AJP - Heart Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Am J Physiol Heart Circ Physiol 288: H1461-H1467, 2005. First published October 21, 2004; doi:10.1152/ajpheart.00948.2004
0363-6135/05 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
288/3/H1461    most recent
00948.2004v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (17)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ogoh, S.
Right arrow Articles by Secher, N. H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ogoh, S.
Right arrow Articles by Secher, N. H.

Dynamic cerebral autoregulation during exhaustive exercise in humans

Shigehiko Ogoh,1,2 Mads K. Dalsgaard,2 Chie C. Yoshiga,2 Ellen A. Dawson,2 David M. Keller,1 Peter B. Raven,1 and Niels H. Secher2

1Department of Integrative Physiology, University of North Texas Health Science Center, Fort Worth, Texas; and 2Department of Anesthesia, Copenhagen Muscle Research Center, Rigshospitalet, University of Copenhagen, Denmark

Submitted 10 September 2004 ; accepted in final form 15 October 2004


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
We investigated whether dynamic cerebral autoregulation is affected by exhaustive exercise using transfer-function gain and phase shift between oscillations in mean arterial pressure (MAP) and middle cerebral artery (MCA) mean blood flow velocity (Vmean). Seven subjects were instrumented with a brachial artery catheter for measurement of MAP and determination of arterial PCO2 (PaCO2) while jugular venous oxygen saturation (SvO2) was determined to assess changes in whole brain blood flow. After a 10-min resting period, the subjects performed dynamic leg-cycle ergometry at 168 ± 5 W (mean ± SE) that was continued to exhaustion with a group average time of 26.8 ± 5.8 min. Despite no significant change in MAP during exercise, MCA Vmean decreased from 70.2 ± 3.6 to 57.4 ± 5.4 cm/s, SvO2 decreased from 68 ± 1 to 58 ± 2% at exhaustion, and both correlated to PaCO2 (5.5 ± 0.2 to 3.9 ± 0.2 kPa; r = 0.47; P = 0.04 and r = 0.74; P < 0.001, respectively). An effect on brain metabolism was indicated by a decrease in the cerebral metabolic ratio of O2 to [glucose + one-half lactate] from 5.6 to 3.8 (P < 0.05). At the same time, the normalized low-frequency gain between MAP and MCA Vmean was increased (P < 0.05), whereas the phase shift tended to decrease. These findings suggest that dynamic cerebral autoregulation was impaired by exhaustive exercise despite a hyperventilation-induced reduction in PaCO2.

cerebral autoregulation; carbon dioxide; blood flow; metabolism

BLOOD FLOW TO THE BRAIN is controlled by regional changes in neural activity vs. global influences including cerebral autoregulation (CA; Ref. 28). However, CA is itself subject to global influences that help to maintain a stable flow despite marked changes in whole body metabolism and arterial blood pressure (ABP), e.g., during exercise. For instance, CA is attenuated by hypercapnia and enhanced by hypocapnia (1, 8, 9, 27), whereas sympathetic activation shifts the CA curve to the right (22) and prevents cerebral hyperperfusion during exercise (13). During the progression toward a maximal effort with either a constant or incremental increase in workload, there is a lowering of arterial carbon dioxide tension (PaCO2) that occurs as a result of hyperventilation (16), and there is an exponential increase in plasma catecholamines (19). Collectively, the decrease in PaCO2 and the sympathetic activation suggest that especially during intense exercise, CA will be enhanced.

Although acute changes in ABP are transmitted to the cerebral circulation, under normal conditions the cerebral blood flow tends to return to its original value within a few seconds (1, 26). This is usually referred to as dynamic CA, and it correlates well with assessments of static autoregulation (26, 37). During mild to heavy exercise, dynamic CA is maintained and may reflect a balance between the influence of sympathetic activity and PaCO2 (5). However, it remains unknown whether dynamic CA becomes enhanced during exhaustive exercise when PaCO2 decreases. To test this question, subjects exercised to exhaustion on a bicycle ergometer while beat-to-beat measurements of middle cerebral artery (MCA) mean blood flow velocity (Vmean) and mean arterial pressure (MAP) were made and analyzed using linear dynamic analysis (26, 39, 41). At the same time, jugular venous oxygen saturation (SvO2) values were determined to assess changes in whole brain blood flow.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Seven men with a mean age of 23 ± 2 yr, height of 180 ± 10 cm, and weight of 72 ± 9 kg (means ± SD) were recruited to participate in the study. All subjects were free of cardiovascular and pulmonary disorders and were not using prescribed or over-the-counter medications. Each subject provided written informed consent as approved by the Ethics Committee of Copenhagen (KF 01-369/97). Subjects were requested to abstain from caffeinated beverages for 12 h and strenuous physical activity and alcohol for at least 24 h before the experiment.

