahigaoka, Osaka 582-0026, Japan
(4)
Health Chemical Co., Ltd., 179 Ikeda, Kume, Tokoname City, Aichi 479-0002, Japan
(5)
Osaka Urban Industry Promotion Center, 1-4-5 Honmachi, Chuo-ku, Osaka City, Osaka 541-0053, Japan

References

  1. Boksem MA, Tops M: Mental fatigue: costs and benefits. Brain Res Rev. 2008, 59 (1): 125-139. 10.1016/j.brainresrev.2008.07.001.View ArticlePubMedGoogle Scholar
  2. Chen MK: The epidemiology of self-perceived fatigue among adults. P rev Med. 1986, 15 (1): 74-81.Google Scholar
  3. Pawlikowska T, Chalder T, Hirsch SR, Wallace P, Wright DJ, Wessely SC: Population based study of fatigue and psychological distress. BMJ. 1994, 308 (6931): 763-766. 10.1136/bmj.308.6931.763.PubMed CentralView ArticlePubMedGoogle Scholar
  4. Watanabe Y: Preface and mini-review: fatigue science for human health. Fatigue Science for Human Health. Edited by: Watanabe Y, Evengård B, Natelson BH, Jason LA, Kuratsune H. 2008, New York: Springer, 5-11.Google Scholar
  5. Beurskens AJ, Bültmann U, Kant I, Vercoulen JH, Bleijenberg G, Swaen GM: Fatigue among working people: validity of a questionnaire measure. Occup Environ Med. 2000, 57 (5): 353-357. 10.1136/oem.57.5.353.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Stewart JM: Autonomic nervous system dysfunction in adolescents with postural orthostatic tachycardia syndrome and chronic fatigue syndrome is characterized by attenuated vagal baroreflex and potentiated sympathetic vasomotion. Pediatr Res. 2000, 48 (2): 218-226. 10.1203/00006450-200008000-00016.View ArticlePubMedGoogle Scholar
  7. Freeman R: The chronic fatigue syndrome is a disease of the autonomic nervous system. Sometimes. Clin Auton Res. 2002, 12 (4): 231-233. 10.1007/s10286-002-0058-2.View ArticlePubMedGoogle Scholar
  8. Winkler AS, Blair D, Marsden JT, Peters TJ, Wessely S, Cleare AJ: Autonomic function and serum erythropoietin levels in chronic fatigue syndrome. J Psychosom Res. 2004, 56 (2): 179-183. 10.1016/S0022-3999(03)00543-9.View ArticlePubMedGoogle Scholar
  9. Newton JL, Okonkwo O, Sutcliffe K, Seth A, Shin J, Jones DE: Symptoms of autonomic dysfunction in chronic fatigue syndrome. QJM. 2007, 100 (8): 519-526. 10.1093/qjmed/hcm057.View ArticlePubMedGoogle Scholar
  10. Wyller VB, Saul JP, Amlie JP, Thaulow E: Sympathetic predominance of cardiovascular regulation during mild orthostatic stress in adolescents with chronic fatigue. Clin Physiol Funct Imaging. 2007, 27 (4): 231-238. 10.1111/j.1475-097X.2007.00743.x.View ArticlePubMedGoogle Scholar
  11. Burton AR, Rahman K, Kadota Y, Lloyd A, Vollmer-Conna U: Reduced heart rate variability predicts poor sleep quality in a case-control study of chronic fatigue syndrome. Exp Brain Res. 2010, 204 (1): 71-78. 10.1007/s00221-010-2296-1.View ArticlePubMedGoogle Scholar
  12. Keselbrener L, Akselrod S, Ahiron A, Eldar M, Barak Y, Rotstein Z: Is fatigue in patients with multiple sclerosis related to autonomic dysfunction?. Clin Auton Res. 2000, 10 (4): 169-175. 10.1007/BF02291352.View ArticlePubMedGoogle Scholar
  13. Merkelbach S, Dillmann U, Kölmel C, Holz I, Muller M: Cardiovascular autonomic dysregulation and fatigue in multiple sclerosis. Mult Scler. 2001, 7 (5): 320-326.View ArticlePubMedGoogle Scholar
  14. Flachenecker P, Rufer A, Bihler I, Hippel C, Reiners K, Toyka KV, Kesselring J: Fatigue in MS is related to sympathetic vasomotor dysfunction. Neurology. 2003, 61 (6): 851-853.View ArticlePubMedGoogle Scholar
  15. Newton JL, Davidson A, Kerr S, Bhala N, Pairman J, Burt J, Jones DE: Autonomic dysfunction in primary biliary cirrhosis correlates with fatigue severity. Eur J Gastroenterol Hepatol. 2007, 19 (2): 125-132. 10.1097/01.meg.0000252629.96043.67.View ArticlePubMedGoogle Scholar
  16. Tanaka M, Mizuno K, Tajima S, Sasabe T, Watanabe Y: Central nervous system fatigue alters autonomic nerve activity. Life Sci. 2009, 84 (7-8): 235-239. 10.1016/j.lfs.2008.12.004.View ArticlePubMedGoogle Scholar
