BS277 Biology of Muscle Fatigue

1. Dominic Micklewright, PhD. Lecturer, Centre for Sports & Exercise Science Department of Biological Sciences University of Essex BS277 Biology of Muscle Fatigue

3. ? What is the cause of fatigue

4. Some Key Principles • Sports Science is multidisciplinary which has resulted in different definitions and explanations of fatigue: • PHYSIOLOGICAL • BIOCHEMICAL • BIOMECHANICAL • PSYCHOLOGICAL • NEUROLOGICAL

5. Some Key Principles • Reductionist approaches: • Conceptual → Mechanistic (Orange peeling) • Macro → Micro • Reductionism limitations due to misinterpretation of the hierarchy of science e.g. particle physics, physics, molecular biology…..psychology, social science

6. Some Key Principles • Linear Models vs. Complex Systems Catastrophic Failure

7. Some Key Principles Complex Systems & Homeostasis…

8. Some Key Principles • Task dependency: • Open vs. Closed Loop Exercise • Prolonged vs. High Int/Short Duration • Contraction type (Conc. v Ecc.; Isometric vs. Isotonic) • Mode: run vs. cycle vs. row vs. throw etc.

9. Some Key Principles • Peripheral vs. Central Fatigue: CENTRAL FATIGUE Upstream of anterior horn cell CNS PERIPHERAL FATIGUE Downstream of anterior horn cell PNS & Muscle

10. Some Key Principles • The concept of maximal: • Is maximal really obtainable? • Max in vivo muscle contraction < max. in vitro muscle contractions. • Pacing / teleoanticipation evident in so called maximal and supramaximal exercise tasks. • Maximal ‘effort’ is an entirely different concept

11. The Models of Fatigue Energy Supply / Depletion Model CV / Anaerobic Model Neuromuscular Model Central Governor / Complex Systems Model FATIGUE Thermoregulatory Model Psychological Model Biomechanical Model

12. SynopsisCV / Anaerobic Model Performance limited by: • Ability of the CV system to supply oxygenated blood to the muscles. • Ability of the CV system to remove metabolites

13. Red Blood Cells EPO & Blood doping found to ↑ RBC count ↑ Cycling performance …but dangerous (Hahn & Gore, 2001) Cardiac Output CO = HR x SV ↓CO … ↓ muscle blood flow A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) Lac & H+ Removal AT occurs at a higher % of VO2MAX among trained (Lucia et al. 2003) Lac production-removal imbalance causes: ↓ intramuscular pH ↓ enzyme activity (PFK) ↓ myoglobin O2 capacity ↑ pain receptor activity Muscle Blood Flow -ive linear relationship between muscle blood flow and power output (Saltin et al, 1998) CV / ANAEROBIC FATIGUE Oxygen Uptake Mitochondria size and density (Hoppeler & Fluck, 2003) Capillarisation (Pringle et al., 2003) Myoglobin capacity (Hoppeler & Fluck, 2003) Aerobic enzyme activity (Hoppeler & Fluck, 2003)

14. Only 90% of available O2 extracted from blood at exhaustion suggesting that cardiac output is not the sole cause of fatigue. (Taken from Gonzalez-Alonso & Calbert, 2003)

15. Red Blood Cells EPO & Blood doping found to ↑ RBC count ↑ Cycling performance …but dangerous (Hahn & Gore, 2001) Cardiac Output CO = HR x SV ↓CO … ↓ muscle blood flow A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) Lac & H+ Removal AT occurs at a higher % of VO2MAX among trained (Lucia et al. 2003) Lac production-removal imbalance causes: ↓ intramuscular pH ↓ enzyme activity (PFK) ↓ myoglobin O2 capacity ↑ pain receptor activity Muscle Blood Flow -ive linear relationship between muscle blood flow and power output (Saltin et al, 1998) CV / ANAEROBIC FATIGUE Oxygen Uptake Mitochondria size and density (Hoppeler & Fluck, 2003) Capillarisation (Pringle et al., 2003) Myoglobin capacity (Hoppeler & Fluck, 2003) Aerobic enzyme activity (Hoppeler & Fluck, 2003)