Protocol. The subjects arrived at the laboratory after fasting overnight. After catheterization, they were seated in a semirecumbent position on a modified Krogh cycle ergometer. After a 10-min resting period, the subjects began cycling at 10 W, which was subsequently adjusted to the target heart rate (HR) of 160 beats/min, i.e., to 168 ± 5 W (mean ± SE), which was continued until they could no longer maintain a pedaling frequency of 60 rpm despite strong verbal encouragement.

Measurements. A catheter (1.1 mm inner diameter, 20 gauge) was placed in the brachial artery of the nondominant arm, and ABP was measured using a Bentley transducer (Uden) positioned at the level of the right atrium and connected to a pressure-monitoring system (model M1275A; Hewlett-Packard). Beat-to-beat data of cardiovascular variables were acquired and collected using a personal computer with customized software. The HR, stroke volume (SV), and thus cardiac output () were calculated from the blood pressure waveform using the Model flow method incorporating age, sex, height, and weight (BeatScope 1.0 software; TNO TPD; Biomedical Instrumentation; Amsterdam, The Netherlands). Model flow measurement provides a reliable estimate of changes in during exercise in healthy young humans (36), and SV and were expressed relative to rest. Arterial blood samples were obtained with subjects at rest and exercising and were stored in ice water until analysis for pH, arterial PO2 (PaO2) and PaCO2, oxygen saturation (SaO2), and glucose and lactate levels (model ABL725; Radiometer; Copenhagen, Denmark). In addition, a catheter (2.2 mm, 14 gauge) was placed in the right internal jugular vein for measurement of internal jugular venous pressure, venous pH, venous PO2 (PvO2) and venous PCO2 (PvCO2), oxygen saturation (SvO2), and glucose and lactate levels. The MCA Vmean was obtained by transcranial Doppler ultrasonography (Multi-Dop X; DWL; Sipplingen, Germany) with a 2-MHz probe placed over the temporal window and fixed with an adjustable headband and adhesive ultrasonic gel (Tensive; Parker Laboratories; Orange, NJ). Cerebral vascular resistance index (CVR index) was expressed as (MAP at MCA level) – (jugular venous pressure)/MCA Vmean. The MAP at the MCA level took into consideration the vertical distance from the fourth intercostal space in the midclavicular line (heart level) to the Doppler probe (i.e., hydrostatic the vertical length x 0.77 mmHg/cm). To evaluate changes in brain activation, the cerebral metabolic ratio was calculated from the arteriovenous differences across the brain for O2/(glucose + one-half lactate) as previously described (7).

Data analysis. Analog signals of ABP and the spectral envelope of MCA Vmean were sampled at 100 Hz and digitized at 12 bits for offline analysis. Beat-to-beat MAP and MCA Vmean values were obtained by integrating analog signals within each cardiac cycle and were linearly interpolated and resampled at 2 Hz for spectral analysis of dynamic CA (39). When subjects were at rest or exercising, dynamic CA was calculated as the transfer-function gain and phase shift between fluctuations in MAP and MCA Vmean (39). The transfer gain and phase shift reflect the relative amplitude and time relationship between the changes in MAP and MCA Vmean over a specified frequency range. From the temporal sequences of MAP and MCA Vmean, the frequency-domain transformations were computed with a fast Fourier transformation algorithm. The transfer function H(f) between the two signals was calculated as H(f) = Sxy(f)/Sxx(f), where Sxx(f) is the autospectrum of changes in MAP and Sxy(f) is the cross-spectrum between the two signals. The transfer function magnitude |H(f)| and phase spectrum |{Phi}(f)| were obtained from the real part HR(f) and imaginary part HI(f) of the complex function


Moreover, the transfer function H(f) was normalized to the mean values of input (x) and output (y) variables as H'(f) = [Sxy(f)x]/[Sxx(f)y], and the normalized gain was calculated as 20 log H'(f) to provide values in decibels. A value of 0 indicates that the output varied by the same fraction of the mean value as the input, and a negative or positive value indicate that the output varied less or more, respectively, than the input.

The squared coherence function MSC(f) was estimated as

where Syy(f) is the autospectrum of changes in MCA Vmean. The squared coherence function reflects the fraction of output power (MCA Vmean) that can be linearly related to the input power (MAP) at each frequency. Similar to a correlation coefficient, this value varies between 0 and 1.

Spectral power of MAP, MCA Vmean, mean value of transfer function gain, phase, and coherence function were calculated in the very-low-frequency (VLF, 0.02 to 0.07 Hz), low-frequency (LF, 0.07 to 0.20 Hz), and high-frequency (HF, 0.20 to 0.30 Hz) ranges to reflect different patterns of the dynamic pressure-flow relationship (39, 40). The ABP fluctuations in the HF range, including those induced by the respiratory frequency, are transferred to MCA Vmean, whereas ABP fluctuations in the LF range are independent of the respiratory frequency, and the LF transfer analysis reflects CA mechanisms (8, 39). Furthermore, the VLF range of both the flow and the pressure variabilities appears to reflect multiple physiological mechanisms that confound interpretation. Thus we used the LF range for the spectral analysis to identify the dynamic CA during exercise.