  17. Chalder T, Berelowitz G, Pawlikowska T, Watts L, Wessely S, Wright D, Wallace EP: Development of a fatigue scale. J Psychosom Res. 1993, 37 (2): 147-153. 10.1016/0022-3999(93)90081-P.View ArticlePubMedGoogle Scholar
  18. Ataka S, Tanaka M, Nozaki S, Mizuma H, Mizuno K, Tahara T, Sugino T, Shirai T, Kajimoto Y, Kuratsune H, Kajimoto O, Watanabe Y: Effects of Applephenon and ascorbic acid on physical fatigue. Nutrition. 2007, 23 (5): 419-423. 10.1016/j.nut.2007.03.002.View ArticlePubMedGoogle Scholar
  19. Ataka S, Tanaka M, Nozaki S, Mizuma H, Mizuno K, Tahara T, Sugino T, Shirai T, Kajimoto Y, Kuratsune H, Kajimoto O, Watanabe Y: Effects of oral administration of caffeine and D-ribose on mental fatigue. Nutrition. 2008, 24 (3): 233-238. 10.1016/j.nut.2007.12.002.View ArticlePubMedGoogle Scholar
  20. Mizuno K, Tanaka M, Nozaki S, Mizuma H, Ataka S, Tahara T, Sugino T, Shirai T, Kajimoto Y, Kuratsune H, Kajimoto O, Watanabe Y: Antifatigue effects of coenzyme Q10 during physical fatigue. Nutrition. 2008, 24 (4): 293-299. 10.1016/j.nut.2007.12.007.View ArticlePubMedGoogle Scholar
  21. Mizuma H, Tanaka M, Nozaki S, Mizuno K, Tahara T, Ataka S, Sugino T, Shirai T, Kajimoto Y, Kuratsune H, Kajimoto O, Watanabe Y: Daily oral administration of crocetin attenuates physical fatigue in human subjects. Nutr Res. 2009, 29 (3): 145-150. 10.1016/j.nutres.2009.02.003.View ArticlePubMedGoogle Scholar
  22. Nozaki S, Tanaka M, Mizuno K, Ataka S, Mizuma H, Tahara T, Sugino T, Shirai T, Eguchi A, Okuyama K, Yoshida K, Kajimoto Y, Kuratsune H, Kajimoto O, Watanabe Y: Mental and physical fatigue-related biochemical alterations. Nutrition. 2009, 25 (1): 51-57. 10.1016/j.nut.2008.07.010.View ArticlePubMedGoogle Scholar
  23. Braver TS, Cohen JD, Nystrom LE, Jonides J, Smith EE, Noll DC: A parametric study of prefrontal cortex involvement in human working memory. Neuroimage. 1997, 5 (1): 49-62. 10.1006/nimg.1996.0247.View ArticlePubMedGoogle Scholar
  24. Mizuno K, Watanabe Y: Utility of an advanced trail making test as a neuropsychological tool for an objective evaluation of work efficiency during mental fatigue. Fatigue Science for Human Health. Edited by: Watanabe Y, Evengård B, Natelson BH, Jason LA, Kuratsune H. 2008, New York: Springer, 47-54.Google Scholar
  25. Kajimoto O: Development of a method of evaluation of fatigue and its economic impacts. Fatigue Science for Human Health. Edited by: Watanabe Y, Evengård B, Natelson BH, Jason LA, Kuratsune H. 2008, New York: Springer, 33-46.Google Scholar
  26. Lee KA, Hicks G, Nino-Murcia G: Validity and reliability of a scale to assess fatigue. Psychiatry Res. 1991, 36 (3): 291-298. 10.1016/0165-1781(91)90027-M.View ArticlePubMedGoogle Scholar
  27. Tanaka M, Fukuda S, Mizuno K, Kuratsune H, Watanabe Y: Stress and coping styles are associated with severe fatigue in medical students. Behav Med. 2009, 35 (3): 87-92.View ArticlePubMedGoogle Scholar
  28. Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ: Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science. 1981, 213 (4504): 220-222. 10.1126/science.6166045.View ArticlePubMedGoogle Scholar
  29. Pomeranz B, Macaulay RJ, Caudill MA, Kutz I, Adam D, Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ: Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol. 1985, 248 (1 Pt 2): 151-153.Google Scholar
  30. Malliani A, Pagani M, Lombardi F, Cerutti S: Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991, 84 (2): 482-492.View ArticlePubMedGoogle Scholar
  31. Appel ML, Berger RD, Saul JP, Smith JM, Cohen RJ: Beat to beat variability in cardiovascular variables: noise or music?. J Am Coll Cardiol. 1989, 14 (5): 1139-1148. 10.1016/0735-1097(89)90408-7.View ArticlePubMedGoogle Scholar
  32. Pagani M, Montano N, Porta A, Malliani A, Abboud FM, Birkett C, Somers VK: Relationship between spectral components of cardiovascular variabilities and direct measures of muscle sympathetic nerve activity in humans. Circulation. 1997, 95 (6): 1441-1448.View ArticlePubMedGoogle Scholar