16. Exposure to altitude increases RBC volume and Hb (Taken from Hahm & Gore, 2001)

17. Red Blood Cells EPO & Blood doping found to ↑ RBC count ↑ Cycling performance …but dangerous (Hahn & Gore, 2001) Cardiac Output CO = HR x SV ↓CO … ↓ muscle blood flow A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) Lac & H+ Removal AT occurs at a higher % of VO2MAX among trained (Lucia et al. 2003) Lac production-removal imbalance causes: ↓ intramuscular pH ↓ enzyme activity (PFK) ↓ myoglobin O2 capacity ↑ pain receptor activity Muscle Blood Flow -ive linear relationship between muscle blood flow and power output (Saltin et al, 1998) CV / ANAEROBIC FATIGUE Oxygen Uptake (Trained vs Untrained) ↑50% Mitochondria size & density (Hoppeler & Fluck 2003) Capillarisation (Pringle et al., 2003) Myoglobin capacity (Hoppeler & Fluck, 2003) Aerobic enzyme activity (Hoppeler & Fluck, 2003)

18. X-Section of a Muscle Fibre Showing Volumne Density of Mitochondria greater by 50% in Endurance Trained Men (Taken from Hoppeler & Fluck, 2003)

19. Red Blood Cells EPO & Blood doping found to ↑ RBC count ↑ Cycling performance …but dangerous (Hahn & Gore, 2001) Cardiac Output CO = HR x SV ↓CO … ↓ muscle blood flow A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) Lac & H+ Removal AT occurs at a higher % of VO2MAX among trained (Lucia et al. 2003) Lac production-removal imbalance causes: ↓ intramuscular pH ↓ enzyme activity (PFK) ↓ myoglobin O2 capacity ↑ pain receptor activity Muscle Blood Flow -ive linear relationship between muscle blood flow and power output (Saltin et al, 1998) CV / ANAEROBIC FATIGUE Oxygen Uptake (Trained vs Untrained) ↑50% Mitochondria size & density (Hoppeler & Fluck 2003) Capillarisation (Pringle et al., 2003) Myoglobin capacity (Hoppeler & Fluck, 2003) Aerobic enzyme activity (Hoppeler & Fluck, 2003)

20. Fatiguing cycling associated with increased muscle lactate and reduced pH (Taken from Stepto et al, 2001)

21. Red Blood Cells EPO & Blood doping found to ↑ RBC count ↑ Cycling performance …but dangerous (Hahn & Gore, 2001) Cardiac Output CO = HR x SV ↓CO … ↓ muscle blood flow A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) Lac & H+ Removal AT occurs at a higher % of VO2MAX among trained (Lucia et al. 2003) Lac production-removal imbalance causes: ↓ intramuscular pH ↓ enzyme activity (PFK) ↓ myoglobin O2 capacity ↑ pain receptor activity Muscle Blood Flow -ive linear relationship between muscle blood flow and power output (Saltin et al, 1998) CV / ANAEROBIC FATIGUE Oxygen Uptake (Trained vs Untrained) ↑50% Mitochondria size & density (Hoppeler & Fluck 2003) Capillarisation (Pringle et al., 2003) Myoglobin capacity (Hoppeler & Fluck, 2003) Aerobic enzyme activity (Hoppeler & Fluck, 2003)

22. SynopsisEnergy Supply / Depletion Model Fatigue due to : • Inadequate supply of ATP to the muscle. • Inadequate depletion of endogenous substrates.

23. ATP Production Failure to supply ATP via various metabolic pathways Glycolysis & lipolysis (Shulman & Rothman, 2001) But…. Intramuscular ATP never below 40% even at fatigue (Green, 1997) Is [ATP] an afferent signal? McCardle’s Disease Metabolic myopathy affects 1/100K ↓Capacity to store glycogen Weakness & pain after exercise Suggests [glycogen] causes fatigue Depletion vs. Supply Depletion assumes fatigue is a direct rather than indirect result of: ↓Muscle/liver glycogen ↓Blood glucose ↓Phosphocreatine 60% & 86% ↓ in gastroc glycogen depletion after 90-min running among rats. (Gigli & Bussman, 2002) Not fully depleted so cannot be sole cause of fatigue ENERGY SUPPLY / DEPLETION Rate of CH2O Oxidation Since muscle fatigue not solely due to availability of CH2O or ATP some have concluded that rate of muscle CH2O oxidation is more important (Noakes et al. 2000)