Resting measurements were made during a 3-min data collection segment, whereas during exercise, the data segments of minutes 6–9 and 12–15 and the 3-min period before exhaustion were used. The power spectra, transfer function gain, phase, and coherence of the minute 12–15 segment could be calculated for only five subjects, because in two subjects the period before exhaustion overlapped.

Statistical analysis. One-way ANOVA (SigmaStat; Jandel Scientific Software; SPSS; Chicago, IL) with repeated measures was used to assess the differences in the steady-state hemodynamic variables, spectral power of HR, MAP and MCA Vmean, transfer function gain, phase, and coherence function in each frequency range between rest and the three exercise segments. A Student-Newman-Keuls test was employed post hoc when main effects were significant, i.e., P < 0.05. Data are expressed as means ± SE, and the relationships between SvO2, MCA Vmean, and PaCO2 are described using linear regression analysis.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Exercise increased ABP, HR, SV, and (Table 1), and exhaustion was reached after 26.8 ± 5.8 min. HR continued to increase with time from 5 min (166 ± 4 beats/min) to exhaustion (185 ± 3 beats/min; P < 0.05), whereas SV and did not change significantly during exercise.


View this table:
[in this window]
[in a new window]
  		Table 1. Cardiovascular and blood gas variables measured with subjects at rest and during exercise to exhaustion

 
Blood gas variables. Throughout exercise, arterial lactate concentrations increased and pH decreased (P < 0.05), whereas PaO2 remained stable (Table 1). However, SaO2 decreased at the beginning of exercise (P < 0.05), whereas SvO2 increased at minute 5 (P < 0.05) and then decreased to a value smaller than at rest (P < 0.05). Thus the arteriovenous difference (a-v diff) in oxygen saturation across the brain decreased at the beginning of exercise (P < 0.05) and then increased at 15 min and at exhaustion to values similar to those obtained at rest. The a-v diff across the brain for lactate demonstrated a small release at rest (–0.45 ± 0.25 mmol/l); however, at 15 min and at exhaustion, an uptake occurred (a-v diff, 1.06 ± 0.23 and 1.00 ± 0.24 mmol/l, respectively; P < 0.05). Thus the cerebral metabolic ratio of O2 to (glucose + one-half lactate) decreased from 5.6 ± 0.7 at rest to 3.0 ± 0.4 and 3.8 ± 0.7 at 15 min and at exhaustion, respectively (P < 0.05).

MAP, MCA Vmean, SvO2, and PaCO2 values. Representative changes in MAP and MCA Vmean during exercise are outlined for one subject in Fig. 1. Despite no significant change in MAP throughout exercise to exhaustion, MCA Vmean decreased gradually toward exhaustion. The increase in MAP from rest to exercise was 23.5 ± 3.2% at 5 min, 19.4 ± 3.8% at 15 min, and 18.3 ± 4.3% at exhaustion (P < 0.05), while the changes in MCA Vmean were 19.7 ± 5.3, 12.8 ± 7.5, and –2.0 ± 9.0%, respectively (Table 1; P < 0.05). Thus CVR index tended to increase from 1.16 ± 0.06 mmHg·s·cm–1 at rest to 1.51 ± 0.23 mmHg·s·cm–1 (P = 0.11) at exhaustion. There was a small increase in PaCO2 at the beginning of exercise, but PaCO2 decreased to below the resting value at exhaustion (P < 0.05). Thus during exercise, the reduction in MCA Vmean was related to the decrease in PaCO2 (MCA Vmean = 33 + 6.8 x PaCO2; r = 0.47; P = 0.04; Fig. 2A). Similarly, SvO2 decreased from 68 ± 1 to 58 ± 2% at exhaustion and was also related to the decrease in PaCO2 (SvO2 = 34 + 5.0 x PaCO2; r = 0.74; P < 0.001; Fig. 2B).



View larger version (36K):
[in this window]
[in a new window]
  		Fig. 1. Mean arterial pressure (MAP) and middle cerebral artery (MCA) mean blood flow velocity (Vmean) during exercise for one subject.

 


View larger version (15K):
[in this window]
[in a new window]
  		Fig. 2. Relationships between MCA Vmean and arterial PCO2 (PaCO2; A) and venous O2 saturation (SvO2) and PaCO2 (B) at rest and during exercise. Values are means ± SE.

