Skip to main content

Advertisement

Log in

The Role of Information Processing Between the Brain and Peripheral Physiological Systems in Pacing and Perception of Effort

  • Review Article
  • Published:
Sports Medicine Aims and scope Submit manuscript

Abstract

This article examines how pacing strategies during exercise are controlled by information processing between the brain and peripheral physiological systems. It is suggested that, although several different pacing strategies can be used by athletes for events of different distance or duration, the underlying principle of how these different overall pacing strategies are controlled is similar. Perhaps the most important factor allowing the establishment of a pacing strategy is knowledge of the endpoint of a particular event. The brain centre controlling pace incorporates knowledge of the endpoint into an algorithm, together with memory of prior events of similar distance or duration, and knowledge of external (environmental) and internal (metabolic) conditions to set a particular optimal pacing strategy for a particular exercise bout. It is proposed that an internal clock, which appears to use scalar rather than absolute time scales, is used by the brain to generate knowledge of the duration or distance still to be covered, so that power output and metabolic rate can be altered appropriately throughout an event of a particular duration or distance. Although the initial pace is set at the beginning of an event in a feedforward manner, no event or internal physiological state will be identical to what has occurred previously. Therefore, continuous adjustments to the power output in the context of the overall pacing strategy occur throughout the exercise bout using feedback information from internal and external receptors. These continuous adjustments in power output require a specific length of time for afferent information to be assessed by the brain’s pace control algorithm, and for efferent neural commands to be generated, and we suggest that it is this time lag that crates the fluctuations in power output that occur during an exercise bout. These non-monotonic changes in power output during exercise, associated with information processing between the brain and peripheral physiological systems, are crucial to maintain the overall pacing strategy chosen by the brain algorithm of each athlete at the start of the exercise bout.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Foster C, Schrager M, Snyder AC, et al. Pacing strategy and athletic performance. Sports Med 1994; 17: 77–85

    Article  PubMed  CAS  Google Scholar 

  2. Lucia A, Hoyos S, Santalla AJ, et al. Tour de France versus Vuelta a Espana: which is harder? Med Sci Sports Exerc 2003; 35: 872–878

    Article  PubMed  Google Scholar 

  3. Bishop D, Bonetti D, Dawson B. The influence of pacing strategy on VO2 and supramaximal kayak performance. Med Sci Sports Exerc 2002; 6: 1041–1047

    Google Scholar 

  4. De Koning JJ, Bobbert MF, Foster C. Determination of optimal pacing strategy in track cycling with an energy flow model. J Sci Med Sport 1999; 2: 266–277

    Article  PubMed  Google Scholar 

  5. Foster C, de Koning JJ, Hettinga F, et al. Effect of competitive distance on energy expenditure during simulated competition. Int J Sports Med 2004; 25: 198–204

    Article  PubMed  CAS  Google Scholar 

  6. Kay D, Cannon J, Marino FE et al. Evidence for neuromuscular fatigue during cycling in warm humid conditions. Eur J Appl Physiol 2001; 84: 115–121

    Article  PubMed  CAS  Google Scholar 

  7. Noakes TD, St Clair Gibson A. Logical limitations to the ‘catastrophe’ models of fatigue during exercise in humans. Br J Sports Med 2004; 38: 648–649

    Article  PubMed  CAS  Google Scholar 

  8. Ansley L, Schabort E, St Clair Gibson A, et al. Regulation of pacing strategies during successive 4-km time trials. Med Sci Sports Exerc 2004; 36: 1819–1825

    Article  PubMed  Google Scholar 

  9. Mattern CO, Kenekick RW, Kertzer R, et al. Impact of starting strategy on cycling performance. Int J Sports Med 2001; 22: 350–355

    Article  PubMed  CAS  Google Scholar 

  10. Foster C, Green MA, Snyder AC, et al. Physiological responses during simulated competition. Med Sci Sports Exerc 1993; 25: 877–882