24. Fatiguing cycling associated with reduced muscle glycogen (Taken from Stepto et al, 2001)

25. ATP Production Failure to supply ATP via various metabolic pathways Glycolysis & lipolysis (Shulman & Rothman, 2001) But…. Intramuscular ATP never below 40% even at fatigue (Green, 1997) Is [ATP] an afferent signal? McCardle’s Disease Metabolic myopathy affects 1/100K ↓Capacity to store glycogen Weakness & pain after exercise Suggests [glycogen] causes fatigue Depletion vs. Supply Depletion assumes fatigue is a direct rather than indirect result of: ↓Muscle/liver glycogen ↓Blood glucose ↓Phosphocreatine 60% & 86% ↓ in gastroc glycogen depletion after 90-min running among rats. (Gigli & Bussman, 2002) Not fully depleted so cannot be sole cause of fatigue ENERGY SUPPLY / DEPLETION Rate of CH2O Oxidation Since muscle fatigue not solely due to availability of CH2O or ATP some have concluded that rate of muscle CH2O oxidation is more important (Noakes et al. 2000)

26. ATP Production Failure to supply ATP via various metabolic pathways Glycolysis & lipolysis (Shulman & Rothman, 2001) But…. Intramuscular ATP never below 40% even at fatigue (Green, 1997) Is [ATP] an afferent signal? McCardle’s Disease Metabolic myopathy affects 1/100K ↓Capacity to store glycogen Weakness & pain after exercise Suggests [glycogen] causes fatigue Depletion vs. Supply Depletion assumes fatigue is a direct rather than indirect result of: ↓Muscle/liver glycogen ↓Blood glucose ↓Phosphocreatine 60% & 86% ↓ in gastroc glycogen depletion after 90-min running among rats. (Gigli & Bussman, 2002) Not fully depleted so cannot be sole cause of fatigue ENERGY SUPPLY / DEPLETION Rate of CH2O Oxidation Since muscle fatigue not solely due to availability of CH2O or ATP some have concluded that rate of muscle CH2O oxidation is more important (Noakes et al. 2000)

27. SynopsisNeuromuscular Model Fatigue due to : • Inhibition of the neuromuscular pathway. • Reduction in central neural drive. • Reduction in responsiveness of the muscle to action potentials. • Failure of excitation-contraction coupling mechanisms. “Functions involved in muscle excitation, recruitment and contraction are what limit performance.” (Noakes, 2000)

28. Methods (Central vs. Peripheral Determination) Electromyography (EMG) muscle electrical activity: Integrated EMG = Filtered & smoothed EMG Root Mean Squared (RMS) = global EMG signal M-Wave = compound action potential from brain. NM Fatigue = ↓Motor Neuron Firing Freq & ↑Relaxation time during MVC Muscle Twitch Interpolation (MTI) – compare Max Cont. between locally twitched vs. voluntary twitched. NM Propagation Theory 10%↓ MVC during prolonged cycling not due to central activation (Millet et al., 2003) Sarcolemma ↓Na+, K+ membrane gradient occur during prolonged cycling resulting in ↓action potential i.e. Na+/K+ muscle pump (Fowels et al, 2002) α-Motor Neurone Muscle receptors less responsive when ↑H+, ↓pH (Lepers et al., 2000) Time to fatigue ↑ in force vs. positioning task. Task dependency? (Hunter et al., 2004) NEURO MUSCULAR MODEL Central Activation Theory Lower central activation found among young and old using MTI during isometric induced fatigue (Stackhouse et al, 2001). ↓Dopamine ↑5HT during prolonged exercise in rats (Bailey et al., 1993) ↑Dop/5HT ratio may ↓central activation due to lower arousal, motivation & NM coordination. Nutritional CH2O may also attenuate changes in ratio (Davis et al., 2000)

29. M-Wave ↑Duration ↓Amplitude = Peripheral Fat / NM Propogation Table from Abbiss & Lausen (2005) showing a selection of studies that have examined central vs. peripheral NM Fatigue