 
Spectral and transfer function analyses. During exercise to exhaustion, there were no significant changes in the spectral power of MCA Vmean across all frequency ranges; the same held for the spectral power of MAP with the exception of the HF range at exhaustion (Table 2; P < 0.05). The transfer function phase shift tended to decrease over time (Figs. 3 and 4), but at minutes 12–15 and at exhaustion, the transfer function gain as well as the normalized values for each frequency range increased from the resting values (P < 0.05). The coherence between MAP and MCA Vmean decreased compared with rest, but there was no significant difference between the values obtained during exercise (Fig. 4). Despite this, throughout exercise, the coherence remained >0.5, i.e., it remained statistically significant.


View this table:
[in this window]
[in a new window]
  		Table 2. Power spectra of beat-to-beat variability of mean arterial pressure and MCA mean blood flow velocity at rest and during exercise

 


View larger version (40K):
[in this window]
[in a new window]
  		Fig. 3. Cross-spectral analysis of the entire spectrum from 0.02 to 0.3 Hz at rest, 6–9 min, 12–15 min, and exhaustion. Group-averaged phase (A), gain (B), and normalized gain (C) between MAP and MCA Vmean are shown. LF, low frequency. Values are means; n = 7 subjects.

 


View larger version (14K):
[in this window]
[in a new window]
  		Fig. 4. Group-averaged low-frequency (0.07–0.2 Hz) transfer function phase (A), gain (B), normalized gain (C), and coherence (D) between MAP and MCA Vmean at rest and during exercise. Values are means ± SE. *P < 0.05, different from rest; {dagger}P < 0.05, different from 6 to 9 min.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The main finding of the present investigation was that the effectiveness of dynamic CA was reduced by exhaustive exercise despite a reduction in PaCO2 and a presumed marked increase in sympathetic activity. Furthermore, the slope of the linear relationship between MCA Vmean and PaCO2 throughout the range of PaCO2 (5.5 to ~3.9 kPa) that was developed by exercise to exhaustion appeared to be markedly less than at rest, i.e., 12 vs. 29%/kPa (12).

The CA maintains a constant cerebral blood flow and is considered to operate within a MAP range of 60–150 mmHg as long as and PaCO2 remain stable (28). However, cerebral blood flow is highly sensitive to alterations in PaCO2 (1, 8, 9, 12, 14, 27, 31). For example, at rest, increases in PaCO2 dilate the cerebral resistance vessels and promote blood flow, whereas a decrease causes vasoconstriction of the cerebral resistance vessels (14, 17, 31), which consequently produces marked changes in MCA Vmean without changes in diameter (12, 14, 31). The relationship between MCA Vmean and PaCO2 is unclear and has been reported to be linear (12), sigmoidal (31), and exponential (14). The cerebral metabolic demand for oxygen also contributes to changes in MCA Vmean (4). Throughout exercise to exhaustion, SvO2 decreased and correlated to the decrease in PaCO2 (see Fig. 2B), which suggests that PaCO2 maintains its ability to cause vasoconstriction of the cerebral resistance vessels during exhaustive exercise. With both MAP and remaining stable during exercise, the relationship between individual MCA Vmean and PaCO2 ranging from 5.5 to 3.9 kPa was linear (see Fig. 2A), but the slope was approximately half of that found both at rest (12) and during exercise combined with the administration of CO2 to the inspired air (24). Moreover, during exercise, MCA Vmean was higher than expected for a given PaCO2.

The cerebral metabolic rate of oxygen remains stable during cerebral activation (23). Therefore, during the initial 5 min of exercise, a decrease in the a-v diff in blood oxygen saturation across the brain indicates enhanced perfusion (see Table 1). However, at 15 min of exercise and at exhaustion, the a-v diff in blood oxygen saturation across the brain was not significantly different from that at rest, which suggests normalization of cerebral blood flow. In addition, the a-v diff of lactate concentration across the brain indicated increased uptake as the subject became tired particularly at exhaustion. Moreover, the cerebral metabolic ratio decreased during exercise to exhaustion. These results substantiate the hypothesis that cerebral metabolism is enhanced by intense exercise. Ide and co-workers (13, 15) found that changes in independent of MAP affect MCA Vmean. However, in the present study, both and MAP remained stable during exhaustive exercise, and the decreases in PaCO2 with exercise-induced hyperventilation therefore played a major role in regulation of MCA Vmean.