    Article  PubMed  CAS  Google Scholar 

  11. Adams GR, Harris RT, Woodard D, et al. Mapping of electrical activity using MRI. J Appl Physiol 2000; 74: 532–537

    Google Scholar 

  12. Enoka RM, Stuart DG. Neurobiology of muscle fatigue. J Appl Physiol 1992; 72: 1631–1648

    Article  PubMed  CAS  Google Scholar 

  13. Yue GH, Ranganathan VK, Siemionow V, et al. Evidence of inability to fully activate human limb muscle. Muscle Nerve 2000; 23: 376–384

    Article  PubMed  CAS  Google Scholar 

  14. Gandevia SC. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev 2001; 81: 1725–1789

    PubMed  CAS  Google Scholar 

  15. Kayser B. Exercise starts and ends in the brain. Eur J Appl Physiol 2003; 90: 405–410

    Article  PubMed  Google Scholar 

  16. Marsden CD, Meadows JC, Merton PA. ‘Muscular wisdom’ that minimizes fatigue during prolonged effort in man: peak rates of motor unit discharge and slowing of discharge during fatigue. In: Desmedt JE, editor. Motor control mechanism in health and disease. New York: Raven, 1983: 169–211

    Google Scholar 

  17. St Clair Gibson A, Lambert EV, Lambert MI, et al. Exercise and fatigue control mechanisms. Int Sport Med J 2001; 2 (3): 14

    Google Scholar 

  18. Ansley L, Robson PJ, St Clair Gibson A, et al. Evidence for anticipatory strategies during supra-maximal exercise lasting longer than 30s. Med Sci Sports Exerc 2004; 36: 309–314

    Article  PubMed  Google Scholar 

  19. St Clair Gibson A, Lambert MI, Noakes TD. Neural control of force output during maximal and submaximal exercise. Sports Med 2001; 31: 637–650

    Article  Google Scholar 

  20. Baden DA. Goals and expectancies: psychological and physiological effects of anticipating the end [dissertation]. Southampton: University of Southampton, 2002

    Google Scholar 

  21. Baden DA, Warwick-Evans LA, Lakorrry J. Am I nearly there? The effect of anticipated running distance on perceived exertion and attentional focus. J Sports Exerc Psychol 2004; 27: 215–231

    Google Scholar 

  22. St Clair Gibson A, Noakes TD. Evidence for complex system integration and dynamic neural regulation of skeletal muscle recruitment during exercise in humans. Br J Sports Med 2004; 38: 797–806

    Article  Google Scholar 

  23. Ulmer H-V. Concept of an extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experentia 1996; 52: 416–420

    Article  CAS  Google Scholar 

  24. Paterson S, Marino FE. Effect of deception of distance on prolonged cycling performance. Percept Mot Skills 2004; 98: 1017–1026

    Article  PubMed  CAS  Google Scholar 

  25. Rauch HGL, St Clair Gibson A, Lambert EV. A signalling role for muscle glycogen in the regulation of pace during prolonged exercise. Br J Sports Med 2005; 39: 34–38

    Article  PubMed  CAS  Google Scholar 

  26. Arbogast S, Vassilakopoulos T, Darques JL, et al. Influence of oxygen supply on activation of group IV muscle afferents after low frequency muscle stimulation. Muscle Nerve 2000; 23: 1187–1193

    Article  PubMed  CAS  Google Scholar 

  27. Haouzi P, Hill JM, Lewis BK, et al. Responses of group HI and IV muscle afferents to distension of the peripheral vascular bed. J Appl Physiol 1999; 87: 545–553

    PubMed  CAS  Google Scholar 

  28. Lambert EV, St Clair Gibson A, Noakes TD. Complex system model of fatigue: integrative homeostatic control of peripheral physiological systems during exercise in humans. Br J Sports Med 2005; 39: 52–62

    Article  PubMed  CAS  Google Scholar 

  29. Rotto DM, Kaufman MP. Effect of metabolic products of muscular contraction on discharge of group III and IV afferents. J Appl Physiol 1988; 64: 2306–2313