30. Methods (Central vs. Peripheral Determination) Electromyography (EMG) muscle electrical activity: Integrated EMG = Filtered & smoothed EMG Root Mean Squared (RMS) = global EMG signal M-Wave = compound action potential from brain. NM Fatigue = ↓Motor Neuron Firing Freq & ↑Relaxation time during MVC Muscle Twitch Interpolation (MTI) – compare Max Cont. between locally twitched vs. voluntary twitched. NM Propagation Theory 10%↓ MVC during prolonged cycling not due to central activation (Millet et al., 2003) Sarcolemma ↓Na+, K+ membrane gradient occur during prolonged cycling resulting in ↓action potential i.e. Na+/K+ muscle pump (Fowels et al, 2002) α-Motor Neurone Muscle receptors less responsive when ↑H+, ↓pH (Lepers et al., 2000) Time to fatigue ↑ in force vs. positioning task. Task dependency? (Hunter et al., 2004) NEURO MUSCULAR MODEL Central Activation Theory Lower central activation found among young and old using MTI during isometric induced fatigue (Stackhouse et al, 2001). ↓Dopamine ↑5HT during prolonged exercise in rats (Bailey et al., 1993) ↑Dop/5HT ratio may ↓central activation due to lower arousal, motivation & NM coordination. Nutritional CH2O may also attenuate changes in ratio (Davis et al., 2000)

31. Methods (Central vs. Peripheral Determination) Electromyography (EMG) muscle electrical activity: Integrated EMG = Filtered & smoothed EMG Root Mean Squared (RMS) = global EMG signal M-Wave = compound action potential from brain. NM Fatigue = ↓Motor Neuron Firing Freq & ↑Relaxation time during MVC Muscle Twitch Interpolation (MTI) – compare Max Cont. between locally twitched vs. voluntary twitched. NM Propagation Theory 10%↓ MVC during prolonged cycling not due to central activation (Millet et al., 2003) Sarcolemma ↓Na+, K+ membrane gradient occur during prolonged cycling resulting in ↓action potential i.e. Na+/K+ muscle pump (Fowels et al, 2002) α-Motor Neurone Muscle receptors less responsive when ↑H+, ↓pH (Lepers et al., 2000) Time to fatigue ↑ in force vs. positioning task. Task dependency? (Hunter et al., 2004) NEURO MUSCULAR MODEL Central Activation Theory Lower central activation found among young and old using MTI during isometric induced fatigue (Stackhouse et al, 2001). ↓Dopamine ↑5HT during prolonged exercise in rats (Bailey et al., 1993) ↑Dop/5HT ratio may ↓central activation due to lower arousal, motivation & NM coordination. Nutritional CH2O may also attenuate changes in ratio (Davis et al., 2000)

32. Methods (Central vs. Peripheral Determination) Electromyography (EMG) muscle electrical activity: Integrated EMG = Filtered & smoothed EMG Root Mean Squared (RMS) = global EMG signal M-Wave = compound action potential from brain. NM Fatigue = ↓Motor Neuron Firing Freq & ↑Relaxation time during MVC Muscle Twitch Interpolation (MTI) – compare Max Cont. between locally twitched vs. voluntary twitched. NM Propagation Theory 10%↓ MVC during prolonged cycling not due to central activation (Millet et al., 2003) Sarcolemma ↓Na+, K+ membrane gradient occur during prolonged cycling resulting in ↓action potential i.e. Na+/K+ muscle pump (Fowels et al, 2002) α-Motor Neurone Muscle receptors less responsive when ↑H+, ↓pH (Lepers et al., 2000) Time to fatigue ↑ in force vs. positioning task. Task dependency? (Hunter et al., 2004) Muscle Power / Peripheral Failure Theory Fatigue occurs within muscle by alteration of the coupling mechanism between the action potential and the contractile proteins. (Hill et al., 2001) Fatigue of a twitched muscle associated with ↓CA+ from sarcoplasmic reticulum which has –ive effect on excitation-contraction coupling process. Reduced CA+ return from contractile proteins may also cause ↑muscle relaxation / fatigue (McKenna et al, 1996). After first few minutes low threshold motor units fatigue but are replaced by high threshold units (Westgaard & De Luca, 1999). Suggests i) individual motor units susceptible to fatigue ii) protective mechanism to prevent catastrophic failure. Early peripheral fatigue followed by later central fatigue is a safety mechanism to prevent catastrophic failure e.g. loss of ATP (St Clair Gibson et al, 2001) NEURO MUSCULAR MODEL Central Activation Theory Lower central activation found among young and old using MTI during isometric induced fatigue (Stackhouse et al, 2001). ↓Dopamine ↑5HT during prolonged exercise in rats (Bailey et al., 1993) ↑Dop/5HT ratio may ↓central activation due to lower arousal, motivation & NM coordination. Nutritional CH2O may also attenuate changes in ratio (Davis et al., 2000)