By using linear dynamic analysis between MAP and MCA Vmean, increases in the LF transfer function gain and normalized gain were identified during exhaustive exercise. Such an increase in transfer function gain between beat-to-beat MAP and MCA Vmean indicates a reduction in dynamic CA (26, 39, 40), whereas at rest, dynamic CA increases when PaCO2 is reduced (8, 27). By deflating thigh-mounted blood pressure cuffs, the rate of regulation, which is an index of dynamic CA, was calculated as 0.38, 0.20, and 0.11 s–1 in hypocapnia, normocapnia, and hypercapnia, respectively (1). Equally, Edwards et al. (9) used transfer function analysis to demonstrate that dynamic CA is improved at low end-tidal PCO2. In the present investigation, the sympathoexcitation associated with exhaustive exercise (10, 11, 33) and hyperventilatory response to metabolic acidosis and its resultant hypocapnia (16) would be expected to enhance dynamic CA (1, 8, 9, 27). However, the transfer function gain was increased, which indicates impairment of dynamic CA. The impairment in dynamic CA may be related to the altered milieu of cerebral vessels associated with the efflux of metabolites into the vascular tissue related to increased brain metabolism (7). In the systemic circulation, such increases in metabolites have been found to alter vasomotor tone (18). However, brain metabolism may not be the only reason that dynamic CA becomes impaired during exercise.

Another possible explanation for impaired dynamic CA is acute hyperammonemia during exhaustive exercise. In patients with acute liver failure, sympathetic regulation of cerebral blood flow is impaired (20), and CA becomes impaired in response to stepwise hypotensive stimuli (21), which may be related to ammonia-induced perturbations of brain metabolism (6, 25). Similarly, intense exercise increases the blood content of ammonia, which easily penetrates the blood-brain-barrier (2). Thus impaired dynamic CA and reduced responsiveness of MCA Vmean to changes in PaCO2 could result from elevated ammonia in the brain during exhaustive exercise.

The range or set point of the function representing both static and dynamic CA is influenced by the prevailing perfusion pressure (35). In chronic hypertension, the limits of the CA function curve are shifted to the higher MAP (28), whereas chronic cerebral hypoperfusion shifts the curve to a lower pressure (38). Acute exposure to orthostatic stress such as head-up tilt and lower body negative pressure results in a downward (3) or rightward (41, 42) shift in the CA curve. Levine et al. (22) speculate that sympathetic activation during lower body negative pressure shifts the CA curve to the right and compromises CA during orthostatic hypotension and may contribute to symptoms of presyncope. However, it has been reported (13) that during heavy exercise, the prospect of hyperperfusion of the brain was prevented by sympathoexcitation and may be reflective of a rightward shift in the CA function curve. In the present investigation, although a rightward shift in the CA curve may have been present especially at exhaustion, dynamic CA was impaired. This impairment was associated with the hyperventilatory response to metabolic acidosis producing hypocapnia; therefore, we conclude that the interaction between sympathoexcitation and decreases in PaCO2 are changed by exhaustive exercise via an unidentified mechanism.

Potential limitations. Estimating changes in cerebral blood flow via MCA Vmean could be influenced by changes in diameter of the insonated vessel. However, MCA diameter remains relatively constant under a variety of conditions (32, 34). Nonetheless, sympathetic activity may induce constriction of MCA during submaximal and, more particularly, during maximal exercise (16). However, sympathetic activation produced during muscle ischemia after rhythmic handgrip exercise does not change the luminar diameter of a systemic conduit artery (30). Pott et al. (29) suggested that the 50% increase of MCA Vmean during strenuous exercise (at >80% of maximal work capacity) may reflect MCA constriction when compared with the only 20% increase of MCA Vmean observed in athletes during low-workload exercise. However, these differences can be explained by the increase in sympathoexcitation producing greater constrictions of the cerebral resistance vessels at the higher workload without changing the MCA diameter. Hence, we contend that the beat-to-beat changes in MCA Vmean during steady-state exercise primarily reflect changes in flow, which is confirmed by the changes in SvO2. It should also be noted that during intense exercise, the MAP profile includes a considerable increase in pulse pressure. Considering that the fluctuations in MCA Vmean encompass changes in both peak systolic and diastolic flow velocities, it is important to consider the potential differences that may occur during these two distinct phases of the MCA Vmean profile. This is particularly important with regard to the increase in the systolic pressure wave that must be countered by CA.

In conclusion, the relationship between MCA Vmean and PaCO2 appears to be linear throughout the range of PaCO2 that was produced by subjects' exercise to exhaustion. However, the slope of the relationship curve was markedly less during exercise than at rest, and despite the large reduction in PaCO2 resulting from hyperventilation, dynamic CA was impaired.


   ACKNOWLEDGMENTS
 
The authors appreciate the time and effort expended by the subjects. The authors also thank Peter Nissen for expert technical assistance and Lisa Marquez for assistance in preparing the document.