    PubMed  CAS  Google Scholar 

  30. Tucker R, Rauch LGH, Harley YX, et al. Impaired exercise performance in heat is associated with an anticipatory reduction in skeletal muscle recruitment. Eur J Physiol 2004; 48: 422–430

    Google Scholar 

  31. St Clair Gibson A, Goedecke JH, Harley YX, et al. Metabolic setpoint control mechanisms in different physiological systems at rest and during exercise. J Theor Biol 2005 Sep 7; 236 (1): 60–72

    Article  Google Scholar 

  32. Albertus Y, Tucker R, St Clair Gibson A, et al. Effect of distance feedback on pacing strategies, perceived exertion and heart rate during 20 km cycle time trials. Med Sci Sports Exerc 2005; 37: 461–468

    Article  PubMed  Google Scholar 

  33. Dunbar CC, Robertson RJ, Braun R, et al. The validity of regulating exercise intensity by ratings of perceived exertion. Med Sci Sports Exerc 1992; 24: 94–99

    PubMed  CAS  Google Scholar 

  34. Schabort EJ, Hopkins WG, Hawley JA. Reproducibility of self-paced treadmill performance of trained treadmill runners. Int J Sports Med 1997; 18: 1–4

    Article  Google Scholar 

  35. Kirkpatrick K. Packet theory of conditioning or timing. Behav Processes 2002; 57: 89–106

    Article  PubMed  Google Scholar 

  36. Kvist A, Lindstrom A, Green M, et al. Carrying large fuel loads during sustained flight is cheaper than expected. Nature 2001; 411: 752–753

    Article  Google Scholar 

  37. Gibbon J, Church RM. Time left: linear versus logarithmic subjective time. J Exp Psychol Anim Behav Process 1981; 7: 87–107

    Article  PubMed  CAS  Google Scholar 

  38. Church RM, Meek WH, Gibbon J. Application of scalar timing theory to individual trials. J Exp Psychol Anim Behav Process 1994; 20: 135–155

    Article  PubMed  CAS  Google Scholar 

  39. Catalano JF. Effect of perceived proximity to end of task upon end-spurt. Percept Mot Skills 1973; 36: 363–377

    Article  PubMed  CAS  Google Scholar 

  40. Catalano JF. End-spurt in addition of numbers. Percept Mot Skills 1974; 39: 121–122

    Article  Google Scholar 

  41. Catalano JF. End-spurt following simple repetitive muscular movement. Percept Mot Skills 1974; 39: 763–766

    Article  PubMed  CAS  Google Scholar 

  42. Nikolopoulos V, Arkinstall MJ, Hawley JA. Pacing strategy in simulated cycle time-trials is based on perceived rather than actual distance. J Sci Med Sport 2001; 4: 212–219

    Article  PubMed  CAS  Google Scholar 

  43. Borg GA. Perceived exertion: a note on ‘history’ and methods. Med Sci Sports 1973; 5: 90–93

    PubMed  CAS  Google Scholar 

  44. Borg GA. Borg’s perceived exertion and pain scales. Champaign (IL): Human Kinetics, 1998

    Google Scholar 

  45. Hunter AM, St Clair Gibson A, Mbambo Z, et al. The effects of heat stress on neuromuscular activity during endurance exercise. Pflugers Arch 2002; 444: 738–743

    Article  PubMed  CAS  Google Scholar 

  46. St Clair Gibson A, Lambert MI, Hawley JA, et al. Measurement of maximal oxygen uptake from two different laboratory protocols in runners and squash players. Med Sci Sports Exerc 1999; 31: 1226–1229

    Article  Google Scholar 

  47. Crystal JD, Church RM, Broadbent HA. Systematic non-linearities in the memory representation of time. J Exp Psychol Anim Behav Process 1997; 23: 267–282

    Article  PubMed  CAS  Google Scholar 

  48. Meek WH, Church RM. Nutrients that modify the speed of internal clock and memory storage processes. Behav Neurosci 1987; 101: 465–475

    Article  Google Scholar 

  49. Malapani C, Rakitin B, Levy R, et al. Coupled temporal memories in Parkinson’s disease: a dopamine-related dysfunction. J Cogn Neurosci 1998; 10: 316–331