33. SynopsisBiomechanical Model Fatigue due to a reduction in mechanical efficiency and economy which provokes… • ↑ CV system demand (CV model) • ↑ Energy consumption (Energy S/D model) • ↑ Metabolite production (Anaerobic model) • ↑ Core temperature (Thermoregulatory model)

34. Mechanisms of Efficiency Task type x muscle property interaction e.g. Optimal cycling cadence for elite 80-90 but for amateur 70-80 (Takaishi et al., 1996). Maybe due to… ↑cardiac output, muscle blood flow, muscle O2 uptake, lac removal (Gotshall, 1996). Faster cadence reduces fast twitch fibre recruitment which are less efficient than slow twitch fibres (Takeshi et al., 1998) Efficiency of Motion ↓Efficiency coincides with ↑ VO2 (Passfield & Doust, 2000) ↓MVC (Lucia et al., 2002). Better economy/efficiency reported for pro cyclists (Lucia et al., 2002) and Kenya runners (Weston et al., 2000) EMG vs. MRI Studies RMS/VO2 ratio declines faster in endurances vs. non-trained subjects (Hug et al., 2004) EMG studies do not reveal diffs. in the recruitment of fibre type. MRI suggests ↑FT recruit cycling @ >60% VO2MAX (Saunders & Evans, 2000) Synergists & antagonists may compensate for fatiguing agonsists (Hunter et al., 2002) BIOMECH. MODEL Stretch/Shortening Cycle Combined action of muscle to produce efficient movement from lengthening (ecc) & shortening (coc.). ↑ Force due to: ↑elastic force in tendons/ligs (Komi, 2000) ↑tx time from stretch to contract (Davis & Bailey, 1997) Golgi tendon organ/ muscle spindle role as afferent signal?

35. Muscle Fibre Composition Muscle Activation Rate (e.g. cadence) Intermusc. Coordn. (Stretch/Shortening) BIOMECH. EFFICIENCY OF MOTION Energy consumption / heat generation % Type I / II recruitment pattern O2 consumption and uptake Accumulation of metabolite Adapted from Abbiss & Laursen, 2005)

36. SynopsisThermoregulatory Model Fatigue due to… • Reaching a critical core body temperature • ↑ Core, muscle and skin temp places demands on other physiological systems/models… • CV, anaerobic, energetics, psychological

37. Thermoregulation • Core body temp = heat production (muscle metabolism) – heat removal (convection, conduction, radiation, evaporation). • Core body temp can ↑ 1°C every 5-7 min but cannot be tolerated @ >40°C for prolonged periods. Exercise limited by heat production/dissipation balance.↑ • Environmental temp & hypertherma known to have –ive effect on performance e.g. mean PO ↓6.5% when environ. Raised from 23-32°C (Tatterson et al., 2000). Central Thermoregulation Exhaustion when cycling in heat occurred at 39.5°C (Nielson et al., 1993) but… Tucker et al., 2004 saw highest power when core body temp greatest (39°C). ∴ core temp not sole cause of fatigue. Anticipation? Periph. Thermoregulation Sweating and dissipation of heat have ↑CV demand due to supplying skin as well as muscles with blood (Nybo et al., 2001). Skin flow plateaus but core temp continues to rise during exercise placing extra CV demand (Nielsen et al., (1997) Fatigue related to extra CV demand imposed by periph theromoregulatory changes THERMO. MODEL

38. Highest Temp coincides with highest power output suggesting this is not the only limiting factor in performance (Taken from Tucker et al, 2004)

39. SynopsisPsychological Model Fatigue due to psychological factors which… • ↓ Central activation & motivation • ↑ Perceived exertion & fatigue