   FOOTNOTES
 

Address for reprint requests and other correspondence: S. Ogoh, Dept. of Integrative Physiology, Univ. of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, Texas, 76107 (E-mail: sogoh{at}hsc.unt.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Aaslid R, Lindegaard KF, Sorteberg W, and Nornes H. Cerebral autoregulation dynamics in humans. Stroke 20: 45–52, 1989.[Abstract/Free Full Text]
  2. Bachmann C. Mechanisms of hyperammonemia. Clin Chem Lab Med 40: 653–662, 2002.[CrossRef][ISI][Medline]
  3. Bondar RL, Dunphy PT, Moradshahi P, Dai H, Kassam MS, Stein F, Schneider S, and Rubin M. Vertical shift in cerebral autoregulation curve: a graded head-up tilt study. Can Aeronaut Space J 45: 3–8, 1999.[Medline]
  4. Brown MM, Wade JP, and Marshall J. Fundamental importance of arterial oxygen content in the regulation of cerebral blood flow in man. Brain 108: 81–93, 1985.[Abstract/Free Full Text]
  5. Brys M, Brown CM, Marthol H, Franta R, and Hilz MJ. Dynamic cerebral autoregulation remains stable during physical challenge in healthy persons. Am J Physiol Heart Circ Physiol 285: H1048–H1054, 2003.[Abstract/Free Full Text]
  6. Butterworth RF, Girard G, and Giguere JF. Regional differences in the capacity for ammonia removal by brain following portocaval anastomosis. J Neurochem 51: 486–490, 1988.[CrossRef][ISI][Medline]
  7. Dalsgaard MK, Ogoh S, Dawson EA, Yoshiga CC, Quistorff B, and Secher NH. Cerebral carbohydrate cost of physical exertion in humans. Am J Physiol Regul Integr Comp Physiol 287: R534–R540, 2004.[Abstract/Free Full Text]
  8. Diehl RR, Linden D, Lucke D, and Berlit P. Phase relationship between cerebral blood flow velocity and blood pressure. A clinical test of autoregulation. Stroke 26: 1801–1804, 1995.[Abstract/Free Full Text]
  9. Edwards MR, Shoemaker JK, and Hughson RL. Dynamic modulation of cerebrovascular resistance as an index of autoregulation under tilt and controlled PET(CO2). Am J Physiol Regul Integr Comp Physiol 283: R653–R662, 2002.[Abstract/Free Full Text]
  10. Fadel PJ, Ogoh S, Watenpaugh DE, Wasmund W, Olivencia-Yurvati A, Smith ML, and Raven PB. Carotid baroreflex regulation of sympathetic nerve activity during dynamic exercise in humans. Am J Physiol Heart Circ Physiol 280: H1383–H1390, 2001.[Abstract/Free Full Text]
  11. Hartley LH, Mason JW, Hogan RP, Jones LG, Kotchen TA, Mougey EH, Wherry FE, Pennington LL, and Ricketts PT. Multiple hormonal responses to graded exercise in relation to physical training. J Appl Physiol 33: 602–606, 1972.[Free Full Text]
  12. Hauge A, Thoresen M, and Walloe L. Changes in cerebral blood flow during hyperventilation and CO2-breathing measured transcutaneously in humans by a bidirectional, pulsed, ultrasound Doppler blood velocitymeter. Acta Physiol Scand 110: 167–173, 1980.[ISI][Medline]
  13. Ide K, Boushel R, Sorensen HM, Fernandes A, Cai Y, Pott F, and Secher NH. Middle cerebral artery blood velocity during exercise with beta-1 adrenergic and unilateral stellate ganglion blockade in humans. Acta Physiol Scand 170: 33–38, 2000.[CrossRef][ISI][Medline]
  14. Ide K, Eliasziw M, and Poulin MJ. Relationship between middle cerebral artery blood velocity and end-tidal PCO2 in the hypocapnic-hypercapnic range in humans. J Appl Physiol 95: 129–137 2003.[Abstract/Free Full Text]
  15. Ide K, Pott F, Van Lieshout JJ, and Secher NH. Middle cerebral artery blood velocity depends on cardiac output during exercise with a large muscle mass. Acta Physiol Scand 162: 13–20, 1998.[CrossRef][ISI][Medline]
  16. Ide K and Secher NH. Cerebral blood flow and metabolism during exercise. Prog Neurobiol 61: 397–414, 2000.[CrossRef][ISI][Medline]
  17. Imms FJ, Russo F, Iyawe VI, and Segal MB. Cerebral blood flow velocity during and after sustained isometric skeletal muscle contractions in man. Clin Sci (Lond) 94: 353–358, 1998.[Medline]
  18. Keller DM, Wasmund WL, Wray DW, Ogoh S, Fadel PJ, Smith ML, and Raven PB. Carotid baroreflex control of leg vascular conductance at rest and during exercise. J Appl Physiol 94: 542–548, 2003.[Abstract/Free Full Text]
  19. Kjaer M and Secher NH. Neural influence on cardiovascular and endocrine responses to static exercise in humans. Sports Med 13: 303–319, 1992.[ISI][Medline]
  20. Lagi A, Laffi G, Cencetti S, Barletta G, Foschi M, Vizzutti F, Bandinelli R, Pantaleo P, Tosti Guerra C, Gentilini P, and La Villa G. Impaired sympathetic regulation of cerebral blood flow in patients with cirrhosis of the liver. Clin Sci (Lond) 103: 43–51, 2002.[Medline]
  21. Lagi A, La Villa G, Barletta G, Cencetti S, Bacalli S, Cipriani M, Foschi M, Lazzeri C, Del Bene R, Gentilini P, and Laffi G. Cerebral autoregulation in patients with cirrhosis and ascites. A transcranial Doppler study. J Hepatol 27: 114–120, 1997.[CrossRef][ISI][Medline]