    Article  PubMed  CAS  Google Scholar 

  50. Palmer GS, Hawley JA, Dennis SC, et al. Heart rate responses during a 4-d cycle race. Med Sci Sports Exerc 1994; 26: 1278–1283

    PubMed  CAS  Google Scholar 

  51. Cafarelli E. Peripheral contributions to the perception of effort. Med Sci Sports Exerc 1982; 14: 382–389

    PubMed  CAS  Google Scholar 

  52. Terblanche E, Wessels JA, Stewart RI, et al. A computer simulation of free-range exercise in the laboratory. J Appl Physiol 1999; 87: 1386–1391

    PubMed  CAS  Google Scholar 

  53. Hu K, Ivanov PC, Chen Z, et al. Non-random fluctuations and multi-scale dynamics regulation of human activity. Physica A 2004; 337: 307–318

    Article  PubMed  Google Scholar 

  54. Ivanov PC, Hausdorff JM, Havlin S, et al. Levels of complexity in scale-invariant neural signals [online]. Available from URL: http://arxiv.org/abs/cond-mat/0409545 [Accessed 2006 Jul 17]

  55. St Clair Gibson A, Schabort EJ, Noakes TD. Reduced neuromuscular activity and force generation during prolonged cycling. Am J Physiol Regul Integr Comp Physiol 2001; 281: R187–R196

    Google Scholar 

  56. Bar-Or O, Skinner JS, Buskirk ER, et al. Physiological and perceptual indicators of physical stress in 41-60 year old men who vary in conditioning level and body fatness. Med Sci Sports 1972; 4: 96–100

    Google Scholar 

  57. Gamberale F. Perceived exertion, heart rate, oxygen uptake and blood lactate in different work operations. Ergonomics 1972; 15: 545–554

    Article  PubMed  CAS  Google Scholar 

  58. Noble BJ, Metz KF, Pandolf KB, et al. Perceptual responses to exercise: a multiple regression study. Med Sci Sports 1973; 5: 104–109

    PubMed  CAS  Google Scholar 

  59. Hampson DB, St Clair Gibson A, Lambert MI, et al. The influence of sensory cues on the performance of effort during exercise and central regulation of exercise performance. Sports Med 2001; 31: 935–952

    Article  PubMed  CAS  Google Scholar 

  60. Mihevic PM. Sensory cues for perceived exertion: a review. Med Sci Sports Exerc 1981; 13: 150–163

    PubMed  CAS  Google Scholar 

  61. Williamson JW, McColl R, Mathews D, et al. Hypnotic manipulation of effort sense during dynamic exercise: cardiovascular responses and brain activation. J Appl Physiol 2001; 90: 1392–1399

    PubMed  CAS  Google Scholar 

  62. St Clair Gibson A, Baden DA, Lambert MI, et al. The conscious perception of the sensation of fatigue. Sports Med 2003; 33: 167–176

    Article  Google Scholar 

  63. Ceci R, Hassmen P. Self-monitored exercise at three different RPE intensities in treadmill vs field running. Med Sci Sports Exerc 1991; 23: 732–738

    PubMed  CAS  Google Scholar 

  64. Dishman RK, Farquhar RP, Cureton KJ. Responses to preferred intensities of exertion in men differing in activity levels. Med Sci Sports Exerc 1994; 26: 783–790

    Article  PubMed  CAS  Google Scholar 

  65. Eston RG, Davies BL, Williams JG. Use of perceived effort ratings to control exercise intensity in young healthy adults. Eur J Appl Physiol Occup Physiol 1987; 56: 222–224

    Article  PubMed  CAS  Google Scholar 

  66. Parfitt G, Rose E, Markland D. The effect of prescribed and preferred intensity exercise on psychological affect and the influence of baseline measures on affect. J Health Psychol 2000; 5: 231–240

    Article  PubMed  CAS  Google Scholar 

  67. Smutok MA, Skrinar GS, Pandolf KB. Exercise intensity: subjective regulation by perceived exertion. Arch Phys Med Rehabil 1980; 61: 569–574