40. Emotion & Drive Fatigue is an emotion or a ‘subjective feeling’ state dependent upon physiological and situational environmental factors. Feelings of fatigue may be related to motivation, anxiety, arousal and confidence. Rating of Perceived Exertion The way peripheral sensations associated with exercise are perceived. Borg scale, OMNI scale. RPE rise with skin temp & HR (Amada-da-silva, 2004) Consciousness We are not consciously aware of specific physiological functions e.g. muscle blood flow, blood pressure, glycogen depletion. RPE is conscious awareness based on many afferent sensations. PSYCHOL. MODEL Information Processing (Exp/Memory Cognition) Pacing strategies determined by information processing between the brain and physiological systems. Knowledge of distance or time during an event provides crucial input to monitor and determine overall pacing strategy (St Clair Gibson et al, 2006). - internal clock - endpoint knowledge - feedback

41. SynopsisCentral Governor / Complex Systems Model Fatigue due to a central governor maintaining homeostasis through… • Integration of peripheral afferent signals and exogenous reference signals • Determine efferent muscular control • Facilitates concepts of teleoanticipation, pacing and perceived exertion. • Differentiates between conscious and subconscious processes.

42. Critique of Peripheral Fatigue • Peripheral fatigue model predicts that exercise always terminates at an absolute, temporarily irreversible end point. • Linear system (power output a direct consequence of input variable e.g. [Bla] • Therefore fatigue and the sensation of fatigue) must coincide with the peripheral physiological input variable. • Often they often do not…

43. Critique of Peripheral Fatigue • Complete substrate depletion at fatigue only found during in vitro studies (Lamb, 1999) but not during in vivo where there is an intact CNS (St Clair-Gibson, 2001) • Not a single study has found a direct relationship between perceptions of exertion and physiological variables. Opposite found in chronic fatigue patients (rest yet feel fatigued). • Physiological factors do not coincide with fatigue…

44. Critique of Peripheral Fatigue • Intramuscular ATP never below 40% even at fatigue (Green, 1997) • 60% & 86% ↓ in gastroc glycogen depletion after 90-min running among rats. (Gigli & Bussman, 2002) • A-V O2 diff did not reach max at point of fatigue therefore CO not the sole cause of fatigue (Gonzalez-Alonso & Calbert, 2003) • [Lac] does not peak until up to 15 mins after exercise.

45. Evidence for Central Governor • Fatigue not caused by peripheral factors by by reduced neural command by the brain (Green, 1997) • Fluctuations in power output (Tucker et al., 2006) and heart rate during exercise (Palmer et al., 1994) more representative of a homeostat system of control rather than a linear model. • Presense of homeostasis in all organ functions helps support model.

46. Evidence for Central Governor • Homeostatic regulation by the CNS could account for continually changing pattern of muscle recruitment during exercise. • Homeostatic control based on a complex black box calculation (Ulmer, 1996) derived from the intergration of multiple afferent signals (Lambert et al., 2005) e.g. • Rauch et al. (2005) signalling role of muscle glycogen concentration during prolonged cycling.

47. Empirical & Theoretical Context CENTRAL GOVERNOR CENTRAL FATIGUE AFFERENT FEEDBACK EFFERENT CONTROL PERIPHERAL FATIGUE MUSCLE CONTRACTION PERIPHERAL ORGANS

48. Hampson, St Clair Gibson, Lambert, & Noakes (2001, p. 944) on Ulmer (1996) Ansley, Robson, St Clair Gibson, & Noakes (2003, p. 313) St Clair Gibson, Lambert, Rauch, Tucker, Baden, Foster & Noakes (2006, p. 708) Rauch, St Clair Gibson, Lambert, & Noakes (2005) INITIAL PACE DURING FIRST MOMENTS (FEED-FORWARD) 1. KNOWLEDGE OF ENDPOINT (Closed loop or open loop) St Clair Gibson & Noakes (2006, p.801) 2. PREVOIUS EXPERIENCE SUBSEQUENT PACING (TELEOANTICIPATION) 1. KNOWLEDGE OF ENDPOINT 2. PREVOIUS EXPERIENCE CENTRAL GOVERNOR COMPLEX ALGORHYTHM 3. AFFERENT FEEDBACK 4. PERCEPTIONS OF AND BELIEFS ABOUT THE PRESENT AND LIKELY FUTURE AFFERENT FEEDBACK EFFERENT CONTROL

49. Teleoanticipation in alleged maximal effort exercise (Taken from Wittekind, Micklewright & Beneke, 2009)

50. PREVIOUS EXPERIENCE AND MEMORY: • EXACTNESS / RELEVANCE Previous Experience CENTRAL GOVERNOR AFFERENT FEEDBACK EFFERENT CONTROL