  22. Levine BD, Giller CA, Lane LD, Buckey JC, and Blomqvist CG. Cerebral versus systemic hemodynamics during graded orthostatic stress in humans. Circulation 90: 298–306, 1994.[Abstract/Free Full Text]
  23. Madsen PL, Sperling BK, Warming T, Schmidt JF, Secher NH, Wildschiodtz G, Holm S, and Lassen NA. Middle cerebral artery blood velocity and cerebral blood flow and O2 uptake during dynamic exercise. J Appl Physiol 74: 245–250, 1993.[Abstract/Free Full Text]
  24. Nybo L and Nielsen B. Middle cerebral artery blood velocity is reduced with hyperthermia during prolonged exercise in humans. J Physiol 534: 279–286, 2001.[Abstract/Free Full Text]
  25. Ott P and Larsen FS. Blood-brain barrier permeability to ammonia in liver failure: a critical reappraisal. Neurochem Int 44: 185–198, 2004.[CrossRef][ISI][Medline]
  26. Panerai RB, Dawson SL, and Potter JF. Linear and nonlinear analysis of human dynamic cerebral autoregulation. Am J Physiol Heart Circ Physiol 277: H1089–H1099, 1999.[Abstract/Free Full Text]
  27. Panerai RB, Deverson ST, Mahony P, Hayes P, and Evans DH. Effects of CO2 on dynamic cerebral autoregulation measurement. Physiol Meas 20: 265–275, 1999.[CrossRef][ISI][Medline]
  28. Paulson OB, Strandgaard S, and Edvinsson L. Cerebral autoregulation. Cerebrovasc Brain Metab Rev 2: 161–192, 1990.[ISI][Medline]
  29. Pott F, Jensen K, Hansen H, Christensen NJ, Lassen NA, and Secher NH. Middle cerebral artery blood velocity and plasma catecholamines during exercise. Acta Physiol Scand 158: 349–356, 1996.[CrossRef][ISI][Medline]
  30. Pott F, Ray CA, Olesen HL, Ide K, and Secher NH. Middle cerebral artery blood velocity, arterial diameter and muscle sympathetic nerve activity during post-exercise muscle ischaemia. Acta Physiol Scand 160: 43–47, 1997.[CrossRef][ISI][Medline]
  31. Ringelstein EB, Sievers C, Ecker S, Schneider PA, and Otis SM. Noninvasive assessment of CO2-induced cerebral vasomotor response in normal individuals and patients with internal carotid artery occlusions. Stroke 19: 963–969, 1988.[Abstract/Free Full Text]
  32. Schreiber SJ, Gottschalk S, Weih M, Villringer A, and Valdueza JM. Assessment of blood flow velocity and diameter of the middle cerebral artery during the acetazolamide provocation test by use of transcranial Doppler sonography and MR imaging. Am J Neuroradiol 21: 1207–1211, 2000.[Abstract/Free Full Text]
  33. Seals DR and Victor RG. Regulation of muscle sympathetic nerve activity during exercise in humans. Exerc Sport Sci Rev 19: 313–349, 1991.[Medline]
  34. Serrador JM, Picot PA, Rutt BK, Shoemaker JK, and Bondar RL. MRI measures of middle cerebral artery diameter in conscious humans during simulated orthostasis. Stroke 31: 1672–1678, 2000.[Abstract/Free Full Text]
  35. Serrador JM, Wood SJ, Picot PA, Stein F, Kassam MS, Bondar RL, Rupert AH, and Schlegel TT. Effect of acute exposure to hypergravity (GX vs. GZ) on dynamic cerebral autoregulation. J Appl Physiol 91: 1986–1994, 2001.[Abstract/Free Full Text]
  36. Sugawara J, Tanabe T, Miyachi M, Yamamoto K, Takahashi K, Iemitsu M, Otsuki T, Homma S, Maeda S, Ajisaka R, and Matsuda M. Non-invasive assessment of cardiac output during exercise in healthy young humans: comparison between Modelflow method and Doppler echocardiography method. Acta Physiol Scand 179: 361–366, 2003.[CrossRef][ISI][Medline]
  37. Tiecks FP, Lam AM, Aaslid R, and Newell DW. Comparison of static and dynamic cerebral autoregulation measurements. Stroke 26: 1014–1019, 1995.[Abstract/Free Full Text]
  38. Young WL, Pile-Spellman J, Prohovnik I, Kader A, and Stein BM. Evidence for adaptive autoregulatory displacement in hypotensive cortical territories adjacent to arteriovenous malformations. Columbia University AVM Study Project. Neurosurgery 34: 601–611, 1994.[ISI][Medline]
  39. Zhang R, Zuckerman JH, Giller CA, and Levine BD. Transfer function analysis of dynamic cerebral autoregulation in humans. Am J Physiol Heart Circ Physiol 274: H233–H241, 1998.[Abstract/Free Full Text]
  40. Zhang R, Zuckerman JH, Iwasaki K, Wilson TE, Crandall CG, and Levine BD. Autonomic neural control of dynamic cerebral autoregulation in humans. Circulation 106: 1814–1820, 2002.[Abstract/Free Full Text]
  41. Zhang R, Zuckerman JH, and Levine BD. Deterioration of cerebral autoregulation during orthostatic stress: insights from the frequency domain. J Appl Physiol 85: 1113–1122, 1998.[Abstract/Free Full Text]
  42. Zhang R, Zuckerman JH, Pawelczyk JA, and Levine BD. Effects of head-down-tilt bed rest on cerebral hemodynamics during orthostatic stress. J Appl Physiol 83: 2139–2145, 1997.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 J. Appl. Physiol.Home page
J. P. Fisher, S. Ogoh, C. N. Young, P. B. Raven, and P. J. Fadel
Regulation of middle cerebral artery blood velocity during dynamic exercise in humans: influence of aging
J Appl Physiol, July 1, 2008; 105(1): 266 - 273.
[Abstract] [Full Text] [PDF]