    PubMed  CAS  Google Scholar 

  68. Ward DS, Bar-Or O, Longmuir P, et al. Use of RPE to control exercise intensity in wheelchair bound children and adults. Pediatr Exerc Sci 1995; 7: 94–102

    Google Scholar 

  69. Williams JG, Eston RG, Stretch C. Use of ratings of perceived exertion to control exercise intensity in children. Pediatr Exerc Sci 1991; 3: 21–27

    Google Scholar 

  70. Buckley J, Eston RG, Sims J. Reliability and validity of a Braille ratings of perceived exertion scale. Br J Sports Med 2000; 34: 297–302

    Article  PubMed  CAS  Google Scholar 

  71. Eston RG, Williams JG. Reliability of ratings of perceived effort for regulation of exercise intensity. Br J Sports Med 1988; 22: 153–155

    Article  PubMed  CAS  Google Scholar 

  72. Eston RG, Parfitt G, Campbell L, et al. Reliability of effort perception for regulating exercise intensity in children using a Cart and Load Effort Rating (CALER) Scale. Pediatr Exerc Sci 2000; 12: 388–397

    Google Scholar 

  73. Cain WS, Stevens JC. Constant-effort contractions related to the electromyogram. Med Sci Sports 1973; 5: 121–127

    PubMed  CAS  Google Scholar 

  74. Noakes TD. Linear relationship between the perception of effort and the duration of constant load exercise that remains. J Appl Physiol 2004; 96: 1571–1572

    Article  PubMed  Google Scholar 

  75. Baldwin J, Snow RJ, Gibala MJ, et al. Glycogen availability does not affect the TCA cycle or TAN pools during prolonged, fatiguing exercise. J Appl Physiol 2003; 94: 2181–2187

    PubMed  CAS  Google Scholar 

  76. Eston RG, Lamb KL, Parfitt G, et al. The validity of predicting maximal oxygen uptake from a perceptually-regulated graded exercise test. Eur J Appl Physiol 2005; 94: 221–227

    Article  PubMed  Google Scholar 

  77. Eston R, Parfitt G, Maccombie M, et al. Scalar time representation of perceived effort during exercise is not altered by an antecedent fatiguing exercise bout. J Appl Physiol. In press

  78. Baden DA, McLean TL, Tucker R, et al. The effect of anticipation during unknown or unexpected exercise duration on rating of perceived exertion, affect and physiological function. Br J Sports Med 2005; 39 (10): 742–746

    Article  PubMed  CAS  Google Scholar 

  79. Noakes TD. Lore of running. Cape Town: Oxford University Press, 1992

    Google Scholar 

  80. Morgan WP, Pollock ML. Psychologic characterization of the elite distance runner. Ann N Y Acad Sci 1977; 301: 382–403

    Article  PubMed  CAS  Google Scholar 

  81. Schomer H. Mental strategies and the perception of effort of marathon runners. Int J Sport Psychol 1986; 17: 41–59

    Google Scholar 

  82. Damasio A. The feeling of what happens: body, emotion and the making of consciousness. London: Vintage Press, 2000

    Google Scholar 

  83. Parvizi J, Damasio A. Consciousness and the brainstem. Cognition 2001; 79: 135–159

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

Funding for the work described in this review was provided by Medical Research Council of South Africa, the University of Cape Town Harry Crossley and Nellie Atkinson Staff Research Funds, Discovery Health, and the National Research Foundation of South Africa through the THRIP initiative. To the knowledge of the authors, there are no conflicts of interest that are directly or indirectly related to the contents of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alan Clair St Gibson.

Rights and permissions

Reprints and permissions

About this article

Cite this article

St Gibson, A.C., Lambert, E.V., Rauch, L.H.G. et al. The Role of Information Processing Between the Brain and Peripheral Physiological Systems in Pacing and Perception of Effort. Sports Med 36, 705–722 (2006). https://doi.org/10.2165/00007256-200636080-00006

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2165/00007256-200636080-00006

Keywords

Navigation