  33. Tang YY, Ma Y, Fan Y, Feng H, Wang J, Feng S, Lu Q, Hu B, Lin Y, Li J, Zhang Y, Wang Y, Zhou L, Fan M: Central and autonomic nervous system interaction is altered by short-term meditation. Proc Natl Acad Sci USA. 2009, 106 (22): 8865-8870. 10.1073/pnas.0904031106.PubMed CentralView ArticlePubMedGoogle Scholar
  34. Thayer JF: On the importance of inhibition: central and peripheral manifestations of nonlinear inhibitory processes in neural systems. Dose Response. 2006, 4 (1): 2-21. 10.2203/dose-response.004.01.002.Thayer.PubMed CentralView ArticlePubMedGoogle Scholar
  35. Thayer JF, Sternberg E: Beyond heart rate variability: vagal regulation of allostatic systems. Ann N Y Acad Sci. 2006, 1088: 361-372. 10.1196/annals.1366.014.View ArticlePubMedGoogle Scholar
  36. Amat J, Baratta MV, Paul E, Bland ST, Watkins LR, Maier SF: Medial prefrontal cortex determines how stressor controllability affects behavior and dorsal raphe nucleus. Nat Neurosci. 2005, 8 (3): 365-371. 10.1038/nn1399.View ArticlePubMedGoogle Scholar
  37. Kubota Y, Sato W, Toichi M, Murai T, Okada T, Hayashi A, Sengoku A: Frontal midline theta rhythm is correlated with cardiac autonomic activities during the performance of an attention demanding meditation procedure. Brain Res Cogn Brain Res. 2001, 11 (2): 281-287. 10.1016/S0926-6410(00)00086-0.View ArticlePubMedGoogle Scholar
  38. Takahashi M, Arito H: Effects of single and repeated cognitive tasks on autonomic balance as observed by an analysis of R-R intervals. Eur J Appl Physiol Occup Physiol. 1996, 72 (4): 316-322. 10.1007/BF00599691.View ArticlePubMedGoogle Scholar
  39. Danckert J, Maruff P, Ymer C, Kinsella G, Yucel M, de Graaff S, Currie J: Goal-directed selective attention and response competition monitoring: evidence from unilateral parietal and anterior cingulate lesions. Neuropsychology. 2000, 14 (1): 16-28.View ArticlePubMedGoogle Scholar
  40. Weissman DH, Giesbrecht B, Song AW, Mangun GR, Woldorff MG: Conflict monitoring in the human anterior cingulate cortex during selective attention to global and local object features. Neuroimage. 2003, 19 (4): 1361-1368. 10.1016/S1053-8119(03)00167-8.View ArticlePubMedGoogle Scholar
  41. Schreppel TJ, Pauli P, Ellgring H, Fallgatter AJ, Herrmann MJ: The impact of prefrontal cortex for selective attention in a visual working memory task. Int J Neurosci. 2008, 118 (12): 1673-88. 10.1080/00207450601067356.View ArticlePubMedGoogle Scholar
  42. Morishima Y, Akaishi R, Yamada Y, Okuda J, Toma K, Sakai K: Task-specific signal transmission from prefrontal cortex in visual selective attention. Nat Neurosci. 2009, 12 (1): 85-91. 10.1038/nn.2237.View ArticlePubMedGoogle Scholar
  43. Yamaguti K, Sasabe T, Kuratsune H, Nishizawa Y, Watanabe Y: The Journal of Therapy. 2008, 90: 537-547. (In Japanese)Google Scholar
  44. Okada T, Tanaka M, Kuratsune H, Watanabe Y, Sadato N: Mechanisms underlying fatigue: a voxel-based morphometric study of chronic fatigue syndrome. BMC Neurol. 2004, 4 (1): 14-10.1186/1471-2377-4-14.PubMed CentralView ArticlePubMedGoogle Scholar
  45. Kuratsune H, Yamaguti K, Lindh G, Evengård B, Hagberg G, Matsumura K, Iwase M, Onoe H, Takahashi M, Machii T, Kanakura Y, Kitani T, Långström B, Watanabe Y: Brain regions involved in fatigue sensation: reduced acetylcarnitine uptake into the brain. Neuroimage. 2002, 17 (3): 1256-1265. 10.1006/nimg.2002.1260.View ArticlePubMedGoogle Scholar
  46. Yamamoto S, Ouchi Y, Onoe H, Yoshikawa E, Tsukada H, Takahashi H, Iwase M, Yamaguti K, Kuratsune H, Watanabe Y: Reduction of serotonin transporters of patients with chronic fatigue syndrome. Neuroreport. 2004, 15 (17): 2571-2574. 10.1097/00001756-200412030-00002.View ArticlePubMedGoogle Scholar
  47. Kondo K: Human herpesvirus latency and fatigue. Uirusu. 2005, 55: 9-17. 10.2222/jsv.55.9. (In Japanese)View ArticlePubMedGoogle Scholar

Copyright

© Tanaka et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement

Behavioral and Brain Functions

ISSN: 1744-9081

Contact us