Home page
 J. Appl. Physiol.Home page
N. H. Secher, T. Seifert, and J. J. Van Lieshout
Cerebral blood flow and metabolism during exercise: implications for fatigue
J Appl Physiol, January 1, 2008; 104(1): 306 - 314.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Physiol. Heart Circ. Physiol.Home page
Y.-S. Kim, R. Krogh-Madsen, P. Rasmussen, P. Plomgaard, S. Ogoh, N. H. Secher, and J. J. van Lieshout
Effects of hyperglycemia on the cerebrovascular response to rhythmic handgrip exercise
Am J Physiol Heart Circ Physiol, July 1, 2007; 293(1): H467 - H473.
[Abstract] [Full Text] [PDF]

Home page
 J. Physiol.Home page
K.-i. Iwasaki, B. D. Levine, R. Zhang, J. H. Zuckerman, J. A. Pawelczyk, A. Diedrich, A. C. Ertl, J. F. Cox, W. H. Cooke, C. A. Giller, et al.
Human cerebral autoregulation before, during and after spaceflight
J. Physiol., March 15, 2007; 579(3): 799 - 810.
[Abstract] [Full Text] [PDF]

Home page
 J. Appl. Physiol.Home page
S. Ogoh, J. P. Fisher, S. Purkayastha, E. A. Dawson, P. J. Fadel, M. J. White, R. Zhang, N. H. Secher, and P. B. Raven
Regulation of middle cerebral artery blood velocity during recovery from dynamic exercise in humans
J Appl Physiol, February 1, 2007; 102(2): 713 - 721.
[Abstract] [Full Text] [PDF]

Home page
 J. Appl. Physiol.Home page
S. Ogoh, R. M. Brothers, Q. Barnes, W. L. Eubank, M. N. Hawkins, S. Purkayastha, A. O-Yurvati, and P. B. Raven
Cardiopulmonary baroreflex is reset during dynamic exercise
J Appl Physiol, January 1, 2006; 100(1): 51 - 59.
[Abstract] [Full Text] [PDF]

Home page
 J. Physiol.Home page
S. Ogoh, R. M. Brothers, Q. Barnes, W. L. Eubank, M. N. Hawkins, S. Purkayastha, A. O-Yurvati, and P. B. Raven
The effect of changes in cardiac output on middle cerebral artery mean blood velocity at rest and during exercise
J. Physiol., December 1, 2005; 569(2): 697 - 704.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Physiol. Heart Circ. Physiol.Home page
R. B. Panerai, M. Moody, P. J. Eames, and J. F. Potter
Dynamic cerebral autoregulation during brain activation paradigms
Am J Physiol Heart Circ Physiol, September 1, 2005; 289(3): H1202 - H1208.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
288/3/H1461    most recent
00948.2004v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (17)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ogoh, S.
Right arrow Articles by Secher, N. H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ogoh, S.
Right arrow Articles by Secher, N. H.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2005 by the American Physiological Society.